From 637ca6a21f84da7d77cd2c59a943f6f638389ddf Mon Sep 17 00:00:00 2001 From: Stefano Fioravanzo Date: Mon, 2 Feb 2026 14:50:52 +0100 Subject: [PATCH 1/7] chore: Remove SDK examples Remove the entire examples/sdk/ directory which contained examples for the Python decorator-based SDK workflow: - skeleton.py: Basic SDK usage tutorial - retry-pipeline.py: Retry configuration example - artifact.py: Artifact handling example - compression-pipeline.py: (already removed in Phase 1) - titanic/: ML classification example - quantile-regression/: Regression example - README.md: SDK documentation Kale 2.0 focuses exclusively on the notebook-based workflow. The SDK/decorator approach is being removed as part of the modernization effort. BREAKING CHANGE: SDK examples are no longer available. Signed-off-by: Stefano Fioravanzo --- examples/sdk/README.md | 14 - examples/sdk/artifact.py | 40 - examples/sdk/quantile-regression/__init__.py | 13 - .../sdk/quantile-regression/data/TestData.csv | 56 -- .../quantile-regression/data/TrainingData.csv | 56 -- .../data/outputTrainingData_qr.csv | 56 -- examples/sdk/quantile-regression/init.py | 25 - .../sdk/quantile-regression/lib/__init__.py | 13 - .../quantile-regression/lib/modelprototype.py | 88 -- .../lib/quantile_regression.py | 466 --------- examples/sdk/quantile-regression/main.py | 37 - .../sdk/quantile-regression/postprocess.py | 49 - .../sdk/quantile-regression/preprocess.py | 67 -- examples/sdk/quantile-regression/settings.py | 34 - examples/sdk/quantile-regression/train.py | 29 - examples/sdk/retry-pipeline.py | 65 -- examples/sdk/skeleton.py | 150 --- examples/sdk/titanic/__init__.py | 13 - examples/sdk/titanic/data/test.csv | 419 -------- examples/sdk/titanic/data/train.csv | 892 ------------------ examples/sdk/titanic/datapreprocessing.py | 73 -- examples/sdk/titanic/feature_engineering.py | 109 --- examples/sdk/titanic/loaddata.py | 27 - examples/sdk/titanic/logistic_regression.py | 29 - examples/sdk/titanic/main.py | 48 - examples/sdk/titanic/randomforest.py | 26 - examples/sdk/titanic/results.py | 28 - examples/sdk/titanic/svm.py | 26 - 28 files changed, 2948 deletions(-) delete mode 100644 examples/sdk/README.md delete mode 100644 examples/sdk/artifact.py delete mode 100644 examples/sdk/quantile-regression/__init__.py delete mode 100644 examples/sdk/quantile-regression/data/TestData.csv delete mode 100644 examples/sdk/quantile-regression/data/TrainingData.csv delete mode 100644 examples/sdk/quantile-regression/data/outputTrainingData_qr.csv delete mode 100644 examples/sdk/quantile-regression/init.py delete mode 100644 examples/sdk/quantile-regression/lib/__init__.py delete mode 100644 examples/sdk/quantile-regression/lib/modelprototype.py delete mode 100644 examples/sdk/quantile-regression/lib/quantile_regression.py delete mode 100644 examples/sdk/quantile-regression/main.py delete mode 100644 examples/sdk/quantile-regression/postprocess.py delete mode 100644 examples/sdk/quantile-regression/preprocess.py delete mode 100644 examples/sdk/quantile-regression/settings.py delete mode 100644 examples/sdk/quantile-regression/train.py delete mode 100644 examples/sdk/retry-pipeline.py delete mode 100644 examples/sdk/skeleton.py delete mode 100644 examples/sdk/titanic/__init__.py delete mode 100755 examples/sdk/titanic/data/test.csv delete mode 100755 examples/sdk/titanic/data/train.csv delete mode 100644 examples/sdk/titanic/datapreprocessing.py delete mode 100644 examples/sdk/titanic/feature_engineering.py delete mode 100644 examples/sdk/titanic/loaddata.py delete mode 100644 examples/sdk/titanic/logistic_regression.py delete mode 100644 examples/sdk/titanic/main.py delete mode 100644 examples/sdk/titanic/randomforest.py delete mode 100644 examples/sdk/titanic/results.py delete mode 100644 examples/sdk/titanic/svm.py diff --git a/examples/sdk/README.md b/examples/sdk/README.md deleted file mode 100644 index 93699bd40..000000000 --- a/examples/sdk/README.md +++ /dev/null @@ -1,14 +0,0 @@ -## Run Kubeflow Pipelines with the Kale SDK - -This folder is a collection of examples to get started with the Kale SDK. - -- `skeleton.py`: a bare bone example that goes through the basics of the Kale - SDK and its APIs -- `compression-pipeline.py`: a more advanced example that shows you how to run - any CLI/non-Python tool from a Kale pipeline -- `retry-pipeline.py`: in this example you will learn to define retry - strategies in case a pipeline step fails. -- `titanic/`: this folder contains Kale's Notebook Titanic pipeline, converted - to use the SDK instead. -- `quantile-regression/`: this folder contains an adaptation of the original - Shell's quantile regression pipeline. diff --git a/examples/sdk/artifact.py b/examples/sdk/artifact.py deleted file mode 100644 index f8c96876f..000000000 --- a/examples/sdk/artifact.py +++ /dev/null @@ -1,40 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -""" -This pipeline showcases how you can create a KFP artifact as part -of a step. -""" - -from kale.sdk import pipeline, step, artifact - - -# Annotate the step with the @artifact decorator and specify the path to -# a HTML file -@artifact(name="test-artifact", path="/home/jovyan/myartifact.html") -@step(name="artifact_generator") -def generate_artifact(): - print("Creating HTML artifact...") - with open("/home/jovyan/myartifact.html", "w") as f: - f.write("Hello, World!") - print("HTML artifact created successfully!") - - -@pipeline(name="generate-artifact", experiment="generate-artifact") -def artifact_pipeline(): - generate_artifact() - - -if __name__ == "__main__": - artifact_pipeline() diff --git a/examples/sdk/quantile-regression/__init__.py b/examples/sdk/quantile-regression/__init__.py deleted file mode 100644 index 1b5b2fa6c..000000000 --- a/examples/sdk/quantile-regression/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/examples/sdk/quantile-regression/data/TestData.csv b/examples/sdk/quantile-regression/data/TestData.csv deleted file mode 100644 index 1de72fa41..000000000 --- a/examples/sdk/quantile-regression/data/TestData.csv +++ /dev/null @@ -1,56 +0,0 @@ -DateTime,coast_load,east_load,f_west_load,north_load,north_c_load,south_c_load,south_load,total_load,west_load,CLOUD_COVER,DEWPOINT,HEAT_INDEX,PRECIPITATION,TEMPERATURE,WIND_CHILL,WIND_DIRECTION,WIND_SPEED,TOTAL_CAP_GEN_RES,TOTAL_CAP_LOAD_RES,lz_north_wind,lz_south_wind,lz_west_wind,system_wind,cop_north_wind,cop_south_wind,cop_west_wind,cop_system_wind,stwpf_north_wind,stwpf_south_wind,stwpf_west_wind,stwpf_system_wind,wgrpp_houston_wind,wgrpp_north_wind,wgrpp_west_wind,wgrpp_system_wind,SYSTEM_LAMBDA_id1,RTORPA_id1,RTOFFPA_id1,RTOLCAP_id1,RTOFFCAP_id1,RTORDPA_id1,RTRRUC_id1,RTOLLASL_id1,RTOLHASL_id1,SYSTEM_LAMBDA_id2,RTORPA_id2,RTOFFPA_id2,RTOLCAP_id2,RTOFFCAP_id2,RTORDPA_id2,RTRRUC_id2,RTOLLASL_id2,RTOLHASL_id2,SYSTEM_LAMBDA_id3,RTORPA_id3,RTOFFPA_id3,RTOLCAP_id3,RTOFFCAP_id3,RTORDPA_id3,RTRRUC_id3,RTOLLASL_id3,RTOLHASL_id3,SYSTEM_LAMBDA_id4,RTORPA_id4,RTOFFPA_id4,RTOLCAP_id4,RTOFFCAP_id4,RTORDPA_id4,RTRRUC_id4,RTOLLASL_id4,RTOLHASL_id4,SYSTEM_LAMBDA_id5,RTORPA_id5,RTOFFPA_id5,RTOLCAP_id5,RTOFFCAP_id5,RTORDPA_id5,RTRRUC_id5,RTOLLASL_id5,RTOLHASL_id5,SYSTEM_LAMBDA_id6,RTORPA_id6,RTOFFPA_id6,RTOLCAP_id6,RTOFFCAP_id6,RTORDPA_id6,RTRRUC_id6,RTOLLASL_id6,RTOLHASL_id6,SYSTEM_LAMBDA_id7,RTORPA_id7,RTOFFPA_id7,RTOLCAP_id7,RTOFFCAP_id7,RTORDPA_id7,RTRRUC_id7,RTOLLASL_id7,RTOLHASL_id7,SYSTEM_LAMBDA_id8,RTORPA_id8,RTOFFPA_id8,RTOLCAP_id8,RTOFFCAP_id8,RTORDPA_id8,RTRRUC_id8,RTOLLASL_id8,RTOLHASL_id8,SYSTEM_LAMBDA_id9,RTORPA_id9,RTOFFPA_id9,RTOLCAP_id9,RTOFFCAP_id9,RTORDPA_id9,RTRRUC_id9,RTOLLASL_id9,RTOLHASL_id9,SYSTEM_LAMBDA_id10,RTORPA_id10,RTOFFPA_id10,RTOLCAP_id10,RTOFFCAP_id10,RTORDPA_id10,RTRRUC_id10,RTOLLASL_id10,RTOLHASL_id10,SYSTEM_LAMBDA_id11,RTORPA_id11,RTOFFPA_id11,RTOLCAP_id11,RTOFFCAP_id11,RTORDPA_id11,RTRRUC_id11,RTOLLASL_id11,RTOLHASL_id11,AVERAGE,DEALS,HIGH,LOW,VOLUME,DA_PRICE,response_var -2019-12-14 00:00:00-06:00,9254.34,1314.05,3670.26,890.18,10963.37,5108.59,2480.75,34853.63,1172.1,19.0,46.0,52.0,0.0,52.0,52.0,0.0,0.0,45587.5,3931.3,43.37,1005.26,5062.73,6111.36,17.5,1563.3,6278.5,7859.3,37.1,1079.8,5296.0,6412.9,624.0,16.8,3570.1,4210.9,35.2095,0.0,0.0,12888.1,4240.44,0.0,0.0,19603.62,44516.64,35.1497,0.0,0.0,12839.68,4240.44,0.0,0.0,19469.61,44200.5,34.7837,0.0,0.0,12959.35,4240.44,0.0,0.0,19469.61,44200.5,34.1095,0.0,0.0,13059.65,4240.44,0.0,0.0,19469.61,44200.5,33.7682,0.0,0.0,13145.69,4240.44,0.0,0.0,19469.61,44200.5,33.5554,0.0,0.0,13232.36,4240.44,0.0,0.0,19469.61,44200.5,33.3767,0.0,0.0,13326.73,4240.44,0.0,0.0,19469.61,44200.5,33.2526,0.0,0.0,13418.16,4240.44,0.0,0.0,19469.61,44200.5,33.1629,0.0,0.0,13496.46,4240.44,0.0,0.0,19469.61,44200.5,24.0896,0.0,0.0,13562.83,4240.44,0.0,0.0,19469.61,44200.5,23.6913,0.0,0.0,13628.07,4240.44,0.0,0.0,19469.61,44200.5,2.15,12.0,2.18,2.14,107000.0,16.61,18.007499999999993 -2019-12-14 02:00:00-06:00,8902.46,1311.28,3623.68,869.65,10728.48,4959.08,2340.06,33937.61,1202.9,19.0,45.0,48.0,0.0,48.0,48.0,240.0,3.0,44089.8,3930.6,81.47,1133.42,3570.26,4785.15,67.2,1722.7,4500.0,6289.9,100.4,1195.6,3666.9,4962.9,663.4,54.0,2239.2,2956.6,36.7482,0.0,0.0,10720.93,4234.23,0.0,0.0,19155.9,41172.68,36.4809,0.0,0.0,10900.8,4234.23,0.0,0.0,19155.9,41172.68,36.4736,0.0,0.0,10962.49,4234.23,0.0,0.0,19155.9,41172.68,36.4485,0.0,0.0,10988.89,4234.23,0.0,0.0,19155.9,41172.68,36.4338,0.0,0.0,11006.0,4234.23,0.0,0.0,19155.9,41172.68,36.4204,0.0,0.0,11021.95,4234.23,0.0,0.0,19155.9,41172.68,36.4107,0.0,0.0,11034.61,4234.23,0.0,0.0,19155.9,41172.68,36.4022,0.0,0.0,11046.31,4234.23,0.0,0.0,19155.9,41172.68,36.3915,0.0,0.0,11057.75,4234.23,0.0,0.0,19155.9,41172.68,36.3819,0.0,0.0,11066.85,4234.23,0.0,0.0,19155.9,41172.68,36.3765,0.0,0.0,11072.25,4234.23,0.0,0.0,19155.9,41172.68,2.15,12.0,2.18,2.14,107000.0,15.79,18.48249999999999 -2019-12-14 03:00:00-06:00,8896.14,1332.94,3621.97,877.07,10851.75,4998.2,2353.97,34169.44,1237.41,0.0,44.0,46.0,0.0,46.0,46.0,0.0,0.0,43034.8,3930.0,33.23,1141.41,2754.4,3929.04,105.5,1495.4,3592.9,5193.8,28.5,1217.0,2794.8,4040.3,692.1,13.7,1562.3,2268.1,37.5839,0.0,0.0,9816.92,4240.07,0.0,0.0,19110.13,40259.95,36.8577,0.0,0.0,10008.45,4240.07,0.0,0.0,19110.13,40259.95,36.8938,0.0,0.0,10037.91,4240.07,0.0,0.0,19110.13,40259.95,36.8713,0.0,0.0,10040.07,4240.07,0.0,0.0,19110.13,40259.95,36.8651,0.0,0.0,10034.92,4240.07,0.0,0.0,19110.13,40259.95,36.8711,0.0,0.0,10019.94,4240.07,0.0,0.0,19110.13,40259.95,36.8805,0.0,0.0,9996.56,4240.07,0.0,0.0,19110.13,40259.95,36.8897,0.0,0.0,9973.65,4240.07,0.0,0.0,19110.13,40259.95,36.8951,0.0,0.0,9960.02,4240.07,0.0,0.0,19110.13,40259.95,36.9006,0.0,0.0,9946.38,4240.07,0.0,0.0,19110.13,40259.95,36.9119,0.0,0.0,9918.08,4240.07,0.0,0.0,19110.13,40259.95,2.15,12.0,2.18,2.14,107000.0,15.62,19.259999999999994 -2019-12-14 04:00:00-06:00,9013.02,1373.12,3620.9,888.53,11261.83,5133.64,2430.86,35035.69,1313.78,0.0,44.0,46.0,0.0,46.0,46.0,0.0,0.0,41938.3,3933.2,122.35,1027.05,2217.31,3366.71,75.1,1381.4,2479.2,3935.7,101.3,998.5,2210.5,3310.3,544.2,55.1,1258.9,1858.2,38.2664,0.0,0.0,8470.19,4239.84,0.0,0.0,19266.91,39546.14,37.7156,0.0,0.0,8666.61,4239.84,0.0,0.0,19266.91,39546.14,37.7223,0.0,0.0,8642.1,4239.84,0.0,0.0,19266.91,39546.14,37.7028,0.0,0.0,8594.06,4239.84,0.0,0.0,19266.91,39546.14,37.7032,0.0,0.0,8543.56,4239.84,0.0,0.0,19266.91,39546.14,37.7044,0.0,0.0,8484.55,4239.84,0.0,0.0,19266.91,39546.14,37.7291,0.0,0.0,8416.26,4239.84,0.0,0.0,19266.91,39546.14,37.7544,0.0,0.0,8348.35,4239.84,0.0,0.0,19266.91,39546.14,37.7745,0.0,0.0,8287.4,4239.84,0.0,0.0,19266.91,39546.14,37.7893,0.0,0.0,8222.73,4239.84,0.0,0.0,19266.91,39546.14,37.8152,0.0,0.0,8139.45,4239.84,0.0,0.0,19266.91,39546.14,2.15,12.0,2.18,2.14,107000.0,16.82,19.929999999999993 -2019-12-14 05:00:00-06:00,9263.01,1447.77,3638.13,897.23,11767.76,5393.24,2525.04,36311.4,1379.23,0.0,43.0,46.0,0.0,46.0,46.0,360.0,3.0,41952.7,3945.6,203.64,1234.07,2336.77,3774.48,59.0,1272.2,2437.6,3768.8,211.0,1158.1,2386.7,3755.8,660.1,129.1,1294.6,2083.8,38.0265,0.0,0.0,8190.48,4247.78,0.0,0.0,20389.94,40743.0,37.8801,0.0,0.0,8291.72,4247.78,0.0,0.0,20389.94,40743.0,37.8874,0.0,0.0,8224.33,4247.78,0.0,0.0,20389.94,40743.0,37.8898,0.0,0.0,8186.29,4247.78,0.0,0.0,20389.94,40743.0,37.8883,0.0,0.0,8161.07,4247.78,0.0,0.0,20389.94,40743.0,37.8946,0.0,0.0,8117.7,4247.78,0.0,0.0,20389.94,40743.0,37.903,0.0,0.0,8061.36,4247.78,0.0,0.0,20389.94,40743.0,37.9206,0.0,0.0,7983.28,4247.78,0.0,0.0,20389.94,40743.0,37.969,0.0,0.0,7879.82,4247.78,0.0,0.0,20389.94,40743.0,38.0186,0.0,0.0,7775.12,4247.78,0.0,0.0,20389.94,40743.0,38.0984,0.0,0.0,7664.37,4247.78,0.0,0.0,20389.94,40743.0,2.15,12.0,2.18,2.14,107000.0,20.04,19.65999999999999 -2019-12-14 06:00:00-06:00,9679.73,1539.05,3683.11,926.26,12490.68,5762.02,2682.32,38189.51,1426.33,0.0,42.0,45.0,0.0,45.0,45.0,10.0,3.0,44401.2,3824.7,260.18,1451.32,2387.7,4099.2,138.3,1083.5,2610.1,3831.9,238.5,1359.8,2360.6,3958.9,823.3,148.8,1272.2,2244.3,18.091,0.0,0.0,9164.18,4177.07,0.0,0.0,20977.15,42232.47,17.9627,0.0,0.0,9264.26,4177.07,0.0,0.0,20977.15,42232.47,18.1265,0.0,0.0,9085.61,4177.07,0.0,0.0,20977.15,42232.47,19.9448,0.0,0.0,8944.72,4177.07,0.0,0.0,20977.15,42232.47,20.0041,0.0,0.0,8822.09,4177.07,0.0,0.0,20977.15,42232.47,20.0663,0.0,0.0,8702.13,4177.07,0.0,0.0,20977.15,42232.47,20.1329,0.0,0.0,8577.86,4177.07,0.0,0.0,20977.15,42232.47,20.2395,0.0,0.0,8454.58,4177.07,0.0,0.0,20977.15,42232.47,20.367,0.0,0.0,8326.35,4177.07,0.0,0.0,20977.15,42232.47,20.5348,0.0,0.0,8206.56,4177.07,0.0,0.0,20977.15,42232.47,20.7417,0.0,0.0,8090.76,4177.07,0.0,0.0,20977.15,42232.47,2.15,12.0,2.18,2.14,107000.0,23.00,18.19999999999999 -2019-12-14 07:00:00-06:00,9989.91,1618.38,3733.02,954.58,13179.29,6151.59,2792.23,39906.68,1487.67,0.0,45.0,48.0,0.0,48.0,48.0,20.0,3.0,45060.4,3898.8,375.77,1767.47,2422.23,4565.47,240.7,1102.6,2883.5,4226.8,364.9,1719.2,2445.6,4529.7,1099.5,264.6,1320.9,2685.0,19.4075,0.0,0.0,7671.16,4198.18,0.0,0.0,20685.57,43252.06,19.4385,0.0,0.0,7705.05,4198.18,0.0,0.0,20685.57,43252.06,19.649,0.0,0.0,7560.16,4198.18,0.0,0.0,20685.57,43252.06,19.8302,0.0,0.0,7456.77,4198.18,0.0,0.0,20685.57,43252.06,19.9904,0.0,0.0,7371.09,4198.18,0.0,0.0,20685.57,43252.06,21.6125,0.0,0.0,7276.52,4198.18,0.0,0.0,20685.57,43252.06,21.6967,0.0,0.0,7188.51,4198.18,0.0,0.0,20685.57,43252.06,21.8061,0.0,0.0,7110.4,4198.18,0.0,0.0,20685.57,43252.06,21.8536,0.0001,0.0,7039.21,4198.18,0.0,0.0,20685.57,43252.06,21.9479,0.0001,0.0,6978.79,4198.18,0.0,0.0,20685.57,43252.06,22.0442,0.0002,0.0,6926.58,4198.18,0.0,0.0,20685.57,43252.06,2.15,12.0,2.18,2.14,107000.0,26.79,18.354999999999993 -2019-12-14 08:00:00-06:00,10251.55,1639.05,3712.56,983.7,13314.7,6278.94,2854.94,40520.29,1484.87,0.0,49.0,56.0,0.0,56.0,56.0,0.0,5.0,46466.1,3901.0,417.3,1473.47,2533.85,4424.62,327.3,1105.1,2738.8,4171.2,417.2,1474.6,2571.1,4462.9,943.0,309.4,1480.3,2732.7,20.3856,0.0,0.0,7712.59,4147.5,0.0,0.0,20661.01,44488.22,19.8868,0.0,0.0,7803.47,4147.5,0.0,0.0,20661.01,44488.22,19.9307,0.0,0.0,7753.3,4147.5,0.0,0.0,20661.01,44488.22,19.9303,0.0,0.0,7749.43,4147.5,0.0,0.0,20661.01,44488.22,19.9285,0.0,0.0,7764.08,4147.5,0.0,0.0,20661.01,44488.22,19.9259,0.0,0.0,7789.17,4147.5,0.0,0.0,20661.01,44488.22,19.9229,0.0,0.0,7818.99,4147.5,0.0,0.0,20661.01,44488.22,19.8475,0.0,0.0,7852.55,4147.5,0.0,0.0,20661.01,44488.22,19.7679,0.0,0.0,7877.15,4147.5,0.0,0.0,20661.01,44488.22,19.6967,0.0,0.0,7898.35,4147.5,0.0,0.0,20661.01,44488.22,19.6605,0.0,0.0,7924.89,4147.5,0.0,0.0,20661.01,44488.22,2.15,12.0,2.18,2.14,107000.0,30.99,20.01749999999999 -2019-12-14 09:00:00-06:00,10385.53,1556.84,3640.94,1035.86,12805.56,6049.95,2844.73,39694.58,1375.17,19.0,48.0,62.0,0.0,62.0,62.0,70.0,6.0,46987.8,3902.0,283.31,940.56,1920.08,3143.95,352.2,1170.7,2382.3,3905.2,295.7,898.9,1939.9,3134.5,502.6,196.9,1051.6,1751.1,19.1985,0.0,0.0,8132.44,4175.89,0.0,0.0,20617.89,44773.4,19.0512,0.0,0.0,8280.42,4175.89,0.0,0.0,20617.89,44773.4,19.0503,0.0,0.0,8322.55,4175.89,0.0,0.0,20617.89,44773.4,19.0487,0.0,0.0,8356.31,4175.89,0.0,0.0,20617.89,44773.4,19.0419,0.0,0.0,8421.9,4175.89,0.0,0.0,20617.89,44773.4,19.0334,0.0,0.0,8506.89,4175.89,0.0,0.0,20617.89,44773.4,19.0104,0.0,0.0,8600.79,4175.89,0.0,0.0,20617.89,44773.4,18.9503,0.0,0.0,8711.06,4175.89,0.0,0.0,20617.89,44773.4,18.7198,0.0,0.0,8843.46,4175.89,0.0,0.0,20617.89,44773.4,18.583,0.0,0.0,8975.18,4175.89,0.0,0.0,20617.89,44773.4,18.4811,0.0,0.0,9086.26,4175.89,0.0,0.0,20617.89,44773.4,2.15,12.0,2.18,2.14,107000.0,26.45,19.532499999999995 -2019-12-14 11:00:00-06:00,10352.89,1378.16,3564.41,909.7,11718.31,5623.91,2862.87,37657.87,1247.63,0.0,45.0,68.0,0.0,69.0,69.0,100.0,8.0,45326.4,3806.7,189.4,1060.83,3192.31,4442.54,144.4,710.4,2298.8,3153.6,197.6,943.3,3107.5,4248.4,514.9,115.4,1899.8,2530.1,17.8652,0.0,0.0,9768.8,4215.13,0.0,0.0,20294.39,44192.01,18.1042,0.0,0.0,9500.76,4215.13,0.0,0.0,20019.39,43653.91,18.0938,0.0,0.0,9553.33,4215.13,0.0,0.0,20019.39,43653.91,18.0944,0.0,0.0,9601.71,4215.13,0.0,0.0,20019.39,43653.91,18.091,0.0,0.0,9659.9,4215.13,0.0,0.0,20019.39,43653.91,18.085,0.0,0.0,9725.01,4215.13,0.0,0.0,20019.39,43653.91,18.0795,0.0,0.0,9797.25,4215.13,0.0,0.0,20019.39,43653.91,18.0778,0.0,0.0,9863.89,4215.13,0.0,0.0,20019.39,43653.91,18.0722,0.0,0.0,9936.7,4215.13,0.0,0.0,20019.39,43653.91,18.0557,0.0,0.0,10023.96,4215.13,0.0,0.0,20019.39,43653.91,18.0179,0.0,0.0,10114.01,4215.13,0.0,0.0,20019.39,43653.91,2.15,12.0,2.18,2.14,107000.0,22.33,18.124999999999993 -2019-12-14 12:00:00-06:00,10328.17,1310.72,3638.46,854.88,11259.77,5514.39,2948.81,37006.58,1151.37,0.0,45.0,70.0,0.0,72.0,72.0,110.0,7.0,45876.6,3775.1,136.94,1794.45,3773.03,5704.42,204.0,1045.3,2929.3,4178.6,136.0,1719.4,3636.0,5491.4,1073.8,74.4,2349.3,3497.5,17.1039,0.0,0.0,11304.61,4197.17,0.0,0.0,20091.12,44560.33,17.0845,0.0,0.0,11329.83,4197.17,0.0,0.0,20091.12,44560.33,17.0459,0.0,0.0,11453.57,4197.17,0.0,0.0,20091.12,44560.33,17.0225,0.0,0.0,11487.1,4197.17,0.0,0.0,20091.12,44560.33,17.0074,0.0,0.0,11519.6,4197.17,0.0,0.0,20091.12,44560.33,16.9954,0.0,0.0,11537.46,4197.17,0.0,0.0,20091.12,44560.33,16.9846,0.0,0.0,11553.86,4197.17,0.0,0.0,20091.12,44560.33,16.9778,0.0,0.0,11564.41,4197.17,0.0,0.0,20091.12,44560.33,16.9718,0.0,0.0,11573.61,4197.17,0.0,0.0,20091.12,44560.33,16.9612,0.0,0.0,11589.99,4197.17,0.0,0.0,20091.12,44560.33,16.9449,0.0,0.0,11615.01,4197.17,0.0,0.0,20091.12,44560.33,2.15,12.0,2.18,2.14,107000.0,25.92,17.324999999999992 -2019-12-14 13:00:00-06:00,10356.6,1275.83,3762.98,893.68,10839.19,5481.73,3078.1,36719.88,1031.77,0.0,45.0,72.0,0.0,74.0,74.0,130.0,6.0,44984.9,3775.1,140.91,2251.49,4609.66,7002.06,155.9,1525.1,3251.4,4932.4,143.7,2179.5,4365.0,6688.2,1379.3,80.2,2962.1,4421.6,16.7998,0.0,0.0,11670.71,4186.14,0.0,0.0,19652.48,45145.47,16.9261,0.0,0.0,11447.87,4186.14,0.0,0.0,19153.48,44435.47,16.8426,0.0,0.0,11485.52,4186.14,0.0,0.0,19153.48,44435.47,16.8317,0.0,0.0,11495.49,4186.14,0.0,0.0,19153.48,44435.47,16.8268,0.0,0.0,11509.69,4186.14,0.0,0.0,19153.48,44435.47,16.825,0.0,0.0,11514.98,4186.14,0.0,0.0,19153.48,44435.47,16.8246,0.0,0.0,11516.17,4186.14,0.0,0.0,19153.48,44435.47,16.8227,0.0,0.0,11521.83,4186.14,0.0,0.0,19153.48,44435.47,16.8141,0.0,0.0,11546.96,4186.14,0.0,0.0,19153.48,44435.47,16.8013,0.0,0.0,11584.34,4186.14,0.0,0.0,19153.48,44435.47,16.7885,0.0,0.0,11621.86,4186.14,0.0,0.0,19153.48,44435.47,2.15,12.0,2.18,2.14,107000.0,20.86,16.659999999999993 -2019-12-14 15:00:00-06:00,10399.54,1242.21,3719.0,864.12,10447.4,5633.76,3245.31,36615.06,1063.72,0.0,45.0,70.0,0.0,72.0,72.0,130.0,14.0,46545.1,3520.1,93.76,2792.91,4073.47,6960.14,165.1,2656.2,4034.5,6855.8,95.5,2780.5,3992.5,6868.5,1860.4,50.2,2479.0,4389.6,17.3061,0.0,0.0,10964.38,4264.95,0.0,0.0,18610.92,44251.42,16.8475,0.0,0.0,11142.9,4264.95,0.0,0.0,18610.92,44251.42,16.8274,0.0,0.0,11213.3,4264.95,0.0,0.0,18610.92,44251.42,16.7977,0.0,0.0,11218.29,4264.95,0.0,0.0,18610.92,44251.42,16.7889,0.0,0.0,11218.78,4264.95,0.0,0.0,18610.92,44251.42,16.7803,0.0,0.0,11219.17,4264.95,0.0,0.0,18610.92,44251.42,16.7725,0.0,0.0,11216.97,4264.95,0.0,0.0,18610.92,44251.42,16.763,0.0,0.0,11219.48,4264.95,0.0,0.0,18610.92,44251.42,16.7487,0.0,0.0,11236.24,4264.95,0.0,0.0,18610.92,44251.42,16.7339,0.0,0.0,11254.55,4264.95,0.0,0.0,18610.92,44251.42,16.7038,0.0,0.0,11270.33,4264.95,0.0,0.0,18610.92,44251.42,2.15,12.0,2.18,2.14,107000.0,17.38,16.78249999999999 -2019-12-14 16:00:00-06:00,10370.68,1243.57,3708.92,846.56,10551.97,5756.83,3262.52,36865.59,1124.54,0.0,47.0,68.0,0.0,69.0,69.0,130.0,14.0,46103.5,3510.2,123.82,2991.42,3365.65,6480.89,131.3,2901.1,3998.9,7031.3,108.5,3051.9,3415.9,6576.3,2118.4,55.0,2168.5,4341.9,17.0172,0.0,0.0,10762.35,4218.07,0.0,0.0,18727.72,43913.56,16.8611,0.0,0.0,10865.53,4218.07,0.0,0.0,18727.72,43913.56,16.872,0.0,0.0,10826.3,4218.07,0.0,0.0,18727.72,43913.56,16.88,0.0,0.0,10789.43,4218.07,0.0,0.0,18727.72,43913.56,16.8725,0.0,0.0,10775.59,4218.07,0.0,0.0,18727.72,43913.56,16.8575,0.0,0.0,10776.11,4218.07,0.0,0.0,18727.72,43913.56,16.8512,0.0,0.0,10768.88,4218.07,0.0,0.0,18727.72,43913.56,16.8524,0.0,0.0,10740.56,4218.07,0.0,0.0,18727.72,43913.56,16.8518,0.0,0.0,10717.4,4218.07,0.0,0.0,18727.72,43913.56,16.8515,0.0,0.0,10693.27,4218.07,0.0,0.0,18727.72,43913.56,16.8554,0.0,0.0,10672.07,4218.07,0.0,0.0,18727.72,43913.56,2.15,12.0,2.18,2.14,107000.0,17.02,16.89999999999999 -2019-12-14 17:00:00-06:00,10583.54,1310.63,3657.81,888.11,11115.52,5913.36,3211.53,37930.76,1250.26,0.0,47.0,63.0,0.0,63.0,63.0,120.0,10.0,45516.5,3511.3,261.44,3335.98,3375.26,6972.68,155.3,3289.2,3759.7,7204.2,243.8,3268.3,3240.4,6752.5,2337.8,148.7,2060.4,4546.9,18.5065,0.0,0.0,8884.62,4269.22,0.0,0.0,18721.29,42304.97,18.192,0.0,0.0,9001.52,4269.22,0.0,0.0,18721.29,42304.97,18.3166,0.0,0.0,8890.32,4269.22,0.0,0.0,18721.29,42304.97,18.4137,0.0,0.0,8761.22,4269.22,0.0,0.0,18721.29,42304.97,18.5419,0.0,0.0,8600.63,4269.22,0.0,0.0,18721.29,42304.97,18.8829,0.0,0.0,8409.45,4269.22,0.0,0.0,18721.29,42304.97,19.2316,0.0,0.0,8207.29,4269.22,0.0,0.0,18721.29,42304.97,19.7614,0.0,0.0,8004.41,4269.22,0.0,0.0,18721.29,42304.97,20.9265,0.0,0.0,7803.46,4269.22,0.0,0.0,18721.29,42304.97,22.6624,0.0,0.0,7602.18,4269.22,0.0,0.0,18721.29,42304.97,22.6634,0.0,0.0,7440.29,4269.22,0.0,0.0,18721.29,42304.97,2.15,12.0,2.18,2.14,107000.0,20.88,18.487499999999994 -2019-12-14 18:00:00-06:00,10824.49,1361.03,3689.14,933.6,11679.26,6115.65,3257.98,39162.96,1301.82,0.0,50.0,60.0,0.0,60.0,60.0,130.0,8.0,47082.1,3789.5,497.54,4006.88,4742.52,9246.94,331.0,3637.8,4951.3,8920.1,500.3,4033.9,4789.3,9323.5,3085.6,341.1,3377.1,6803.8,18.5317,0.0,0.0,8542.06,4284.26,0.0,0.0,18792.53,44001.08,18.5701,0.0,0.0,8448.09,4284.26,0.0,0.0,18792.53,44001.08,18.6567,0.0,0.0,8405.49,4284.26,0.0,0.0,18792.53,44001.08,18.6932,0.0,0.0,8391.99,4284.26,0.0,0.0,18792.53,44001.08,18.7242,0.0,0.0,8381.21,4284.26,0.0,0.0,18792.53,44001.08,18.7602,0.0,0.0,8368.23,4284.26,0.0,0.0,18792.53,44001.08,18.7648,0.0,0.0,8370.11,4284.26,0.0,0.0,18792.53,44001.08,18.7379,0.0,0.0,8386.86,4284.26,0.0,0.0,18792.53,44001.08,18.6988,0.0,0.0,8409.66,4284.26,0.0,0.0,18792.53,44001.08,18.6582,0.0,0.0,8433.16,4284.26,0.0,0.0,18792.53,44001.08,18.6238,0.0,0.0,8453.85,4284.26,0.0,0.0,18792.53,44001.08,2.15,12.0,2.18,2.14,107000.0,19.24,19.024999999999995 -2019-12-14 19:00:00-06:00,10691.06,1347.15,3657.79,926.8,11566.72,5977.88,3204.7,38674.54,1302.44,0.0,53.0,59.0,0.0,59.0,59.0,130.0,7.0,48022.4,3798.9,588.98,4443.06,6205.2,11237.24,594.1,3912.6,6002.7,10509.4,592.8,4494.5,6525.7,11613.0,3572.4,445.2,4780.4,8798.0,16.4018,0.0,0.0,11429.25,4293.11,0.0,0.0,18836.18,46728.82,16.5425,0.0,0.0,11226.39,4349.1,0.0,0.0,18648.68,46379.82,16.457,0.0,0.0,11269.15,4349.1,0.0,0.0,18648.68,46379.82,16.5193,0.0,0.0,11287.37,4349.1,0.0,0.0,18648.68,46379.82,16.5726,0.0,0.0,11317.23,4349.1,0.0,0.0,18648.68,46379.82,16.5931,0.0,0.0,11363.96,4349.1,0.0,0.0,18648.68,46379.82,16.5856,0.0,0.0,11411.51,4349.1,0.0,0.0,18648.68,46379.82,16.5857,0.0,0.0,11451.74,4349.1,0.0,0.0,18648.68,46379.82,16.5768,0.0,0.0,11500.7,4349.1,0.0,0.0,18648.68,46379.82,16.5341,0.0,0.0,11559.18,4349.1,0.0,0.0,18648.68,46379.82,16.49,0.0,0.0,11601.81,4349.1,0.0,0.0,18648.68,46379.82,2.15,12.0,2.18,2.14,107000.0,16.85,16.9075 -2019-12-14 20:00:00-06:00,10585.6,1350.86,3622.99,922.92,11506.99,5822.58,3091.84,38222.37,1318.59,0.0,55.0,59.0,0.0,59.0,59.0,120.0,6.0,49724.8,3784.9,644.93,4603.22,7394.55,12642.7,740.3,4735.8,8078.1,13554.2,647.6,4697.0,7583.5,12928.1,3767.6,510.1,5537.1,9814.8,15.0554,0.0,0.0,12962.43,4485.26,0.0,0.0,18481.97,47860.71,15.5805,0.0,0.0,12569.69,4485.26,0.0,0.0,18138.97,47332.71,15.5348,0.0,0.0,12624.35,4485.26,0.0,0.0,18138.97,47332.71,15.5035,0.0,0.0,12663.8,4485.26,0.0,0.0,18138.97,47332.71,15.4652,0.0,0.0,12707.54,4485.26,0.0,0.0,18138.97,47332.71,15.4094,0.0,0.0,12757.44,4485.26,0.0,0.0,18138.97,47332.71,15.3603,0.0,0.0,12800.54,4485.26,0.0,0.0,18138.97,47332.71,15.3178,0.0,0.0,12837.77,4485.26,0.0,0.0,18138.97,47332.71,15.29,0.0,0.0,12887.5,4485.26,0.0,0.0,18138.97,47332.71,15.2672,0.0,0.0,12934.71,4485.26,0.0,0.0,18138.97,47332.71,15.2528,0.0,0.0,12974.8,4485.26,0.0,0.0,18138.97,47332.71,2.15,12.0,2.18,2.14,107000.0,16.31,14.892499999999998 -2019-12-14 21:00:00-06:00,10446.99,1337.82,3683.86,914.06,11446.58,5659.08,2970.78,37694.51,1235.33,75.0,57.0,61.0,0.0,61.0,61.0,140.0,8.0,49971.3,3775.5,647.62,4601.86,8223.46,13472.94,695.4,5036.1,9138.8,14870.3,647.9,4653.1,8584.9,13885.9,3639.0,516.9,6521.7,10677.6,15.1543,0.0,0.0,12728.44,4491.13,0.0,0.0,17643.05,47365.21,15.2582,0.0,0.0,12688.93,4491.13,0.0,0.0,17463.05,46890.21,15.1795,0.0,0.0,12766.91,4491.13,0.0,0.0,17463.05,46890.21,15.1172,0.0,0.0,12840.75,4491.13,0.0,0.0,17463.05,46890.21,14.9936,0.0,0.0,12910.71,4491.13,0.0,0.0,17463.05,46890.21,14.9506,0.0,0.0,12988.73,4491.13,0.0,0.0,17463.05,46890.21,14.902,0.0,0.0,13064.46,4491.13,0.0,0.0,17463.05,46890.21,14.8521,0.0,0.0,13141.48,4491.13,0.0,0.0,17463.05,46890.21,14.8015,0.0,0.0,13219.29,4491.13,0.0,0.0,17463.05,46890.21,14.747,0.0,0.0,13305.58,4491.13,0.0,0.0,17463.05,46890.21,14.6815,0.0,0.0,13404.87,4491.13,0.0,0.0,17463.05,46890.21,2.15,12.0,2.18,2.14,107000.0,15.40,14.670000000000002 -2019-12-14 22:00:00-06:00,10180.23,1283.4,3683.26,883.0,11119.9,5428.06,2844.27,36580.49,1158.38,100.0,59.0,63.0,0.0,63.0,63.0,120.0,5.0,45603.0,3931.7,649.72,4566.35,8947.92,14163.99,665.2,4913.9,9335.7,14914.8,645.9,4648.8,9400.5,14695.2,3640.5,507.8,7446.8,11595.1,14.519,0.0,0.0,13611.74,4496.22,0.0,0.0,17437.79,47434.05,14.6583,0.0,0.0,13575.63,4496.22,0.0,0.0,17287.9,47076.65,14.5037,0.0,0.0,13695.11,4496.22,0.0,0.0,17287.9,47076.65,14.3635,0.0,0.0,13813.47,4496.22,0.0,0.0,17287.9,47076.65,14.2354,0.0,0.0,13931.49,4496.22,0.0,0.0,17287.9,47076.65,14.095,0.0,0.0,14050.71,4496.22,0.0,0.0,17287.9,47076.65,13.9426,0.0,0.0,14173.96,4496.22,0.0,0.0,17287.9,47076.65,13.7843,0.0,0.0,14300.71,4496.22,0.0,0.0,17287.9,47076.65,13.6249,0.0,0.0,14419.14,4496.22,0.0,0.0,17287.9,47076.65,13.5548,0.0,0.0,14527.46,4496.22,0.0,0.0,17287.9,47076.65,13.3244,0.0,0.0,14641.31,4496.22,0.0,0.0,17287.9,47076.65,2.15,12.0,2.18,2.14,107000.0,14.59,14.7975 -2019-12-14 23:00:00-06:00,9839.14,1227.72,3690.98,851.91,10665.58,5127.62,2709.66,35213.57,1100.95,100.0,60.0,63.0,0.0,63.0,63.0,0.0,0.0,44716.7,3929.7,637.75,4456.65,9044.52,14138.92,663.5,4635.7,8686.1,13985.3,655.2,4520.9,9491.8,14667.9,3476.4,521.3,7550.9,11548.6,16.3131,0.0,0.0,11466.2,4492.61,0.0,0.0,15302.87,43526.97,16.3104,0.0,0.0,11506.29,4492.61,0.0,0.0,15302.87,43526.97,16.2452,0.0,0.0,11645.03,4492.61,0.0,0.0,15302.87,43526.97,16.1981,0.0,0.0,11779.41,4492.61,0.0,0.0,15302.87,43526.97,16.1508,0.0,0.0,11913.84,4492.61,0.0,0.0,15302.87,43526.97,16.0726,0.0,0.0,12043.94,4492.61,0.0,0.0,15302.87,43526.97,15.6276,0.0,0.0,12173.3,4492.61,0.0,0.0,15302.87,43526.97,15.1421,0.0,0.0,12308.59,4492.61,0.0,0.0,15302.87,43526.97,14.6678,0.0,0.0,12446.31,4492.61,0.0,0.0,15302.87,43526.97,14.4318,0.0,0.0,12573.75,4492.61,0.0,0.0,15302.87,43526.97,14.2839,0.0,0.0,12688.24,4492.61,0.0,0.0,15302.87,43526.97,2.15,12.0,2.18,2.14,107000.0,12.68,16.542500000000004 -2019-12-15 00:00:00-06:00,9498.9,1174.85,3690.92,741.33,10258.0,4862.74,2582.45,33863.34,1054.15,75.0,65.0,70.0,0.0,68.0,68.0,160.0,6.0,43859.0,3956.4,595.3,4398.8,9014.05,14008.15,661.2,4476.3,8863.1,14000.6,598.7,4470.8,9325.4,14394.9,3466.8,458.0,7229.6,11154.4,14.7691,0.0,0.0,12518.59,4489.94,0.0,0.0,15324.08,43182.66,14.7666,0.0,0.0,12557.57,4489.94,0.0,0.0,15324.08,43182.66,14.6095,0.0,0.0,12673.45,4489.94,0.0,0.0,15324.08,43182.66,14.4623,0.0,0.0,12776.85,4489.94,0.0,0.0,15324.08,43182.66,14.339,0.0,0.0,12869.74,4489.94,0.0,0.0,15324.08,43182.66,14.2312,0.0,0.0,12961.77,4489.94,0.0,0.0,15324.08,43182.66,14.1108,0.0,0.0,13057.59,4489.94,0.0,0.0,15324.08,43182.66,13.9382,0.0,0.0,13150.08,4489.94,0.0,0.0,15324.08,43182.66,13.7731,0.0,0.0,13231.33,4489.94,0.0,0.0,15324.08,43182.66,13.615,0.0,0.0,13310.89,4489.94,0.0,0.0,15324.08,43182.66,13.558,0.0,0.0,13395.09,4489.94,0.0,0.0,15324.08,43182.66,2.12,4.0,2.12,2.12,40000.0,12.76,14.935000000000004 -2019-12-15 01:00:00-06:00,9221.47,1150.14,3670.5,683.79,10045.26,4693.2,2502.07,33029.94,1063.51,75.0,66.0,72.0,0.0,69.0,69.0,180.0,11.0,43068.3,3970.5,631.56,4388.58,8892.63,13912.77,657.4,4359.2,8455.1,13471.7,617.3,4442.6,8992.1,14052.0,3479.1,470.7,6853.9,10803.7,13.7482,0.0,0.0,12333.43,4489.54,0.0,0.0,14937.75,41940.13,13.8296,0.0,0.0,12299.29,4489.54,0.0,0.0,14937.75,41940.13,13.7092,0.0,0.0,12367.24,4489.54,0.0,0.0,14937.75,41940.13,13.5829,0.0,0.0,12430.3,4489.54,0.0,0.0,14937.75,41940.13,13.5629,0.0,0.0,12489.89,4489.54,0.0,0.0,14937.75,41940.13,13.4426,0.0,0.0,12550.83,4489.54,0.0,0.0,14937.75,41940.13,13.3362,0.0,0.0,12612.08,4489.54,0.0,0.0,14937.75,41940.13,13.2341,0.0,0.0,12667.61,4489.54,0.0,0.0,14937.75,41940.13,13.1479,0.0,0.0,12714.44,4489.54,0.0,0.0,14937.75,41940.13,13.0646,0.0,0.0,12759.89,4489.54,0.0,0.0,14937.75,41940.13,12.9834,0.0,0.0,12804.56,4489.54,0.0,0.0,14937.75,41940.13,2.12,4.0,2.12,2.12,40000.0,10.15,13.450000000000003 -2019-12-15 03:00:00-06:00,8947.54,1106.62,3595.01,668.91,9856.76,4577.64,2397.84,32280.48,1130.16,75.0,66.0,72.0,0.0,70.0,70.0,170.0,8.0,43257.6,3939.2,638.81,4307.64,8100.37,13046.82,579.4,4473.9,8276.9,13330.2,635.4,4335.9,8171.1,13142.4,3390.4,497.9,6335.9,10224.2,13.1939,0.0,0.0,12828.75,4481.11,0.0,0.0,14748.95,41403.84,13.0325,0.0,0.0,12909.52,4481.11,0.0,0.0,14748.95,41403.84,13.0059,0.0,0.0,12919.25,4481.11,0.0,0.0,14748.95,41403.84,12.9795,0.0,0.0,12932.52,4481.11,0.0,0.0,14748.95,41403.84,12.9648,0.0,0.0,12941.5,4481.11,0.0,0.0,14748.95,41403.84,12.9651,0.0,0.0,12941.31,4481.11,0.0,0.0,14748.95,41403.84,12.9799,0.0,0.0,12932.31,4481.11,0.0,0.0,14748.95,41403.84,12.9983,0.0,0.0,12922.16,4481.11,0.0,0.0,14748.95,41403.84,13.0009,0.0,0.0,12920.74,4481.11,0.0,0.0,14748.95,41403.84,12.998,0.0,0.0,12922.34,4481.11,0.0,0.0,14748.95,41403.84,13.0064,0.0,0.0,12917.74,4481.11,0.0,0.0,14748.95,41403.84,2.12,4.0,2.12,2.12,40000.0,8.64,12.929999999999996 -2019-12-15 06:00:00-06:00,9077.42,1159.0,3588.42,880.21,10350.96,5014.88,2434.45,33810.16,1304.82,75.0,66.0,72.0,0.0,70.0,70.0,170.0,10.0,45413.1,3912.0,692.93,4467.74,7164.99,12325.66,568.3,4357.0,7601.2,12526.5,701.9,4520.9,7214.1,12436.9,3511.7,527.9,5445.2,9484.8,12.6157,0.0,0.0,12978.53,4304.28,0.0,0.0,16326.12,42851.57,12.3133,0.0,0.0,13086.69,4304.28,0.0,0.0,16326.12,42851.57,12.3967,0.0,0.0,13020.64,4304.28,0.0,0.0,16326.12,42851.57,12.6956,0.0,0.0,12927.54,4304.28,0.0,0.0,16326.12,42851.57,12.9425,0.0,0.0,12844.38,4304.28,0.0,0.0,16326.12,42851.57,13.0916,0.0,0.0,12771.01,4304.28,0.0,0.0,16326.12,42851.57,13.1727,0.0,0.0,12702.03,4304.28,0.0,0.0,16326.12,42851.57,13.2665,0.0,0.0,12626.35,4304.28,0.0,0.0,16326.12,42851.57,13.3736,0.0,0.0,12539.91,4304.28,0.0,0.0,16326.12,42851.57,13.4845,0.0,0.0,12445.3,4304.28,0.0,0.0,16326.12,42851.57,13.5726,0.0,0.0,12343.7,4304.28,0.0,0.0,16326.12,42851.57,2.12,4.0,2.12,2.12,40000.0,15.31,12.684999999999999 -2019-12-15 08:00:00-06:00,9593.04,1246.88,3593.79,965.16,11078.97,5559.1,2583.85,35988.25,1367.48,50.0,67.0,73.0,0.0,72.0,72.0,170.0,9.0,47188.1,3927.3,570.57,4169.62,6681.46,11421.65,573.0,4291.2,6750.9,11615.1,585.5,4296.2,6812.0,11693.7,3290.7,434.1,5072.6,8797.4,13.6832,0.0,0.0,12439.78,4302.5,0.0,0.0,17160.36,44372.48,13.8847,0.0,0.0,12568.73,4302.5,0.0,0.0,17160.36,44372.48,14.1634,0.0,0.0,12432.43,4302.5,0.0,0.0,17160.36,44372.48,14.2464,0.0,0.0,12314.94,4302.5,0.0,0.0,17160.36,44372.48,14.3436,0.0,0.0,12203.6,4302.5,0.0,0.0,17160.36,44372.48,14.447,0.0,0.0,12096.02,4302.5,0.0,0.0,17160.36,44372.48,14.5374,0.0,0.0,12003.52,4302.5,0.0,0.0,17160.36,44372.48,14.619,0.0,0.0,11922.27,4302.5,0.0,0.0,17160.36,44372.48,14.7377,0.0,0.0,11829.43,4302.5,0.0,0.0,17160.36,44372.48,14.9164,0.0,0.0,11702.14,4302.5,0.0,0.0,17160.36,44372.48,15.0402,0.0,0.0,11607.62,4302.5,0.0,0.0,17160.36,44372.48,2.12,4.0,2.12,2.12,40000.0,16.24,14.024999999999999 -2019-12-15 10:00:00-06:00,10725.33,1265.24,3474.73,1006.7,10913.17,5654.54,2907.08,37252.39,1305.6,75.0,67.0,81.0,0.0,79.0,79.0,180.0,14.0,47360.3,3801.2,203.43,3803.54,4954.24,8961.21,342.8,3610.8,5311.1,9264.7,217.6,3821.5,4882.3,8921.4,2916.6,133.6,3361.2,6411.4,16.4392,0.0,0.0,11177.02,4268.59,0.0,0.0,17947.82,44910.96,16.4006,0.0,0.0,11244.67,4268.59,0.0,0.0,17947.82,44910.96,16.4328,0.0,0.0,11187.09,4268.59,0.0,0.0,17947.82,44910.96,16.4403,0.0,0.0,11141.27,4268.59,0.0,0.0,17947.82,44910.96,16.4453,0.0,0.0,11119.72,4268.59,0.0,0.0,17947.82,44910.96,16.447,0.0,0.0,11128.69,4268.59,0.0,0.0,17947.82,44910.96,16.4492,0.0,0.0,11133.5,4268.59,0.0,0.0,17947.82,44910.96,16.4705,0.0,0.0,11129.92,4268.59,0.0,0.0,17947.82,44910.96,16.4969,0.0,0.0,11130.43,4268.59,0.0,0.0,17947.82,44910.96,16.5397,0.0,0.0,11115.67,4268.59,0.0,0.0,17947.82,44910.96,16.5629,0.0,0.0,11119.12,4268.59,0.0,0.0,17947.82,44910.96,2.12,4.0,2.12,2.12,40000.0,17.16,16.519999999999996 -2019-12-15 11:00:00-06:00,11273.91,1271.53,3446.27,999.26,10728.72,5493.58,3084.89,37607.81,1309.65,50.0,65.0,82.0,0.0,81.0,81.0,190.0,15.0,46776.6,3801.2,133.88,3973.35,6189.87,10297.1,227.8,3426.0,4615.7,8269.5,134.2,3985.5,5914.8,10034.5,3005.7,70.0,4101.3,7177.0,16.6249,0.0,0.0,11057.8,4254.35,0.0,0.0,18066.47,44907.27,16.6256,0.0,0.0,11092.02,4254.35,0.0,0.0,18066.47,44907.27,16.6312,0.0,0.0,11071.76,4254.35,0.0,0.0,18066.47,44907.27,16.6693,0.0,0.0,11050.31,4254.35,0.0,0.0,18066.47,44907.27,16.7016,0.0,0.0,11033.29,4254.35,0.0,0.0,18066.47,44907.27,16.7337,0.0,0.0,11016.9,4254.35,0.0,0.0,18066.47,44907.27,16.7511,0.0,0.0,10991.74,4254.35,0.0,0.0,18066.47,44907.27,16.7701,0.0,0.0,10962.21,4254.35,0.0,0.0,18066.47,44907.27,16.7887,0.0,0.0,10933.61,4254.35,0.0,0.0,18066.47,44907.27,16.8083,0.0,0.0,10902.19,4254.35,0.0,0.0,18066.47,44907.27,16.8207,0.0,0.0,10866.59,4254.35,0.0,0.0,18066.47,44907.27,2.12,4.0,2.12,2.12,40000.0,19.51,16.715 -2019-12-15 13:00:00-06:00,11875.59,1330.41,3469.83,979.83,10617.16,5568.43,3372.58,38509.53,1295.69,75.0,64.0,84.0,0.0,82.0,82.0,210.0,14.0,48619.9,3789.3,124.29,3641.2,7917.17,11682.66,113.7,3738.1,6179.0,10030.8,126.7,3678.6,8088.0,11893.3,2796.9,73.6,5846.8,8717.3,14.9082,0.0,0.0,12846.72,4216.91,0.0,0.0,18207.68,47828.17,14.8129,0.0,0.0,12889.46,4216.91,0.0,0.0,18207.68,47828.17,14.8501,0.0,0.0,12849.87,4216.91,0.0,0.0,18207.68,47828.17,14.8749,0.0,0.0,12820.33,4216.91,0.0,0.0,18207.68,47828.17,14.9302,0.0,0.0,12754.27,4216.91,0.0,0.0,18207.68,47828.17,14.9838,0.0,0.0,12692.68,4216.91,0.0,0.0,18207.68,47828.17,15.0322,0.0,0.0,12638.82,4216.91,0.0,0.0,18207.68,47828.17,15.0769,0.0,0.0,12589.08,4216.91,0.0,0.0,18207.68,47828.17,15.1068,0.0,0.0,12556.45,4216.91,0.0,0.0,18207.68,47828.17,15.1402,0.0,0.0,12525.38,4216.91,0.0,0.0,18207.68,47828.17,15.1744,0.0,0.0,12493.91,4216.91,0.0,0.0,18207.68,47828.17,2.12,4.0,2.12,2.12,40000.0,19.23,14.857499999999991 -2019-12-15 14:00:00-06:00,12028.45,1356.31,3468.7,889.98,10631.94,5679.95,3487.79,38869.23,1326.12,50.0,64.0,86.0,0.0,84.0,84.0,180.0,15.0,49304.1,3528.2,161.31,3689.73,7804.77,11655.81,114.9,3719.0,7167.9,11001.8,152.1,3718.7,7790.5,11661.3,2816.4,94.4,5767.2,8678.0,16.4257,0.0,0.0,11882.09,4210.25,0.0,0.0,18210.14,47125.16,16.3706,0.0,0.0,11887.98,4210.25,0.0,0.0,18210.14,47125.16,16.583,0.0,0.0,11811.43,4210.25,0.0,0.0,18210.14,47125.16,16.7285,0.0,0.0,11735.71,4210.25,0.0,0.0,18210.14,47125.16,16.7415,0.0,0.0,11689.11,4210.25,0.0,0.0,18210.14,47125.16,16.7462,0.0,0.0,11654.21,4210.25,0.0,0.0,18210.14,47125.16,16.7502,0.0,0.0,11621.1,4210.25,0.0,0.0,18210.14,47125.16,16.7523,0.0,0.0,11602.75,4210.25,0.0,0.0,18210.14,47125.16,16.753,0.0,0.0,11596.95,4210.25,0.0,0.0,18210.14,47125.16,16.7534,0.0,0.0,11594.27,4210.25,0.0,0.0,18210.14,47125.16,16.7544,0.0,0.0,11585.55,4210.25,0.0,0.0,18210.14,47125.16,2.12,4.0,2.12,2.12,40000.0,19.23,15.80249999999999 -2019-12-15 17:00:00-06:00,12212.97,1429.74,3454.98,881.02,11287.22,6263.66,3484.95,40533.89,1519.34,75.0,66.0,79.0,0.0,77.0,77.0,170.0,9.0,49771.4,3528.5,480.27,4629.56,8379.1,13488.93,387.2,4217.7,8335.9,12940.8,429.7,4650.9,8486.6,13567.2,3654.0,296.2,6267.9,10218.1,16.2998,0.0,0.0,11691.69,4221.34,0.0,0.0,18180.32,47771.41,16.2295,0.0,0.0,11694.23,4221.34,0.0,0.0,18180.32,47771.41,16.3595,0.0,0.0,11570.39,4221.34,0.0,0.0,18180.32,47771.41,16.4681,0.0,0.0,11409.87,4221.34,0.0,0.0,18180.32,47771.41,16.6016,0.0,0.0,11223.33,4221.34,0.0,0.0,18180.32,47771.41,16.7292,0.0,0.0,11009.89,4221.34,0.0,0.0,18180.32,47771.41,16.8716,0.0,0.0,10796.7,4221.34,0.0,0.0,18180.32,47771.41,16.9691,0.0,0.0,10579.41,4221.34,0.0,0.0,18180.32,47771.41,17.1124,0.0,0.0,10375.55,4221.34,0.0,0.0,18180.32,47771.41,17.328,0.0,0.0,10190.59,4221.34,0.0,0.0,18180.32,47771.41,17.4837,0.0,0.0,10050.1,4221.34,0.0,0.0,18180.32,47771.41,2.12,4.0,2.12,2.12,40000.0,21.60,15.699999999999987 -2019-12-15 18:00:00-06:00,12542.89,1478.27,3550.84,956.75,11923.97,6595.29,3590.11,42176.84,1538.72,75.0,67.0,77.0,0.0,76.0,76.0,170.0,13.0,50016.2,3804.6,672.76,4910.45,8589.91,14173.12,504.6,4732.7,8143.6,13380.9,691.8,4951.8,8651.0,14294.6,3948.1,528.4,6383.8,10860.3,27.7348,0.0,0.0,9429.28,4230.39,0.0,0.0,18091.27,47885.22,27.6199,0.0,0.0,9463.45,4230.39,0.0,0.0,18091.27,47885.22,27.692,0.0,0.0,9400.57,4230.39,0.0,0.0,18091.27,47885.22,27.6884,0.0,0.0,9359.49,4230.39,0.0,0.0,18091.27,47885.22,27.6736,0.0,0.0,9331.7,4230.39,0.0,0.0,18091.27,47885.22,27.6543,0.0,0.0,9309.28,4230.39,0.0,0.0,18091.27,47885.22,27.6305,0.0,0.0,9292.15,4230.39,0.0,0.0,18091.27,47885.22,27.6028,0.0,0.0,9279.67,4230.39,0.0,0.0,18091.27,47885.22,27.5718,0.0,0.0,9271.13,4230.39,0.0,0.0,18091.27,47885.22,27.574,0.0,0.0,9261.76,4230.39,0.0,0.0,18091.27,47885.22,27.5736,0.0,0.0,9257.28,4230.39,0.0,0.0,18091.27,47885.22,2.12,4.0,2.12,2.12,40000.0,18.81,18.73749999999999 -2019-12-15 19:00:00-06:00,12482.63,1465.93,3608.86,1057.61,11980.35,6567.71,3579.65,42213.73,1470.98,75.0,69.0,78.0,0.0,75.0,75.0,170.0,10.0,49392.8,3796.0,652.28,5129.92,8360.01,14142.21,670.2,4910.2,8318.1,13898.5,648.4,5192.0,8432.5,14272.9,4208.4,491.7,6087.3,10787.4,34.5809,0.0,0.0,9642.88,4242.13,0.0,0.0,18146.89,48630.32,34.4273,0.0,0.0,9774.07,4242.13,0.0,0.0,18146.89,48630.32,34.423,0.0,0.0,9797.74,4242.13,0.0,0.0,18146.89,48630.32,34.4148,0.0,0.0,9818.2,4242.13,0.0,0.0,18146.89,48630.32,34.4085,0.0,0.0,9842.24,4242.13,0.0,0.0,18146.89,48630.32,34.4066,0.0,0.0,9869.42,4242.13,0.0,0.0,18146.89,48630.32,34.4045,0.0,0.0,9897.92,4242.13,0.0,0.0,18146.89,48630.32,25.7349,0.0,0.0,9952.08,4242.13,0.0,0.0,18146.89,48630.32,25.7373,0.0,0.0,9999.77,4242.13,0.0,0.0,18146.89,48630.32,25.6733,0.0,0.0,10043.97,4242.13,0.0,0.0,18146.89,48630.32,25.6646,0.0,0.0,10079.91,4242.13,0.0,0.0,18146.89,48630.32,2.12,4.0,2.12,2.12,40000.0,17.09,19.549999999999994 -2019-12-15 21:00:00-06:00,11976.06,1378.13,3637.55,971.58,11678.09,6156.86,3426.06,40568.82,1344.48,100.0,69.0,76.0,0.0,74.0,74.0,170.0,9.0,47334.4,3786.9,736.47,5285.26,7830.84,13852.57,609.4,5084.6,7237.2,12931.2,728.1,5314.3,7910.8,13953.2,4348.5,568.5,5620.7,10537.7,18.2665,0.0,0.0,10108.67,4432.27,0.0,0.0,17645.59,47855.05,18.3206,0.0,0.0,10147.3,4432.27,0.0,0.0,17645.59,47855.05,18.2387,0.0,0.0,10238.11,4432.27,0.0,0.0,17645.59,47855.05,18.219,0.0,0.0,10322.13,4432.27,0.0,0.0,17645.59,47855.05,18.2082,0.0,0.0,10419.93,4432.27,0.0,0.0,17645.59,47855.05,18.197,0.0,0.0,10527.15,4432.27,0.0,0.0,17645.59,47855.05,18.1834,0.0,0.0,10651.16,4432.27,0.0,0.0,17645.59,47855.05,16.3767,0.0,0.0,10794.92,4432.27,0.0,0.0,17645.59,47855.05,16.3444,0.0,0.0,10927.6,4432.27,0.0,0.0,17645.59,47855.05,16.3375,0.0,0.0,11071.6,4432.27,0.0,0.0,17645.59,47855.05,16.2596,0.0,0.0,11213.94,4432.27,0.0,0.0,17645.59,47855.05,2.12,4.0,2.12,2.12,40000.0,18.17,17.169999999999987 -2019-12-15 22:00:00-06:00,11403.93,1269.76,3642.78,898.89,11018.22,5722.49,3264.34,38461.96,1241.55,75.0,69.0,76.0,0.0,74.0,74.0,170.0,7.0,45203.5,3900.4,692.72,5188.95,6603.66,12485.33,591.0,5025.0,6596.3,12212.3,718.1,5261.6,6636.5,12616.2,4304.2,565.5,4462.7,9332.4,26.2168,0.0,0.0,9908.37,4433.26,0.0,0.0,17056.27,45950.73,26.4915,0.0,0.0,9683.44,4433.26,0.0,0.0,16736.27,45404.73,26.2231,0.0,0.0,9884.83,4433.26,0.0,0.0,16736.27,45404.73,25.9743,0.0,0.0,10089.25,4433.26,0.0,0.0,16736.27,45404.73,25.9085,0.0,0.0,10288.91,4433.26,0.0,0.0,16736.27,45404.73,25.8307,0.0,0.0,10497.08,4433.26,0.0,0.0,16736.27,45404.73,21.0525,0.0,0.0,10700.64,4433.26,0.0,0.0,16736.27,45404.73,16.5754,0.0,0.0,10908.32,4433.26,0.0,0.0,16736.27,45404.73,16.5642,0.0,0.0,11108.77,4433.26,0.0,0.0,16736.27,45404.73,16.4883,0.0,0.0,11301.46,4433.26,0.0,0.0,16736.27,45404.73,16.369,0.0,0.0,11499.58,4433.26,0.0,0.0,16736.27,45404.73,2.12,4.0,2.12,2.12,40000.0,15.89,18.29499999999999 -2019-12-15 23:00:00-06:00,10748.55,1165.75,3681.1,872.7,10261.45,5253.94,3064.11,36189.83,1142.23,75.0,69.0,76.0,0.0,74.0,74.0,170.0,11.0,44679.0,3896.5,510.68,5063.97,6296.75,11871.4,688.8,5026.5,6006.0,11721.3,515.6,5100.4,6137.9,11753.9,4173.4,394.0,3988.2,8555.6,17.4825,0.0,0.0,9601.86,4438.05,0.0,0.0,16365.59,43240.45,17.2535,0.0,0.0,9756.34,4438.05,0.0,0.0,16365.59,43240.45,16.982,0.0,0.0,9976.41,4438.05,0.0,0.0,16365.59,43240.45,16.716,0.0,0.0,10198.71,4438.05,0.0,0.0,16365.59,43240.45,16.6267,0.0,0.0,10412.0,4438.05,0.0,0.0,16365.59,43240.45,16.448,0.0,0.0,10614.33,4438.05,0.0,0.0,16365.59,43240.45,16.3388,0.0,0.0,10811.79,4438.05,0.0,0.0,16365.59,43240.45,16.2565,0.0,0.0,11005.45,4438.05,0.0,0.0,16365.59,43240.45,16.18,0.0,0.0,11196.03,4438.05,0.0,0.0,16365.59,43240.45,16.1322,0.0,0.0,11373.53,4438.05,0.0,0.0,16365.59,43240.45,16.0778,0.0,0.0,11534.66,4438.05,0.0,0.0,16365.59,43240.45,2.12,4.0,2.12,2.12,40000.0,14.84,17.507499999999993 -2019-12-16 00:00:00-06:00,10203.4,1085.48,3626.61,842.88,9811.99,4853.9,2909.26,34480.38,1146.86,75.0,69.0,76.0,0.0,74.0,74.0,170.0,10.0,43091.4,3855.7,412.8,4986.2,6200.94,11599.94,640.4,4892.4,5104.3,10637.1,421.4,4947.5,6108.4,11477.3,4018.1,305.6,3981.0,8304.7,16.5804,0.0,0.0,11446.86,4451.18,0.0,0.0,16288.42,43620.18,16.3133,0.0,0.0,11558.74,4451.18,0.0,0.0,16288.42,43620.18,16.2279,0.0,0.0,11707.46,4451.18,0.0,0.0,16288.42,43620.18,15.5316,0.0,0.0,11973.42,4451.18,0.0,0.0,16288.42,43620.18,15.3046,0.0,0.0,12097.93,4451.18,0.0,0.0,16288.42,43620.18,15.1238,0.0,0.0,12218.52,4451.18,0.0,0.0,16288.42,43620.18,14.9751,0.0,0.0,12338.42,4451.18,0.0,0.0,16288.42,43620.18,14.8002,0.0,0.0,12453.02,4451.18,0.0,0.0,16288.42,43620.18,14.6136,0.0,0.0,12561.32,4451.18,0.0,0.0,16288.42,43620.18,14.3375,0.0,0.0,12666.3,4451.18,0.0,0.0,16288.42,43620.18,14.2267,0.0,0.0,12767.11,4451.18,0.0,0.0,16288.42,43620.18,2.245,22.0,2.27,2.235,139000.0,14.13,15.747499999999993 -2019-12-16 02:00:00-06:00,9684.51,1031.88,3672.98,779.65,9706.22,4501.64,2684.63,33183.68,1122.18,75.0,69.0,76.0,0.0,73.0,73.0,160.0,6.0,42855.9,3851.7,343.32,4715.84,6001.91,11061.07,393.5,4458.7,5182.4,10034.6,328.6,4719.6,6000.1,11048.3,3763.3,210.4,3960.4,7934.1,14.5739,0.0,0.0,12165.71,4472.05,0.0,0.0,16374.66,42790.95,14.2892,0.0,0.0,12284.32,4472.05,0.0,0.0,16374.66,42790.95,14.1963,0.0,0.0,12350.43,4472.05,0.0,0.0,16374.66,42790.95,14.073,0.0,0.0,12444.67,4472.05,0.0,0.0,16374.66,42790.95,13.9537,0.0,0.0,12537.45,4472.05,0.0,0.0,16374.66,42790.95,13.8874,0.0,0.0,12591.4,4472.05,0.0,0.0,16374.66,42790.95,13.8563,0.0,0.0,12620.1,4472.05,0.0,0.0,16374.66,42790.95,13.8302,0.0,0.0,12645.48,4472.05,0.0,0.0,16374.66,42790.95,13.8042,0.0,0.0,12670.78,4472.05,0.0,0.0,16374.66,42790.95,13.7831,0.0,0.0,12692.16,4472.05,0.0,0.0,16374.66,42790.95,13.758,0.0,0.0,12708.7,4472.05,0.0,0.0,16374.66,42790.95,2.245,22.0,2.27,2.235,139000.0,14.51,14.747499999999995 -2019-12-16 03:00:00-06:00,9638.92,1035.49,3709.7,798.87,9975.93,4451.2,2614.51,33353.31,1128.68,75.0,69.0,76.0,0.0,74.0,74.0,160.0,9.0,43017.8,3956.0,520.96,4304.26,6129.38,10954.6,470.7,4409.8,5258.4,10138.9,503.9,4334.6,5993.7,10832.2,3367.0,366.1,3980.7,7713.8,14.0963,0.0,0.0,12832.13,4475.2,0.0,0.0,16701.83,43492.08,13.851,0.0,0.0,13021.45,4475.2,0.0,0.0,16701.83,43492.08,13.7243,0.0,0.0,13122.17,4475.2,0.0,0.0,16701.83,43492.08,13.5859,0.0,0.0,13228.39,4475.2,0.0,0.0,16701.83,43492.08,13.5085,0.0,0.0,13284.17,4475.2,0.0,0.0,16701.83,43492.08,13.4838,0.0,0.0,13333.43,4475.2,0.0,0.0,16701.83,43492.08,13.4922,0.0,0.0,13327.55,4475.2,0.0,0.0,16701.83,43492.08,13.4988,0.0,0.0,13305.04,4475.2,0.0,0.0,16701.83,43492.08,13.5107,0.0,0.0,13282.4,4475.2,0.0,0.0,16701.83,43492.08,13.5479,0.0,0.0,13256.19,4475.2,0.0,0.0,16701.83,43492.08,13.6061,0.0,0.0,13215.47,4475.2,0.0,0.0,16701.83,43492.08,2.245,22.0,2.27,2.235,139000.0,15.11,14.162499999999998 -2019-12-16 04:00:00-06:00,9826.17,1071.22,3804.42,871.82,10621.78,4548.54,2594.38,34461.17,1122.82,100.0,69.0,76.0,0.0,73.0,73.0,170.0,8.0,43134.3,3956.2,602.95,3927.37,6487.24,11017.56,508.1,4072.9,5263.8,9844.8,602.0,3917.1,6394.9,10914.0,2962.9,459.0,4374.6,7796.5,14.314,0.0,0.0,13063.88,4472.99,0.0,0.0,16977.8,43896.07,14.1323,0.0,0.0,13098.61,4472.99,0.0,0.0,16977.8,43896.07,14.1979,0.0,0.0,13021.92,4472.99,0.0,0.0,16977.8,43896.07,14.2337,0.0,0.0,12960.5,4472.99,0.0,0.0,16977.8,43896.07,14.2785,0.0,0.0,12915.09,4472.99,0.0,0.0,16977.8,43896.07,14.341,0.0,0.0,12869.53,4472.99,0.0,0.0,16977.8,43896.07,14.4224,0.0,0.0,12802.69,4472.99,0.0,0.0,16977.8,43896.07,16.0548,0.0,0.0,12699.58,4472.99,0.0,0.0,16977.8,43896.07,16.5006,0.0,0.0,12593.57,4472.99,0.0,0.0,16977.8,43896.07,18.4833,0.0,0.0,12482.99,4472.99,0.0,0.0,16977.8,43896.07,19.7226,0.0,0.0,12348.83,4472.99,0.0,0.0,16977.8,43896.07,2.245,22.0,2.27,2.235,139000.0,15.77,14.377500000000005 -2019-12-16 05:00:00-06:00,10350.84,1166.04,3950.92,937.38,11860.28,4918.08,2725.87,37049.33,1139.91,100.0,70.0,76.0,0.0,73.0,73.0,160.0,9.0,43905.2,3958.3,569.85,3808.04,6840.23,11218.12,538.4,3569.1,5603.0,9710.5,562.9,3922.4,6769.4,11254.7,2948.4,411.5,4774.9,8134.8,16.2502,0.0,0.0,12071.08,4477.95,0.0,0.0,18033.64,45631.86,15.0467,0.0,0.0,12395.29,4477.95,0.0,0.0,18033.64,45631.86,15.642,0.0,0.0,12190.26,4477.95,0.0,0.0,18033.64,45631.86,16.0897,0.0,0.0,12021.58,4477.95,0.0,0.0,18033.64,45631.86,17.094,0.0,0.0,11855.15,4477.95,0.0,0.0,18033.64,45631.86,17.8914,0.0,0.0,11710.34,4477.95,0.0,0.0,18033.64,45631.86,18.0853,0.0,0.0,11528.42,4477.95,0.0,0.0,18033.64,45631.86,19.0328,0.0,0.0,11299.2,4477.95,0.0,0.0,18033.64,45631.86,20.0784,0.0,0.0,11042.98,4477.95,0.0,0.0,18033.64,45631.86,21.4378,0.0,0.0,10814.96,4477.95,0.0,0.0,18033.64,45631.86,21.7032,0.0,0.0,10587.03,4477.95,0.0,0.0,18033.64,45631.86,2.245,22.0,2.27,2.235,139000.0,17.38,15.000000000000004 -2019-12-16 06:00:00-06:00,11089.17,1325.75,4120.32,1068.51,13596.6,5570.84,2996.43,40993.46,1225.85,100.0,70.0,76.0,0.0,74.0,74.0,160.0,7.0,48510.2,3841.6,602.52,3245.27,6788.87,10636.66,604.3,3028.2,6212.5,9845.0,593.6,3300.9,6677.4,10571.9,2464.0,437.1,4726.1,7627.2,15.795,0.0,0.0,12348.65,4124.3,0.0,0.0,19266.96,48324.93,15.8403,0.0,0.0,12370.84,4124.3,0.0,0.0,19266.96,48324.93,16.4204,0.0,0.0,11986.24,4124.3,0.0,0.0,19266.96,48324.93,16.7415,0.0,0.0,11631.56,4124.3,0.0,0.0,19266.96,48324.93,17.0193,0.0,0.0,11327.39,4124.3,0.0,0.0,19266.96,48324.93,17.2443,0.0,0.0,11057.53,4124.3,0.0,0.0,19266.96,48324.93,17.3408,0.0,0.0,10819.08,4124.3,0.0,0.0,19266.96,48324.93,17.4421,0.0,0.0,10602.38,4124.3,0.0,0.0,19266.96,48324.93,17.8022,0.0,0.0,10382.64,4124.3,0.0,0.0,19266.96,48324.93,18.4575,0.0,0.0,10198.83,4124.3,0.0,0.0,19266.96,48324.93,19.1078,0.0,0.0,10047.19,4124.3,0.0,0.0,19266.96,48324.93,2.245,22.0,2.27,2.235,139000.0,28.25,16.695000000000004 -2019-12-16 08:00:00-06:00,11576.21,1460.11,3937.84,1137.65,14807.55,6046.97,3063.38,43485.15,1455.43,100.0,70.0,78.0,0.0,75.0,75.0,170.0,9.0,49352.6,3866.1,488.46,2242.9,5212.7,7944.06,641.8,2313.2,5612.3,8567.3,494.6,2273.4,5045.4,7813.4,1660.5,351.5,3255.7,5267.7,30.7655,0.0002,0.0,6929.39,4196.36,0.0,0.0,19657.08,47043.17,21.6172,0.0,0.0,7196.1,4196.36,0.0,0.0,19657.08,47043.17,21.9506,0.0,0.0,7176.73,4196.36,0.0,0.0,19657.08,47043.17,21.8214,0.0,0.0,7169.0,4196.36,0.0,0.0,19657.08,47043.17,21.5638,0.0,0.0,7150.97,4196.36,0.0,0.0,19657.08,47043.17,21.2807,0.0,0.0,7136.49,4196.36,0.0,0.0,19657.08,47043.17,21.1526,0.0,0.0,7119.82,4196.36,0.0,0.0,19657.08,47043.17,21.0739,0.0,0.0,7102.65,4196.36,0.0,0.0,19657.08,47043.17,20.959,0.0001,0.0,7093.38,4196.36,0.0,0.0,19657.08,47043.17,20.889,0.0001,0.0,7074.15,4196.36,0.0,0.0,19657.08,47043.17,21.0756,0.0001,0.0,7041.3,4196.36,0.0,0.0,19657.08,47043.17,2.245,22.0,2.27,2.235,139000.0,22.42,23.947499999999998 -2019-12-16 09:00:00-06:00,11916.96,1511.02,3824.27,1131.53,15049.85,6151.61,3174.65,44234.82,1474.93,100.0,70.0,80.0,0.01,77.0,77.0,170.0,11.0,49849.6,3847.6,560.83,1989.44,5920.14,8470.41,593.1,2462.7,5356.2,8412.0,552.5,2003.4,5814.7,8370.6,1521.5,387.7,3822.1,5731.3,23.8875,0.0043,0.0,6382.03,4154.29,0.0,0.0,19948.57,46878.53,22.774,0.0036,0.0,6415.85,4154.29,0.0,0.0,19893.57,46804.53,23.2631,0.0053,0.0,6347.2,4154.29,0.0,0.0,19893.57,46804.53,23.6329,0.0073,0.0,6291.15,4154.29,0.0,0.0,19893.57,46804.53,23.6339,0.0096,0.0,6242.46,4154.29,0.0,0.0,19893.57,46804.53,24.2992,0.0128,0.0,6191.81,4154.29,0.0,0.0,19893.57,46804.53,26.7709,0.0175,0.0,6134.34,4154.29,0.0,0.0,19893.57,46804.53,35.3479,0.0227,0.0,6085.95,4154.29,0.0,0.0,19893.57,46804.53,35.7053,0.0259,0.0,6061.45,4154.29,0.0,0.0,19893.57,46804.53,42.7747,0.0275,0.0,6050.44,4154.29,0.0,0.0,19893.57,46804.53,42.7755,0.0285,0.0,6043.4,4154.29,0.0,0.0,19893.57,46804.53,2.245,22.0,2.27,2.235,139000.0,22.27,23.167500000000004 -2019-12-16 11:00:00-06:00,12223.96,1581.44,3688.95,1124.17,15298.56,6264.58,3385.6,45023.72,1456.46,100.0,58.0,61.0,0.01,61.0,61.0,300.0,16.0,51254.3,3745.8,742.19,2077.86,7092.66,9912.71,652.4,2396.3,6651.3,9700.0,756.2,2088.9,6967.8,9812.9,1467.4,577.2,4711.0,6755.6,20.7961,0.0,0.0,7334.98,4209.05,0.0,0.0,19404.67,49029.14,20.9006,0.0,0.0,7375.87,4209.05,0.0,0.0,19404.67,49029.14,20.9002,0.0,0.0,7451.02,4209.05,0.0,0.0,19404.67,49029.14,20.9,0.0,0.0,7517.91,4209.05,0.0,0.0,19404.67,49029.14,20.4157,0.0,0.0,7565.2,4209.05,0.0,0.0,19404.67,49029.14,20.0682,0.0,0.0,7630.04,4209.05,0.0,0.0,19404.67,49029.14,19.9967,0.0,0.0,7699.98,4209.05,0.0,0.0,19404.67,49029.14,19.9157,0.0,0.0,7775.96,4209.05,0.0,0.0,19404.67,49029.14,19.7655,0.0,0.0,7842.23,4209.05,0.0,0.0,19404.67,49029.14,19.5895,0.0,0.0,7911.94,4209.05,0.0,0.0,19404.67,49029.14,19.5437,0.0,0.0,7993.05,4209.05,0.0,0.0,19404.67,49029.14,2.245,22.0,2.27,2.235,139000.0,20.43,22.189999999999994 -2019-12-16 13:00:00-06:00,11229.95,1599.82,3730.6,1129.88,15149.57,6019.86,3503.75,43702.11,1338.67,100.0,51.0,57.0,0.01,57.0,57.0,310.0,15.0,51633.0,3750.7,885.65,2865.19,7977.73,11728.57,828.0,3047.4,7511.7,11387.1,869.7,2876.6,7859.0,11605.3,2205.6,720.7,5379.6,8305.9,19.9254,0.0,0.0,8302.78,4423.99,0.0,0.0,19256.05,50078.16,20.0284,0.0,0.0,8170.38,4423.99,0.0,0.0,18909.05,49293.16,19.9372,0.0,0.0,8232.21,4423.99,0.0,0.0,18909.05,49293.16,19.9334,0.0,0.0,8294.41,4423.99,0.0,0.0,18909.05,49293.16,19.9285,0.0,0.0,8367.35,4423.99,0.0,0.0,18909.05,49293.16,19.9111,0.0,0.0,8441.29,4423.99,0.0,0.0,18909.05,49293.16,19.6607,0.0,0.0,8516.61,4423.99,0.0,0.0,18909.05,49293.16,19.4994,0.0,0.0,8591.02,4423.99,0.0,0.0,18909.05,49293.16,19.2422,0.0,0.0,8667.85,4423.99,0.0,0.0,18909.05,49293.16,19.0696,0.0,0.0,8741.85,4423.99,0.0,0.0,18909.05,49293.16,19.0432,0.0,0.0,8822.7,4423.99,0.0,0.0,18909.05,49293.16,2.245,22.0,2.27,2.235,139000.0,18.82,19.79499999999999 -2019-12-16 14:00:00-06:00,10935.06,1591.21,3780.95,1174.13,15064.24,5947.5,3506.12,43270.56,1271.35,100.0,48.0,56.0,0.01,56.0,56.0,330.0,18.0,53186.4,3738.8,927.05,3659.85,8485.86,13072.76,889.4,3698.4,8501.6,13089.4,940.3,3667.5,8504.0,13111.8,2801.8,809.8,6094.6,9706.2,16.3768,0.0,0.0,11627.29,4507.76,0.0,0.0,19158.65,51720.71,16.6273,0.0,0.0,11432.99,4507.76,0.0,0.0,19158.65,51720.71,16.6485,0.0,0.0,11461.62,4507.76,0.0,0.0,19158.65,51720.71,16.6945,0.0,0.0,11502.52,4507.76,0.0,0.0,19158.65,51720.71,16.7477,0.0,0.0,11547.59,4507.76,0.0,0.0,19158.65,51720.71,16.7792,0.0,0.0,11595.31,4507.76,0.0,0.0,19158.65,51720.71,16.7802,0.0,0.0,11645.96,4507.76,0.0,0.0,19158.65,51720.71,16.7641,0.0,0.0,11691.95,4507.76,0.0,0.0,19158.65,51720.71,16.7475,0.0,0.0,11739.22,4507.76,0.0,0.0,19158.65,51720.71,16.7256,0.0,0.0,11791.91,4507.76,0.0,0.0,19158.65,51720.71,16.6669,0.0,0.0,11848.09,4507.76,0.0,0.0,19158.65,51720.71,2.245,22.0,2.27,2.235,139000.0,17.61,17.09999999999999 -2019-12-16 15:00:00-06:00,10820.85,1581.33,3800.11,1118.47,15208.18,5894.81,3470.46,43180.27,1286.06,100.0,46.0,54.0,0.0,54.0,54.0,340.0,15.0,53904.4,3678.1,891.02,4385.38,8937.72,14214.12,894.9,4149.4,8839.9,13884.2,887.2,4535.6,8813.6,14236.4,3520.1,734.0,6377.8,10631.9,16.4475,0.0,0.0,12397.49,4401.82,0.0,0.0,19139.8,52140.96,16.4579,0.0,0.0,12340.29,4401.82,0.0,0.0,19112.8,52112.96,16.4556,0.0,0.0,12351.16,4401.82,0.0,0.0,19112.8,52112.96,16.4551,0.0,0.0,12361.97,4401.82,0.0,0.0,19112.8,52112.96,16.4544,0.0,0.0,12359.14,4401.82,0.0,0.0,19112.8,52112.96,16.4549,0.0,0.0,12355.18,4401.82,0.0,0.0,19112.8,52112.96,16.4549,0.0,0.0,12354.75,4401.82,0.0,0.0,19112.8,52112.96,16.455,0.0,0.0,12354.36,4401.82,0.0,0.0,19112.8,52112.96,16.4562,0.0,0.0,12340.74,4401.82,0.0,0.0,19112.8,52112.96,16.4579,0.0,0.0,12320.8,4401.82,0.0,0.0,19112.8,52112.96,16.4594,0.0,0.0,12304.09,4401.82,0.0,0.0,19112.8,52112.96,2.245,22.0,2.27,2.235,139000.0,16.29,16.557499999999994 -2019-12-16 16:00:00-06:00,10840.46,1641.03,3796.51,1174.08,15816.63,6072.86,3413.82,44120.12,1364.72,75.0,44.0,53.0,0.0,53.0,53.0,340.0,22.0,54044.0,3684.7,923.5,4187.91,9547.92,14659.33,937.0,4642.7,9028.1,14607.8,933.0,4283.2,9418.8,14635.0,3285.2,784.0,6846.5,10915.7,16.5483,0.0,0.0,12586.03,4455.02,0.0,0.0,19016.98,53079.46,16.4931,0.0,0.0,12580.57,4496.58,0.0,0.0,18996.98,53037.9,16.4684,0.0,0.0,12537.68,4496.58,0.0,0.0,18996.98,53037.9,16.4402,0.0,0.0,12499.21,4496.58,0.0,0.0,18996.98,53037.9,16.4408,0.0,0.0,12449.45,4496.58,0.0,0.0,18996.98,53037.9,16.4418,0.0,0.0,12393.94,4496.58,0.0,0.0,18996.98,53037.9,16.4448,0.0,0.0,12314.68,4496.58,0.0,0.0,18996.98,53037.9,16.4483,0.0,0.0,12230.19,4496.58,0.0,0.0,18996.98,53037.9,16.4536,0.0,0.0,12125.44,4496.58,0.0,0.0,18996.98,53037.9,16.4582,0.0,0.0,12027.3,4496.58,0.0,0.0,18996.98,53037.9,16.4887,0.0,0.0,11928.38,4496.58,0.0,0.0,18996.98,53037.9,2.245,22.0,2.27,2.235,139000.0,17.00,16.194999999999993 -2019-12-16 17:00:00-06:00,11258.55,1778.82,3781.3,1180.94,16834.2,6603.23,3373.56,46327.94,1517.34,75.0,42.0,51.0,0.0,51.0,51.0,340.0,21.0,53785.6,3688.2,854.01,4246.02,9445.05,14545.08,885.0,5015.3,8890.9,14791.2,849.3,4342.9,9628.7,14820.9,3388.3,689.6,7066.8,11144.7,16.6297,0.0,0.0,11863.34,4343.76,0.0,0.0,19034.5,52821.08,16.7601,0.0,0.0,11680.41,4343.76,0.0,0.0,19034.5,52821.08,17.0158,0.0,0.0,11491.14,4343.76,0.0,0.0,19034.5,52821.08,17.3696,0.0,0.0,11242.47,4343.76,0.0,0.0,19034.5,52821.08,17.856,0.0,0.0,10941.81,4343.76,0.0,0.0,19034.5,52821.08,18.1055,0.0,0.0,10602.54,4343.76,0.0,0.0,19034.5,52821.08,18.4044,0.0,0.0,10236.15,4343.76,0.0,0.0,19034.5,52821.08,18.9426,0.0,0.0,9857.95,4343.76,0.0,0.0,19034.5,52821.08,19.6603,0.0,0.0,9492.85,4343.76,0.0,0.0,19034.5,52821.08,20.0184,0.0,0.0,9161.35,4343.76,0.0,0.0,19034.5,52821.08,20.1356,0.0,0.0,8884.69,4343.76,0.0,0.0,19034.5,52821.08,2.245,22.0,2.27,2.235,139000.0,20.47,17.132499999999993 -2019-12-16 18:00:00-06:00,11438.85,1889.83,3908.51,1203.94,17650.82,7285.02,3444.09,48426.19,1605.14,75.0,40.0,50.0,0.0,50.0,43.0,350.0,23.0,52654.9,3764.9,917.37,4111.41,9274.77,14303.55,942.0,4423.2,8545.4,13910.6,920.0,4186.8,8999.4,14106.2,3214.2,771.2,6576.8,10562.2,30.5132,0.0001,0.0,6950.99,4177.46,0.0,0.0,19520.35,52157.13,28.3983,0.0001,0.0,6972.69,4177.46,0.0,0.0,19520.35,52157.13,28.3947,0.0002,0.0,6926.77,4177.46,0.0,0.0,19520.35,52157.13,28.3205,0.0002,0.0,6852.47,4177.46,0.0,0.0,19520.35,52157.13,28.2573,0.0004,0.0,6787.97,4177.46,0.0,0.0,19520.35,52157.13,28.2226,0.0005,0.0,6739.18,4177.46,0.0,0.0,19520.35,52157.13,28.2175,0.0006,0.0,6699.76,4177.46,0.0,0.0,19520.35,52157.13,28.2186,0.0008,0.0,6660.8,4177.46,0.0,0.0,19520.35,52157.13,28.2469,0.001,0.0,6631.87,4177.46,0.0,0.0,19520.35,52157.13,28.2997,0.0011,0.0,6610.78,4177.46,0.0,0.0,19520.35,52157.13,28.3703,0.0013,0.0,6590.81,4177.46,0.0,0.0,19520.35,52157.13,2.245,22.0,2.27,2.235,139000.0,19.75,31.21999999999999 -2019-12-16 19:00:00-06:00,11603.65,1883.24,4025.31,1199.65,17633.16,7457.99,3385.41,48754.2,1565.79,75.0,38.0,49.0,0.0,49.0,42.0,350.0,18.0,53608.6,3782.3,950.8,4364.39,9988.62,15303.81,895.0,4492.6,9487.6,14875.2,945.9,4423.5,9807.7,15177.1,3411.2,816.6,7499.7,11727.5,21.0134,0.0,0.0,7171.87,4512.21,0.0,0.0,19190.2,52595.91,20.9263,0.0,0.0,7236.15,4562.17,0.0,0.0,19166.2,52545.96,21.0,0.0,0.0,7260.35,4562.17,0.0,0.0,19166.2,52545.96,21.0061,0.0,0.0,7278.91,4562.17,0.0,0.0,19166.2,52545.96,21.0127,0.0,0.0,7276.51,4562.17,0.0,0.0,19166.2,52545.96,21.0188,0.0,0.0,7264.67,4562.17,0.0,0.0,19166.2,52545.96,21.1111,0.0,0.0,7249.27,4562.17,0.0,0.0,19166.2,52545.96,21.1111,0.0,0.0,7247.51,4562.17,0.0,0.0,19166.2,52545.96,21.111,0.0,0.0,7244.7,4562.17,0.0,0.0,19166.2,52545.96,21.1229,0.0,0.0,7231.16,4562.17,0.0,0.0,19166.2,52545.96,21.1279,0.0,0.0,7229.32,4562.17,0.0,0.0,19166.2,52545.96,2.245,22.0,2.27,2.235,139000.0,18.91,20.509999999999994 -2019-12-16 21:00:00-06:00,11304.92,1908.36,4122.01,1146.13,16957.02,7431.69,3189.72,47572.08,1512.23,19.0,35.0,45.0,0.0,45.0,37.0,350.0,18.0,54147.1,3761.7,971.7,4807.71,9829.94,15609.35,945.6,4624.3,9574.9,15144.8,972.3,4978.9,9901.3,15852.5,3955.6,846.0,7441.6,12243.2,25.6897,0.0,0.0,8564.43,4724.14,0.0,0.0,19096.37,53494.17,28.6383,0.0,0.0,8504.38,4847.06,0.0,0.0,19031.37,53371.25,27.9899,0.0,0.0,8588.67,4847.06,0.0,0.0,19031.37,53371.25,27.6922,0.0,0.0,8670.45,4847.06,0.0,0.0,19031.37,53371.25,27.4967,0.0,0.0,8765.87,4847.06,0.0,0.0,19031.37,53371.25,27.3461,0.0,0.0,8879.42,4847.06,0.0,0.0,19031.37,53371.25,27.1025,0.0,0.0,9011.38,4847.06,0.0,0.0,19031.37,53371.25,25.6055,0.0,0.0,9150.85,4847.06,0.0,0.0,19031.37,53371.25,24.2596,0.0,0.0,9293.66,4847.06,0.0,0.0,19031.37,53371.25,24.2805,0.0,0.0,9449.84,4847.06,0.0,0.0,19031.37,53371.25,24.2126,0.0,0.0,9624.8,4847.06,0.0,0.0,19031.37,53371.25,2.245,22.0,2.27,2.235,139000.0,16.62,16.852499999999996 -2019-12-16 22:00:00-06:00,10848.23,1797.22,4015.11,1104.25,15974.23,7110.33,2994.09,45331.84,1488.38,50.0,35.0,45.0,0.0,45.0,38.0,350.0,16.0,54135.5,3829.1,933.39,4770.17,9785.13,15488.69,922.2,4958.6,9733.3,15614.1,939.5,4845.0,9861.9,15646.4,3827.5,796.3,7308.9,11932.7,17.8404,0.0,0.0,10347.51,4494.03,0.0,0.0,19132.97,53156.86,17.9642,0.0,0.0,10354.71,4543.96,0.0,0.0,19068.97,53001.93,17.7449,0.0,0.0,10561.1,4543.96,0.0,0.0,19068.97,53001.93,17.578,0.0,0.0,10744.22,4543.96,0.0,0.0,19068.97,53001.93,17.4028,0.0,0.0,10923.53,4543.96,0.0,0.0,19068.97,53001.93,17.2555,0.0,0.0,11105.48,4543.96,0.0,0.0,19068.97,53001.93,17.0694,0.0,0.0,11297.44,4543.96,0.0,0.0,19068.97,53001.93,16.8664,0.0,0.0,11497.31,4543.96,0.0,0.0,19068.97,53001.93,16.6851,0.0,0.0,11692.83,4543.96,0.0,0.0,19068.97,53001.93,16.6284,0.0,0.0,11884.51,4543.96,0.0,0.0,19068.97,53001.93,16.6123,0.0,0.0,12081.73,4543.96,0.0,0.0,19068.97,53001.93,2.245,22.0,2.27,2.235,139000.0,15.47,17.3575 -2019-12-16 23:00:00-06:00,10415.41,1696.03,3926.96,1056.85,15027.02,6752.42,2790.68,43117.04,1451.69,75.0,34.0,44.0,0.0,44.0,36.0,350.0,20.0,52780.9,3827.3,880.51,4806.69,9331.14,15018.34,916.5,4978.7,8977.3,14872.5,887.6,4885.3,9378.7,15151.6,3907.9,750.9,7061.0,11719.8,18.9604,0.0,0.0,11693.27,4504.74,0.0,0.0,19187.68,52619.54,19.0407,0.0,0.0,11532.57,4554.55,0.0,0.0,19013.68,52292.73,18.9742,0.0,0.0,11734.93,4554.55,0.0,0.0,19013.68,52292.73,18.9439,0.0,0.0,11931.49,4554.55,0.0,0.0,19013.68,52292.73,18.7413,0.0,0.0,12116.95,4554.55,0.0,0.0,19013.68,52292.73,18.4784,0.0,0.0,12294.29,4554.55,0.0,0.0,19013.68,52292.73,18.2384,0.0,0.0,12466.52,4554.55,0.0,0.0,19013.68,52292.73,17.4979,0.0,0.0,12635.29,4554.55,0.0,0.0,19013.68,52292.73,17.416,0.0,0.0,12800.83,4554.55,0.0,0.0,19013.68,52292.73,17.3516,0.0,0.0,12954.67,4554.55,0.0,0.0,19013.68,52292.73,17.3057,0.0,0.0,13096.04,4554.55,0.0,0.0,19013.68,52292.73,2.245,22.0,2.27,2.235,139000.0,13.67,16.337500000000002 diff --git a/examples/sdk/quantile-regression/data/TrainingData.csv b/examples/sdk/quantile-regression/data/TrainingData.csv deleted file mode 100644 index 1de72fa41..000000000 --- a/examples/sdk/quantile-regression/data/TrainingData.csv +++ /dev/null @@ -1,56 +0,0 @@ -DateTime,coast_load,east_load,f_west_load,north_load,north_c_load,south_c_load,south_load,total_load,west_load,CLOUD_COVER,DEWPOINT,HEAT_INDEX,PRECIPITATION,TEMPERATURE,WIND_CHILL,WIND_DIRECTION,WIND_SPEED,TOTAL_CAP_GEN_RES,TOTAL_CAP_LOAD_RES,lz_north_wind,lz_south_wind,lz_west_wind,system_wind,cop_north_wind,cop_south_wind,cop_west_wind,cop_system_wind,stwpf_north_wind,stwpf_south_wind,stwpf_west_wind,stwpf_system_wind,wgrpp_houston_wind,wgrpp_north_wind,wgrpp_west_wind,wgrpp_system_wind,SYSTEM_LAMBDA_id1,RTORPA_id1,RTOFFPA_id1,RTOLCAP_id1,RTOFFCAP_id1,RTORDPA_id1,RTRRUC_id1,RTOLLASL_id1,RTOLHASL_id1,SYSTEM_LAMBDA_id2,RTORPA_id2,RTOFFPA_id2,RTOLCAP_id2,RTOFFCAP_id2,RTORDPA_id2,RTRRUC_id2,RTOLLASL_id2,RTOLHASL_id2,SYSTEM_LAMBDA_id3,RTORPA_id3,RTOFFPA_id3,RTOLCAP_id3,RTOFFCAP_id3,RTORDPA_id3,RTRRUC_id3,RTOLLASL_id3,RTOLHASL_id3,SYSTEM_LAMBDA_id4,RTORPA_id4,RTOFFPA_id4,RTOLCAP_id4,RTOFFCAP_id4,RTORDPA_id4,RTRRUC_id4,RTOLLASL_id4,RTOLHASL_id4,SYSTEM_LAMBDA_id5,RTORPA_id5,RTOFFPA_id5,RTOLCAP_id5,RTOFFCAP_id5,RTORDPA_id5,RTRRUC_id5,RTOLLASL_id5,RTOLHASL_id5,SYSTEM_LAMBDA_id6,RTORPA_id6,RTOFFPA_id6,RTOLCAP_id6,RTOFFCAP_id6,RTORDPA_id6,RTRRUC_id6,RTOLLASL_id6,RTOLHASL_id6,SYSTEM_LAMBDA_id7,RTORPA_id7,RTOFFPA_id7,RTOLCAP_id7,RTOFFCAP_id7,RTORDPA_id7,RTRRUC_id7,RTOLLASL_id7,RTOLHASL_id7,SYSTEM_LAMBDA_id8,RTORPA_id8,RTOFFPA_id8,RTOLCAP_id8,RTOFFCAP_id8,RTORDPA_id8,RTRRUC_id8,RTOLLASL_id8,RTOLHASL_id8,SYSTEM_LAMBDA_id9,RTORPA_id9,RTOFFPA_id9,RTOLCAP_id9,RTOFFCAP_id9,RTORDPA_id9,RTRRUC_id9,RTOLLASL_id9,RTOLHASL_id9,SYSTEM_LAMBDA_id10,RTORPA_id10,RTOFFPA_id10,RTOLCAP_id10,RTOFFCAP_id10,RTORDPA_id10,RTRRUC_id10,RTOLLASL_id10,RTOLHASL_id10,SYSTEM_LAMBDA_id11,RTORPA_id11,RTOFFPA_id11,RTOLCAP_id11,RTOFFCAP_id11,RTORDPA_id11,RTRRUC_id11,RTOLLASL_id11,RTOLHASL_id11,AVERAGE,DEALS,HIGH,LOW,VOLUME,DA_PRICE,response_var -2019-12-14 00:00:00-06:00,9254.34,1314.05,3670.26,890.18,10963.37,5108.59,2480.75,34853.63,1172.1,19.0,46.0,52.0,0.0,52.0,52.0,0.0,0.0,45587.5,3931.3,43.37,1005.26,5062.73,6111.36,17.5,1563.3,6278.5,7859.3,37.1,1079.8,5296.0,6412.9,624.0,16.8,3570.1,4210.9,35.2095,0.0,0.0,12888.1,4240.44,0.0,0.0,19603.62,44516.64,35.1497,0.0,0.0,12839.68,4240.44,0.0,0.0,19469.61,44200.5,34.7837,0.0,0.0,12959.35,4240.44,0.0,0.0,19469.61,44200.5,34.1095,0.0,0.0,13059.65,4240.44,0.0,0.0,19469.61,44200.5,33.7682,0.0,0.0,13145.69,4240.44,0.0,0.0,19469.61,44200.5,33.5554,0.0,0.0,13232.36,4240.44,0.0,0.0,19469.61,44200.5,33.3767,0.0,0.0,13326.73,4240.44,0.0,0.0,19469.61,44200.5,33.2526,0.0,0.0,13418.16,4240.44,0.0,0.0,19469.61,44200.5,33.1629,0.0,0.0,13496.46,4240.44,0.0,0.0,19469.61,44200.5,24.0896,0.0,0.0,13562.83,4240.44,0.0,0.0,19469.61,44200.5,23.6913,0.0,0.0,13628.07,4240.44,0.0,0.0,19469.61,44200.5,2.15,12.0,2.18,2.14,107000.0,16.61,18.007499999999993 -2019-12-14 02:00:00-06:00,8902.46,1311.28,3623.68,869.65,10728.48,4959.08,2340.06,33937.61,1202.9,19.0,45.0,48.0,0.0,48.0,48.0,240.0,3.0,44089.8,3930.6,81.47,1133.42,3570.26,4785.15,67.2,1722.7,4500.0,6289.9,100.4,1195.6,3666.9,4962.9,663.4,54.0,2239.2,2956.6,36.7482,0.0,0.0,10720.93,4234.23,0.0,0.0,19155.9,41172.68,36.4809,0.0,0.0,10900.8,4234.23,0.0,0.0,19155.9,41172.68,36.4736,0.0,0.0,10962.49,4234.23,0.0,0.0,19155.9,41172.68,36.4485,0.0,0.0,10988.89,4234.23,0.0,0.0,19155.9,41172.68,36.4338,0.0,0.0,11006.0,4234.23,0.0,0.0,19155.9,41172.68,36.4204,0.0,0.0,11021.95,4234.23,0.0,0.0,19155.9,41172.68,36.4107,0.0,0.0,11034.61,4234.23,0.0,0.0,19155.9,41172.68,36.4022,0.0,0.0,11046.31,4234.23,0.0,0.0,19155.9,41172.68,36.3915,0.0,0.0,11057.75,4234.23,0.0,0.0,19155.9,41172.68,36.3819,0.0,0.0,11066.85,4234.23,0.0,0.0,19155.9,41172.68,36.3765,0.0,0.0,11072.25,4234.23,0.0,0.0,19155.9,41172.68,2.15,12.0,2.18,2.14,107000.0,15.79,18.48249999999999 -2019-12-14 03:00:00-06:00,8896.14,1332.94,3621.97,877.07,10851.75,4998.2,2353.97,34169.44,1237.41,0.0,44.0,46.0,0.0,46.0,46.0,0.0,0.0,43034.8,3930.0,33.23,1141.41,2754.4,3929.04,105.5,1495.4,3592.9,5193.8,28.5,1217.0,2794.8,4040.3,692.1,13.7,1562.3,2268.1,37.5839,0.0,0.0,9816.92,4240.07,0.0,0.0,19110.13,40259.95,36.8577,0.0,0.0,10008.45,4240.07,0.0,0.0,19110.13,40259.95,36.8938,0.0,0.0,10037.91,4240.07,0.0,0.0,19110.13,40259.95,36.8713,0.0,0.0,10040.07,4240.07,0.0,0.0,19110.13,40259.95,36.8651,0.0,0.0,10034.92,4240.07,0.0,0.0,19110.13,40259.95,36.8711,0.0,0.0,10019.94,4240.07,0.0,0.0,19110.13,40259.95,36.8805,0.0,0.0,9996.56,4240.07,0.0,0.0,19110.13,40259.95,36.8897,0.0,0.0,9973.65,4240.07,0.0,0.0,19110.13,40259.95,36.8951,0.0,0.0,9960.02,4240.07,0.0,0.0,19110.13,40259.95,36.9006,0.0,0.0,9946.38,4240.07,0.0,0.0,19110.13,40259.95,36.9119,0.0,0.0,9918.08,4240.07,0.0,0.0,19110.13,40259.95,2.15,12.0,2.18,2.14,107000.0,15.62,19.259999999999994 -2019-12-14 04:00:00-06:00,9013.02,1373.12,3620.9,888.53,11261.83,5133.64,2430.86,35035.69,1313.78,0.0,44.0,46.0,0.0,46.0,46.0,0.0,0.0,41938.3,3933.2,122.35,1027.05,2217.31,3366.71,75.1,1381.4,2479.2,3935.7,101.3,998.5,2210.5,3310.3,544.2,55.1,1258.9,1858.2,38.2664,0.0,0.0,8470.19,4239.84,0.0,0.0,19266.91,39546.14,37.7156,0.0,0.0,8666.61,4239.84,0.0,0.0,19266.91,39546.14,37.7223,0.0,0.0,8642.1,4239.84,0.0,0.0,19266.91,39546.14,37.7028,0.0,0.0,8594.06,4239.84,0.0,0.0,19266.91,39546.14,37.7032,0.0,0.0,8543.56,4239.84,0.0,0.0,19266.91,39546.14,37.7044,0.0,0.0,8484.55,4239.84,0.0,0.0,19266.91,39546.14,37.7291,0.0,0.0,8416.26,4239.84,0.0,0.0,19266.91,39546.14,37.7544,0.0,0.0,8348.35,4239.84,0.0,0.0,19266.91,39546.14,37.7745,0.0,0.0,8287.4,4239.84,0.0,0.0,19266.91,39546.14,37.7893,0.0,0.0,8222.73,4239.84,0.0,0.0,19266.91,39546.14,37.8152,0.0,0.0,8139.45,4239.84,0.0,0.0,19266.91,39546.14,2.15,12.0,2.18,2.14,107000.0,16.82,19.929999999999993 -2019-12-14 05:00:00-06:00,9263.01,1447.77,3638.13,897.23,11767.76,5393.24,2525.04,36311.4,1379.23,0.0,43.0,46.0,0.0,46.0,46.0,360.0,3.0,41952.7,3945.6,203.64,1234.07,2336.77,3774.48,59.0,1272.2,2437.6,3768.8,211.0,1158.1,2386.7,3755.8,660.1,129.1,1294.6,2083.8,38.0265,0.0,0.0,8190.48,4247.78,0.0,0.0,20389.94,40743.0,37.8801,0.0,0.0,8291.72,4247.78,0.0,0.0,20389.94,40743.0,37.8874,0.0,0.0,8224.33,4247.78,0.0,0.0,20389.94,40743.0,37.8898,0.0,0.0,8186.29,4247.78,0.0,0.0,20389.94,40743.0,37.8883,0.0,0.0,8161.07,4247.78,0.0,0.0,20389.94,40743.0,37.8946,0.0,0.0,8117.7,4247.78,0.0,0.0,20389.94,40743.0,37.903,0.0,0.0,8061.36,4247.78,0.0,0.0,20389.94,40743.0,37.9206,0.0,0.0,7983.28,4247.78,0.0,0.0,20389.94,40743.0,37.969,0.0,0.0,7879.82,4247.78,0.0,0.0,20389.94,40743.0,38.0186,0.0,0.0,7775.12,4247.78,0.0,0.0,20389.94,40743.0,38.0984,0.0,0.0,7664.37,4247.78,0.0,0.0,20389.94,40743.0,2.15,12.0,2.18,2.14,107000.0,20.04,19.65999999999999 -2019-12-14 06:00:00-06:00,9679.73,1539.05,3683.11,926.26,12490.68,5762.02,2682.32,38189.51,1426.33,0.0,42.0,45.0,0.0,45.0,45.0,10.0,3.0,44401.2,3824.7,260.18,1451.32,2387.7,4099.2,138.3,1083.5,2610.1,3831.9,238.5,1359.8,2360.6,3958.9,823.3,148.8,1272.2,2244.3,18.091,0.0,0.0,9164.18,4177.07,0.0,0.0,20977.15,42232.47,17.9627,0.0,0.0,9264.26,4177.07,0.0,0.0,20977.15,42232.47,18.1265,0.0,0.0,9085.61,4177.07,0.0,0.0,20977.15,42232.47,19.9448,0.0,0.0,8944.72,4177.07,0.0,0.0,20977.15,42232.47,20.0041,0.0,0.0,8822.09,4177.07,0.0,0.0,20977.15,42232.47,20.0663,0.0,0.0,8702.13,4177.07,0.0,0.0,20977.15,42232.47,20.1329,0.0,0.0,8577.86,4177.07,0.0,0.0,20977.15,42232.47,20.2395,0.0,0.0,8454.58,4177.07,0.0,0.0,20977.15,42232.47,20.367,0.0,0.0,8326.35,4177.07,0.0,0.0,20977.15,42232.47,20.5348,0.0,0.0,8206.56,4177.07,0.0,0.0,20977.15,42232.47,20.7417,0.0,0.0,8090.76,4177.07,0.0,0.0,20977.15,42232.47,2.15,12.0,2.18,2.14,107000.0,23.00,18.19999999999999 -2019-12-14 07:00:00-06:00,9989.91,1618.38,3733.02,954.58,13179.29,6151.59,2792.23,39906.68,1487.67,0.0,45.0,48.0,0.0,48.0,48.0,20.0,3.0,45060.4,3898.8,375.77,1767.47,2422.23,4565.47,240.7,1102.6,2883.5,4226.8,364.9,1719.2,2445.6,4529.7,1099.5,264.6,1320.9,2685.0,19.4075,0.0,0.0,7671.16,4198.18,0.0,0.0,20685.57,43252.06,19.4385,0.0,0.0,7705.05,4198.18,0.0,0.0,20685.57,43252.06,19.649,0.0,0.0,7560.16,4198.18,0.0,0.0,20685.57,43252.06,19.8302,0.0,0.0,7456.77,4198.18,0.0,0.0,20685.57,43252.06,19.9904,0.0,0.0,7371.09,4198.18,0.0,0.0,20685.57,43252.06,21.6125,0.0,0.0,7276.52,4198.18,0.0,0.0,20685.57,43252.06,21.6967,0.0,0.0,7188.51,4198.18,0.0,0.0,20685.57,43252.06,21.8061,0.0,0.0,7110.4,4198.18,0.0,0.0,20685.57,43252.06,21.8536,0.0001,0.0,7039.21,4198.18,0.0,0.0,20685.57,43252.06,21.9479,0.0001,0.0,6978.79,4198.18,0.0,0.0,20685.57,43252.06,22.0442,0.0002,0.0,6926.58,4198.18,0.0,0.0,20685.57,43252.06,2.15,12.0,2.18,2.14,107000.0,26.79,18.354999999999993 -2019-12-14 08:00:00-06:00,10251.55,1639.05,3712.56,983.7,13314.7,6278.94,2854.94,40520.29,1484.87,0.0,49.0,56.0,0.0,56.0,56.0,0.0,5.0,46466.1,3901.0,417.3,1473.47,2533.85,4424.62,327.3,1105.1,2738.8,4171.2,417.2,1474.6,2571.1,4462.9,943.0,309.4,1480.3,2732.7,20.3856,0.0,0.0,7712.59,4147.5,0.0,0.0,20661.01,44488.22,19.8868,0.0,0.0,7803.47,4147.5,0.0,0.0,20661.01,44488.22,19.9307,0.0,0.0,7753.3,4147.5,0.0,0.0,20661.01,44488.22,19.9303,0.0,0.0,7749.43,4147.5,0.0,0.0,20661.01,44488.22,19.9285,0.0,0.0,7764.08,4147.5,0.0,0.0,20661.01,44488.22,19.9259,0.0,0.0,7789.17,4147.5,0.0,0.0,20661.01,44488.22,19.9229,0.0,0.0,7818.99,4147.5,0.0,0.0,20661.01,44488.22,19.8475,0.0,0.0,7852.55,4147.5,0.0,0.0,20661.01,44488.22,19.7679,0.0,0.0,7877.15,4147.5,0.0,0.0,20661.01,44488.22,19.6967,0.0,0.0,7898.35,4147.5,0.0,0.0,20661.01,44488.22,19.6605,0.0,0.0,7924.89,4147.5,0.0,0.0,20661.01,44488.22,2.15,12.0,2.18,2.14,107000.0,30.99,20.01749999999999 -2019-12-14 09:00:00-06:00,10385.53,1556.84,3640.94,1035.86,12805.56,6049.95,2844.73,39694.58,1375.17,19.0,48.0,62.0,0.0,62.0,62.0,70.0,6.0,46987.8,3902.0,283.31,940.56,1920.08,3143.95,352.2,1170.7,2382.3,3905.2,295.7,898.9,1939.9,3134.5,502.6,196.9,1051.6,1751.1,19.1985,0.0,0.0,8132.44,4175.89,0.0,0.0,20617.89,44773.4,19.0512,0.0,0.0,8280.42,4175.89,0.0,0.0,20617.89,44773.4,19.0503,0.0,0.0,8322.55,4175.89,0.0,0.0,20617.89,44773.4,19.0487,0.0,0.0,8356.31,4175.89,0.0,0.0,20617.89,44773.4,19.0419,0.0,0.0,8421.9,4175.89,0.0,0.0,20617.89,44773.4,19.0334,0.0,0.0,8506.89,4175.89,0.0,0.0,20617.89,44773.4,19.0104,0.0,0.0,8600.79,4175.89,0.0,0.0,20617.89,44773.4,18.9503,0.0,0.0,8711.06,4175.89,0.0,0.0,20617.89,44773.4,18.7198,0.0,0.0,8843.46,4175.89,0.0,0.0,20617.89,44773.4,18.583,0.0,0.0,8975.18,4175.89,0.0,0.0,20617.89,44773.4,18.4811,0.0,0.0,9086.26,4175.89,0.0,0.0,20617.89,44773.4,2.15,12.0,2.18,2.14,107000.0,26.45,19.532499999999995 -2019-12-14 11:00:00-06:00,10352.89,1378.16,3564.41,909.7,11718.31,5623.91,2862.87,37657.87,1247.63,0.0,45.0,68.0,0.0,69.0,69.0,100.0,8.0,45326.4,3806.7,189.4,1060.83,3192.31,4442.54,144.4,710.4,2298.8,3153.6,197.6,943.3,3107.5,4248.4,514.9,115.4,1899.8,2530.1,17.8652,0.0,0.0,9768.8,4215.13,0.0,0.0,20294.39,44192.01,18.1042,0.0,0.0,9500.76,4215.13,0.0,0.0,20019.39,43653.91,18.0938,0.0,0.0,9553.33,4215.13,0.0,0.0,20019.39,43653.91,18.0944,0.0,0.0,9601.71,4215.13,0.0,0.0,20019.39,43653.91,18.091,0.0,0.0,9659.9,4215.13,0.0,0.0,20019.39,43653.91,18.085,0.0,0.0,9725.01,4215.13,0.0,0.0,20019.39,43653.91,18.0795,0.0,0.0,9797.25,4215.13,0.0,0.0,20019.39,43653.91,18.0778,0.0,0.0,9863.89,4215.13,0.0,0.0,20019.39,43653.91,18.0722,0.0,0.0,9936.7,4215.13,0.0,0.0,20019.39,43653.91,18.0557,0.0,0.0,10023.96,4215.13,0.0,0.0,20019.39,43653.91,18.0179,0.0,0.0,10114.01,4215.13,0.0,0.0,20019.39,43653.91,2.15,12.0,2.18,2.14,107000.0,22.33,18.124999999999993 -2019-12-14 12:00:00-06:00,10328.17,1310.72,3638.46,854.88,11259.77,5514.39,2948.81,37006.58,1151.37,0.0,45.0,70.0,0.0,72.0,72.0,110.0,7.0,45876.6,3775.1,136.94,1794.45,3773.03,5704.42,204.0,1045.3,2929.3,4178.6,136.0,1719.4,3636.0,5491.4,1073.8,74.4,2349.3,3497.5,17.1039,0.0,0.0,11304.61,4197.17,0.0,0.0,20091.12,44560.33,17.0845,0.0,0.0,11329.83,4197.17,0.0,0.0,20091.12,44560.33,17.0459,0.0,0.0,11453.57,4197.17,0.0,0.0,20091.12,44560.33,17.0225,0.0,0.0,11487.1,4197.17,0.0,0.0,20091.12,44560.33,17.0074,0.0,0.0,11519.6,4197.17,0.0,0.0,20091.12,44560.33,16.9954,0.0,0.0,11537.46,4197.17,0.0,0.0,20091.12,44560.33,16.9846,0.0,0.0,11553.86,4197.17,0.0,0.0,20091.12,44560.33,16.9778,0.0,0.0,11564.41,4197.17,0.0,0.0,20091.12,44560.33,16.9718,0.0,0.0,11573.61,4197.17,0.0,0.0,20091.12,44560.33,16.9612,0.0,0.0,11589.99,4197.17,0.0,0.0,20091.12,44560.33,16.9449,0.0,0.0,11615.01,4197.17,0.0,0.0,20091.12,44560.33,2.15,12.0,2.18,2.14,107000.0,25.92,17.324999999999992 -2019-12-14 13:00:00-06:00,10356.6,1275.83,3762.98,893.68,10839.19,5481.73,3078.1,36719.88,1031.77,0.0,45.0,72.0,0.0,74.0,74.0,130.0,6.0,44984.9,3775.1,140.91,2251.49,4609.66,7002.06,155.9,1525.1,3251.4,4932.4,143.7,2179.5,4365.0,6688.2,1379.3,80.2,2962.1,4421.6,16.7998,0.0,0.0,11670.71,4186.14,0.0,0.0,19652.48,45145.47,16.9261,0.0,0.0,11447.87,4186.14,0.0,0.0,19153.48,44435.47,16.8426,0.0,0.0,11485.52,4186.14,0.0,0.0,19153.48,44435.47,16.8317,0.0,0.0,11495.49,4186.14,0.0,0.0,19153.48,44435.47,16.8268,0.0,0.0,11509.69,4186.14,0.0,0.0,19153.48,44435.47,16.825,0.0,0.0,11514.98,4186.14,0.0,0.0,19153.48,44435.47,16.8246,0.0,0.0,11516.17,4186.14,0.0,0.0,19153.48,44435.47,16.8227,0.0,0.0,11521.83,4186.14,0.0,0.0,19153.48,44435.47,16.8141,0.0,0.0,11546.96,4186.14,0.0,0.0,19153.48,44435.47,16.8013,0.0,0.0,11584.34,4186.14,0.0,0.0,19153.48,44435.47,16.7885,0.0,0.0,11621.86,4186.14,0.0,0.0,19153.48,44435.47,2.15,12.0,2.18,2.14,107000.0,20.86,16.659999999999993 -2019-12-14 15:00:00-06:00,10399.54,1242.21,3719.0,864.12,10447.4,5633.76,3245.31,36615.06,1063.72,0.0,45.0,70.0,0.0,72.0,72.0,130.0,14.0,46545.1,3520.1,93.76,2792.91,4073.47,6960.14,165.1,2656.2,4034.5,6855.8,95.5,2780.5,3992.5,6868.5,1860.4,50.2,2479.0,4389.6,17.3061,0.0,0.0,10964.38,4264.95,0.0,0.0,18610.92,44251.42,16.8475,0.0,0.0,11142.9,4264.95,0.0,0.0,18610.92,44251.42,16.8274,0.0,0.0,11213.3,4264.95,0.0,0.0,18610.92,44251.42,16.7977,0.0,0.0,11218.29,4264.95,0.0,0.0,18610.92,44251.42,16.7889,0.0,0.0,11218.78,4264.95,0.0,0.0,18610.92,44251.42,16.7803,0.0,0.0,11219.17,4264.95,0.0,0.0,18610.92,44251.42,16.7725,0.0,0.0,11216.97,4264.95,0.0,0.0,18610.92,44251.42,16.763,0.0,0.0,11219.48,4264.95,0.0,0.0,18610.92,44251.42,16.7487,0.0,0.0,11236.24,4264.95,0.0,0.0,18610.92,44251.42,16.7339,0.0,0.0,11254.55,4264.95,0.0,0.0,18610.92,44251.42,16.7038,0.0,0.0,11270.33,4264.95,0.0,0.0,18610.92,44251.42,2.15,12.0,2.18,2.14,107000.0,17.38,16.78249999999999 -2019-12-14 16:00:00-06:00,10370.68,1243.57,3708.92,846.56,10551.97,5756.83,3262.52,36865.59,1124.54,0.0,47.0,68.0,0.0,69.0,69.0,130.0,14.0,46103.5,3510.2,123.82,2991.42,3365.65,6480.89,131.3,2901.1,3998.9,7031.3,108.5,3051.9,3415.9,6576.3,2118.4,55.0,2168.5,4341.9,17.0172,0.0,0.0,10762.35,4218.07,0.0,0.0,18727.72,43913.56,16.8611,0.0,0.0,10865.53,4218.07,0.0,0.0,18727.72,43913.56,16.872,0.0,0.0,10826.3,4218.07,0.0,0.0,18727.72,43913.56,16.88,0.0,0.0,10789.43,4218.07,0.0,0.0,18727.72,43913.56,16.8725,0.0,0.0,10775.59,4218.07,0.0,0.0,18727.72,43913.56,16.8575,0.0,0.0,10776.11,4218.07,0.0,0.0,18727.72,43913.56,16.8512,0.0,0.0,10768.88,4218.07,0.0,0.0,18727.72,43913.56,16.8524,0.0,0.0,10740.56,4218.07,0.0,0.0,18727.72,43913.56,16.8518,0.0,0.0,10717.4,4218.07,0.0,0.0,18727.72,43913.56,16.8515,0.0,0.0,10693.27,4218.07,0.0,0.0,18727.72,43913.56,16.8554,0.0,0.0,10672.07,4218.07,0.0,0.0,18727.72,43913.56,2.15,12.0,2.18,2.14,107000.0,17.02,16.89999999999999 -2019-12-14 17:00:00-06:00,10583.54,1310.63,3657.81,888.11,11115.52,5913.36,3211.53,37930.76,1250.26,0.0,47.0,63.0,0.0,63.0,63.0,120.0,10.0,45516.5,3511.3,261.44,3335.98,3375.26,6972.68,155.3,3289.2,3759.7,7204.2,243.8,3268.3,3240.4,6752.5,2337.8,148.7,2060.4,4546.9,18.5065,0.0,0.0,8884.62,4269.22,0.0,0.0,18721.29,42304.97,18.192,0.0,0.0,9001.52,4269.22,0.0,0.0,18721.29,42304.97,18.3166,0.0,0.0,8890.32,4269.22,0.0,0.0,18721.29,42304.97,18.4137,0.0,0.0,8761.22,4269.22,0.0,0.0,18721.29,42304.97,18.5419,0.0,0.0,8600.63,4269.22,0.0,0.0,18721.29,42304.97,18.8829,0.0,0.0,8409.45,4269.22,0.0,0.0,18721.29,42304.97,19.2316,0.0,0.0,8207.29,4269.22,0.0,0.0,18721.29,42304.97,19.7614,0.0,0.0,8004.41,4269.22,0.0,0.0,18721.29,42304.97,20.9265,0.0,0.0,7803.46,4269.22,0.0,0.0,18721.29,42304.97,22.6624,0.0,0.0,7602.18,4269.22,0.0,0.0,18721.29,42304.97,22.6634,0.0,0.0,7440.29,4269.22,0.0,0.0,18721.29,42304.97,2.15,12.0,2.18,2.14,107000.0,20.88,18.487499999999994 -2019-12-14 18:00:00-06:00,10824.49,1361.03,3689.14,933.6,11679.26,6115.65,3257.98,39162.96,1301.82,0.0,50.0,60.0,0.0,60.0,60.0,130.0,8.0,47082.1,3789.5,497.54,4006.88,4742.52,9246.94,331.0,3637.8,4951.3,8920.1,500.3,4033.9,4789.3,9323.5,3085.6,341.1,3377.1,6803.8,18.5317,0.0,0.0,8542.06,4284.26,0.0,0.0,18792.53,44001.08,18.5701,0.0,0.0,8448.09,4284.26,0.0,0.0,18792.53,44001.08,18.6567,0.0,0.0,8405.49,4284.26,0.0,0.0,18792.53,44001.08,18.6932,0.0,0.0,8391.99,4284.26,0.0,0.0,18792.53,44001.08,18.7242,0.0,0.0,8381.21,4284.26,0.0,0.0,18792.53,44001.08,18.7602,0.0,0.0,8368.23,4284.26,0.0,0.0,18792.53,44001.08,18.7648,0.0,0.0,8370.11,4284.26,0.0,0.0,18792.53,44001.08,18.7379,0.0,0.0,8386.86,4284.26,0.0,0.0,18792.53,44001.08,18.6988,0.0,0.0,8409.66,4284.26,0.0,0.0,18792.53,44001.08,18.6582,0.0,0.0,8433.16,4284.26,0.0,0.0,18792.53,44001.08,18.6238,0.0,0.0,8453.85,4284.26,0.0,0.0,18792.53,44001.08,2.15,12.0,2.18,2.14,107000.0,19.24,19.024999999999995 -2019-12-14 19:00:00-06:00,10691.06,1347.15,3657.79,926.8,11566.72,5977.88,3204.7,38674.54,1302.44,0.0,53.0,59.0,0.0,59.0,59.0,130.0,7.0,48022.4,3798.9,588.98,4443.06,6205.2,11237.24,594.1,3912.6,6002.7,10509.4,592.8,4494.5,6525.7,11613.0,3572.4,445.2,4780.4,8798.0,16.4018,0.0,0.0,11429.25,4293.11,0.0,0.0,18836.18,46728.82,16.5425,0.0,0.0,11226.39,4349.1,0.0,0.0,18648.68,46379.82,16.457,0.0,0.0,11269.15,4349.1,0.0,0.0,18648.68,46379.82,16.5193,0.0,0.0,11287.37,4349.1,0.0,0.0,18648.68,46379.82,16.5726,0.0,0.0,11317.23,4349.1,0.0,0.0,18648.68,46379.82,16.5931,0.0,0.0,11363.96,4349.1,0.0,0.0,18648.68,46379.82,16.5856,0.0,0.0,11411.51,4349.1,0.0,0.0,18648.68,46379.82,16.5857,0.0,0.0,11451.74,4349.1,0.0,0.0,18648.68,46379.82,16.5768,0.0,0.0,11500.7,4349.1,0.0,0.0,18648.68,46379.82,16.5341,0.0,0.0,11559.18,4349.1,0.0,0.0,18648.68,46379.82,16.49,0.0,0.0,11601.81,4349.1,0.0,0.0,18648.68,46379.82,2.15,12.0,2.18,2.14,107000.0,16.85,16.9075 -2019-12-14 20:00:00-06:00,10585.6,1350.86,3622.99,922.92,11506.99,5822.58,3091.84,38222.37,1318.59,0.0,55.0,59.0,0.0,59.0,59.0,120.0,6.0,49724.8,3784.9,644.93,4603.22,7394.55,12642.7,740.3,4735.8,8078.1,13554.2,647.6,4697.0,7583.5,12928.1,3767.6,510.1,5537.1,9814.8,15.0554,0.0,0.0,12962.43,4485.26,0.0,0.0,18481.97,47860.71,15.5805,0.0,0.0,12569.69,4485.26,0.0,0.0,18138.97,47332.71,15.5348,0.0,0.0,12624.35,4485.26,0.0,0.0,18138.97,47332.71,15.5035,0.0,0.0,12663.8,4485.26,0.0,0.0,18138.97,47332.71,15.4652,0.0,0.0,12707.54,4485.26,0.0,0.0,18138.97,47332.71,15.4094,0.0,0.0,12757.44,4485.26,0.0,0.0,18138.97,47332.71,15.3603,0.0,0.0,12800.54,4485.26,0.0,0.0,18138.97,47332.71,15.3178,0.0,0.0,12837.77,4485.26,0.0,0.0,18138.97,47332.71,15.29,0.0,0.0,12887.5,4485.26,0.0,0.0,18138.97,47332.71,15.2672,0.0,0.0,12934.71,4485.26,0.0,0.0,18138.97,47332.71,15.2528,0.0,0.0,12974.8,4485.26,0.0,0.0,18138.97,47332.71,2.15,12.0,2.18,2.14,107000.0,16.31,14.892499999999998 -2019-12-14 21:00:00-06:00,10446.99,1337.82,3683.86,914.06,11446.58,5659.08,2970.78,37694.51,1235.33,75.0,57.0,61.0,0.0,61.0,61.0,140.0,8.0,49971.3,3775.5,647.62,4601.86,8223.46,13472.94,695.4,5036.1,9138.8,14870.3,647.9,4653.1,8584.9,13885.9,3639.0,516.9,6521.7,10677.6,15.1543,0.0,0.0,12728.44,4491.13,0.0,0.0,17643.05,47365.21,15.2582,0.0,0.0,12688.93,4491.13,0.0,0.0,17463.05,46890.21,15.1795,0.0,0.0,12766.91,4491.13,0.0,0.0,17463.05,46890.21,15.1172,0.0,0.0,12840.75,4491.13,0.0,0.0,17463.05,46890.21,14.9936,0.0,0.0,12910.71,4491.13,0.0,0.0,17463.05,46890.21,14.9506,0.0,0.0,12988.73,4491.13,0.0,0.0,17463.05,46890.21,14.902,0.0,0.0,13064.46,4491.13,0.0,0.0,17463.05,46890.21,14.8521,0.0,0.0,13141.48,4491.13,0.0,0.0,17463.05,46890.21,14.8015,0.0,0.0,13219.29,4491.13,0.0,0.0,17463.05,46890.21,14.747,0.0,0.0,13305.58,4491.13,0.0,0.0,17463.05,46890.21,14.6815,0.0,0.0,13404.87,4491.13,0.0,0.0,17463.05,46890.21,2.15,12.0,2.18,2.14,107000.0,15.40,14.670000000000002 -2019-12-14 22:00:00-06:00,10180.23,1283.4,3683.26,883.0,11119.9,5428.06,2844.27,36580.49,1158.38,100.0,59.0,63.0,0.0,63.0,63.0,120.0,5.0,45603.0,3931.7,649.72,4566.35,8947.92,14163.99,665.2,4913.9,9335.7,14914.8,645.9,4648.8,9400.5,14695.2,3640.5,507.8,7446.8,11595.1,14.519,0.0,0.0,13611.74,4496.22,0.0,0.0,17437.79,47434.05,14.6583,0.0,0.0,13575.63,4496.22,0.0,0.0,17287.9,47076.65,14.5037,0.0,0.0,13695.11,4496.22,0.0,0.0,17287.9,47076.65,14.3635,0.0,0.0,13813.47,4496.22,0.0,0.0,17287.9,47076.65,14.2354,0.0,0.0,13931.49,4496.22,0.0,0.0,17287.9,47076.65,14.095,0.0,0.0,14050.71,4496.22,0.0,0.0,17287.9,47076.65,13.9426,0.0,0.0,14173.96,4496.22,0.0,0.0,17287.9,47076.65,13.7843,0.0,0.0,14300.71,4496.22,0.0,0.0,17287.9,47076.65,13.6249,0.0,0.0,14419.14,4496.22,0.0,0.0,17287.9,47076.65,13.5548,0.0,0.0,14527.46,4496.22,0.0,0.0,17287.9,47076.65,13.3244,0.0,0.0,14641.31,4496.22,0.0,0.0,17287.9,47076.65,2.15,12.0,2.18,2.14,107000.0,14.59,14.7975 -2019-12-14 23:00:00-06:00,9839.14,1227.72,3690.98,851.91,10665.58,5127.62,2709.66,35213.57,1100.95,100.0,60.0,63.0,0.0,63.0,63.0,0.0,0.0,44716.7,3929.7,637.75,4456.65,9044.52,14138.92,663.5,4635.7,8686.1,13985.3,655.2,4520.9,9491.8,14667.9,3476.4,521.3,7550.9,11548.6,16.3131,0.0,0.0,11466.2,4492.61,0.0,0.0,15302.87,43526.97,16.3104,0.0,0.0,11506.29,4492.61,0.0,0.0,15302.87,43526.97,16.2452,0.0,0.0,11645.03,4492.61,0.0,0.0,15302.87,43526.97,16.1981,0.0,0.0,11779.41,4492.61,0.0,0.0,15302.87,43526.97,16.1508,0.0,0.0,11913.84,4492.61,0.0,0.0,15302.87,43526.97,16.0726,0.0,0.0,12043.94,4492.61,0.0,0.0,15302.87,43526.97,15.6276,0.0,0.0,12173.3,4492.61,0.0,0.0,15302.87,43526.97,15.1421,0.0,0.0,12308.59,4492.61,0.0,0.0,15302.87,43526.97,14.6678,0.0,0.0,12446.31,4492.61,0.0,0.0,15302.87,43526.97,14.4318,0.0,0.0,12573.75,4492.61,0.0,0.0,15302.87,43526.97,14.2839,0.0,0.0,12688.24,4492.61,0.0,0.0,15302.87,43526.97,2.15,12.0,2.18,2.14,107000.0,12.68,16.542500000000004 -2019-12-15 00:00:00-06:00,9498.9,1174.85,3690.92,741.33,10258.0,4862.74,2582.45,33863.34,1054.15,75.0,65.0,70.0,0.0,68.0,68.0,160.0,6.0,43859.0,3956.4,595.3,4398.8,9014.05,14008.15,661.2,4476.3,8863.1,14000.6,598.7,4470.8,9325.4,14394.9,3466.8,458.0,7229.6,11154.4,14.7691,0.0,0.0,12518.59,4489.94,0.0,0.0,15324.08,43182.66,14.7666,0.0,0.0,12557.57,4489.94,0.0,0.0,15324.08,43182.66,14.6095,0.0,0.0,12673.45,4489.94,0.0,0.0,15324.08,43182.66,14.4623,0.0,0.0,12776.85,4489.94,0.0,0.0,15324.08,43182.66,14.339,0.0,0.0,12869.74,4489.94,0.0,0.0,15324.08,43182.66,14.2312,0.0,0.0,12961.77,4489.94,0.0,0.0,15324.08,43182.66,14.1108,0.0,0.0,13057.59,4489.94,0.0,0.0,15324.08,43182.66,13.9382,0.0,0.0,13150.08,4489.94,0.0,0.0,15324.08,43182.66,13.7731,0.0,0.0,13231.33,4489.94,0.0,0.0,15324.08,43182.66,13.615,0.0,0.0,13310.89,4489.94,0.0,0.0,15324.08,43182.66,13.558,0.0,0.0,13395.09,4489.94,0.0,0.0,15324.08,43182.66,2.12,4.0,2.12,2.12,40000.0,12.76,14.935000000000004 -2019-12-15 01:00:00-06:00,9221.47,1150.14,3670.5,683.79,10045.26,4693.2,2502.07,33029.94,1063.51,75.0,66.0,72.0,0.0,69.0,69.0,180.0,11.0,43068.3,3970.5,631.56,4388.58,8892.63,13912.77,657.4,4359.2,8455.1,13471.7,617.3,4442.6,8992.1,14052.0,3479.1,470.7,6853.9,10803.7,13.7482,0.0,0.0,12333.43,4489.54,0.0,0.0,14937.75,41940.13,13.8296,0.0,0.0,12299.29,4489.54,0.0,0.0,14937.75,41940.13,13.7092,0.0,0.0,12367.24,4489.54,0.0,0.0,14937.75,41940.13,13.5829,0.0,0.0,12430.3,4489.54,0.0,0.0,14937.75,41940.13,13.5629,0.0,0.0,12489.89,4489.54,0.0,0.0,14937.75,41940.13,13.4426,0.0,0.0,12550.83,4489.54,0.0,0.0,14937.75,41940.13,13.3362,0.0,0.0,12612.08,4489.54,0.0,0.0,14937.75,41940.13,13.2341,0.0,0.0,12667.61,4489.54,0.0,0.0,14937.75,41940.13,13.1479,0.0,0.0,12714.44,4489.54,0.0,0.0,14937.75,41940.13,13.0646,0.0,0.0,12759.89,4489.54,0.0,0.0,14937.75,41940.13,12.9834,0.0,0.0,12804.56,4489.54,0.0,0.0,14937.75,41940.13,2.12,4.0,2.12,2.12,40000.0,10.15,13.450000000000003 -2019-12-15 03:00:00-06:00,8947.54,1106.62,3595.01,668.91,9856.76,4577.64,2397.84,32280.48,1130.16,75.0,66.0,72.0,0.0,70.0,70.0,170.0,8.0,43257.6,3939.2,638.81,4307.64,8100.37,13046.82,579.4,4473.9,8276.9,13330.2,635.4,4335.9,8171.1,13142.4,3390.4,497.9,6335.9,10224.2,13.1939,0.0,0.0,12828.75,4481.11,0.0,0.0,14748.95,41403.84,13.0325,0.0,0.0,12909.52,4481.11,0.0,0.0,14748.95,41403.84,13.0059,0.0,0.0,12919.25,4481.11,0.0,0.0,14748.95,41403.84,12.9795,0.0,0.0,12932.52,4481.11,0.0,0.0,14748.95,41403.84,12.9648,0.0,0.0,12941.5,4481.11,0.0,0.0,14748.95,41403.84,12.9651,0.0,0.0,12941.31,4481.11,0.0,0.0,14748.95,41403.84,12.9799,0.0,0.0,12932.31,4481.11,0.0,0.0,14748.95,41403.84,12.9983,0.0,0.0,12922.16,4481.11,0.0,0.0,14748.95,41403.84,13.0009,0.0,0.0,12920.74,4481.11,0.0,0.0,14748.95,41403.84,12.998,0.0,0.0,12922.34,4481.11,0.0,0.0,14748.95,41403.84,13.0064,0.0,0.0,12917.74,4481.11,0.0,0.0,14748.95,41403.84,2.12,4.0,2.12,2.12,40000.0,8.64,12.929999999999996 -2019-12-15 06:00:00-06:00,9077.42,1159.0,3588.42,880.21,10350.96,5014.88,2434.45,33810.16,1304.82,75.0,66.0,72.0,0.0,70.0,70.0,170.0,10.0,45413.1,3912.0,692.93,4467.74,7164.99,12325.66,568.3,4357.0,7601.2,12526.5,701.9,4520.9,7214.1,12436.9,3511.7,527.9,5445.2,9484.8,12.6157,0.0,0.0,12978.53,4304.28,0.0,0.0,16326.12,42851.57,12.3133,0.0,0.0,13086.69,4304.28,0.0,0.0,16326.12,42851.57,12.3967,0.0,0.0,13020.64,4304.28,0.0,0.0,16326.12,42851.57,12.6956,0.0,0.0,12927.54,4304.28,0.0,0.0,16326.12,42851.57,12.9425,0.0,0.0,12844.38,4304.28,0.0,0.0,16326.12,42851.57,13.0916,0.0,0.0,12771.01,4304.28,0.0,0.0,16326.12,42851.57,13.1727,0.0,0.0,12702.03,4304.28,0.0,0.0,16326.12,42851.57,13.2665,0.0,0.0,12626.35,4304.28,0.0,0.0,16326.12,42851.57,13.3736,0.0,0.0,12539.91,4304.28,0.0,0.0,16326.12,42851.57,13.4845,0.0,0.0,12445.3,4304.28,0.0,0.0,16326.12,42851.57,13.5726,0.0,0.0,12343.7,4304.28,0.0,0.0,16326.12,42851.57,2.12,4.0,2.12,2.12,40000.0,15.31,12.684999999999999 -2019-12-15 08:00:00-06:00,9593.04,1246.88,3593.79,965.16,11078.97,5559.1,2583.85,35988.25,1367.48,50.0,67.0,73.0,0.0,72.0,72.0,170.0,9.0,47188.1,3927.3,570.57,4169.62,6681.46,11421.65,573.0,4291.2,6750.9,11615.1,585.5,4296.2,6812.0,11693.7,3290.7,434.1,5072.6,8797.4,13.6832,0.0,0.0,12439.78,4302.5,0.0,0.0,17160.36,44372.48,13.8847,0.0,0.0,12568.73,4302.5,0.0,0.0,17160.36,44372.48,14.1634,0.0,0.0,12432.43,4302.5,0.0,0.0,17160.36,44372.48,14.2464,0.0,0.0,12314.94,4302.5,0.0,0.0,17160.36,44372.48,14.3436,0.0,0.0,12203.6,4302.5,0.0,0.0,17160.36,44372.48,14.447,0.0,0.0,12096.02,4302.5,0.0,0.0,17160.36,44372.48,14.5374,0.0,0.0,12003.52,4302.5,0.0,0.0,17160.36,44372.48,14.619,0.0,0.0,11922.27,4302.5,0.0,0.0,17160.36,44372.48,14.7377,0.0,0.0,11829.43,4302.5,0.0,0.0,17160.36,44372.48,14.9164,0.0,0.0,11702.14,4302.5,0.0,0.0,17160.36,44372.48,15.0402,0.0,0.0,11607.62,4302.5,0.0,0.0,17160.36,44372.48,2.12,4.0,2.12,2.12,40000.0,16.24,14.024999999999999 -2019-12-15 10:00:00-06:00,10725.33,1265.24,3474.73,1006.7,10913.17,5654.54,2907.08,37252.39,1305.6,75.0,67.0,81.0,0.0,79.0,79.0,180.0,14.0,47360.3,3801.2,203.43,3803.54,4954.24,8961.21,342.8,3610.8,5311.1,9264.7,217.6,3821.5,4882.3,8921.4,2916.6,133.6,3361.2,6411.4,16.4392,0.0,0.0,11177.02,4268.59,0.0,0.0,17947.82,44910.96,16.4006,0.0,0.0,11244.67,4268.59,0.0,0.0,17947.82,44910.96,16.4328,0.0,0.0,11187.09,4268.59,0.0,0.0,17947.82,44910.96,16.4403,0.0,0.0,11141.27,4268.59,0.0,0.0,17947.82,44910.96,16.4453,0.0,0.0,11119.72,4268.59,0.0,0.0,17947.82,44910.96,16.447,0.0,0.0,11128.69,4268.59,0.0,0.0,17947.82,44910.96,16.4492,0.0,0.0,11133.5,4268.59,0.0,0.0,17947.82,44910.96,16.4705,0.0,0.0,11129.92,4268.59,0.0,0.0,17947.82,44910.96,16.4969,0.0,0.0,11130.43,4268.59,0.0,0.0,17947.82,44910.96,16.5397,0.0,0.0,11115.67,4268.59,0.0,0.0,17947.82,44910.96,16.5629,0.0,0.0,11119.12,4268.59,0.0,0.0,17947.82,44910.96,2.12,4.0,2.12,2.12,40000.0,17.16,16.519999999999996 -2019-12-15 11:00:00-06:00,11273.91,1271.53,3446.27,999.26,10728.72,5493.58,3084.89,37607.81,1309.65,50.0,65.0,82.0,0.0,81.0,81.0,190.0,15.0,46776.6,3801.2,133.88,3973.35,6189.87,10297.1,227.8,3426.0,4615.7,8269.5,134.2,3985.5,5914.8,10034.5,3005.7,70.0,4101.3,7177.0,16.6249,0.0,0.0,11057.8,4254.35,0.0,0.0,18066.47,44907.27,16.6256,0.0,0.0,11092.02,4254.35,0.0,0.0,18066.47,44907.27,16.6312,0.0,0.0,11071.76,4254.35,0.0,0.0,18066.47,44907.27,16.6693,0.0,0.0,11050.31,4254.35,0.0,0.0,18066.47,44907.27,16.7016,0.0,0.0,11033.29,4254.35,0.0,0.0,18066.47,44907.27,16.7337,0.0,0.0,11016.9,4254.35,0.0,0.0,18066.47,44907.27,16.7511,0.0,0.0,10991.74,4254.35,0.0,0.0,18066.47,44907.27,16.7701,0.0,0.0,10962.21,4254.35,0.0,0.0,18066.47,44907.27,16.7887,0.0,0.0,10933.61,4254.35,0.0,0.0,18066.47,44907.27,16.8083,0.0,0.0,10902.19,4254.35,0.0,0.0,18066.47,44907.27,16.8207,0.0,0.0,10866.59,4254.35,0.0,0.0,18066.47,44907.27,2.12,4.0,2.12,2.12,40000.0,19.51,16.715 -2019-12-15 13:00:00-06:00,11875.59,1330.41,3469.83,979.83,10617.16,5568.43,3372.58,38509.53,1295.69,75.0,64.0,84.0,0.0,82.0,82.0,210.0,14.0,48619.9,3789.3,124.29,3641.2,7917.17,11682.66,113.7,3738.1,6179.0,10030.8,126.7,3678.6,8088.0,11893.3,2796.9,73.6,5846.8,8717.3,14.9082,0.0,0.0,12846.72,4216.91,0.0,0.0,18207.68,47828.17,14.8129,0.0,0.0,12889.46,4216.91,0.0,0.0,18207.68,47828.17,14.8501,0.0,0.0,12849.87,4216.91,0.0,0.0,18207.68,47828.17,14.8749,0.0,0.0,12820.33,4216.91,0.0,0.0,18207.68,47828.17,14.9302,0.0,0.0,12754.27,4216.91,0.0,0.0,18207.68,47828.17,14.9838,0.0,0.0,12692.68,4216.91,0.0,0.0,18207.68,47828.17,15.0322,0.0,0.0,12638.82,4216.91,0.0,0.0,18207.68,47828.17,15.0769,0.0,0.0,12589.08,4216.91,0.0,0.0,18207.68,47828.17,15.1068,0.0,0.0,12556.45,4216.91,0.0,0.0,18207.68,47828.17,15.1402,0.0,0.0,12525.38,4216.91,0.0,0.0,18207.68,47828.17,15.1744,0.0,0.0,12493.91,4216.91,0.0,0.0,18207.68,47828.17,2.12,4.0,2.12,2.12,40000.0,19.23,14.857499999999991 -2019-12-15 14:00:00-06:00,12028.45,1356.31,3468.7,889.98,10631.94,5679.95,3487.79,38869.23,1326.12,50.0,64.0,86.0,0.0,84.0,84.0,180.0,15.0,49304.1,3528.2,161.31,3689.73,7804.77,11655.81,114.9,3719.0,7167.9,11001.8,152.1,3718.7,7790.5,11661.3,2816.4,94.4,5767.2,8678.0,16.4257,0.0,0.0,11882.09,4210.25,0.0,0.0,18210.14,47125.16,16.3706,0.0,0.0,11887.98,4210.25,0.0,0.0,18210.14,47125.16,16.583,0.0,0.0,11811.43,4210.25,0.0,0.0,18210.14,47125.16,16.7285,0.0,0.0,11735.71,4210.25,0.0,0.0,18210.14,47125.16,16.7415,0.0,0.0,11689.11,4210.25,0.0,0.0,18210.14,47125.16,16.7462,0.0,0.0,11654.21,4210.25,0.0,0.0,18210.14,47125.16,16.7502,0.0,0.0,11621.1,4210.25,0.0,0.0,18210.14,47125.16,16.7523,0.0,0.0,11602.75,4210.25,0.0,0.0,18210.14,47125.16,16.753,0.0,0.0,11596.95,4210.25,0.0,0.0,18210.14,47125.16,16.7534,0.0,0.0,11594.27,4210.25,0.0,0.0,18210.14,47125.16,16.7544,0.0,0.0,11585.55,4210.25,0.0,0.0,18210.14,47125.16,2.12,4.0,2.12,2.12,40000.0,19.23,15.80249999999999 -2019-12-15 17:00:00-06:00,12212.97,1429.74,3454.98,881.02,11287.22,6263.66,3484.95,40533.89,1519.34,75.0,66.0,79.0,0.0,77.0,77.0,170.0,9.0,49771.4,3528.5,480.27,4629.56,8379.1,13488.93,387.2,4217.7,8335.9,12940.8,429.7,4650.9,8486.6,13567.2,3654.0,296.2,6267.9,10218.1,16.2998,0.0,0.0,11691.69,4221.34,0.0,0.0,18180.32,47771.41,16.2295,0.0,0.0,11694.23,4221.34,0.0,0.0,18180.32,47771.41,16.3595,0.0,0.0,11570.39,4221.34,0.0,0.0,18180.32,47771.41,16.4681,0.0,0.0,11409.87,4221.34,0.0,0.0,18180.32,47771.41,16.6016,0.0,0.0,11223.33,4221.34,0.0,0.0,18180.32,47771.41,16.7292,0.0,0.0,11009.89,4221.34,0.0,0.0,18180.32,47771.41,16.8716,0.0,0.0,10796.7,4221.34,0.0,0.0,18180.32,47771.41,16.9691,0.0,0.0,10579.41,4221.34,0.0,0.0,18180.32,47771.41,17.1124,0.0,0.0,10375.55,4221.34,0.0,0.0,18180.32,47771.41,17.328,0.0,0.0,10190.59,4221.34,0.0,0.0,18180.32,47771.41,17.4837,0.0,0.0,10050.1,4221.34,0.0,0.0,18180.32,47771.41,2.12,4.0,2.12,2.12,40000.0,21.60,15.699999999999987 -2019-12-15 18:00:00-06:00,12542.89,1478.27,3550.84,956.75,11923.97,6595.29,3590.11,42176.84,1538.72,75.0,67.0,77.0,0.0,76.0,76.0,170.0,13.0,50016.2,3804.6,672.76,4910.45,8589.91,14173.12,504.6,4732.7,8143.6,13380.9,691.8,4951.8,8651.0,14294.6,3948.1,528.4,6383.8,10860.3,27.7348,0.0,0.0,9429.28,4230.39,0.0,0.0,18091.27,47885.22,27.6199,0.0,0.0,9463.45,4230.39,0.0,0.0,18091.27,47885.22,27.692,0.0,0.0,9400.57,4230.39,0.0,0.0,18091.27,47885.22,27.6884,0.0,0.0,9359.49,4230.39,0.0,0.0,18091.27,47885.22,27.6736,0.0,0.0,9331.7,4230.39,0.0,0.0,18091.27,47885.22,27.6543,0.0,0.0,9309.28,4230.39,0.0,0.0,18091.27,47885.22,27.6305,0.0,0.0,9292.15,4230.39,0.0,0.0,18091.27,47885.22,27.6028,0.0,0.0,9279.67,4230.39,0.0,0.0,18091.27,47885.22,27.5718,0.0,0.0,9271.13,4230.39,0.0,0.0,18091.27,47885.22,27.574,0.0,0.0,9261.76,4230.39,0.0,0.0,18091.27,47885.22,27.5736,0.0,0.0,9257.28,4230.39,0.0,0.0,18091.27,47885.22,2.12,4.0,2.12,2.12,40000.0,18.81,18.73749999999999 -2019-12-15 19:00:00-06:00,12482.63,1465.93,3608.86,1057.61,11980.35,6567.71,3579.65,42213.73,1470.98,75.0,69.0,78.0,0.0,75.0,75.0,170.0,10.0,49392.8,3796.0,652.28,5129.92,8360.01,14142.21,670.2,4910.2,8318.1,13898.5,648.4,5192.0,8432.5,14272.9,4208.4,491.7,6087.3,10787.4,34.5809,0.0,0.0,9642.88,4242.13,0.0,0.0,18146.89,48630.32,34.4273,0.0,0.0,9774.07,4242.13,0.0,0.0,18146.89,48630.32,34.423,0.0,0.0,9797.74,4242.13,0.0,0.0,18146.89,48630.32,34.4148,0.0,0.0,9818.2,4242.13,0.0,0.0,18146.89,48630.32,34.4085,0.0,0.0,9842.24,4242.13,0.0,0.0,18146.89,48630.32,34.4066,0.0,0.0,9869.42,4242.13,0.0,0.0,18146.89,48630.32,34.4045,0.0,0.0,9897.92,4242.13,0.0,0.0,18146.89,48630.32,25.7349,0.0,0.0,9952.08,4242.13,0.0,0.0,18146.89,48630.32,25.7373,0.0,0.0,9999.77,4242.13,0.0,0.0,18146.89,48630.32,25.6733,0.0,0.0,10043.97,4242.13,0.0,0.0,18146.89,48630.32,25.6646,0.0,0.0,10079.91,4242.13,0.0,0.0,18146.89,48630.32,2.12,4.0,2.12,2.12,40000.0,17.09,19.549999999999994 -2019-12-15 21:00:00-06:00,11976.06,1378.13,3637.55,971.58,11678.09,6156.86,3426.06,40568.82,1344.48,100.0,69.0,76.0,0.0,74.0,74.0,170.0,9.0,47334.4,3786.9,736.47,5285.26,7830.84,13852.57,609.4,5084.6,7237.2,12931.2,728.1,5314.3,7910.8,13953.2,4348.5,568.5,5620.7,10537.7,18.2665,0.0,0.0,10108.67,4432.27,0.0,0.0,17645.59,47855.05,18.3206,0.0,0.0,10147.3,4432.27,0.0,0.0,17645.59,47855.05,18.2387,0.0,0.0,10238.11,4432.27,0.0,0.0,17645.59,47855.05,18.219,0.0,0.0,10322.13,4432.27,0.0,0.0,17645.59,47855.05,18.2082,0.0,0.0,10419.93,4432.27,0.0,0.0,17645.59,47855.05,18.197,0.0,0.0,10527.15,4432.27,0.0,0.0,17645.59,47855.05,18.1834,0.0,0.0,10651.16,4432.27,0.0,0.0,17645.59,47855.05,16.3767,0.0,0.0,10794.92,4432.27,0.0,0.0,17645.59,47855.05,16.3444,0.0,0.0,10927.6,4432.27,0.0,0.0,17645.59,47855.05,16.3375,0.0,0.0,11071.6,4432.27,0.0,0.0,17645.59,47855.05,16.2596,0.0,0.0,11213.94,4432.27,0.0,0.0,17645.59,47855.05,2.12,4.0,2.12,2.12,40000.0,18.17,17.169999999999987 -2019-12-15 22:00:00-06:00,11403.93,1269.76,3642.78,898.89,11018.22,5722.49,3264.34,38461.96,1241.55,75.0,69.0,76.0,0.0,74.0,74.0,170.0,7.0,45203.5,3900.4,692.72,5188.95,6603.66,12485.33,591.0,5025.0,6596.3,12212.3,718.1,5261.6,6636.5,12616.2,4304.2,565.5,4462.7,9332.4,26.2168,0.0,0.0,9908.37,4433.26,0.0,0.0,17056.27,45950.73,26.4915,0.0,0.0,9683.44,4433.26,0.0,0.0,16736.27,45404.73,26.2231,0.0,0.0,9884.83,4433.26,0.0,0.0,16736.27,45404.73,25.9743,0.0,0.0,10089.25,4433.26,0.0,0.0,16736.27,45404.73,25.9085,0.0,0.0,10288.91,4433.26,0.0,0.0,16736.27,45404.73,25.8307,0.0,0.0,10497.08,4433.26,0.0,0.0,16736.27,45404.73,21.0525,0.0,0.0,10700.64,4433.26,0.0,0.0,16736.27,45404.73,16.5754,0.0,0.0,10908.32,4433.26,0.0,0.0,16736.27,45404.73,16.5642,0.0,0.0,11108.77,4433.26,0.0,0.0,16736.27,45404.73,16.4883,0.0,0.0,11301.46,4433.26,0.0,0.0,16736.27,45404.73,16.369,0.0,0.0,11499.58,4433.26,0.0,0.0,16736.27,45404.73,2.12,4.0,2.12,2.12,40000.0,15.89,18.29499999999999 -2019-12-15 23:00:00-06:00,10748.55,1165.75,3681.1,872.7,10261.45,5253.94,3064.11,36189.83,1142.23,75.0,69.0,76.0,0.0,74.0,74.0,170.0,11.0,44679.0,3896.5,510.68,5063.97,6296.75,11871.4,688.8,5026.5,6006.0,11721.3,515.6,5100.4,6137.9,11753.9,4173.4,394.0,3988.2,8555.6,17.4825,0.0,0.0,9601.86,4438.05,0.0,0.0,16365.59,43240.45,17.2535,0.0,0.0,9756.34,4438.05,0.0,0.0,16365.59,43240.45,16.982,0.0,0.0,9976.41,4438.05,0.0,0.0,16365.59,43240.45,16.716,0.0,0.0,10198.71,4438.05,0.0,0.0,16365.59,43240.45,16.6267,0.0,0.0,10412.0,4438.05,0.0,0.0,16365.59,43240.45,16.448,0.0,0.0,10614.33,4438.05,0.0,0.0,16365.59,43240.45,16.3388,0.0,0.0,10811.79,4438.05,0.0,0.0,16365.59,43240.45,16.2565,0.0,0.0,11005.45,4438.05,0.0,0.0,16365.59,43240.45,16.18,0.0,0.0,11196.03,4438.05,0.0,0.0,16365.59,43240.45,16.1322,0.0,0.0,11373.53,4438.05,0.0,0.0,16365.59,43240.45,16.0778,0.0,0.0,11534.66,4438.05,0.0,0.0,16365.59,43240.45,2.12,4.0,2.12,2.12,40000.0,14.84,17.507499999999993 -2019-12-16 00:00:00-06:00,10203.4,1085.48,3626.61,842.88,9811.99,4853.9,2909.26,34480.38,1146.86,75.0,69.0,76.0,0.0,74.0,74.0,170.0,10.0,43091.4,3855.7,412.8,4986.2,6200.94,11599.94,640.4,4892.4,5104.3,10637.1,421.4,4947.5,6108.4,11477.3,4018.1,305.6,3981.0,8304.7,16.5804,0.0,0.0,11446.86,4451.18,0.0,0.0,16288.42,43620.18,16.3133,0.0,0.0,11558.74,4451.18,0.0,0.0,16288.42,43620.18,16.2279,0.0,0.0,11707.46,4451.18,0.0,0.0,16288.42,43620.18,15.5316,0.0,0.0,11973.42,4451.18,0.0,0.0,16288.42,43620.18,15.3046,0.0,0.0,12097.93,4451.18,0.0,0.0,16288.42,43620.18,15.1238,0.0,0.0,12218.52,4451.18,0.0,0.0,16288.42,43620.18,14.9751,0.0,0.0,12338.42,4451.18,0.0,0.0,16288.42,43620.18,14.8002,0.0,0.0,12453.02,4451.18,0.0,0.0,16288.42,43620.18,14.6136,0.0,0.0,12561.32,4451.18,0.0,0.0,16288.42,43620.18,14.3375,0.0,0.0,12666.3,4451.18,0.0,0.0,16288.42,43620.18,14.2267,0.0,0.0,12767.11,4451.18,0.0,0.0,16288.42,43620.18,2.245,22.0,2.27,2.235,139000.0,14.13,15.747499999999993 -2019-12-16 02:00:00-06:00,9684.51,1031.88,3672.98,779.65,9706.22,4501.64,2684.63,33183.68,1122.18,75.0,69.0,76.0,0.0,73.0,73.0,160.0,6.0,42855.9,3851.7,343.32,4715.84,6001.91,11061.07,393.5,4458.7,5182.4,10034.6,328.6,4719.6,6000.1,11048.3,3763.3,210.4,3960.4,7934.1,14.5739,0.0,0.0,12165.71,4472.05,0.0,0.0,16374.66,42790.95,14.2892,0.0,0.0,12284.32,4472.05,0.0,0.0,16374.66,42790.95,14.1963,0.0,0.0,12350.43,4472.05,0.0,0.0,16374.66,42790.95,14.073,0.0,0.0,12444.67,4472.05,0.0,0.0,16374.66,42790.95,13.9537,0.0,0.0,12537.45,4472.05,0.0,0.0,16374.66,42790.95,13.8874,0.0,0.0,12591.4,4472.05,0.0,0.0,16374.66,42790.95,13.8563,0.0,0.0,12620.1,4472.05,0.0,0.0,16374.66,42790.95,13.8302,0.0,0.0,12645.48,4472.05,0.0,0.0,16374.66,42790.95,13.8042,0.0,0.0,12670.78,4472.05,0.0,0.0,16374.66,42790.95,13.7831,0.0,0.0,12692.16,4472.05,0.0,0.0,16374.66,42790.95,13.758,0.0,0.0,12708.7,4472.05,0.0,0.0,16374.66,42790.95,2.245,22.0,2.27,2.235,139000.0,14.51,14.747499999999995 -2019-12-16 03:00:00-06:00,9638.92,1035.49,3709.7,798.87,9975.93,4451.2,2614.51,33353.31,1128.68,75.0,69.0,76.0,0.0,74.0,74.0,160.0,9.0,43017.8,3956.0,520.96,4304.26,6129.38,10954.6,470.7,4409.8,5258.4,10138.9,503.9,4334.6,5993.7,10832.2,3367.0,366.1,3980.7,7713.8,14.0963,0.0,0.0,12832.13,4475.2,0.0,0.0,16701.83,43492.08,13.851,0.0,0.0,13021.45,4475.2,0.0,0.0,16701.83,43492.08,13.7243,0.0,0.0,13122.17,4475.2,0.0,0.0,16701.83,43492.08,13.5859,0.0,0.0,13228.39,4475.2,0.0,0.0,16701.83,43492.08,13.5085,0.0,0.0,13284.17,4475.2,0.0,0.0,16701.83,43492.08,13.4838,0.0,0.0,13333.43,4475.2,0.0,0.0,16701.83,43492.08,13.4922,0.0,0.0,13327.55,4475.2,0.0,0.0,16701.83,43492.08,13.4988,0.0,0.0,13305.04,4475.2,0.0,0.0,16701.83,43492.08,13.5107,0.0,0.0,13282.4,4475.2,0.0,0.0,16701.83,43492.08,13.5479,0.0,0.0,13256.19,4475.2,0.0,0.0,16701.83,43492.08,13.6061,0.0,0.0,13215.47,4475.2,0.0,0.0,16701.83,43492.08,2.245,22.0,2.27,2.235,139000.0,15.11,14.162499999999998 -2019-12-16 04:00:00-06:00,9826.17,1071.22,3804.42,871.82,10621.78,4548.54,2594.38,34461.17,1122.82,100.0,69.0,76.0,0.0,73.0,73.0,170.0,8.0,43134.3,3956.2,602.95,3927.37,6487.24,11017.56,508.1,4072.9,5263.8,9844.8,602.0,3917.1,6394.9,10914.0,2962.9,459.0,4374.6,7796.5,14.314,0.0,0.0,13063.88,4472.99,0.0,0.0,16977.8,43896.07,14.1323,0.0,0.0,13098.61,4472.99,0.0,0.0,16977.8,43896.07,14.1979,0.0,0.0,13021.92,4472.99,0.0,0.0,16977.8,43896.07,14.2337,0.0,0.0,12960.5,4472.99,0.0,0.0,16977.8,43896.07,14.2785,0.0,0.0,12915.09,4472.99,0.0,0.0,16977.8,43896.07,14.341,0.0,0.0,12869.53,4472.99,0.0,0.0,16977.8,43896.07,14.4224,0.0,0.0,12802.69,4472.99,0.0,0.0,16977.8,43896.07,16.0548,0.0,0.0,12699.58,4472.99,0.0,0.0,16977.8,43896.07,16.5006,0.0,0.0,12593.57,4472.99,0.0,0.0,16977.8,43896.07,18.4833,0.0,0.0,12482.99,4472.99,0.0,0.0,16977.8,43896.07,19.7226,0.0,0.0,12348.83,4472.99,0.0,0.0,16977.8,43896.07,2.245,22.0,2.27,2.235,139000.0,15.77,14.377500000000005 -2019-12-16 05:00:00-06:00,10350.84,1166.04,3950.92,937.38,11860.28,4918.08,2725.87,37049.33,1139.91,100.0,70.0,76.0,0.0,73.0,73.0,160.0,9.0,43905.2,3958.3,569.85,3808.04,6840.23,11218.12,538.4,3569.1,5603.0,9710.5,562.9,3922.4,6769.4,11254.7,2948.4,411.5,4774.9,8134.8,16.2502,0.0,0.0,12071.08,4477.95,0.0,0.0,18033.64,45631.86,15.0467,0.0,0.0,12395.29,4477.95,0.0,0.0,18033.64,45631.86,15.642,0.0,0.0,12190.26,4477.95,0.0,0.0,18033.64,45631.86,16.0897,0.0,0.0,12021.58,4477.95,0.0,0.0,18033.64,45631.86,17.094,0.0,0.0,11855.15,4477.95,0.0,0.0,18033.64,45631.86,17.8914,0.0,0.0,11710.34,4477.95,0.0,0.0,18033.64,45631.86,18.0853,0.0,0.0,11528.42,4477.95,0.0,0.0,18033.64,45631.86,19.0328,0.0,0.0,11299.2,4477.95,0.0,0.0,18033.64,45631.86,20.0784,0.0,0.0,11042.98,4477.95,0.0,0.0,18033.64,45631.86,21.4378,0.0,0.0,10814.96,4477.95,0.0,0.0,18033.64,45631.86,21.7032,0.0,0.0,10587.03,4477.95,0.0,0.0,18033.64,45631.86,2.245,22.0,2.27,2.235,139000.0,17.38,15.000000000000004 -2019-12-16 06:00:00-06:00,11089.17,1325.75,4120.32,1068.51,13596.6,5570.84,2996.43,40993.46,1225.85,100.0,70.0,76.0,0.0,74.0,74.0,160.0,7.0,48510.2,3841.6,602.52,3245.27,6788.87,10636.66,604.3,3028.2,6212.5,9845.0,593.6,3300.9,6677.4,10571.9,2464.0,437.1,4726.1,7627.2,15.795,0.0,0.0,12348.65,4124.3,0.0,0.0,19266.96,48324.93,15.8403,0.0,0.0,12370.84,4124.3,0.0,0.0,19266.96,48324.93,16.4204,0.0,0.0,11986.24,4124.3,0.0,0.0,19266.96,48324.93,16.7415,0.0,0.0,11631.56,4124.3,0.0,0.0,19266.96,48324.93,17.0193,0.0,0.0,11327.39,4124.3,0.0,0.0,19266.96,48324.93,17.2443,0.0,0.0,11057.53,4124.3,0.0,0.0,19266.96,48324.93,17.3408,0.0,0.0,10819.08,4124.3,0.0,0.0,19266.96,48324.93,17.4421,0.0,0.0,10602.38,4124.3,0.0,0.0,19266.96,48324.93,17.8022,0.0,0.0,10382.64,4124.3,0.0,0.0,19266.96,48324.93,18.4575,0.0,0.0,10198.83,4124.3,0.0,0.0,19266.96,48324.93,19.1078,0.0,0.0,10047.19,4124.3,0.0,0.0,19266.96,48324.93,2.245,22.0,2.27,2.235,139000.0,28.25,16.695000000000004 -2019-12-16 08:00:00-06:00,11576.21,1460.11,3937.84,1137.65,14807.55,6046.97,3063.38,43485.15,1455.43,100.0,70.0,78.0,0.0,75.0,75.0,170.0,9.0,49352.6,3866.1,488.46,2242.9,5212.7,7944.06,641.8,2313.2,5612.3,8567.3,494.6,2273.4,5045.4,7813.4,1660.5,351.5,3255.7,5267.7,30.7655,0.0002,0.0,6929.39,4196.36,0.0,0.0,19657.08,47043.17,21.6172,0.0,0.0,7196.1,4196.36,0.0,0.0,19657.08,47043.17,21.9506,0.0,0.0,7176.73,4196.36,0.0,0.0,19657.08,47043.17,21.8214,0.0,0.0,7169.0,4196.36,0.0,0.0,19657.08,47043.17,21.5638,0.0,0.0,7150.97,4196.36,0.0,0.0,19657.08,47043.17,21.2807,0.0,0.0,7136.49,4196.36,0.0,0.0,19657.08,47043.17,21.1526,0.0,0.0,7119.82,4196.36,0.0,0.0,19657.08,47043.17,21.0739,0.0,0.0,7102.65,4196.36,0.0,0.0,19657.08,47043.17,20.959,0.0001,0.0,7093.38,4196.36,0.0,0.0,19657.08,47043.17,20.889,0.0001,0.0,7074.15,4196.36,0.0,0.0,19657.08,47043.17,21.0756,0.0001,0.0,7041.3,4196.36,0.0,0.0,19657.08,47043.17,2.245,22.0,2.27,2.235,139000.0,22.42,23.947499999999998 -2019-12-16 09:00:00-06:00,11916.96,1511.02,3824.27,1131.53,15049.85,6151.61,3174.65,44234.82,1474.93,100.0,70.0,80.0,0.01,77.0,77.0,170.0,11.0,49849.6,3847.6,560.83,1989.44,5920.14,8470.41,593.1,2462.7,5356.2,8412.0,552.5,2003.4,5814.7,8370.6,1521.5,387.7,3822.1,5731.3,23.8875,0.0043,0.0,6382.03,4154.29,0.0,0.0,19948.57,46878.53,22.774,0.0036,0.0,6415.85,4154.29,0.0,0.0,19893.57,46804.53,23.2631,0.0053,0.0,6347.2,4154.29,0.0,0.0,19893.57,46804.53,23.6329,0.0073,0.0,6291.15,4154.29,0.0,0.0,19893.57,46804.53,23.6339,0.0096,0.0,6242.46,4154.29,0.0,0.0,19893.57,46804.53,24.2992,0.0128,0.0,6191.81,4154.29,0.0,0.0,19893.57,46804.53,26.7709,0.0175,0.0,6134.34,4154.29,0.0,0.0,19893.57,46804.53,35.3479,0.0227,0.0,6085.95,4154.29,0.0,0.0,19893.57,46804.53,35.7053,0.0259,0.0,6061.45,4154.29,0.0,0.0,19893.57,46804.53,42.7747,0.0275,0.0,6050.44,4154.29,0.0,0.0,19893.57,46804.53,42.7755,0.0285,0.0,6043.4,4154.29,0.0,0.0,19893.57,46804.53,2.245,22.0,2.27,2.235,139000.0,22.27,23.167500000000004 -2019-12-16 11:00:00-06:00,12223.96,1581.44,3688.95,1124.17,15298.56,6264.58,3385.6,45023.72,1456.46,100.0,58.0,61.0,0.01,61.0,61.0,300.0,16.0,51254.3,3745.8,742.19,2077.86,7092.66,9912.71,652.4,2396.3,6651.3,9700.0,756.2,2088.9,6967.8,9812.9,1467.4,577.2,4711.0,6755.6,20.7961,0.0,0.0,7334.98,4209.05,0.0,0.0,19404.67,49029.14,20.9006,0.0,0.0,7375.87,4209.05,0.0,0.0,19404.67,49029.14,20.9002,0.0,0.0,7451.02,4209.05,0.0,0.0,19404.67,49029.14,20.9,0.0,0.0,7517.91,4209.05,0.0,0.0,19404.67,49029.14,20.4157,0.0,0.0,7565.2,4209.05,0.0,0.0,19404.67,49029.14,20.0682,0.0,0.0,7630.04,4209.05,0.0,0.0,19404.67,49029.14,19.9967,0.0,0.0,7699.98,4209.05,0.0,0.0,19404.67,49029.14,19.9157,0.0,0.0,7775.96,4209.05,0.0,0.0,19404.67,49029.14,19.7655,0.0,0.0,7842.23,4209.05,0.0,0.0,19404.67,49029.14,19.5895,0.0,0.0,7911.94,4209.05,0.0,0.0,19404.67,49029.14,19.5437,0.0,0.0,7993.05,4209.05,0.0,0.0,19404.67,49029.14,2.245,22.0,2.27,2.235,139000.0,20.43,22.189999999999994 -2019-12-16 13:00:00-06:00,11229.95,1599.82,3730.6,1129.88,15149.57,6019.86,3503.75,43702.11,1338.67,100.0,51.0,57.0,0.01,57.0,57.0,310.0,15.0,51633.0,3750.7,885.65,2865.19,7977.73,11728.57,828.0,3047.4,7511.7,11387.1,869.7,2876.6,7859.0,11605.3,2205.6,720.7,5379.6,8305.9,19.9254,0.0,0.0,8302.78,4423.99,0.0,0.0,19256.05,50078.16,20.0284,0.0,0.0,8170.38,4423.99,0.0,0.0,18909.05,49293.16,19.9372,0.0,0.0,8232.21,4423.99,0.0,0.0,18909.05,49293.16,19.9334,0.0,0.0,8294.41,4423.99,0.0,0.0,18909.05,49293.16,19.9285,0.0,0.0,8367.35,4423.99,0.0,0.0,18909.05,49293.16,19.9111,0.0,0.0,8441.29,4423.99,0.0,0.0,18909.05,49293.16,19.6607,0.0,0.0,8516.61,4423.99,0.0,0.0,18909.05,49293.16,19.4994,0.0,0.0,8591.02,4423.99,0.0,0.0,18909.05,49293.16,19.2422,0.0,0.0,8667.85,4423.99,0.0,0.0,18909.05,49293.16,19.0696,0.0,0.0,8741.85,4423.99,0.0,0.0,18909.05,49293.16,19.0432,0.0,0.0,8822.7,4423.99,0.0,0.0,18909.05,49293.16,2.245,22.0,2.27,2.235,139000.0,18.82,19.79499999999999 -2019-12-16 14:00:00-06:00,10935.06,1591.21,3780.95,1174.13,15064.24,5947.5,3506.12,43270.56,1271.35,100.0,48.0,56.0,0.01,56.0,56.0,330.0,18.0,53186.4,3738.8,927.05,3659.85,8485.86,13072.76,889.4,3698.4,8501.6,13089.4,940.3,3667.5,8504.0,13111.8,2801.8,809.8,6094.6,9706.2,16.3768,0.0,0.0,11627.29,4507.76,0.0,0.0,19158.65,51720.71,16.6273,0.0,0.0,11432.99,4507.76,0.0,0.0,19158.65,51720.71,16.6485,0.0,0.0,11461.62,4507.76,0.0,0.0,19158.65,51720.71,16.6945,0.0,0.0,11502.52,4507.76,0.0,0.0,19158.65,51720.71,16.7477,0.0,0.0,11547.59,4507.76,0.0,0.0,19158.65,51720.71,16.7792,0.0,0.0,11595.31,4507.76,0.0,0.0,19158.65,51720.71,16.7802,0.0,0.0,11645.96,4507.76,0.0,0.0,19158.65,51720.71,16.7641,0.0,0.0,11691.95,4507.76,0.0,0.0,19158.65,51720.71,16.7475,0.0,0.0,11739.22,4507.76,0.0,0.0,19158.65,51720.71,16.7256,0.0,0.0,11791.91,4507.76,0.0,0.0,19158.65,51720.71,16.6669,0.0,0.0,11848.09,4507.76,0.0,0.0,19158.65,51720.71,2.245,22.0,2.27,2.235,139000.0,17.61,17.09999999999999 -2019-12-16 15:00:00-06:00,10820.85,1581.33,3800.11,1118.47,15208.18,5894.81,3470.46,43180.27,1286.06,100.0,46.0,54.0,0.0,54.0,54.0,340.0,15.0,53904.4,3678.1,891.02,4385.38,8937.72,14214.12,894.9,4149.4,8839.9,13884.2,887.2,4535.6,8813.6,14236.4,3520.1,734.0,6377.8,10631.9,16.4475,0.0,0.0,12397.49,4401.82,0.0,0.0,19139.8,52140.96,16.4579,0.0,0.0,12340.29,4401.82,0.0,0.0,19112.8,52112.96,16.4556,0.0,0.0,12351.16,4401.82,0.0,0.0,19112.8,52112.96,16.4551,0.0,0.0,12361.97,4401.82,0.0,0.0,19112.8,52112.96,16.4544,0.0,0.0,12359.14,4401.82,0.0,0.0,19112.8,52112.96,16.4549,0.0,0.0,12355.18,4401.82,0.0,0.0,19112.8,52112.96,16.4549,0.0,0.0,12354.75,4401.82,0.0,0.0,19112.8,52112.96,16.455,0.0,0.0,12354.36,4401.82,0.0,0.0,19112.8,52112.96,16.4562,0.0,0.0,12340.74,4401.82,0.0,0.0,19112.8,52112.96,16.4579,0.0,0.0,12320.8,4401.82,0.0,0.0,19112.8,52112.96,16.4594,0.0,0.0,12304.09,4401.82,0.0,0.0,19112.8,52112.96,2.245,22.0,2.27,2.235,139000.0,16.29,16.557499999999994 -2019-12-16 16:00:00-06:00,10840.46,1641.03,3796.51,1174.08,15816.63,6072.86,3413.82,44120.12,1364.72,75.0,44.0,53.0,0.0,53.0,53.0,340.0,22.0,54044.0,3684.7,923.5,4187.91,9547.92,14659.33,937.0,4642.7,9028.1,14607.8,933.0,4283.2,9418.8,14635.0,3285.2,784.0,6846.5,10915.7,16.5483,0.0,0.0,12586.03,4455.02,0.0,0.0,19016.98,53079.46,16.4931,0.0,0.0,12580.57,4496.58,0.0,0.0,18996.98,53037.9,16.4684,0.0,0.0,12537.68,4496.58,0.0,0.0,18996.98,53037.9,16.4402,0.0,0.0,12499.21,4496.58,0.0,0.0,18996.98,53037.9,16.4408,0.0,0.0,12449.45,4496.58,0.0,0.0,18996.98,53037.9,16.4418,0.0,0.0,12393.94,4496.58,0.0,0.0,18996.98,53037.9,16.4448,0.0,0.0,12314.68,4496.58,0.0,0.0,18996.98,53037.9,16.4483,0.0,0.0,12230.19,4496.58,0.0,0.0,18996.98,53037.9,16.4536,0.0,0.0,12125.44,4496.58,0.0,0.0,18996.98,53037.9,16.4582,0.0,0.0,12027.3,4496.58,0.0,0.0,18996.98,53037.9,16.4887,0.0,0.0,11928.38,4496.58,0.0,0.0,18996.98,53037.9,2.245,22.0,2.27,2.235,139000.0,17.00,16.194999999999993 -2019-12-16 17:00:00-06:00,11258.55,1778.82,3781.3,1180.94,16834.2,6603.23,3373.56,46327.94,1517.34,75.0,42.0,51.0,0.0,51.0,51.0,340.0,21.0,53785.6,3688.2,854.01,4246.02,9445.05,14545.08,885.0,5015.3,8890.9,14791.2,849.3,4342.9,9628.7,14820.9,3388.3,689.6,7066.8,11144.7,16.6297,0.0,0.0,11863.34,4343.76,0.0,0.0,19034.5,52821.08,16.7601,0.0,0.0,11680.41,4343.76,0.0,0.0,19034.5,52821.08,17.0158,0.0,0.0,11491.14,4343.76,0.0,0.0,19034.5,52821.08,17.3696,0.0,0.0,11242.47,4343.76,0.0,0.0,19034.5,52821.08,17.856,0.0,0.0,10941.81,4343.76,0.0,0.0,19034.5,52821.08,18.1055,0.0,0.0,10602.54,4343.76,0.0,0.0,19034.5,52821.08,18.4044,0.0,0.0,10236.15,4343.76,0.0,0.0,19034.5,52821.08,18.9426,0.0,0.0,9857.95,4343.76,0.0,0.0,19034.5,52821.08,19.6603,0.0,0.0,9492.85,4343.76,0.0,0.0,19034.5,52821.08,20.0184,0.0,0.0,9161.35,4343.76,0.0,0.0,19034.5,52821.08,20.1356,0.0,0.0,8884.69,4343.76,0.0,0.0,19034.5,52821.08,2.245,22.0,2.27,2.235,139000.0,20.47,17.132499999999993 -2019-12-16 18:00:00-06:00,11438.85,1889.83,3908.51,1203.94,17650.82,7285.02,3444.09,48426.19,1605.14,75.0,40.0,50.0,0.0,50.0,43.0,350.0,23.0,52654.9,3764.9,917.37,4111.41,9274.77,14303.55,942.0,4423.2,8545.4,13910.6,920.0,4186.8,8999.4,14106.2,3214.2,771.2,6576.8,10562.2,30.5132,0.0001,0.0,6950.99,4177.46,0.0,0.0,19520.35,52157.13,28.3983,0.0001,0.0,6972.69,4177.46,0.0,0.0,19520.35,52157.13,28.3947,0.0002,0.0,6926.77,4177.46,0.0,0.0,19520.35,52157.13,28.3205,0.0002,0.0,6852.47,4177.46,0.0,0.0,19520.35,52157.13,28.2573,0.0004,0.0,6787.97,4177.46,0.0,0.0,19520.35,52157.13,28.2226,0.0005,0.0,6739.18,4177.46,0.0,0.0,19520.35,52157.13,28.2175,0.0006,0.0,6699.76,4177.46,0.0,0.0,19520.35,52157.13,28.2186,0.0008,0.0,6660.8,4177.46,0.0,0.0,19520.35,52157.13,28.2469,0.001,0.0,6631.87,4177.46,0.0,0.0,19520.35,52157.13,28.2997,0.0011,0.0,6610.78,4177.46,0.0,0.0,19520.35,52157.13,28.3703,0.0013,0.0,6590.81,4177.46,0.0,0.0,19520.35,52157.13,2.245,22.0,2.27,2.235,139000.0,19.75,31.21999999999999 -2019-12-16 19:00:00-06:00,11603.65,1883.24,4025.31,1199.65,17633.16,7457.99,3385.41,48754.2,1565.79,75.0,38.0,49.0,0.0,49.0,42.0,350.0,18.0,53608.6,3782.3,950.8,4364.39,9988.62,15303.81,895.0,4492.6,9487.6,14875.2,945.9,4423.5,9807.7,15177.1,3411.2,816.6,7499.7,11727.5,21.0134,0.0,0.0,7171.87,4512.21,0.0,0.0,19190.2,52595.91,20.9263,0.0,0.0,7236.15,4562.17,0.0,0.0,19166.2,52545.96,21.0,0.0,0.0,7260.35,4562.17,0.0,0.0,19166.2,52545.96,21.0061,0.0,0.0,7278.91,4562.17,0.0,0.0,19166.2,52545.96,21.0127,0.0,0.0,7276.51,4562.17,0.0,0.0,19166.2,52545.96,21.0188,0.0,0.0,7264.67,4562.17,0.0,0.0,19166.2,52545.96,21.1111,0.0,0.0,7249.27,4562.17,0.0,0.0,19166.2,52545.96,21.1111,0.0,0.0,7247.51,4562.17,0.0,0.0,19166.2,52545.96,21.111,0.0,0.0,7244.7,4562.17,0.0,0.0,19166.2,52545.96,21.1229,0.0,0.0,7231.16,4562.17,0.0,0.0,19166.2,52545.96,21.1279,0.0,0.0,7229.32,4562.17,0.0,0.0,19166.2,52545.96,2.245,22.0,2.27,2.235,139000.0,18.91,20.509999999999994 -2019-12-16 21:00:00-06:00,11304.92,1908.36,4122.01,1146.13,16957.02,7431.69,3189.72,47572.08,1512.23,19.0,35.0,45.0,0.0,45.0,37.0,350.0,18.0,54147.1,3761.7,971.7,4807.71,9829.94,15609.35,945.6,4624.3,9574.9,15144.8,972.3,4978.9,9901.3,15852.5,3955.6,846.0,7441.6,12243.2,25.6897,0.0,0.0,8564.43,4724.14,0.0,0.0,19096.37,53494.17,28.6383,0.0,0.0,8504.38,4847.06,0.0,0.0,19031.37,53371.25,27.9899,0.0,0.0,8588.67,4847.06,0.0,0.0,19031.37,53371.25,27.6922,0.0,0.0,8670.45,4847.06,0.0,0.0,19031.37,53371.25,27.4967,0.0,0.0,8765.87,4847.06,0.0,0.0,19031.37,53371.25,27.3461,0.0,0.0,8879.42,4847.06,0.0,0.0,19031.37,53371.25,27.1025,0.0,0.0,9011.38,4847.06,0.0,0.0,19031.37,53371.25,25.6055,0.0,0.0,9150.85,4847.06,0.0,0.0,19031.37,53371.25,24.2596,0.0,0.0,9293.66,4847.06,0.0,0.0,19031.37,53371.25,24.2805,0.0,0.0,9449.84,4847.06,0.0,0.0,19031.37,53371.25,24.2126,0.0,0.0,9624.8,4847.06,0.0,0.0,19031.37,53371.25,2.245,22.0,2.27,2.235,139000.0,16.62,16.852499999999996 -2019-12-16 22:00:00-06:00,10848.23,1797.22,4015.11,1104.25,15974.23,7110.33,2994.09,45331.84,1488.38,50.0,35.0,45.0,0.0,45.0,38.0,350.0,16.0,54135.5,3829.1,933.39,4770.17,9785.13,15488.69,922.2,4958.6,9733.3,15614.1,939.5,4845.0,9861.9,15646.4,3827.5,796.3,7308.9,11932.7,17.8404,0.0,0.0,10347.51,4494.03,0.0,0.0,19132.97,53156.86,17.9642,0.0,0.0,10354.71,4543.96,0.0,0.0,19068.97,53001.93,17.7449,0.0,0.0,10561.1,4543.96,0.0,0.0,19068.97,53001.93,17.578,0.0,0.0,10744.22,4543.96,0.0,0.0,19068.97,53001.93,17.4028,0.0,0.0,10923.53,4543.96,0.0,0.0,19068.97,53001.93,17.2555,0.0,0.0,11105.48,4543.96,0.0,0.0,19068.97,53001.93,17.0694,0.0,0.0,11297.44,4543.96,0.0,0.0,19068.97,53001.93,16.8664,0.0,0.0,11497.31,4543.96,0.0,0.0,19068.97,53001.93,16.6851,0.0,0.0,11692.83,4543.96,0.0,0.0,19068.97,53001.93,16.6284,0.0,0.0,11884.51,4543.96,0.0,0.0,19068.97,53001.93,16.6123,0.0,0.0,12081.73,4543.96,0.0,0.0,19068.97,53001.93,2.245,22.0,2.27,2.235,139000.0,15.47,17.3575 -2019-12-16 23:00:00-06:00,10415.41,1696.03,3926.96,1056.85,15027.02,6752.42,2790.68,43117.04,1451.69,75.0,34.0,44.0,0.0,44.0,36.0,350.0,20.0,52780.9,3827.3,880.51,4806.69,9331.14,15018.34,916.5,4978.7,8977.3,14872.5,887.6,4885.3,9378.7,15151.6,3907.9,750.9,7061.0,11719.8,18.9604,0.0,0.0,11693.27,4504.74,0.0,0.0,19187.68,52619.54,19.0407,0.0,0.0,11532.57,4554.55,0.0,0.0,19013.68,52292.73,18.9742,0.0,0.0,11734.93,4554.55,0.0,0.0,19013.68,52292.73,18.9439,0.0,0.0,11931.49,4554.55,0.0,0.0,19013.68,52292.73,18.7413,0.0,0.0,12116.95,4554.55,0.0,0.0,19013.68,52292.73,18.4784,0.0,0.0,12294.29,4554.55,0.0,0.0,19013.68,52292.73,18.2384,0.0,0.0,12466.52,4554.55,0.0,0.0,19013.68,52292.73,17.4979,0.0,0.0,12635.29,4554.55,0.0,0.0,19013.68,52292.73,17.416,0.0,0.0,12800.83,4554.55,0.0,0.0,19013.68,52292.73,17.3516,0.0,0.0,12954.67,4554.55,0.0,0.0,19013.68,52292.73,17.3057,0.0,0.0,13096.04,4554.55,0.0,0.0,19013.68,52292.73,2.245,22.0,2.27,2.235,139000.0,13.67,16.337500000000002 diff --git a/examples/sdk/quantile-regression/data/outputTrainingData_qr.csv b/examples/sdk/quantile-regression/data/outputTrainingData_qr.csv deleted file mode 100644 index af99c71e6..000000000 --- a/examples/sdk/quantile-regression/data/outputTrainingData_qr.csv +++ /dev/null @@ -1,56 +0,0 @@ -response_var_prediction,DateTime --2.2702721451918664,2019-12-14 06:00:00 --2.6066589489011625,2019-12-14 08:00:00 --0.4637159083741462,2019-12-14 09:00:00 -1.6363317168411582,2019-12-14 10:00:00 -1.897332672331836,2019-12-14 11:00:00 -2.6127861691502785,2019-12-14 12:00:00 -3.8519613157442367,2019-12-14 13:00:00 -2.935804858027451,2019-12-14 14:00:00 -1.4668193930438769,2019-12-14 15:00:00 -1.0387088770721737,2019-12-14 17:00:00 --0.41756130493301713,2019-12-14 18:00:00 -0.47089013670542146,2019-12-14 19:00:00 --1.049601532028574,2019-12-14 21:00:00 --0.5502611710892724,2019-12-14 22:00:00 -0.8061035044978564,2019-12-14 23:00:00 -1.1326171306430395,2019-12-15 00:00:00 --0.2074057807499788,2019-12-15 01:00:00 --2.407532743861326,2019-12-15 02:00:00 --3.5342640853767273,2019-12-15 03:00:00 --0.478609403129159,2019-12-15 04:00:00 --0.8329436296169019,2019-12-15 05:00:00 --2.6904395470089635,2019-12-15 06:00:00 --3.0908627764451895,2019-12-15 07:00:00 --3.809791048187143,2019-12-15 09:00:00 --4.576419628035193,2019-12-15 12:00:00 --3.2431251849024845,2019-12-15 14:00:00 --2.3585860614187077,2019-12-15 16:00:00 --1.1926873787110288,2019-12-15 17:00:00 --2.2872092934803274,2019-12-15 19:00:00 --2.506397825170507,2019-12-15 20:00:00 --1.0682585907354334,2019-12-15 23:00:00 -1.5275117828727458,2019-12-16 00:00:00 -1.7417680103512572,2019-12-16 01:00:00 -1.7982597100860245,2019-12-16 03:00:00 -1.544549198196187,2019-12-16 04:00:00 --0.758389862845446,2019-12-16 05:00:00 --1.4142113017942046,2019-12-16 06:00:00 --3.156408396050099,2019-12-16 08:00:00 --2.7836392002694366,2019-12-16 09:00:00 --1.9344990706828291,2019-12-16 10:00:00 -0.5230711133857735,2019-12-16 11:00:00 -0.29502510989644115,2019-12-16 12:00:00 -2.8549751514266672,2019-12-16 14:00:00 -3.3253474057509425,2019-12-16 15:00:00 -3.5622705761995563,2019-12-16 17:00:00 -1.5907408087672525,2019-12-16 19:00:00 --0.46870005284848304,2019-12-16 20:00:00 --1.2573876548657221,2019-12-16 21:00:00 --0.1608405633819885,2019-12-16 22:00:00 -2.63251638292917,2019-12-16 23:00:00 -5.708062041179195,2019-12-17 00:00:00 -5.254127162624196,2019-12-17 01:00:00 -3.4346513270514194,2019-12-17 03:00:00 -0.7320324164297214,2019-12-17 04:00:00 --0.7975838811188627,2019-12-17 05:00:00 diff --git a/examples/sdk/quantile-regression/init.py b/examples/sdk/quantile-regression/init.py deleted file mode 100644 index 7e10e06f7..000000000 --- a/examples/sdk/quantile-regression/init.py +++ /dev/null @@ -1,25 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="init") -def init(): - import pandas as pd - from settings import TRAINING_DATA - - df = pd.read_csv(TRAINING_DATA) - - return df diff --git a/examples/sdk/quantile-regression/lib/__init__.py b/examples/sdk/quantile-regression/lib/__init__.py deleted file mode 100644 index 1b5b2fa6c..000000000 --- a/examples/sdk/quantile-regression/lib/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/examples/sdk/quantile-regression/lib/modelprototype.py b/examples/sdk/quantile-regression/lib/modelprototype.py deleted file mode 100644 index ede1810b6..000000000 --- a/examples/sdk/quantile-regression/lib/modelprototype.py +++ /dev/null @@ -1,88 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -# Prototype of a model class for an ML framework. -# Most of the member functions of the class will use two types of inputs: -# - raw_data := a tuple of numpy arrays -# - settings := a dictionary providing information to run the function. -# This dictionary will be initialized from the 'settings' -# section of the input json contract. Hence, all the -# information necessary to use all the member functions of -# the model should be already present in the 'settings' -# section of the json contract or at the latest added during -# the preprocessing operation. - - -class ModelPrototype: - - def __init__(self, raw_data, settings): - # Inputs: - # raw_data := tuple of numpy arrays - # settings:= dictionary that specifies the settings for the - # model - - # CODE here - - return - - def get_parameters(self): - # function use to retrieve the parameters of the model - # Outputs: - # model_parameters := data structure containing values for the - # parameters (should be set to None if there - # is nothing to saved) - - model_parameters = None - - # CODE HERE - - return model_parameters - - def set_parameters(self, model_parameters): - # function used to update the model parameters - # Input - # model_parameters := data structure containing values for the - # parameters - - # CODE HERE - - return - - def training(self, raw_data, settings): - # function used to train the model - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for - # the model - # Output: - # history := data structure storing information from the - # training operation. (should be set to None if there is - # nothing to saved) - history = None - # CODE HERE - - return history - - def predict(self, raw_data, settings): - # function used to perform predictions - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for - # the model - # Output: - # raw_predictions := tuple of numpy arrays - - # CODE HERE - - return raw_predictions diff --git a/examples/sdk/quantile-regression/lib/quantile_regression.py b/examples/sdk/quantile-regression/lib/quantile_regression.py deleted file mode 100644 index 9b328e44f..000000000 --- a/examples/sdk/quantile-regression/lib/quantile_regression.py +++ /dev/null @@ -1,466 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import numpy as np -import statsmodels.api as sm - -from sklearn.ensemble import GradientBoostingRegressor - -import tensorflow as tf -from tensorflow import keras - - -def tilted_loss(q, y, f): - e = (y - f) - return keras.backend.mean(keras.backend.maximum(q * e, (q - 1) * e), - axis=-1) - - -class QuantileRegression: - - def __init__(self, raw_data, settings): - # Inputs: - # raw_data := tuple of numpy arrays - # settings:= dictionary that specifies the settings for the model - - Xraw, Yraw, _ = raw_data - - self.model = sm.QuantReg(Yraw, - Xraw).fit() - - return - - def get_parameters(self): - # function use to retrieve the parameters of the model - # Outputs: - # model_parameters := data structure containing values for the - # parameters (should be set to None if there is nothing to saved) - model_parameters = {} - # Retrieving coefficients - model_parameters['coeff'] = self.model.params[1:] - # Retrieveing intercept - model_parameters['intercept'] = self.model.params[0] - return model_parameters - - def set_parameters(self, model_parameters): - # function used to update the model parameters - # Input - # model_parameters := data structure containing values for the - # parameters - # Set coefficients - self.model.params[1:] = model_parameters['coeff'] - # Set intercept - self.model.params[0] = model_parameters['intercept'] - return - - def training(self, raw_data, settings): - # function used to train the model - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for the model - # - # Output: - # history := data structure storing information from the training - # operation. - # (should be set to None if there is nothing to saved) - - q = settings['q'] - max_iter = settings['max_iter'] - - Xraw, Yraw, _ = raw_data - - self.model = sm.QuantReg(Yraw, - Xraw).fit(q=q, - max_iter=max_iter) - - history = None # since there is no training history to be saved, - # history is set to None - return history - - def predict(self, raw_data, settings): - # function used to perform predictions - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for the model - # Output: - # raw_predictions := tuple of numpy arrays - - Xraw, _, _ = raw_data - - raw_predictions = self.model.predict(Xraw) - - return (raw_predictions) - - -class GradientBoostingQuantileRegression: - - def __init__(self, raw_data, settings): - # Inputs: - # raw_data := tuple of numpy arrays - # settings:= dictionary that specifies the settings for the model - - self.model = GradientBoostingRegressor(loss=settings["loss"], - alpha=settings["alpha"], - n_estimators=settings[ - "n_estimators"], - max_depth=settings["max_depth"], - learning_rate=settings[ - "learning_rate"], - min_samples_leaf=settings[ - "min_samples_leaf"], - min_samples_split=settings[ - "min_samples_split"], - verbose=settings["verbose"]) - - return - - def get_parameters(self): - # function use to retrieve the parameters of the model - # Outputs: - # model_parameters := dictionary containing values for the parameters - # (should be set to None if there is nothing to saved) - model_parameters = {} - # Retrieving coefficients - model_parameters = self.model.get_params() - - return model_parameters - - def set_parameters(self, model_parameters): - # function used to update the model parameters - # Input - # model_parameters := dictionary structure containing values for the - # parameters - - self.model.alpha = model_parameters["alpha"] - self.model.criterion = model_parameters["criterion"] - self.model.alpha = model_parameters["alpha"] - self.model.criterion = model_parameters["criterion"] - self.model.max_depth = model_parameters["max_depth"] - self.model.min_samples_leaf = model_parameters["min_samples_leaf"] - self.model.n_estimators = model_parameters["n_estimators"] - - return - - def training(self, raw_data, settings): - # function used to train the model - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for the model - # Output: - # history := data structure storing information from the training - # operation. - # (should be set to None if there is nothing to saved) - - Xraw, Yraw, _ = raw_data - - self.model.fit(Xraw, - Yraw) - - history = None # since there is no training history to be saved, - # history is set to None - return history - - def predict(self, raw_data, settings): - # function used to perform predictions - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for the model - # Output: - # raw_predictions := tuple of numpy arrays - - Xraw, _, _ = raw_data - - raw_predictions = self.model.predict(Xraw) - - return (raw_predictions) - - -class KerasQuantileRegression: - - def __init__(self, raw_data, settings): - # Inputs: - # raw_data := tuple of numpy arrays - # settings:= dictionary that specifies the settings for the model - - Xraw, _, _ = raw_data - - if len(Xraw.shape) == 1: - input_dim = 1 - - else: - input_dim = Xraw.shape[1] - - self.model = keras.Sequential( - [keras.layers.Dense(settings["units"], - activation=tf.nn.relu, - input_dim=input_dim), - keras.layers.Dense(settings["units"], - activation=tf.nn.relu), - keras.layers.Dense(1)]) - return - - def get_parameters(self): - # function use to retrieve the parameters of the model - # Outputs: - # model_parameters := list containing values for the parameters (should - # be set to None if there is nothing to saved) - model_parameters = [] - # Retrieving coefficients - model_parameters = self.model.get_weights() - - return model_parameters - - def set_parameters(self, model_parameters): - # function used to update the model parameters - # Input - # model_parameters := list structure containing values for the weights - self.model.set_weights(model_parameters) - - return - - def training(self, raw_data, settings): - # function used to train the model - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for the model - # Output: - # history := data structure storing information from the training - # operation. - # (should be set to None if there is nothing to saved) - - Xraw, Yraw, _ = raw_data - - optimizer = tf.optimizers.Adam(settings["learning_rate"]) - early_stop = keras.callbacks.EarlyStopping(monitor="val_loss", - patience=settings[ - "patience"]) - - self.model.compile(loss=lambda y, f: tilted_loss(settings["q"], - y, - f), - optimizer=optimizer) - - self.model.fit(Xraw, - Yraw, - epochs=settings["epochs"], - batch_size=settings["batch_size"], - verbose=settings["verbose"], - validation_split=settings["validation_split"], - callbacks=[early_stop]) - - history = None # since there is no training history to be saved, - # history is set to None - return history - - def predict(self, raw_data, settings): - # function used to perform predictions - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for the model - # Output: - # raw_predictions := tuple of numpy arrays - - Xraw, _, _ = raw_data - - raw_predictions = self.model.predict(Xraw) - - prediction_list = [] - - for value in raw_predictions: - prediction_list.append(value[0]) - - return (np.array(prediction_list)) - - -# Create network -class q_model: - def __init__(self, - sess, - quantiles, - in_shape=1, - out_shape=1, - batch_size=32): - - # To fix the tf.placeholder() is not compatible with eager execution - # issue. - tf.compat.v1.disable_eager_execution() - - self.sess = sess - - self.quantiles = quantiles - self.num_quantiles = len(quantiles) - - self.in_shape = in_shape - self.out_shape = out_shape - self.batch_size = batch_size - - self.outputs = [] - self.losses = [] - self.loss_history = [] - - self.build_model() - - def build_model(self, - scope='q_model', - reuse=tf.compat.v1.AUTO_REUSE, - units=512): - - with tf.compat.v1.variable_scope(scope, reuse=reuse) as scope: - self.x = tf.compat.v1.placeholder(tf.float32, - shape=(None, - self.in_shape)) - - self.y = tf.compat.v1.placeholder(tf.float32, - shape=(None, - self.out_shape)) - - self.layer0 = tf.compat.v1.layers.dense(self.x, - units=units, - activation=tf.nn.relu) - - self.layer1 = tf.compat.v1.layers.dense(self.layer0, - units=units, - activation=tf.nn.relu) - - # Create outputs and losses for all quantiles - for i, q in enumerate(self.quantiles): - # Get output layers - output = tf.compat.v1.layers.dense(self.layer1, self.out_shape, - name="{}_q{}".format(i, int( - q * 100))) - self.outputs.append(output) - - # Create losses - error = tf.subtract(self.y, output) - loss = tf.reduce_mean(tf.maximum(q * error, (q - 1) * error), - axis=-1) - - self.losses.append(loss) - - # Create combined loss - self.combined_loss = tf.reduce_mean(tf.add_n(self.losses)) - self.train_step = tf.compat.v1.train.AdamOptimizer().minimize( - self.combined_loss) - - def fit(self, x, y, epochs=200): - for epoch in range(epochs): - epoch_losses = [] - - for idx in range(0, x.shape[0], self.batch_size): - batch_x = x[idx: min(idx + self.batch_size, x.shape[0]), :] - batch_y = y[idx: min(idx + self.batch_size, y.shape[0])] - - batch_y = batch_y.reshape(len(batch_y), 1) - - feed_dict = {self.x: batch_x, - self.y: batch_y} - - _, c_loss = self.sess.run( - [self.train_step, self.combined_loss], - feed_dict) - epoch_losses.append(c_loss) - - epoch_loss = np.mean(epoch_losses) - self.loss_history.append(epoch_loss) - if epoch % 100 == 0: - print("Epoch {}: {}".format(epoch, epoch_loss)) - - def predict(self, x): - # Run model to get outputs - feed_dict = {self.x: x} - predictions = self.sess.run(self.outputs, feed_dict) - - return predictions - - -class TensorFlowQuantileRegression: - - def __init__(self, raw_data, settings): - # Inputs: - # raw_data := tuple of numpy arrays - # settings:= dictionary that specifies the settings for the model - - self.sess = tf.compat.v1.Session() - - Xraw, _, _ = raw_data - - # Model instantiation - self.model = q_model(self.sess, - settings["quantiles"], - in_shape=Xraw.shape[1], - batch_size=settings["batch_size"]) - - return - - def get_parameters(self): - # function use to retrieve the parameters of the model - # Outputs: - # model_parameters := Dictionary containing values for the parameters - # (should be set to None if there is nothing to saved) - model_parameters = {} - # Retrieving coefficients - model_parameters["x"] = self.model.x - model_parameters["y"] = self.model.y - model_parameters["layer0"] = self.model.layer0 - model_parameters["layer1"] = self.model.layer1 - - return model_parameters - - def set_parameters(self, model_parameters): - # function used to update the model parameters - # Input - # model_parameters := list structure containing values for the weights - self.model.x = model_parameters["x"] - self.model.y = model_parameters["y"] - self.model.layer0 = model_parameters["layer0"] - self.model.layer1 = model_parameters["layer1"] - - return - - def training(self, raw_data, settings): - # function used to train the model - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for the model - # Output: - # history := data structure storing information from the training - # operation. - # (should be set to None if there is nothing to saved) - - Xraw, Yraw, _ = raw_data - - # Initialize all variables - init_op = tf.compat.v1.global_variables_initializer() - self.sess.run(init_op) - - self.model.fit(Xraw, - Yraw, - settings["epochs"]) - - history = None # since there is no training history to be saved, - # history is set to None - return history - - def predict(self, raw_data, settings): - # function used to perform predictions - # Input: - # raw_data := tuple of numpy arrays - # settings := dictionary that specifies the settings for the model - # Output: - # raw_predictions := tuple of numpy arrays - - Xraw, _, _ = raw_data - raw_predictions = self.model.predict(Xraw) - - return (raw_predictions) diff --git a/examples/sdk/quantile-regression/main.py b/examples/sdk/quantile-regression/main.py deleted file mode 100644 index 3c4170b6f..000000000 --- a/examples/sdk/quantile-regression/main.py +++ /dev/null @@ -1,37 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import pipeline - - -from init import init -from preprocess import preprocess -from train import train_and_predict -from postprocess import postprocess - - -@pipeline( - name="quantile-regression", - experiment="quantile-regression", - autosnapshot=False, -) -def quantile_regression(): - df = init() - raw_input, processing_info = preprocess(df) - raw_predictions = train_and_predict(raw_input) - postprocess(raw_input, raw_predictions, processing_info) - - -if __name__ == "__main__": - quantile_regression() diff --git a/examples/sdk/quantile-regression/postprocess.py b/examples/sdk/quantile-regression/postprocess.py deleted file mode 100644 index 11db60c17..000000000 --- a/examples/sdk/quantile-regression/postprocess.py +++ /dev/null @@ -1,49 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="postprocess") -def postprocess(raw_input, raw_output, processing_info): - import pandas as pd - - from settings import OUTPUTS, DATE_TIME, OUTPUT_DATA - - # Generating pandas Dataframe - output = OUTPUTS[0] - df = pd.DataFrame() - - # '''if 'scaling' in processing_info: - # shift_y, scale_y = processing_info['scaling'] - # raw_output = scale_y * raw_output + shift_y - # print(raw_output)''' - - # We need to fix this issue. There should be a link between preprocessing - # and post processing for the response variable. - # At the moment, we just apply PP to predictors. Not that we need to apply - # PP to response, but the way it is written it - # is assumed that we apply PP to both predictors and response - - df[output + '_prediction'] = raw_output - - # Including time if necessary - _, _, Time = raw_input - if len(Time) > 0: - time_var = DATE_TIME - df[time_var] = Time - df[time_var] = pd.to_datetime(df[time_var]) - - df.to_csv(OUTPUT_DATA, index=False) - print("Postprocess: output saved to disk") diff --git a/examples/sdk/quantile-regression/preprocess.py b/examples/sdk/quantile-regression/preprocess.py deleted file mode 100644 index 081abac27..000000000 --- a/examples/sdk/quantile-regression/preprocess.py +++ /dev/null @@ -1,67 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="preprocess") -def preprocess(df): - import pandas as pd - import numpy as np - - from settings import INPUTS, OUTPUTS, DATE_TIME - - print("Preprocessing data") - - processing_info = {} - - # get labels - output = OUTPUTS[0] - - X = df[INPUTS].values - - var_time = DATE_TIME - if len(var_time) > 0: - df[var_time] = pd.to_datetime(df[var_time]) - Time = df[var_time].values - else: - Time = np.array([]) - - if 'scaling' in processing_info: - shift_x, scale_x = processing_info['scaling'] - - else: - # must be training case - shift_x = np.mean(X, - axis=0) - - scale_x = np.std(X, - axis=0, - keepdims=True) - - processing_info['scaling'] = [shift_x, scale_x] - - Xraw = (X - shift_x) / scale_x - - if len(Xraw.shape) == 1: - Xraw = Xraw[:, None] - - if output in df.columns.tolist(): # in prediction case output variable - # might not be present - Yraw = df[output].values - else: - Yraw = np.array([]) - - raw_input = [Xraw, Yraw, Time] - return raw_input, processing_info diff --git a/examples/sdk/quantile-regression/settings.py b/examples/sdk/quantile-regression/settings.py deleted file mode 100644 index 099cf82f9..000000000 --- a/examples/sdk/quantile-regression/settings.py +++ /dev/null @@ -1,34 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os - -INPUTS = ["CLOUD_COVER", "DEWPOINT", "HEAT_INDEX", "TEMPERATURE", "WIND_CHILL", - "WIND_DIRECTION", "WIND_SPEED", "TOTAL_CAP_GEN_RES", - "TOTAL_CAP_LOAD_RES", "AVERAGE", "total_load", "DA_PRICE"] -OUTPUTS = ["response_var"] -DATE_TIME = "DateTime" - -_DATA_FOLDER = "./data" -_TRAIN_DATA_FILE = "TrainingData.csv" -_TEST_DATA_FILE = "TestData.csv" -_OUTPUT_FILE = "outputTrainingData_qr.csv" -TRAINING_DATA = os.path.join(_DATA_FOLDER, _TRAIN_DATA_FILE) -TEST_DATA = os.path.join(_DATA_FOLDER, _TEST_DATA_FILE) -OUTPUT_DATA = os.path.join(_DATA_FOLDER, _OUTPUT_FILE) - -MODEL_SETTINGS = { - "q": 0.5, - "max_iter": 5000 -} diff --git a/examples/sdk/quantile-regression/train.py b/examples/sdk/quantile-regression/train.py deleted file mode 100644 index 88ca98d8f..000000000 --- a/examples/sdk/quantile-regression/train.py +++ /dev/null @@ -1,29 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="trainpredict") -def train_and_predict(raw_input): - from lib.quantile_regression import QuantileRegression - - from settings import MODEL_SETTINGS - - model = QuantileRegression(raw_input, MODEL_SETTINGS) - print("Running training") - model.training(raw_input, MODEL_SETTINGS) - - print("Running prediction") - return model.predict(raw_input, MODEL_SETTINGS) diff --git a/examples/sdk/retry-pipeline.py b/examples/sdk/retry-pipeline.py deleted file mode 100644 index c243b5366..000000000 --- a/examples/sdk/retry-pipeline.py +++ /dev/null @@ -1,65 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -""" -This pipeline showcases how you can easily define a retry strategy for a -failing step. -""" - -from kale.sdk import pipeline, step - - -""" -A single step can fail multiple times before succeeding with its task. Use -`retry_count` to define the number of times a step will be retried in case -of failure. -You can control the retry strategy with these other arguments: -- `retry_interval` (string): The time interval between retries. By default - it's seconds but you can specify minutes or hours e.g. "2m" (2 minutes); - "1h" (1 hour)/ -- `retry_factor`: The exponential backoff factor applied to `retry_interval`. - For example, if `retry_interval="60"` (60 seconds) and `retry_factor=2`, - the first retry will happen after 60 seconds, then after 120, 240 and so - on... -- `retry_max_interval`: The maximum interval that can be reached with the - backoff strategy. -""" -@step(name="failing", - retry_count=5, - retry_interval="60" - ) -def failing(): - from random import choice - - if choice([0, 0, 1]): - raise RuntimeError("Life's hard, try again!") - - return "Succeeded" - - -@step(name="dummy") -def dummy(result): - print(result) - - -@pipeline(name="retry-strategy", - experiment="retry-strategy", - autosnapshot=False) -def retry_strategy_pipeline(): - res = failing() - dummy(res) - - -if __name__ == "__main__": - retry_strategy_pipeline() diff --git a/examples/sdk/skeleton.py b/examples/sdk/skeleton.py deleted file mode 100644 index 3e2822893..000000000 --- a/examples/sdk/skeleton.py +++ /dev/null @@ -1,150 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -""" -This is a skeleton script that shows how you can build a Kubeflow pipeline -using the Kale SDK. -""" - -""" -The only imports you need to convert your python code to a pipeline are these -two decorators. -""" -from kale.sdk import pipeline, step - - -""" -Defining a step is as simple as decorating a Python function. When a function -is decorated with `@step`, Kale will generate a KFP pipeline step executing -the decorated function. - -Just make sure to `import` all your modules *inside* the function definition, -as the code that will run in the Kubeflow pipeline won't have the entire -context of the current script. -""" -@step(name="my_step") -def foo(a): - import sys - sys.stdout.write(a) - # return multiple values. These could be used by different subsequent - # pipeline steps. - return "Some", "Data" - - -@step(name="second_step") -def foo2(b, c): - print(b + c) - - -@step(name="third_step") -def foo3(b, c): - print(b + c) - - -""" -You are not restricted to defining all your functions in a single source file. -Organize your "step" functions as you like in other local scripts and import -then. Treat your functions just like any other Python project, Kale just needs -to access the function *objects*, not their original source code. - -E.g.: - -``` -# import the `@step` decorated function `processing_step`, from file -# `data_processing.py` -from .data_processing import processing_step -``` -""" - -""" -Define the pipeline: - -Once you have all your steps (i.e. functions) defined, all you need to do to -define and create the pipeline is to call all of these functions from a single -"entry-point", just like you would normally do for running your code locally. - -Use the `pipeline` decorator to tell Kale that this is the function defining -the pipeline structure. Decide a pipeline name and an experiment. In Kubeflow -Pipelines, experiments are containers of runs. Ideally you should create a new -experiment for every new project. - -Note that until now you have been writing *plain Python*. All the step -functions can be written as any other Python function, with no restrictions, -and you can even import them from other local files. - -The `@pipeline` decorated function poses some syntax restrictions, as Kale -needs to parse it to create a corresponding pipeline representation. Whenever -these restrictions are not met, Kale will try to fail gracefully and inform you -how you should fix it. These are the notable constraints: - -- You can add input arguments to define *pipeline parameters*. All input - arguments expect a default value. -- The body of the function does not accept arbitrary Python statements. All - you can write is function calls, chaining the together with their return - arguments. -- Each line should contain a function call with its return value. -- Use tuple unpacking to return multiple values -""" -@pipeline(name="my-beautiful-pipeline", - experiment="learning-the-kale-sdk") -def my_pipeline(parameter="input"): - data1, data2 = foo(parameter) - foo2(data1, parameter) - foo3(data2, parameter) - - -""" -Add a script entry-point to call the function from CLI. - -You can override the default pipeline parameters when calling the pipeline, -just remember that only keyword argument are accepted when calling a -`@pipeline` decorated function. - -Once you write the entry-point, you can either run the pipeline locally, or -compile and run the pipeline in Kubeflow. - -## Local run: - -``` -python3 skeleton.py -``` - -That's it. Running the script itself will invoke the `@pipeline` decorated -functions. At this point Kale will validate your code and make sure that it can -be converted into a pipeline. Then, Kale will start a local execution, so that -you can uncover bugs early, before actually submitting the run to Kubeflow. - -This is a great way to quickly debug what is going on in your code and speed up -the development process. - -## Compile and run in Kubeflow - -Compiling the pipeline and running it in Kubeflow Pipelines is extremely easy: - -``` -python3 skeleton.py --kfp -``` - -When running the above command, the following things will happen: - -- Kale validates the current code, to make sure that it can be converted to a - pipeline -- Kale creates a new KFP pipeline, using the specified docker image as the - base image for the pipeline steps -- Kale creates (if necessary) a new KFP experiment, based on the provided name -- Kale uploads a new pipeline definition -- Kale starts a new pipeline run -""" -if __name__ == "__main__": - my_pipeline(parameter="test") diff --git a/examples/sdk/titanic/__init__.py b/examples/sdk/titanic/__init__.py deleted file mode 100644 index 1b5b2fa6c..000000000 --- a/examples/sdk/titanic/__init__.py +++ /dev/null @@ -1,13 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. diff --git a/examples/sdk/titanic/data/test.csv b/examples/sdk/titanic/data/test.csv deleted file mode 100755 index f705412e6..000000000 --- a/examples/sdk/titanic/data/test.csv +++ /dev/null @@ -1,419 +0,0 @@ -PassengerId,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked -892,3,"Kelly, Mr. James",male,34.5,0,0,330911,7.8292,,Q -893,3,"Wilkes, Mrs. James (Ellen Needs)",female,47,1,0,363272,7,,S -894,2,"Myles, Mr. Thomas Francis",male,62,0,0,240276,9.6875,,Q -895,3,"Wirz, Mr. Albert",male,27,0,0,315154,8.6625,,S -896,3,"Hirvonen, Mrs. Alexander (Helga E Lindqvist)",female,22,1,1,3101298,12.2875,,S -897,3,"Svensson, Mr. Johan Cervin",male,14,0,0,7538,9.225,,S -898,3,"Connolly, Miss. Kate",female,30,0,0,330972,7.6292,,Q -899,2,"Caldwell, Mr. Albert Francis",male,26,1,1,248738,29,,S -900,3,"Abrahim, Mrs. Joseph (Sophie Halaut Easu)",female,18,0,0,2657,7.2292,,C -901,3,"Davies, Mr. John Samuel",male,21,2,0,A/4 48871,24.15,,S -902,3,"Ilieff, Mr. Ylio",male,,0,0,349220,7.8958,,S -903,1,"Jones, Mr. Charles Cresson",male,46,0,0,694,26,,S -904,1,"Snyder, Mrs. John Pillsbury (Nelle Stevenson)",female,23,1,0,21228,82.2667,B45,S -905,2,"Howard, Mr. Benjamin",male,63,1,0,24065,26,,S -906,1,"Chaffee, Mrs. Herbert Fuller (Carrie Constance Toogood)",female,47,1,0,W.E.P. 5734,61.175,E31,S -907,2,"del Carlo, Mrs. Sebastiano (Argenia Genovesi)",female,24,1,0,SC/PARIS 2167,27.7208,,C -908,2,"Keane, Mr. Daniel",male,35,0,0,233734,12.35,,Q -909,3,"Assaf, Mr. Gerios",male,21,0,0,2692,7.225,,C -910,3,"Ilmakangas, Miss. Ida Livija",female,27,1,0,STON/O2. 3101270,7.925,,S -911,3,"Assaf Khalil, Mrs. Mariana (Miriam"")""",female,45,0,0,2696,7.225,,C -912,1,"Rothschild, Mr. Martin",male,55,1,0,PC 17603,59.4,,C -913,3,"Olsen, Master. Artur Karl",male,9,0,1,C 17368,3.1708,,S -914,1,"Flegenheim, Mrs. Alfred (Antoinette)",female,,0,0,PC 17598,31.6833,,S -915,1,"Williams, Mr. Richard Norris II",male,21,0,1,PC 17597,61.3792,,C -916,1,"Ryerson, Mrs. Arthur Larned (Emily Maria Borie)",female,48,1,3,PC 17608,262.375,B57 B59 B63 B66,C -917,3,"Robins, Mr. Alexander A",male,50,1,0,A/5. 3337,14.5,,S -918,1,"Ostby, Miss. Helene Ragnhild",female,22,0,1,113509,61.9792,B36,C -919,3,"Daher, Mr. Shedid",male,22.5,0,0,2698,7.225,,C -920,1,"Brady, Mr. John Bertram",male,41,0,0,113054,30.5,A21,S -921,3,"Samaan, Mr. Elias",male,,2,0,2662,21.6792,,C -922,2,"Louch, Mr. Charles Alexander",male,50,1,0,SC/AH 3085,26,,S -923,2,"Jefferys, Mr. Clifford Thomas",male,24,2,0,C.A. 31029,31.5,,S -924,3,"Dean, Mrs. Bertram (Eva Georgetta Light)",female,33,1,2,C.A. 2315,20.575,,S -925,3,"Johnston, Mrs. Andrew G (Elizabeth Lily"" Watson)""",female,,1,2,W./C. 6607,23.45,,S -926,1,"Mock, Mr. Philipp Edmund",male,30,1,0,13236,57.75,C78,C -927,3,"Katavelas, Mr. Vassilios (Catavelas Vassilios"")""",male,18.5,0,0,2682,7.2292,,C -928,3,"Roth, Miss. Sarah A",female,,0,0,342712,8.05,,S -929,3,"Cacic, Miss. Manda",female,21,0,0,315087,8.6625,,S -930,3,"Sap, Mr. Julius",male,25,0,0,345768,9.5,,S -931,3,"Hee, Mr. Ling",male,,0,0,1601,56.4958,,S -932,3,"Karun, Mr. Franz",male,39,0,1,349256,13.4167,,C -933,1,"Franklin, Mr. Thomas Parham",male,,0,0,113778,26.55,D34,S -934,3,"Goldsmith, Mr. Nathan",male,41,0,0,SOTON/O.Q. 3101263,7.85,,S -935,2,"Corbett, Mrs. Walter H (Irene Colvin)",female,30,0,0,237249,13,,S -936,1,"Kimball, Mrs. Edwin Nelson Jr (Gertrude Parsons)",female,45,1,0,11753,52.5542,D19,S -937,3,"Peltomaki, Mr. Nikolai Johannes",male,25,0,0,STON/O 2. 3101291,7.925,,S -938,1,"Chevre, Mr. Paul Romaine",male,45,0,0,PC 17594,29.7,A9,C -939,3,"Shaughnessy, Mr. Patrick",male,,0,0,370374,7.75,,Q -940,1,"Bucknell, Mrs. William Robert (Emma Eliza Ward)",female,60,0,0,11813,76.2917,D15,C -941,3,"Coutts, Mrs. William (Winnie Minnie"" Treanor)""",female,36,0,2,C.A. 37671,15.9,,S -942,1,"Smith, Mr. Lucien Philip",male,24,1,0,13695,60,C31,S -943,2,"Pulbaum, Mr. Franz",male,27,0,0,SC/PARIS 2168,15.0333,,C -944,2,"Hocking, Miss. Ellen Nellie""""",female,20,2,1,29105,23,,S -945,1,"Fortune, Miss. Ethel Flora",female,28,3,2,19950,263,C23 C25 C27,S -946,2,"Mangiavacchi, Mr. Serafino Emilio",male,,0,0,SC/A.3 2861,15.5792,,C -947,3,"Rice, Master. Albert",male,10,4,1,382652,29.125,,Q -948,3,"Cor, Mr. Bartol",male,35,0,0,349230,7.8958,,S -949,3,"Abelseth, Mr. Olaus Jorgensen",male,25,0,0,348122,7.65,F G63,S -950,3,"Davison, Mr. Thomas Henry",male,,1,0,386525,16.1,,S -951,1,"Chaudanson, Miss. Victorine",female,36,0,0,PC 17608,262.375,B61,C -952,3,"Dika, Mr. Mirko",male,17,0,0,349232,7.8958,,S -953,2,"McCrae, Mr. Arthur Gordon",male,32,0,0,237216,13.5,,S -954,3,"Bjorklund, Mr. Ernst Herbert",male,18,0,0,347090,7.75,,S -955,3,"Bradley, Miss. Bridget Delia",female,22,0,0,334914,7.725,,Q -956,1,"Ryerson, Master. John Borie",male,13,2,2,PC 17608,262.375,B57 B59 B63 B66,C -957,2,"Corey, Mrs. Percy C (Mary Phyllis Elizabeth Miller)",female,,0,0,F.C.C. 13534,21,,S -958,3,"Burns, Miss. Mary Delia",female,18,0,0,330963,7.8792,,Q -959,1,"Moore, Mr. Clarence Bloomfield",male,47,0,0,113796,42.4,,S -960,1,"Tucker, Mr. Gilbert Milligan Jr",male,31,0,0,2543,28.5375,C53,C -961,1,"Fortune, Mrs. Mark (Mary McDougald)",female,60,1,4,19950,263,C23 C25 C27,S -962,3,"Mulvihill, Miss. Bertha E",female,24,0,0,382653,7.75,,Q -963,3,"Minkoff, Mr. Lazar",male,21,0,0,349211,7.8958,,S -964,3,"Nieminen, Miss. Manta Josefina",female,29,0,0,3101297,7.925,,S -965,1,"Ovies y Rodriguez, Mr. Servando",male,28.5,0,0,PC 17562,27.7208,D43,C -966,1,"Geiger, Miss. Amalie",female,35,0,0,113503,211.5,C130,C -967,1,"Keeping, Mr. Edwin",male,32.5,0,0,113503,211.5,C132,C -968,3,"Miles, Mr. Frank",male,,0,0,359306,8.05,,S -969,1,"Cornell, Mrs. Robert Clifford (Malvina Helen Lamson)",female,55,2,0,11770,25.7,C101,S -970,2,"Aldworth, Mr. Charles Augustus",male,30,0,0,248744,13,,S -971,3,"Doyle, Miss. Elizabeth",female,24,0,0,368702,7.75,,Q -972,3,"Boulos, Master. Akar",male,6,1,1,2678,15.2458,,C -973,1,"Straus, Mr. Isidor",male,67,1,0,PC 17483,221.7792,C55 C57,S -974,1,"Case, Mr. Howard Brown",male,49,0,0,19924,26,,S -975,3,"Demetri, Mr. Marinko",male,,0,0,349238,7.8958,,S -976,2,"Lamb, Mr. John Joseph",male,,0,0,240261,10.7083,,Q -977,3,"Khalil, Mr. Betros",male,,1,0,2660,14.4542,,C -978,3,"Barry, Miss. Julia",female,27,0,0,330844,7.8792,,Q -979,3,"Badman, Miss. Emily Louisa",female,18,0,0,A/4 31416,8.05,,S -980,3,"O'Donoghue, Ms. Bridget",female,,0,0,364856,7.75,,Q -981,2,"Wells, Master. Ralph Lester",male,2,1,1,29103,23,,S -982,3,"Dyker, Mrs. Adolf Fredrik (Anna Elisabeth Judith Andersson)",female,22,1,0,347072,13.9,,S -983,3,"Pedersen, Mr. Olaf",male,,0,0,345498,7.775,,S -984,1,"Davidson, Mrs. Thornton (Orian Hays)",female,27,1,2,F.C. 12750,52,B71,S -985,3,"Guest, Mr. Robert",male,,0,0,376563,8.05,,S -986,1,"Birnbaum, Mr. Jakob",male,25,0,0,13905,26,,C -987,3,"Tenglin, Mr. Gunnar Isidor",male,25,0,0,350033,7.7958,,S -988,1,"Cavendish, Mrs. Tyrell William (Julia Florence Siegel)",female,76,1,0,19877,78.85,C46,S -989,3,"Makinen, Mr. Kalle Edvard",male,29,0,0,STON/O 2. 3101268,7.925,,S -990,3,"Braf, Miss. Elin Ester Maria",female,20,0,0,347471,7.8542,,S -991,3,"Nancarrow, Mr. William Henry",male,33,0,0,A./5. 3338,8.05,,S -992,1,"Stengel, Mrs. Charles Emil Henry (Annie May Morris)",female,43,1,0,11778,55.4417,C116,C -993,2,"Weisz, Mr. Leopold",male,27,1,0,228414,26,,S -994,3,"Foley, Mr. William",male,,0,0,365235,7.75,,Q -995,3,"Johansson Palmquist, Mr. Oskar Leander",male,26,0,0,347070,7.775,,S -996,3,"Thomas, Mrs. Alexander (Thamine Thelma"")""",female,16,1,1,2625,8.5167,,C -997,3,"Holthen, Mr. Johan Martin",male,28,0,0,C 4001,22.525,,S -998,3,"Buckley, Mr. Daniel",male,21,0,0,330920,7.8208,,Q -999,3,"Ryan, Mr. Edward",male,,0,0,383162,7.75,,Q -1000,3,"Willer, Mr. Aaron (Abi Weller"")""",male,,0,0,3410,8.7125,,S -1001,2,"Swane, Mr. George",male,18.5,0,0,248734,13,F,S -1002,2,"Stanton, Mr. Samuel Ward",male,41,0,0,237734,15.0458,,C -1003,3,"Shine, Miss. Ellen Natalia",female,,0,0,330968,7.7792,,Q -1004,1,"Evans, Miss. Edith Corse",female,36,0,0,PC 17531,31.6792,A29,C -1005,3,"Buckley, Miss. Katherine",female,18.5,0,0,329944,7.2833,,Q -1006,1,"Straus, Mrs. Isidor (Rosalie Ida Blun)",female,63,1,0,PC 17483,221.7792,C55 C57,S -1007,3,"Chronopoulos, Mr. Demetrios",male,18,1,0,2680,14.4542,,C -1008,3,"Thomas, Mr. John",male,,0,0,2681,6.4375,,C -1009,3,"Sandstrom, Miss. Beatrice Irene",female,1,1,1,PP 9549,16.7,G6,S -1010,1,"Beattie, Mr. Thomson",male,36,0,0,13050,75.2417,C6,C -1011,2,"Chapman, Mrs. John Henry (Sara Elizabeth Lawry)",female,29,1,0,SC/AH 29037,26,,S -1012,2,"Watt, Miss. Bertha J",female,12,0,0,C.A. 33595,15.75,,S -1013,3,"Kiernan, Mr. John",male,,1,0,367227,7.75,,Q -1014,1,"Schabert, Mrs. Paul (Emma Mock)",female,35,1,0,13236,57.75,C28,C -1015,3,"Carver, Mr. Alfred John",male,28,0,0,392095,7.25,,S -1016,3,"Kennedy, Mr. John",male,,0,0,368783,7.75,,Q -1017,3,"Cribb, Miss. Laura Alice",female,17,0,1,371362,16.1,,S -1018,3,"Brobeck, Mr. Karl Rudolf",male,22,0,0,350045,7.7958,,S -1019,3,"McCoy, Miss. Alicia",female,,2,0,367226,23.25,,Q -1020,2,"Bowenur, Mr. Solomon",male,42,0,0,211535,13,,S -1021,3,"Petersen, Mr. Marius",male,24,0,0,342441,8.05,,S -1022,3,"Spinner, Mr. Henry John",male,32,0,0,STON/OQ. 369943,8.05,,S -1023,1,"Gracie, Col. Archibald IV",male,53,0,0,113780,28.5,C51,C -1024,3,"Lefebre, Mrs. Frank (Frances)",female,,0,4,4133,25.4667,,S -1025,3,"Thomas, Mr. Charles P",male,,1,0,2621,6.4375,,C -1026,3,"Dintcheff, Mr. Valtcho",male,43,0,0,349226,7.8958,,S -1027,3,"Carlsson, Mr. Carl Robert",male,24,0,0,350409,7.8542,,S -1028,3,"Zakarian, Mr. Mapriededer",male,26.5,0,0,2656,7.225,,C -1029,2,"Schmidt, Mr. August",male,26,0,0,248659,13,,S -1030,3,"Drapkin, Miss. Jennie",female,23,0,0,SOTON/OQ 392083,8.05,,S -1031,3,"Goodwin, Mr. Charles Frederick",male,40,1,6,CA 2144,46.9,,S -1032,3,"Goodwin, Miss. Jessie Allis",female,10,5,2,CA 2144,46.9,,S -1033,1,"Daniels, Miss. Sarah",female,33,0,0,113781,151.55,,S -1034,1,"Ryerson, Mr. Arthur Larned",male,61,1,3,PC 17608,262.375,B57 B59 B63 B66,C -1035,2,"Beauchamp, Mr. Henry James",male,28,0,0,244358,26,,S -1036,1,"Lindeberg-Lind, Mr. Erik Gustaf (Mr Edward Lingrey"")""",male,42,0,0,17475,26.55,,S -1037,3,"Vander Planke, Mr. Julius",male,31,3,0,345763,18,,S -1038,1,"Hilliard, Mr. Herbert Henry",male,,0,0,17463,51.8625,E46,S -1039,3,"Davies, Mr. Evan",male,22,0,0,SC/A4 23568,8.05,,S -1040,1,"Crafton, Mr. John Bertram",male,,0,0,113791,26.55,,S -1041,2,"Lahtinen, Rev. William",male,30,1,1,250651,26,,S -1042,1,"Earnshaw, Mrs. Boulton (Olive Potter)",female,23,0,1,11767,83.1583,C54,C -1043,3,"Matinoff, Mr. Nicola",male,,0,0,349255,7.8958,,C -1044,3,"Storey, Mr. Thomas",male,60.5,0,0,3701,,,S -1045,3,"Klasen, Mrs. (Hulda Kristina Eugenia Lofqvist)",female,36,0,2,350405,12.1833,,S -1046,3,"Asplund, Master. Filip Oscar",male,13,4,2,347077,31.3875,,S -1047,3,"Duquemin, Mr. Joseph",male,24,0,0,S.O./P.P. 752,7.55,,S -1048,1,"Bird, Miss. Ellen",female,29,0,0,PC 17483,221.7792,C97,S -1049,3,"Lundin, Miss. Olga Elida",female,23,0,0,347469,7.8542,,S -1050,1,"Borebank, Mr. John James",male,42,0,0,110489,26.55,D22,S -1051,3,"Peacock, Mrs. Benjamin (Edith Nile)",female,26,0,2,SOTON/O.Q. 3101315,13.775,,S -1052,3,"Smyth, Miss. Julia",female,,0,0,335432,7.7333,,Q -1053,3,"Touma, Master. Georges Youssef",male,7,1,1,2650,15.2458,,C -1054,2,"Wright, Miss. Marion",female,26,0,0,220844,13.5,,S -1055,3,"Pearce, Mr. Ernest",male,,0,0,343271,7,,S -1056,2,"Peruschitz, Rev. Joseph Maria",male,41,0,0,237393,13,,S -1057,3,"Kink-Heilmann, Mrs. Anton (Luise Heilmann)",female,26,1,1,315153,22.025,,S -1058,1,"Brandeis, Mr. Emil",male,48,0,0,PC 17591,50.4958,B10,C -1059,3,"Ford, Mr. Edward Watson",male,18,2,2,W./C. 6608,34.375,,S -1060,1,"Cassebeer, Mrs. Henry Arthur Jr (Eleanor Genevieve Fosdick)",female,,0,0,17770,27.7208,,C -1061,3,"Hellstrom, Miss. Hilda Maria",female,22,0,0,7548,8.9625,,S -1062,3,"Lithman, Mr. Simon",male,,0,0,S.O./P.P. 251,7.55,,S -1063,3,"Zakarian, Mr. Ortin",male,27,0,0,2670,7.225,,C -1064,3,"Dyker, Mr. Adolf Fredrik",male,23,1,0,347072,13.9,,S -1065,3,"Torfa, Mr. Assad",male,,0,0,2673,7.2292,,C -1066,3,"Asplund, Mr. Carl Oscar Vilhelm Gustafsson",male,40,1,5,347077,31.3875,,S -1067,2,"Brown, Miss. Edith Eileen",female,15,0,2,29750,39,,S -1068,2,"Sincock, Miss. Maude",female,20,0,0,C.A. 33112,36.75,,S -1069,1,"Stengel, Mr. Charles Emil Henry",male,54,1,0,11778,55.4417,C116,C -1070,2,"Becker, Mrs. Allen Oliver (Nellie E Baumgardner)",female,36,0,3,230136,39,F4,S -1071,1,"Compton, Mrs. Alexander Taylor (Mary Eliza Ingersoll)",female,64,0,2,PC 17756,83.1583,E45,C -1072,2,"McCrie, Mr. James Matthew",male,30,0,0,233478,13,,S -1073,1,"Compton, Mr. Alexander Taylor Jr",male,37,1,1,PC 17756,83.1583,E52,C -1074,1,"Marvin, Mrs. Daniel Warner (Mary Graham Carmichael Farquarson)",female,18,1,0,113773,53.1,D30,S -1075,3,"Lane, Mr. Patrick",male,,0,0,7935,7.75,,Q -1076,1,"Douglas, Mrs. Frederick Charles (Mary Helene Baxter)",female,27,1,1,PC 17558,247.5208,B58 B60,C -1077,2,"Maybery, Mr. Frank Hubert",male,40,0,0,239059,16,,S -1078,2,"Phillips, Miss. Alice Frances Louisa",female,21,0,1,S.O./P.P. 2,21,,S -1079,3,"Davies, Mr. Joseph",male,17,2,0,A/4 48873,8.05,,S -1080,3,"Sage, Miss. Ada",female,,8,2,CA. 2343,69.55,,S -1081,2,"Veal, Mr. James",male,40,0,0,28221,13,,S -1082,2,"Angle, Mr. William A",male,34,1,0,226875,26,,S -1083,1,"Salomon, Mr. Abraham L",male,,0,0,111163,26,,S -1084,3,"van Billiard, Master. Walter John",male,11.5,1,1,A/5. 851,14.5,,S -1085,2,"Lingane, Mr. John",male,61,0,0,235509,12.35,,Q -1086,2,"Drew, Master. Marshall Brines",male,8,0,2,28220,32.5,,S -1087,3,"Karlsson, Mr. Julius Konrad Eugen",male,33,0,0,347465,7.8542,,S -1088,1,"Spedden, Master. Robert Douglas",male,6,0,2,16966,134.5,E34,C -1089,3,"Nilsson, Miss. Berta Olivia",female,18,0,0,347066,7.775,,S -1090,2,"Baimbrigge, Mr. Charles Robert",male,23,0,0,C.A. 31030,10.5,,S -1091,3,"Rasmussen, Mrs. (Lena Jacobsen Solvang)",female,,0,0,65305,8.1125,,S -1092,3,"Murphy, Miss. Nora",female,,0,0,36568,15.5,,Q -1093,3,"Danbom, Master. Gilbert Sigvard Emanuel",male,0.33,0,2,347080,14.4,,S -1094,1,"Astor, Col. John Jacob",male,47,1,0,PC 17757,227.525,C62 C64,C -1095,2,"Quick, Miss. Winifred Vera",female,8,1,1,26360,26,,S -1096,2,"Andrew, Mr. Frank Thomas",male,25,0,0,C.A. 34050,10.5,,S -1097,1,"Omont, Mr. Alfred Fernand",male,,0,0,F.C. 12998,25.7417,,C -1098,3,"McGowan, Miss. Katherine",female,35,0,0,9232,7.75,,Q -1099,2,"Collett, Mr. Sidney C Stuart",male,24,0,0,28034,10.5,,S -1100,1,"Rosenbaum, Miss. Edith Louise",female,33,0,0,PC 17613,27.7208,A11,C -1101,3,"Delalic, Mr. Redjo",male,25,0,0,349250,7.8958,,S -1102,3,"Andersen, Mr. Albert Karvin",male,32,0,0,C 4001,22.525,,S -1103,3,"Finoli, Mr. Luigi",male,,0,0,SOTON/O.Q. 3101308,7.05,,S -1104,2,"Deacon, Mr. Percy William",male,17,0,0,S.O.C. 14879,73.5,,S -1105,2,"Howard, Mrs. Benjamin (Ellen Truelove Arman)",female,60,1,0,24065,26,,S -1106,3,"Andersson, Miss. Ida Augusta Margareta",female,38,4,2,347091,7.775,,S -1107,1,"Head, Mr. Christopher",male,42,0,0,113038,42.5,B11,S -1108,3,"Mahon, Miss. Bridget Delia",female,,0,0,330924,7.8792,,Q -1109,1,"Wick, Mr. George Dennick",male,57,1,1,36928,164.8667,,S -1110,1,"Widener, Mrs. George Dunton (Eleanor Elkins)",female,50,1,1,113503,211.5,C80,C -1111,3,"Thomson, Mr. Alexander Morrison",male,,0,0,32302,8.05,,S -1112,2,"Duran y More, Miss. Florentina",female,30,1,0,SC/PARIS 2148,13.8583,,C -1113,3,"Reynolds, Mr. Harold J",male,21,0,0,342684,8.05,,S -1114,2,"Cook, Mrs. (Selena Rogers)",female,22,0,0,W./C. 14266,10.5,F33,S -1115,3,"Karlsson, Mr. Einar Gervasius",male,21,0,0,350053,7.7958,,S -1116,1,"Candee, Mrs. Edward (Helen Churchill Hungerford)",female,53,0,0,PC 17606,27.4458,,C -1117,3,"Moubarek, Mrs. George (Omine Amenia"" Alexander)""",female,,0,2,2661,15.2458,,C -1118,3,"Asplund, Mr. Johan Charles",male,23,0,0,350054,7.7958,,S -1119,3,"McNeill, Miss. Bridget",female,,0,0,370368,7.75,,Q -1120,3,"Everett, Mr. Thomas James",male,40.5,0,0,C.A. 6212,15.1,,S -1121,2,"Hocking, Mr. Samuel James Metcalfe",male,36,0,0,242963,13,,S -1122,2,"Sweet, Mr. George Frederick",male,14,0,0,220845,65,,S -1123,1,"Willard, Miss. Constance",female,21,0,0,113795,26.55,,S -1124,3,"Wiklund, Mr. Karl Johan",male,21,1,0,3101266,6.4958,,S -1125,3,"Linehan, Mr. Michael",male,,0,0,330971,7.8792,,Q -1126,1,"Cumings, Mr. John Bradley",male,39,1,0,PC 17599,71.2833,C85,C -1127,3,"Vendel, Mr. Olof Edvin",male,20,0,0,350416,7.8542,,S -1128,1,"Warren, Mr. Frank Manley",male,64,1,0,110813,75.25,D37,C -1129,3,"Baccos, Mr. Raffull",male,20,0,0,2679,7.225,,C -1130,2,"Hiltunen, Miss. Marta",female,18,1,1,250650,13,,S -1131,1,"Douglas, Mrs. Walter Donald (Mahala Dutton)",female,48,1,0,PC 17761,106.425,C86,C -1132,1,"Lindstrom, Mrs. Carl Johan (Sigrid Posse)",female,55,0,0,112377,27.7208,,C -1133,2,"Christy, Mrs. (Alice Frances)",female,45,0,2,237789,30,,S -1134,1,"Spedden, Mr. Frederic Oakley",male,45,1,1,16966,134.5,E34,C -1135,3,"Hyman, Mr. Abraham",male,,0,0,3470,7.8875,,S -1136,3,"Johnston, Master. William Arthur Willie""""",male,,1,2,W./C. 6607,23.45,,S -1137,1,"Kenyon, Mr. Frederick R",male,41,1,0,17464,51.8625,D21,S -1138,2,"Karnes, Mrs. J Frank (Claire Bennett)",female,22,0,0,F.C.C. 13534,21,,S -1139,2,"Drew, Mr. James Vivian",male,42,1,1,28220,32.5,,S -1140,2,"Hold, Mrs. Stephen (Annie Margaret Hill)",female,29,1,0,26707,26,,S -1141,3,"Khalil, Mrs. Betros (Zahie Maria"" Elias)""",female,,1,0,2660,14.4542,,C -1142,2,"West, Miss. Barbara J",female,0.92,1,2,C.A. 34651,27.75,,S -1143,3,"Abrahamsson, Mr. Abraham August Johannes",male,20,0,0,SOTON/O2 3101284,7.925,,S -1144,1,"Clark, Mr. Walter Miller",male,27,1,0,13508,136.7792,C89,C -1145,3,"Salander, Mr. Karl Johan",male,24,0,0,7266,9.325,,S -1146,3,"Wenzel, Mr. Linhart",male,32.5,0,0,345775,9.5,,S -1147,3,"MacKay, Mr. George William",male,,0,0,C.A. 42795,7.55,,S -1148,3,"Mahon, Mr. John",male,,0,0,AQ/4 3130,7.75,,Q -1149,3,"Niklasson, Mr. Samuel",male,28,0,0,363611,8.05,,S -1150,2,"Bentham, Miss. Lilian W",female,19,0,0,28404,13,,S -1151,3,"Midtsjo, Mr. Karl Albert",male,21,0,0,345501,7.775,,S -1152,3,"de Messemaeker, Mr. Guillaume Joseph",male,36.5,1,0,345572,17.4,,S -1153,3,"Nilsson, Mr. August Ferdinand",male,21,0,0,350410,7.8542,,S -1154,2,"Wells, Mrs. Arthur Henry (Addie"" Dart Trevaskis)""",female,29,0,2,29103,23,,S -1155,3,"Klasen, Miss. Gertrud Emilia",female,1,1,1,350405,12.1833,,S -1156,2,"Portaluppi, Mr. Emilio Ilario Giuseppe",male,30,0,0,C.A. 34644,12.7375,,C -1157,3,"Lyntakoff, Mr. Stanko",male,,0,0,349235,7.8958,,S -1158,1,"Chisholm, Mr. Roderick Robert Crispin",male,,0,0,112051,0,,S -1159,3,"Warren, Mr. Charles William",male,,0,0,C.A. 49867,7.55,,S -1160,3,"Howard, Miss. May Elizabeth",female,,0,0,A. 2. 39186,8.05,,S -1161,3,"Pokrnic, Mr. Mate",male,17,0,0,315095,8.6625,,S -1162,1,"McCaffry, Mr. Thomas Francis",male,46,0,0,13050,75.2417,C6,C -1163,3,"Fox, Mr. Patrick",male,,0,0,368573,7.75,,Q -1164,1,"Clark, Mrs. Walter Miller (Virginia McDowell)",female,26,1,0,13508,136.7792,C89,C -1165,3,"Lennon, Miss. Mary",female,,1,0,370371,15.5,,Q -1166,3,"Saade, Mr. Jean Nassr",male,,0,0,2676,7.225,,C -1167,2,"Bryhl, Miss. Dagmar Jenny Ingeborg ",female,20,1,0,236853,26,,S -1168,2,"Parker, Mr. Clifford Richard",male,28,0,0,SC 14888,10.5,,S -1169,2,"Faunthorpe, Mr. Harry",male,40,1,0,2926,26,,S -1170,2,"Ware, Mr. John James",male,30,1,0,CA 31352,21,,S -1171,2,"Oxenham, Mr. Percy Thomas",male,22,0,0,W./C. 14260,10.5,,S -1172,3,"Oreskovic, Miss. Jelka",female,23,0,0,315085,8.6625,,S -1173,3,"Peacock, Master. Alfred Edward",male,0.75,1,1,SOTON/O.Q. 3101315,13.775,,S -1174,3,"Fleming, Miss. Honora",female,,0,0,364859,7.75,,Q -1175,3,"Touma, Miss. Maria Youssef",female,9,1,1,2650,15.2458,,C -1176,3,"Rosblom, Miss. Salli Helena",female,2,1,1,370129,20.2125,,S -1177,3,"Dennis, Mr. William",male,36,0,0,A/5 21175,7.25,,S -1178,3,"Franklin, Mr. Charles (Charles Fardon)",male,,0,0,SOTON/O.Q. 3101314,7.25,,S -1179,1,"Snyder, Mr. John Pillsbury",male,24,1,0,21228,82.2667,B45,S -1180,3,"Mardirosian, Mr. Sarkis",male,,0,0,2655,7.2292,F E46,C -1181,3,"Ford, Mr. Arthur",male,,0,0,A/5 1478,8.05,,S -1182,1,"Rheims, Mr. George Alexander Lucien",male,,0,0,PC 17607,39.6,,S -1183,3,"Daly, Miss. Margaret Marcella Maggie""""",female,30,0,0,382650,6.95,,Q -1184,3,"Nasr, Mr. Mustafa",male,,0,0,2652,7.2292,,C -1185,1,"Dodge, Dr. Washington",male,53,1,1,33638,81.8583,A34,S -1186,3,"Wittevrongel, Mr. Camille",male,36,0,0,345771,9.5,,S -1187,3,"Angheloff, Mr. Minko",male,26,0,0,349202,7.8958,,S -1188,2,"Laroche, Miss. Louise",female,1,1,2,SC/Paris 2123,41.5792,,C -1189,3,"Samaan, Mr. Hanna",male,,2,0,2662,21.6792,,C -1190,1,"Loring, Mr. Joseph Holland",male,30,0,0,113801,45.5,,S -1191,3,"Johansson, Mr. Nils",male,29,0,0,347467,7.8542,,S -1192,3,"Olsson, Mr. Oscar Wilhelm",male,32,0,0,347079,7.775,,S -1193,2,"Malachard, Mr. Noel",male,,0,0,237735,15.0458,D,C -1194,2,"Phillips, Mr. Escott Robert",male,43,0,1,S.O./P.P. 2,21,,S -1195,3,"Pokrnic, Mr. Tome",male,24,0,0,315092,8.6625,,S -1196,3,"McCarthy, Miss. Catherine Katie""""",female,,0,0,383123,7.75,,Q -1197,1,"Crosby, Mrs. Edward Gifford (Catherine Elizabeth Halstead)",female,64,1,1,112901,26.55,B26,S -1198,1,"Allison, Mr. Hudson Joshua Creighton",male,30,1,2,113781,151.55,C22 C26,S -1199,3,"Aks, Master. Philip Frank",male,0.83,0,1,392091,9.35,,S -1200,1,"Hays, Mr. Charles Melville",male,55,1,1,12749,93.5,B69,S -1201,3,"Hansen, Mrs. Claus Peter (Jennie L Howard)",female,45,1,0,350026,14.1083,,S -1202,3,"Cacic, Mr. Jego Grga",male,18,0,0,315091,8.6625,,S -1203,3,"Vartanian, Mr. David",male,22,0,0,2658,7.225,,C -1204,3,"Sadowitz, Mr. Harry",male,,0,0,LP 1588,7.575,,S -1205,3,"Carr, Miss. Jeannie",female,37,0,0,368364,7.75,,Q -1206,1,"White, Mrs. John Stuart (Ella Holmes)",female,55,0,0,PC 17760,135.6333,C32,C -1207,3,"Hagardon, Miss. Kate",female,17,0,0,AQ/3. 30631,7.7333,,Q -1208,1,"Spencer, Mr. William Augustus",male,57,1,0,PC 17569,146.5208,B78,C -1209,2,"Rogers, Mr. Reginald Harry",male,19,0,0,28004,10.5,,S -1210,3,"Jonsson, Mr. Nils Hilding",male,27,0,0,350408,7.8542,,S -1211,2,"Jefferys, Mr. Ernest Wilfred",male,22,2,0,C.A. 31029,31.5,,S -1212,3,"Andersson, Mr. Johan Samuel",male,26,0,0,347075,7.775,,S -1213,3,"Krekorian, Mr. Neshan",male,25,0,0,2654,7.2292,F E57,C -1214,2,"Nesson, Mr. Israel",male,26,0,0,244368,13,F2,S -1215,1,"Rowe, Mr. Alfred G",male,33,0,0,113790,26.55,,S -1216,1,"Kreuchen, Miss. Emilie",female,39,0,0,24160,211.3375,,S -1217,3,"Assam, Mr. Ali",male,23,0,0,SOTON/O.Q. 3101309,7.05,,S -1218,2,"Becker, Miss. Ruth Elizabeth",female,12,2,1,230136,39,F4,S -1219,1,"Rosenshine, Mr. George (Mr George Thorne"")""",male,46,0,0,PC 17585,79.2,,C -1220,2,"Clarke, Mr. Charles Valentine",male,29,1,0,2003,26,,S -1221,2,"Enander, Mr. Ingvar",male,21,0,0,236854,13,,S -1222,2,"Davies, Mrs. John Morgan (Elizabeth Agnes Mary White) ",female,48,0,2,C.A. 33112,36.75,,S -1223,1,"Dulles, Mr. William Crothers",male,39,0,0,PC 17580,29.7,A18,C -1224,3,"Thomas, Mr. Tannous",male,,0,0,2684,7.225,,C -1225,3,"Nakid, Mrs. Said (Waika Mary"" Mowad)""",female,19,1,1,2653,15.7417,,C -1226,3,"Cor, Mr. Ivan",male,27,0,0,349229,7.8958,,S -1227,1,"Maguire, Mr. John Edward",male,30,0,0,110469,26,C106,S -1228,2,"de Brito, Mr. Jose Joaquim",male,32,0,0,244360,13,,S -1229,3,"Elias, Mr. Joseph",male,39,0,2,2675,7.2292,,C -1230,2,"Denbury, Mr. Herbert",male,25,0,0,C.A. 31029,31.5,,S -1231,3,"Betros, Master. Seman",male,,0,0,2622,7.2292,,C -1232,2,"Fillbrook, Mr. Joseph Charles",male,18,0,0,C.A. 15185,10.5,,S -1233,3,"Lundstrom, Mr. Thure Edvin",male,32,0,0,350403,7.5792,,S -1234,3,"Sage, Mr. John George",male,,1,9,CA. 2343,69.55,,S -1235,1,"Cardeza, Mrs. James Warburton Martinez (Charlotte Wardle Drake)",female,58,0,1,PC 17755,512.3292,B51 B53 B55,C -1236,3,"van Billiard, Master. James William",male,,1,1,A/5. 851,14.5,,S -1237,3,"Abelseth, Miss. Karen Marie",female,16,0,0,348125,7.65,,S -1238,2,"Botsford, Mr. William Hull",male,26,0,0,237670,13,,S -1239,3,"Whabee, Mrs. George Joseph (Shawneene Abi-Saab)",female,38,0,0,2688,7.2292,,C -1240,2,"Giles, Mr. Ralph",male,24,0,0,248726,13.5,,S -1241,2,"Walcroft, Miss. Nellie",female,31,0,0,F.C.C. 13528,21,,S -1242,1,"Greenfield, Mrs. Leo David (Blanche Strouse)",female,45,0,1,PC 17759,63.3583,D10 D12,C -1243,2,"Stokes, Mr. Philip Joseph",male,25,0,0,F.C.C. 13540,10.5,,S -1244,2,"Dibden, Mr. William",male,18,0,0,S.O.C. 14879,73.5,,S -1245,2,"Herman, Mr. Samuel",male,49,1,2,220845,65,,S -1246,3,"Dean, Miss. Elizabeth Gladys Millvina""""",female,0.17,1,2,C.A. 2315,20.575,,S -1247,1,"Julian, Mr. Henry Forbes",male,50,0,0,113044,26,E60,S -1248,1,"Brown, Mrs. John Murray (Caroline Lane Lamson)",female,59,2,0,11769,51.4792,C101,S -1249,3,"Lockyer, Mr. Edward",male,,0,0,1222,7.8792,,S -1250,3,"O'Keefe, Mr. Patrick",male,,0,0,368402,7.75,,Q -1251,3,"Lindell, Mrs. Edvard Bengtsson (Elin Gerda Persson)",female,30,1,0,349910,15.55,,S -1252,3,"Sage, Master. William Henry",male,14.5,8,2,CA. 2343,69.55,,S -1253,2,"Mallet, Mrs. Albert (Antoinette Magnin)",female,24,1,1,S.C./PARIS 2079,37.0042,,C -1254,2,"Ware, Mrs. John James (Florence Louise Long)",female,31,0,0,CA 31352,21,,S -1255,3,"Strilic, Mr. Ivan",male,27,0,0,315083,8.6625,,S -1256,1,"Harder, Mrs. George Achilles (Dorothy Annan)",female,25,1,0,11765,55.4417,E50,C -1257,3,"Sage, Mrs. John (Annie Bullen)",female,,1,9,CA. 2343,69.55,,S -1258,3,"Caram, Mr. Joseph",male,,1,0,2689,14.4583,,C -1259,3,"Riihivouri, Miss. Susanna Juhantytar Sanni""""",female,22,0,0,3101295,39.6875,,S -1260,1,"Gibson, Mrs. Leonard (Pauline C Boeson)",female,45,0,1,112378,59.4,,C -1261,2,"Pallas y Castello, Mr. Emilio",male,29,0,0,SC/PARIS 2147,13.8583,,C -1262,2,"Giles, Mr. Edgar",male,21,1,0,28133,11.5,,S -1263,1,"Wilson, Miss. Helen Alice",female,31,0,0,16966,134.5,E39 E41,C -1264,1,"Ismay, Mr. Joseph Bruce",male,49,0,0,112058,0,B52 B54 B56,S -1265,2,"Harbeck, Mr. William H",male,44,0,0,248746,13,,S -1266,1,"Dodge, Mrs. Washington (Ruth Vidaver)",female,54,1,1,33638,81.8583,A34,S -1267,1,"Bowen, Miss. Grace Scott",female,45,0,0,PC 17608,262.375,,C -1268,3,"Kink, Miss. Maria",female,22,2,0,315152,8.6625,,S -1269,2,"Cotterill, Mr. Henry Harry""""",male,21,0,0,29107,11.5,,S -1270,1,"Hipkins, Mr. William Edward",male,55,0,0,680,50,C39,S -1271,3,"Asplund, Master. Carl Edgar",male,5,4,2,347077,31.3875,,S -1272,3,"O'Connor, Mr. Patrick",male,,0,0,366713,7.75,,Q -1273,3,"Foley, Mr. Joseph",male,26,0,0,330910,7.8792,,Q -1274,3,"Risien, Mrs. Samuel (Emma)",female,,0,0,364498,14.5,,S -1275,3,"McNamee, Mrs. Neal (Eileen O'Leary)",female,19,1,0,376566,16.1,,S -1276,2,"Wheeler, Mr. Edwin Frederick""""",male,,0,0,SC/PARIS 2159,12.875,,S -1277,2,"Herman, Miss. Kate",female,24,1,2,220845,65,,S -1278,3,"Aronsson, Mr. Ernst Axel Algot",male,24,0,0,349911,7.775,,S -1279,2,"Ashby, Mr. John",male,57,0,0,244346,13,,S -1280,3,"Canavan, Mr. Patrick",male,21,0,0,364858,7.75,,Q -1281,3,"Palsson, Master. Paul Folke",male,6,3,1,349909,21.075,,S -1282,1,"Payne, Mr. Vivian Ponsonby",male,23,0,0,12749,93.5,B24,S -1283,1,"Lines, Mrs. Ernest H (Elizabeth Lindsey James)",female,51,0,1,PC 17592,39.4,D28,S -1284,3,"Abbott, Master. Eugene Joseph",male,13,0,2,C.A. 2673,20.25,,S -1285,2,"Gilbert, Mr. William",male,47,0,0,C.A. 30769,10.5,,S -1286,3,"Kink-Heilmann, Mr. Anton",male,29,3,1,315153,22.025,,S -1287,1,"Smith, Mrs. Lucien Philip (Mary Eloise Hughes)",female,18,1,0,13695,60,C31,S -1288,3,"Colbert, Mr. Patrick",male,24,0,0,371109,7.25,,Q -1289,1,"Frolicher-Stehli, Mrs. Maxmillian (Margaretha Emerentia Stehli)",female,48,1,1,13567,79.2,B41,C -1290,3,"Larsson-Rondberg, Mr. Edvard A",male,22,0,0,347065,7.775,,S -1291,3,"Conlon, Mr. Thomas Henry",male,31,0,0,21332,7.7333,,Q -1292,1,"Bonnell, Miss. Caroline",female,30,0,0,36928,164.8667,C7,S -1293,2,"Gale, Mr. Harry",male,38,1,0,28664,21,,S -1294,1,"Gibson, Miss. Dorothy Winifred",female,22,0,1,112378,59.4,,C -1295,1,"Carrau, Mr. Jose Pedro",male,17,0,0,113059,47.1,,S -1296,1,"Frauenthal, Mr. Isaac Gerald",male,43,1,0,17765,27.7208,D40,C -1297,2,"Nourney, Mr. Alfred (Baron von Drachstedt"")""",male,20,0,0,SC/PARIS 2166,13.8625,D38,C -1298,2,"Ware, Mr. William Jeffery",male,23,1,0,28666,10.5,,S -1299,1,"Widener, Mr. George Dunton",male,50,1,1,113503,211.5,C80,C -1300,3,"Riordan, Miss. Johanna Hannah""""",female,,0,0,334915,7.7208,,Q -1301,3,"Peacock, Miss. Treasteall",female,3,1,1,SOTON/O.Q. 3101315,13.775,,S -1302,3,"Naughton, Miss. Hannah",female,,0,0,365237,7.75,,Q -1303,1,"Minahan, Mrs. William Edward (Lillian E Thorpe)",female,37,1,0,19928,90,C78,Q -1304,3,"Henriksson, Miss. Jenny Lovisa",female,28,0,0,347086,7.775,,S -1305,3,"Spector, Mr. Woolf",male,,0,0,A.5. 3236,8.05,,S -1306,1,"Oliva y Ocana, Dona. Fermina",female,39,0,0,PC 17758,108.9,C105,C -1307,3,"Saether, Mr. Simon Sivertsen",male,38.5,0,0,SOTON/O.Q. 3101262,7.25,,S -1308,3,"Ware, Mr. Frederick",male,,0,0,359309,8.05,,S -1309,3,"Peter, Master. Michael J",male,,1,1,2668,22.3583,,C diff --git a/examples/sdk/titanic/data/train.csv b/examples/sdk/titanic/data/train.csv deleted file mode 100755 index 63b68ab0b..000000000 --- a/examples/sdk/titanic/data/train.csv +++ /dev/null @@ -1,892 +0,0 @@ -PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked -1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S -2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C -3,1,3,"Heikkinen, Miss. Laina",female,26,0,0,STON/O2. 3101282,7.925,,S -4,1,1,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",female,35,1,0,113803,53.1,C123,S -5,0,3,"Allen, Mr. William Henry",male,35,0,0,373450,8.05,,S -6,0,3,"Moran, Mr. James",male,,0,0,330877,8.4583,,Q -7,0,1,"McCarthy, Mr. Timothy J",male,54,0,0,17463,51.8625,E46,S -8,0,3,"Palsson, Master. Gosta Leonard",male,2,3,1,349909,21.075,,S -9,1,3,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",female,27,0,2,347742,11.1333,,S -10,1,2,"Nasser, Mrs. Nicholas (Adele Achem)",female,14,1,0,237736,30.0708,,C -11,1,3,"Sandstrom, Miss. Marguerite Rut",female,4,1,1,PP 9549,16.7,G6,S -12,1,1,"Bonnell, Miss. Elizabeth",female,58,0,0,113783,26.55,C103,S -13,0,3,"Saundercock, Mr. William Henry",male,20,0,0,A/5. 2151,8.05,,S -14,0,3,"Andersson, Mr. Anders Johan",male,39,1,5,347082,31.275,,S -15,0,3,"Vestrom, Miss. Hulda Amanda Adolfina",female,14,0,0,350406,7.8542,,S -16,1,2,"Hewlett, Mrs. (Mary D Kingcome) ",female,55,0,0,248706,16,,S -17,0,3,"Rice, Master. Eugene",male,2,4,1,382652,29.125,,Q -18,1,2,"Williams, Mr. Charles Eugene",male,,0,0,244373,13,,S -19,0,3,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)",female,31,1,0,345763,18,,S -20,1,3,"Masselmani, Mrs. Fatima",female,,0,0,2649,7.225,,C -21,0,2,"Fynney, Mr. Joseph J",male,35,0,0,239865,26,,S -22,1,2,"Beesley, Mr. Lawrence",male,34,0,0,248698,13,D56,S -23,1,3,"McGowan, Miss. Anna ""Annie""",female,15,0,0,330923,8.0292,,Q -24,1,1,"Sloper, Mr. William Thompson",male,28,0,0,113788,35.5,A6,S -25,0,3,"Palsson, Miss. Torborg Danira",female,8,3,1,349909,21.075,,S -26,1,3,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",female,38,1,5,347077,31.3875,,S -27,0,3,"Emir, Mr. Farred Chehab",male,,0,0,2631,7.225,,C -28,0,1,"Fortune, Mr. Charles Alexander",male,19,3,2,19950,263,C23 C25 C27,S -29,1,3,"O'Dwyer, Miss. Ellen ""Nellie""",female,,0,0,330959,7.8792,,Q -30,0,3,"Todoroff, Mr. Lalio",male,,0,0,349216,7.8958,,S -31,0,1,"Uruchurtu, Don. Manuel E",male,40,0,0,PC 17601,27.7208,,C -32,1,1,"Spencer, Mrs. William Augustus (Marie Eugenie)",female,,1,0,PC 17569,146.5208,B78,C -33,1,3,"Glynn, Miss. Mary Agatha",female,,0,0,335677,7.75,,Q -34,0,2,"Wheadon, Mr. Edward H",male,66,0,0,C.A. 24579,10.5,,S -35,0,1,"Meyer, Mr. Edgar Joseph",male,28,1,0,PC 17604,82.1708,,C -36,0,1,"Holverson, Mr. Alexander Oskar",male,42,1,0,113789,52,,S -37,1,3,"Mamee, Mr. Hanna",male,,0,0,2677,7.2292,,C -38,0,3,"Cann, Mr. Ernest Charles",male,21,0,0,A./5. 2152,8.05,,S -39,0,3,"Vander Planke, Miss. Augusta Maria",female,18,2,0,345764,18,,S -40,1,3,"Nicola-Yarred, Miss. Jamila",female,14,1,0,2651,11.2417,,C -41,0,3,"Ahlin, Mrs. Johan (Johanna Persdotter Larsson)",female,40,1,0,7546,9.475,,S -42,0,2,"Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)",female,27,1,0,11668,21,,S -43,0,3,"Kraeff, Mr. Theodor",male,,0,0,349253,7.8958,,C -44,1,2,"Laroche, Miss. Simonne Marie Anne Andree",female,3,1,2,SC/Paris 2123,41.5792,,C -45,1,3,"Devaney, Miss. Margaret Delia",female,19,0,0,330958,7.8792,,Q -46,0,3,"Rogers, Mr. William John",male,,0,0,S.C./A.4. 23567,8.05,,S -47,0,3,"Lennon, Mr. Denis",male,,1,0,370371,15.5,,Q -48,1,3,"O'Driscoll, Miss. Bridget",female,,0,0,14311,7.75,,Q -49,0,3,"Samaan, Mr. Youssef",male,,2,0,2662,21.6792,,C -50,0,3,"Arnold-Franchi, Mrs. Josef (Josefine Franchi)",female,18,1,0,349237,17.8,,S -51,0,3,"Panula, Master. Juha Niilo",male,7,4,1,3101295,39.6875,,S -52,0,3,"Nosworthy, Mr. Richard Cater",male,21,0,0,A/4. 39886,7.8,,S -53,1,1,"Harper, Mrs. Henry Sleeper (Myna Haxtun)",female,49,1,0,PC 17572,76.7292,D33,C -54,1,2,"Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)",female,29,1,0,2926,26,,S -55,0,1,"Ostby, Mr. Engelhart Cornelius",male,65,0,1,113509,61.9792,B30,C -56,1,1,"Woolner, Mr. Hugh",male,,0,0,19947,35.5,C52,S -57,1,2,"Rugg, Miss. Emily",female,21,0,0,C.A. 31026,10.5,,S -58,0,3,"Novel, Mr. Mansouer",male,28.5,0,0,2697,7.2292,,C -59,1,2,"West, Miss. Constance Mirium",female,5,1,2,C.A. 34651,27.75,,S -60,0,3,"Goodwin, Master. William Frederick",male,11,5,2,CA 2144,46.9,,S -61,0,3,"Sirayanian, Mr. Orsen",male,22,0,0,2669,7.2292,,C -62,1,1,"Icard, Miss. Amelie",female,38,0,0,113572,80,B28, -63,0,1,"Harris, Mr. Henry Birkhardt",male,45,1,0,36973,83.475,C83,S -64,0,3,"Skoog, Master. Harald",male,4,3,2,347088,27.9,,S -65,0,1,"Stewart, Mr. Albert A",male,,0,0,PC 17605,27.7208,,C -66,1,3,"Moubarek, Master. Gerios",male,,1,1,2661,15.2458,,C -67,1,2,"Nye, Mrs. (Elizabeth Ramell)",female,29,0,0,C.A. 29395,10.5,F33,S -68,0,3,"Crease, Mr. Ernest James",male,19,0,0,S.P. 3464,8.1583,,S -69,1,3,"Andersson, Miss. Erna Alexandra",female,17,4,2,3101281,7.925,,S -70,0,3,"Kink, Mr. Vincenz",male,26,2,0,315151,8.6625,,S -71,0,2,"Jenkin, Mr. Stephen Curnow",male,32,0,0,C.A. 33111,10.5,,S -72,0,3,"Goodwin, Miss. Lillian Amy",female,16,5,2,CA 2144,46.9,,S -73,0,2,"Hood, Mr. Ambrose Jr",male,21,0,0,S.O.C. 14879,73.5,,S -74,0,3,"Chronopoulos, Mr. Apostolos",male,26,1,0,2680,14.4542,,C -75,1,3,"Bing, Mr. Lee",male,32,0,0,1601,56.4958,,S -76,0,3,"Moen, Mr. Sigurd Hansen",male,25,0,0,348123,7.65,F G73,S -77,0,3,"Staneff, Mr. Ivan",male,,0,0,349208,7.8958,,S -78,0,3,"Moutal, Mr. Rahamin Haim",male,,0,0,374746,8.05,,S -79,1,2,"Caldwell, Master. Alden Gates",male,0.83,0,2,248738,29,,S -80,1,3,"Dowdell, Miss. Elizabeth",female,30,0,0,364516,12.475,,S -81,0,3,"Waelens, Mr. Achille",male,22,0,0,345767,9,,S -82,1,3,"Sheerlinck, Mr. Jan Baptist",male,29,0,0,345779,9.5,,S -83,1,3,"McDermott, Miss. Brigdet Delia",female,,0,0,330932,7.7875,,Q -84,0,1,"Carrau, Mr. Francisco M",male,28,0,0,113059,47.1,,S -85,1,2,"Ilett, Miss. Bertha",female,17,0,0,SO/C 14885,10.5,,S -86,1,3,"Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)",female,33,3,0,3101278,15.85,,S -87,0,3,"Ford, Mr. William Neal",male,16,1,3,W./C. 6608,34.375,,S -88,0,3,"Slocovski, Mr. Selman Francis",male,,0,0,SOTON/OQ 392086,8.05,,S -89,1,1,"Fortune, Miss. Mabel Helen",female,23,3,2,19950,263,C23 C25 C27,S -90,0,3,"Celotti, Mr. Francesco",male,24,0,0,343275,8.05,,S -91,0,3,"Christmann, Mr. Emil",male,29,0,0,343276,8.05,,S -92,0,3,"Andreasson, Mr. Paul Edvin",male,20,0,0,347466,7.8542,,S -93,0,1,"Chaffee, Mr. Herbert Fuller",male,46,1,0,W.E.P. 5734,61.175,E31,S -94,0,3,"Dean, Mr. Bertram Frank",male,26,1,2,C.A. 2315,20.575,,S -95,0,3,"Coxon, Mr. Daniel",male,59,0,0,364500,7.25,,S -96,0,3,"Shorney, Mr. Charles Joseph",male,,0,0,374910,8.05,,S -97,0,1,"Goldschmidt, Mr. George B",male,71,0,0,PC 17754,34.6542,A5,C -98,1,1,"Greenfield, Mr. William Bertram",male,23,0,1,PC 17759,63.3583,D10 D12,C -99,1,2,"Doling, Mrs. John T (Ada Julia Bone)",female,34,0,1,231919,23,,S -100,0,2,"Kantor, Mr. Sinai",male,34,1,0,244367,26,,S -101,0,3,"Petranec, Miss. Matilda",female,28,0,0,349245,7.8958,,S -102,0,3,"Petroff, Mr. Pastcho (""Pentcho"")",male,,0,0,349215,7.8958,,S -103,0,1,"White, Mr. Richard Frasar",male,21,0,1,35281,77.2875,D26,S -104,0,3,"Johansson, Mr. Gustaf Joel",male,33,0,0,7540,8.6542,,S -105,0,3,"Gustafsson, Mr. Anders Vilhelm",male,37,2,0,3101276,7.925,,S -106,0,3,"Mionoff, Mr. Stoytcho",male,28,0,0,349207,7.8958,,S -107,1,3,"Salkjelsvik, Miss. Anna Kristine",female,21,0,0,343120,7.65,,S -108,1,3,"Moss, Mr. Albert Johan",male,,0,0,312991,7.775,,S -109,0,3,"Rekic, Mr. Tido",male,38,0,0,349249,7.8958,,S -110,1,3,"Moran, Miss. Bertha",female,,1,0,371110,24.15,,Q -111,0,1,"Porter, Mr. Walter Chamberlain",male,47,0,0,110465,52,C110,S -112,0,3,"Zabour, Miss. Hileni",female,14.5,1,0,2665,14.4542,,C -113,0,3,"Barton, Mr. David John",male,22,0,0,324669,8.05,,S -114,0,3,"Jussila, Miss. Katriina",female,20,1,0,4136,9.825,,S -115,0,3,"Attalah, Miss. Malake",female,17,0,0,2627,14.4583,,C -116,0,3,"Pekoniemi, Mr. Edvard",male,21,0,0,STON/O 2. 3101294,7.925,,S -117,0,3,"Connors, Mr. Patrick",male,70.5,0,0,370369,7.75,,Q -118,0,2,"Turpin, Mr. William John Robert",male,29,1,0,11668,21,,S -119,0,1,"Baxter, Mr. Quigg Edmond",male,24,0,1,PC 17558,247.5208,B58 B60,C -120,0,3,"Andersson, Miss. Ellis Anna Maria",female,2,4,2,347082,31.275,,S -121,0,2,"Hickman, Mr. Stanley George",male,21,2,0,S.O.C. 14879,73.5,,S -122,0,3,"Moore, Mr. Leonard Charles",male,,0,0,A4. 54510,8.05,,S -123,0,2,"Nasser, Mr. Nicholas",male,32.5,1,0,237736,30.0708,,C -124,1,2,"Webber, Miss. Susan",female,32.5,0,0,27267,13,E101,S -125,0,1,"White, Mr. Percival Wayland",male,54,0,1,35281,77.2875,D26,S -126,1,3,"Nicola-Yarred, Master. Elias",male,12,1,0,2651,11.2417,,C -127,0,3,"McMahon, Mr. Martin",male,,0,0,370372,7.75,,Q -128,1,3,"Madsen, Mr. Fridtjof Arne",male,24,0,0,C 17369,7.1417,,S -129,1,3,"Peter, Miss. Anna",female,,1,1,2668,22.3583,F E69,C -130,0,3,"Ekstrom, Mr. Johan",male,45,0,0,347061,6.975,,S -131,0,3,"Drazenoic, Mr. Jozef",male,33,0,0,349241,7.8958,,C -132,0,3,"Coelho, Mr. Domingos Fernandeo",male,20,0,0,SOTON/O.Q. 3101307,7.05,,S -133,0,3,"Robins, Mrs. Alexander A (Grace Charity Laury)",female,47,1,0,A/5. 3337,14.5,,S -134,1,2,"Weisz, Mrs. Leopold (Mathilde Francoise Pede)",female,29,1,0,228414,26,,S -135,0,2,"Sobey, Mr. Samuel James Hayden",male,25,0,0,C.A. 29178,13,,S -136,0,2,"Richard, Mr. Emile",male,23,0,0,SC/PARIS 2133,15.0458,,C -137,1,1,"Newsom, Miss. Helen Monypeny",female,19,0,2,11752,26.2833,D47,S -138,0,1,"Futrelle, Mr. Jacques Heath",male,37,1,0,113803,53.1,C123,S -139,0,3,"Osen, Mr. Olaf Elon",male,16,0,0,7534,9.2167,,S -140,0,1,"Giglio, Mr. Victor",male,24,0,0,PC 17593,79.2,B86,C -141,0,3,"Boulos, Mrs. Joseph (Sultana)",female,,0,2,2678,15.2458,,C -142,1,3,"Nysten, Miss. Anna Sofia",female,22,0,0,347081,7.75,,S -143,1,3,"Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck)",female,24,1,0,STON/O2. 3101279,15.85,,S -144,0,3,"Burke, Mr. Jeremiah",male,19,0,0,365222,6.75,,Q -145,0,2,"Andrew, Mr. Edgardo Samuel",male,18,0,0,231945,11.5,,S -146,0,2,"Nicholls, Mr. Joseph Charles",male,19,1,1,C.A. 33112,36.75,,S -147,1,3,"Andersson, Mr. August Edvard (""Wennerstrom"")",male,27,0,0,350043,7.7958,,S -148,0,3,"Ford, Miss. Robina Maggie ""Ruby""",female,9,2,2,W./C. 6608,34.375,,S -149,0,2,"Navratil, Mr. Michel (""Louis M Hoffman"")",male,36.5,0,2,230080,26,F2,S -150,0,2,"Byles, Rev. Thomas Roussel Davids",male,42,0,0,244310,13,,S -151,0,2,"Bateman, Rev. Robert James",male,51,0,0,S.O.P. 1166,12.525,,S -152,1,1,"Pears, Mrs. Thomas (Edith Wearne)",female,22,1,0,113776,66.6,C2,S -153,0,3,"Meo, Mr. Alfonzo",male,55.5,0,0,A.5. 11206,8.05,,S -154,0,3,"van Billiard, Mr. Austin Blyler",male,40.5,0,2,A/5. 851,14.5,,S -155,0,3,"Olsen, Mr. Ole Martin",male,,0,0,Fa 265302,7.3125,,S -156,0,1,"Williams, Mr. Charles Duane",male,51,0,1,PC 17597,61.3792,,C -157,1,3,"Gilnagh, Miss. Katherine ""Katie""",female,16,0,0,35851,7.7333,,Q -158,0,3,"Corn, Mr. Harry",male,30,0,0,SOTON/OQ 392090,8.05,,S -159,0,3,"Smiljanic, Mr. Mile",male,,0,0,315037,8.6625,,S -160,0,3,"Sage, Master. Thomas Henry",male,,8,2,CA. 2343,69.55,,S -161,0,3,"Cribb, Mr. John Hatfield",male,44,0,1,371362,16.1,,S -162,1,2,"Watt, Mrs. James (Elizabeth ""Bessie"" Inglis Milne)",female,40,0,0,C.A. 33595,15.75,,S -163,0,3,"Bengtsson, Mr. John Viktor",male,26,0,0,347068,7.775,,S -164,0,3,"Calic, Mr. Jovo",male,17,0,0,315093,8.6625,,S -165,0,3,"Panula, Master. Eino Viljami",male,1,4,1,3101295,39.6875,,S -166,1,3,"Goldsmith, Master. Frank John William ""Frankie""",male,9,0,2,363291,20.525,,S -167,1,1,"Chibnall, Mrs. (Edith Martha Bowerman)",female,,0,1,113505,55,E33,S -168,0,3,"Skoog, Mrs. William (Anna Bernhardina Karlsson)",female,45,1,4,347088,27.9,,S -169,0,1,"Baumann, Mr. John D",male,,0,0,PC 17318,25.925,,S -170,0,3,"Ling, Mr. Lee",male,28,0,0,1601,56.4958,,S -171,0,1,"Van der hoef, Mr. Wyckoff",male,61,0,0,111240,33.5,B19,S -172,0,3,"Rice, Master. Arthur",male,4,4,1,382652,29.125,,Q -173,1,3,"Johnson, Miss. Eleanor Ileen",female,1,1,1,347742,11.1333,,S -174,0,3,"Sivola, Mr. Antti Wilhelm",male,21,0,0,STON/O 2. 3101280,7.925,,S -175,0,1,"Smith, Mr. James Clinch",male,56,0,0,17764,30.6958,A7,C -176,0,3,"Klasen, Mr. Klas Albin",male,18,1,1,350404,7.8542,,S -177,0,3,"Lefebre, Master. Henry Forbes",male,,3,1,4133,25.4667,,S -178,0,1,"Isham, Miss. Ann Elizabeth",female,50,0,0,PC 17595,28.7125,C49,C -179,0,2,"Hale, Mr. Reginald",male,30,0,0,250653,13,,S -180,0,3,"Leonard, Mr. Lionel",male,36,0,0,LINE,0,,S -181,0,3,"Sage, Miss. Constance Gladys",female,,8,2,CA. 2343,69.55,,S -182,0,2,"Pernot, Mr. Rene",male,,0,0,SC/PARIS 2131,15.05,,C -183,0,3,"Asplund, Master. Clarence Gustaf Hugo",male,9,4,2,347077,31.3875,,S -184,1,2,"Becker, Master. Richard F",male,1,2,1,230136,39,F4,S -185,1,3,"Kink-Heilmann, Miss. Luise Gretchen",female,4,0,2,315153,22.025,,S -186,0,1,"Rood, Mr. Hugh Roscoe",male,,0,0,113767,50,A32,S -187,1,3,"O'Brien, Mrs. Thomas (Johanna ""Hannah"" Godfrey)",female,,1,0,370365,15.5,,Q -188,1,1,"Romaine, Mr. Charles Hallace (""Mr C Rolmane"")",male,45,0,0,111428,26.55,,S -189,0,3,"Bourke, Mr. John",male,40,1,1,364849,15.5,,Q -190,0,3,"Turcin, Mr. Stjepan",male,36,0,0,349247,7.8958,,S -191,1,2,"Pinsky, Mrs. (Rosa)",female,32,0,0,234604,13,,S -192,0,2,"Carbines, Mr. William",male,19,0,0,28424,13,,S -193,1,3,"Andersen-Jensen, Miss. Carla Christine Nielsine",female,19,1,0,350046,7.8542,,S -194,1,2,"Navratil, Master. Michel M",male,3,1,1,230080,26,F2,S -195,1,1,"Brown, Mrs. James Joseph (Margaret Tobin)",female,44,0,0,PC 17610,27.7208,B4,C -196,1,1,"Lurette, Miss. Elise",female,58,0,0,PC 17569,146.5208,B80,C -197,0,3,"Mernagh, Mr. Robert",male,,0,0,368703,7.75,,Q -198,0,3,"Olsen, Mr. Karl Siegwart Andreas",male,42,0,1,4579,8.4042,,S -199,1,3,"Madigan, Miss. Margaret ""Maggie""",female,,0,0,370370,7.75,,Q -200,0,2,"Yrois, Miss. Henriette (""Mrs Harbeck"")",female,24,0,0,248747,13,,S -201,0,3,"Vande Walle, Mr. Nestor Cyriel",male,28,0,0,345770,9.5,,S -202,0,3,"Sage, Mr. Frederick",male,,8,2,CA. 2343,69.55,,S -203,0,3,"Johanson, Mr. Jakob Alfred",male,34,0,0,3101264,6.4958,,S -204,0,3,"Youseff, Mr. Gerious",male,45.5,0,0,2628,7.225,,C -205,1,3,"Cohen, Mr. Gurshon ""Gus""",male,18,0,0,A/5 3540,8.05,,S -206,0,3,"Strom, Miss. Telma Matilda",female,2,0,1,347054,10.4625,G6,S -207,0,3,"Backstrom, Mr. Karl Alfred",male,32,1,0,3101278,15.85,,S -208,1,3,"Albimona, Mr. Nassef Cassem",male,26,0,0,2699,18.7875,,C -209,1,3,"Carr, Miss. Helen ""Ellen""",female,16,0,0,367231,7.75,,Q -210,1,1,"Blank, Mr. Henry",male,40,0,0,112277,31,A31,C -211,0,3,"Ali, Mr. Ahmed",male,24,0,0,SOTON/O.Q. 3101311,7.05,,S -212,1,2,"Cameron, Miss. Clear Annie",female,35,0,0,F.C.C. 13528,21,,S -213,0,3,"Perkin, Mr. John Henry",male,22,0,0,A/5 21174,7.25,,S -214,0,2,"Givard, Mr. Hans Kristensen",male,30,0,0,250646,13,,S -215,0,3,"Kiernan, Mr. Philip",male,,1,0,367229,7.75,,Q -216,1,1,"Newell, Miss. Madeleine",female,31,1,0,35273,113.275,D36,C -217,1,3,"Honkanen, Miss. Eliina",female,27,0,0,STON/O2. 3101283,7.925,,S -218,0,2,"Jacobsohn, Mr. Sidney Samuel",male,42,1,0,243847,27,,S -219,1,1,"Bazzani, Miss. Albina",female,32,0,0,11813,76.2917,D15,C -220,0,2,"Harris, Mr. Walter",male,30,0,0,W/C 14208,10.5,,S -221,1,3,"Sunderland, Mr. Victor Francis",male,16,0,0,SOTON/OQ 392089,8.05,,S -222,0,2,"Bracken, Mr. James H",male,27,0,0,220367,13,,S -223,0,3,"Green, Mr. George Henry",male,51,0,0,21440,8.05,,S -224,0,3,"Nenkoff, Mr. Christo",male,,0,0,349234,7.8958,,S -225,1,1,"Hoyt, Mr. Frederick Maxfield",male,38,1,0,19943,90,C93,S -226,0,3,"Berglund, Mr. Karl Ivar Sven",male,22,0,0,PP 4348,9.35,,S -227,1,2,"Mellors, Mr. William John",male,19,0,0,SW/PP 751,10.5,,S -228,0,3,"Lovell, Mr. John Hall (""Henry"")",male,20.5,0,0,A/5 21173,7.25,,S -229,0,2,"Fahlstrom, Mr. Arne Jonas",male,18,0,0,236171,13,,S -230,0,3,"Lefebre, Miss. Mathilde",female,,3,1,4133,25.4667,,S -231,1,1,"Harris, Mrs. Henry Birkhardt (Irene Wallach)",female,35,1,0,36973,83.475,C83,S -232,0,3,"Larsson, Mr. Bengt Edvin",male,29,0,0,347067,7.775,,S -233,0,2,"Sjostedt, Mr. Ernst Adolf",male,59,0,0,237442,13.5,,S -234,1,3,"Asplund, Miss. Lillian Gertrud",female,5,4,2,347077,31.3875,,S -235,0,2,"Leyson, Mr. Robert William Norman",male,24,0,0,C.A. 29566,10.5,,S -236,0,3,"Harknett, Miss. Alice Phoebe",female,,0,0,W./C. 6609,7.55,,S -237,0,2,"Hold, Mr. Stephen",male,44,1,0,26707,26,,S -238,1,2,"Collyer, Miss. Marjorie ""Lottie""",female,8,0,2,C.A. 31921,26.25,,S -239,0,2,"Pengelly, Mr. Frederick William",male,19,0,0,28665,10.5,,S -240,0,2,"Hunt, Mr. George Henry",male,33,0,0,SCO/W 1585,12.275,,S -241,0,3,"Zabour, Miss. Thamine",female,,1,0,2665,14.4542,,C -242,1,3,"Murphy, Miss. Katherine ""Kate""",female,,1,0,367230,15.5,,Q -243,0,2,"Coleridge, Mr. Reginald Charles",male,29,0,0,W./C. 14263,10.5,,S -244,0,3,"Maenpaa, Mr. Matti Alexanteri",male,22,0,0,STON/O 2. 3101275,7.125,,S -245,0,3,"Attalah, Mr. Sleiman",male,30,0,0,2694,7.225,,C -246,0,1,"Minahan, Dr. William Edward",male,44,2,0,19928,90,C78,Q -247,0,3,"Lindahl, Miss. Agda Thorilda Viktoria",female,25,0,0,347071,7.775,,S -248,1,2,"Hamalainen, Mrs. William (Anna)",female,24,0,2,250649,14.5,,S -249,1,1,"Beckwith, Mr. Richard Leonard",male,37,1,1,11751,52.5542,D35,S -250,0,2,"Carter, Rev. Ernest Courtenay",male,54,1,0,244252,26,,S -251,0,3,"Reed, Mr. James George",male,,0,0,362316,7.25,,S -252,0,3,"Strom, Mrs. Wilhelm (Elna Matilda Persson)",female,29,1,1,347054,10.4625,G6,S -253,0,1,"Stead, Mr. William Thomas",male,62,0,0,113514,26.55,C87,S -254,0,3,"Lobb, Mr. William Arthur",male,30,1,0,A/5. 3336,16.1,,S -255,0,3,"Rosblom, Mrs. Viktor (Helena Wilhelmina)",female,41,0,2,370129,20.2125,,S -256,1,3,"Touma, Mrs. Darwis (Hanne Youssef Razi)",female,29,0,2,2650,15.2458,,C -257,1,1,"Thorne, Mrs. Gertrude Maybelle",female,,0,0,PC 17585,79.2,,C -258,1,1,"Cherry, Miss. Gladys",female,30,0,0,110152,86.5,B77,S -259,1,1,"Ward, Miss. Anna",female,35,0,0,PC 17755,512.3292,,C -260,1,2,"Parrish, Mrs. (Lutie Davis)",female,50,0,1,230433,26,,S -261,0,3,"Smith, Mr. Thomas",male,,0,0,384461,7.75,,Q -262,1,3,"Asplund, Master. Edvin Rojj Felix",male,3,4,2,347077,31.3875,,S -263,0,1,"Taussig, Mr. Emil",male,52,1,1,110413,79.65,E67,S -264,0,1,"Harrison, Mr. William",male,40,0,0,112059,0,B94,S -265,0,3,"Henry, Miss. Delia",female,,0,0,382649,7.75,,Q -266,0,2,"Reeves, Mr. David",male,36,0,0,C.A. 17248,10.5,,S -267,0,3,"Panula, Mr. Ernesti Arvid",male,16,4,1,3101295,39.6875,,S -268,1,3,"Persson, Mr. Ernst Ulrik",male,25,1,0,347083,7.775,,S -269,1,1,"Graham, Mrs. William Thompson (Edith Junkins)",female,58,0,1,PC 17582,153.4625,C125,S -270,1,1,"Bissette, Miss. Amelia",female,35,0,0,PC 17760,135.6333,C99,S -271,0,1,"Cairns, Mr. Alexander",male,,0,0,113798,31,,S -272,1,3,"Tornquist, Mr. William Henry",male,25,0,0,LINE,0,,S -273,1,2,"Mellinger, Mrs. (Elizabeth Anne Maidment)",female,41,0,1,250644,19.5,,S -274,0,1,"Natsch, Mr. Charles H",male,37,0,1,PC 17596,29.7,C118,C -275,1,3,"Healy, Miss. Hanora ""Nora""",female,,0,0,370375,7.75,,Q -276,1,1,"Andrews, Miss. Kornelia Theodosia",female,63,1,0,13502,77.9583,D7,S -277,0,3,"Lindblom, Miss. Augusta Charlotta",female,45,0,0,347073,7.75,,S -278,0,2,"Parkes, Mr. Francis ""Frank""",male,,0,0,239853,0,,S -279,0,3,"Rice, Master. Eric",male,7,4,1,382652,29.125,,Q -280,1,3,"Abbott, Mrs. Stanton (Rosa Hunt)",female,35,1,1,C.A. 2673,20.25,,S -281,0,3,"Duane, Mr. Frank",male,65,0,0,336439,7.75,,Q -282,0,3,"Olsson, Mr. Nils Johan Goransson",male,28,0,0,347464,7.8542,,S -283,0,3,"de Pelsmaeker, Mr. Alfons",male,16,0,0,345778,9.5,,S -284,1,3,"Dorking, Mr. Edward Arthur",male,19,0,0,A/5. 10482,8.05,,S -285,0,1,"Smith, Mr. Richard William",male,,0,0,113056,26,A19,S -286,0,3,"Stankovic, Mr. Ivan",male,33,0,0,349239,8.6625,,C -287,1,3,"de Mulder, Mr. Theodore",male,30,0,0,345774,9.5,,S -288,0,3,"Naidenoff, Mr. Penko",male,22,0,0,349206,7.8958,,S -289,1,2,"Hosono, Mr. Masabumi",male,42,0,0,237798,13,,S -290,1,3,"Connolly, Miss. Kate",female,22,0,0,370373,7.75,,Q -291,1,1,"Barber, Miss. Ellen ""Nellie""",female,26,0,0,19877,78.85,,S -292,1,1,"Bishop, Mrs. Dickinson H (Helen Walton)",female,19,1,0,11967,91.0792,B49,C -293,0,2,"Levy, Mr. Rene Jacques",male,36,0,0,SC/Paris 2163,12.875,D,C -294,0,3,"Haas, Miss. Aloisia",female,24,0,0,349236,8.85,,S -295,0,3,"Mineff, Mr. Ivan",male,24,0,0,349233,7.8958,,S -296,0,1,"Lewy, Mr. Ervin G",male,,0,0,PC 17612,27.7208,,C -297,0,3,"Hanna, Mr. Mansour",male,23.5,0,0,2693,7.2292,,C -298,0,1,"Allison, Miss. Helen Loraine",female,2,1,2,113781,151.55,C22 C26,S -299,1,1,"Saalfeld, Mr. Adolphe",male,,0,0,19988,30.5,C106,S -300,1,1,"Baxter, Mrs. James (Helene DeLaudeniere Chaput)",female,50,0,1,PC 17558,247.5208,B58 B60,C -301,1,3,"Kelly, Miss. Anna Katherine ""Annie Kate""",female,,0,0,9234,7.75,,Q -302,1,3,"McCoy, Mr. Bernard",male,,2,0,367226,23.25,,Q -303,0,3,"Johnson, Mr. William Cahoone Jr",male,19,0,0,LINE,0,,S -304,1,2,"Keane, Miss. Nora A",female,,0,0,226593,12.35,E101,Q -305,0,3,"Williams, Mr. Howard Hugh ""Harry""",male,,0,0,A/5 2466,8.05,,S -306,1,1,"Allison, Master. Hudson Trevor",male,0.92,1,2,113781,151.55,C22 C26,S -307,1,1,"Fleming, Miss. Margaret",female,,0,0,17421,110.8833,,C -308,1,1,"Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo)",female,17,1,0,PC 17758,108.9,C65,C -309,0,2,"Abelson, Mr. Samuel",male,30,1,0,P/PP 3381,24,,C -310,1,1,"Francatelli, Miss. Laura Mabel",female,30,0,0,PC 17485,56.9292,E36,C -311,1,1,"Hays, Miss. Margaret Bechstein",female,24,0,0,11767,83.1583,C54,C -312,1,1,"Ryerson, Miss. Emily Borie",female,18,2,2,PC 17608,262.375,B57 B59 B63 B66,C -313,0,2,"Lahtinen, Mrs. William (Anna Sylfven)",female,26,1,1,250651,26,,S -314,0,3,"Hendekovic, Mr. Ignjac",male,28,0,0,349243,7.8958,,S -315,0,2,"Hart, Mr. Benjamin",male,43,1,1,F.C.C. 13529,26.25,,S -316,1,3,"Nilsson, Miss. Helmina Josefina",female,26,0,0,347470,7.8542,,S -317,1,2,"Kantor, Mrs. Sinai (Miriam Sternin)",female,24,1,0,244367,26,,S -318,0,2,"Moraweck, Dr. Ernest",male,54,0,0,29011,14,,S -319,1,1,"Wick, Miss. Mary Natalie",female,31,0,2,36928,164.8667,C7,S -320,1,1,"Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone)",female,40,1,1,16966,134.5,E34,C -321,0,3,"Dennis, Mr. Samuel",male,22,0,0,A/5 21172,7.25,,S -322,0,3,"Danoff, Mr. Yoto",male,27,0,0,349219,7.8958,,S -323,1,2,"Slayter, Miss. Hilda Mary",female,30,0,0,234818,12.35,,Q -324,1,2,"Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh)",female,22,1,1,248738,29,,S -325,0,3,"Sage, Mr. George John Jr",male,,8,2,CA. 2343,69.55,,S -326,1,1,"Young, Miss. Marie Grice",female,36,0,0,PC 17760,135.6333,C32,C -327,0,3,"Nysveen, Mr. Johan Hansen",male,61,0,0,345364,6.2375,,S -328,1,2,"Ball, Mrs. (Ada E Hall)",female,36,0,0,28551,13,D,S -329,1,3,"Goldsmith, Mrs. Frank John (Emily Alice Brown)",female,31,1,1,363291,20.525,,S -330,1,1,"Hippach, Miss. Jean Gertrude",female,16,0,1,111361,57.9792,B18,C -331,1,3,"McCoy, Miss. Agnes",female,,2,0,367226,23.25,,Q -332,0,1,"Partner, Mr. Austen",male,45.5,0,0,113043,28.5,C124,S -333,0,1,"Graham, Mr. George Edward",male,38,0,1,PC 17582,153.4625,C91,S -334,0,3,"Vander Planke, Mr. Leo Edmondus",male,16,2,0,345764,18,,S -335,1,1,"Frauenthal, Mrs. Henry William (Clara Heinsheimer)",female,,1,0,PC 17611,133.65,,S -336,0,3,"Denkoff, Mr. Mitto",male,,0,0,349225,7.8958,,S -337,0,1,"Pears, Mr. Thomas Clinton",male,29,1,0,113776,66.6,C2,S -338,1,1,"Burns, Miss. Elizabeth Margaret",female,41,0,0,16966,134.5,E40,C -339,1,3,"Dahl, Mr. Karl Edwart",male,45,0,0,7598,8.05,,S -340,0,1,"Blackwell, Mr. Stephen Weart",male,45,0,0,113784,35.5,T,S -341,1,2,"Navratil, Master. Edmond Roger",male,2,1,1,230080,26,F2,S -342,1,1,"Fortune, Miss. Alice Elizabeth",female,24,3,2,19950,263,C23 C25 C27,S -343,0,2,"Collander, Mr. Erik Gustaf",male,28,0,0,248740,13,,S -344,0,2,"Sedgwick, Mr. Charles Frederick Waddington",male,25,0,0,244361,13,,S -345,0,2,"Fox, Mr. Stanley Hubert",male,36,0,0,229236,13,,S -346,1,2,"Brown, Miss. Amelia ""Mildred""",female,24,0,0,248733,13,F33,S -347,1,2,"Smith, Miss. Marion Elsie",female,40,0,0,31418,13,,S -348,1,3,"Davison, Mrs. Thomas Henry (Mary E Finck)",female,,1,0,386525,16.1,,S -349,1,3,"Coutts, Master. William Loch ""William""",male,3,1,1,C.A. 37671,15.9,,S -350,0,3,"Dimic, Mr. Jovan",male,42,0,0,315088,8.6625,,S -351,0,3,"Odahl, Mr. Nils Martin",male,23,0,0,7267,9.225,,S -352,0,1,"Williams-Lambert, Mr. Fletcher Fellows",male,,0,0,113510,35,C128,S -353,0,3,"Elias, Mr. Tannous",male,15,1,1,2695,7.2292,,C -354,0,3,"Arnold-Franchi, Mr. Josef",male,25,1,0,349237,17.8,,S -355,0,3,"Yousif, Mr. Wazli",male,,0,0,2647,7.225,,C -356,0,3,"Vanden Steen, Mr. Leo Peter",male,28,0,0,345783,9.5,,S -357,1,1,"Bowerman, Miss. Elsie Edith",female,22,0,1,113505,55,E33,S -358,0,2,"Funk, Miss. Annie Clemmer",female,38,0,0,237671,13,,S -359,1,3,"McGovern, Miss. Mary",female,,0,0,330931,7.8792,,Q -360,1,3,"Mockler, Miss. Helen Mary ""Ellie""",female,,0,0,330980,7.8792,,Q -361,0,3,"Skoog, Mr. Wilhelm",male,40,1,4,347088,27.9,,S -362,0,2,"del Carlo, Mr. Sebastiano",male,29,1,0,SC/PARIS 2167,27.7208,,C -363,0,3,"Barbara, Mrs. (Catherine David)",female,45,0,1,2691,14.4542,,C -364,0,3,"Asim, Mr. Adola",male,35,0,0,SOTON/O.Q. 3101310,7.05,,S -365,0,3,"O'Brien, Mr. Thomas",male,,1,0,370365,15.5,,Q -366,0,3,"Adahl, Mr. Mauritz Nils Martin",male,30,0,0,C 7076,7.25,,S -367,1,1,"Warren, Mrs. Frank Manley (Anna Sophia Atkinson)",female,60,1,0,110813,75.25,D37,C -368,1,3,"Moussa, Mrs. (Mantoura Boulos)",female,,0,0,2626,7.2292,,C -369,1,3,"Jermyn, Miss. Annie",female,,0,0,14313,7.75,,Q -370,1,1,"Aubart, Mme. Leontine Pauline",female,24,0,0,PC 17477,69.3,B35,C -371,1,1,"Harder, Mr. George Achilles",male,25,1,0,11765,55.4417,E50,C -372,0,3,"Wiklund, Mr. Jakob Alfred",male,18,1,0,3101267,6.4958,,S -373,0,3,"Beavan, Mr. William Thomas",male,19,0,0,323951,8.05,,S -374,0,1,"Ringhini, Mr. Sante",male,22,0,0,PC 17760,135.6333,,C -375,0,3,"Palsson, Miss. Stina Viola",female,3,3,1,349909,21.075,,S -376,1,1,"Meyer, Mrs. Edgar Joseph (Leila Saks)",female,,1,0,PC 17604,82.1708,,C -377,1,3,"Landergren, Miss. Aurora Adelia",female,22,0,0,C 7077,7.25,,S -378,0,1,"Widener, Mr. Harry Elkins",male,27,0,2,113503,211.5,C82,C -379,0,3,"Betros, Mr. Tannous",male,20,0,0,2648,4.0125,,C -380,0,3,"Gustafsson, Mr. Karl Gideon",male,19,0,0,347069,7.775,,S -381,1,1,"Bidois, Miss. Rosalie",female,42,0,0,PC 17757,227.525,,C -382,1,3,"Nakid, Miss. Maria (""Mary"")",female,1,0,2,2653,15.7417,,C -383,0,3,"Tikkanen, Mr. Juho",male,32,0,0,STON/O 2. 3101293,7.925,,S -384,1,1,"Holverson, Mrs. Alexander Oskar (Mary Aline Towner)",female,35,1,0,113789,52,,S -385,0,3,"Plotcharsky, Mr. Vasil",male,,0,0,349227,7.8958,,S -386,0,2,"Davies, Mr. Charles Henry",male,18,0,0,S.O.C. 14879,73.5,,S -387,0,3,"Goodwin, Master. Sidney Leonard",male,1,5,2,CA 2144,46.9,,S -388,1,2,"Buss, Miss. Kate",female,36,0,0,27849,13,,S -389,0,3,"Sadlier, Mr. Matthew",male,,0,0,367655,7.7292,,Q -390,1,2,"Lehmann, Miss. Bertha",female,17,0,0,SC 1748,12,,C -391,1,1,"Carter, Mr. William Ernest",male,36,1,2,113760,120,B96 B98,S -392,1,3,"Jansson, Mr. Carl Olof",male,21,0,0,350034,7.7958,,S -393,0,3,"Gustafsson, Mr. Johan Birger",male,28,2,0,3101277,7.925,,S -394,1,1,"Newell, Miss. Marjorie",female,23,1,0,35273,113.275,D36,C -395,1,3,"Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson)",female,24,0,2,PP 9549,16.7,G6,S -396,0,3,"Johansson, Mr. Erik",male,22,0,0,350052,7.7958,,S -397,0,3,"Olsson, Miss. Elina",female,31,0,0,350407,7.8542,,S -398,0,2,"McKane, Mr. Peter David",male,46,0,0,28403,26,,S -399,0,2,"Pain, Dr. Alfred",male,23,0,0,244278,10.5,,S -400,1,2,"Trout, Mrs. William H (Jessie L)",female,28,0,0,240929,12.65,,S -401,1,3,"Niskanen, Mr. Juha",male,39,0,0,STON/O 2. 3101289,7.925,,S -402,0,3,"Adams, Mr. John",male,26,0,0,341826,8.05,,S -403,0,3,"Jussila, Miss. Mari Aina",female,21,1,0,4137,9.825,,S -404,0,3,"Hakkarainen, Mr. Pekka Pietari",male,28,1,0,STON/O2. 3101279,15.85,,S -405,0,3,"Oreskovic, Miss. Marija",female,20,0,0,315096,8.6625,,S -406,0,2,"Gale, Mr. Shadrach",male,34,1,0,28664,21,,S -407,0,3,"Widegren, Mr. Carl/Charles Peter",male,51,0,0,347064,7.75,,S -408,1,2,"Richards, Master. William Rowe",male,3,1,1,29106,18.75,,S -409,0,3,"Birkeland, Mr. Hans Martin Monsen",male,21,0,0,312992,7.775,,S -410,0,3,"Lefebre, Miss. Ida",female,,3,1,4133,25.4667,,S -411,0,3,"Sdycoff, Mr. Todor",male,,0,0,349222,7.8958,,S -412,0,3,"Hart, Mr. Henry",male,,0,0,394140,6.8583,,Q -413,1,1,"Minahan, Miss. Daisy E",female,33,1,0,19928,90,C78,Q -414,0,2,"Cunningham, Mr. Alfred Fleming",male,,0,0,239853,0,,S -415,1,3,"Sundman, Mr. Johan Julian",male,44,0,0,STON/O 2. 3101269,7.925,,S -416,0,3,"Meek, Mrs. Thomas (Annie Louise Rowley)",female,,0,0,343095,8.05,,S -417,1,2,"Drew, Mrs. James Vivian (Lulu Thorne Christian)",female,34,1,1,28220,32.5,,S -418,1,2,"Silven, Miss. Lyyli Karoliina",female,18,0,2,250652,13,,S -419,0,2,"Matthews, Mr. William John",male,30,0,0,28228,13,,S -420,0,3,"Van Impe, Miss. Catharina",female,10,0,2,345773,24.15,,S -421,0,3,"Gheorgheff, Mr. Stanio",male,,0,0,349254,7.8958,,C -422,0,3,"Charters, Mr. David",male,21,0,0,A/5. 13032,7.7333,,Q -423,0,3,"Zimmerman, Mr. Leo",male,29,0,0,315082,7.875,,S -424,0,3,"Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren)",female,28,1,1,347080,14.4,,S -425,0,3,"Rosblom, Mr. Viktor Richard",male,18,1,1,370129,20.2125,,S -426,0,3,"Wiseman, Mr. Phillippe",male,,0,0,A/4. 34244,7.25,,S -427,1,2,"Clarke, Mrs. Charles V (Ada Maria Winfield)",female,28,1,0,2003,26,,S -428,1,2,"Phillips, Miss. Kate Florence (""Mrs Kate Louise Phillips Marshall"")",female,19,0,0,250655,26,,S -429,0,3,"Flynn, Mr. James",male,,0,0,364851,7.75,,Q -430,1,3,"Pickard, Mr. Berk (Berk Trembisky)",male,32,0,0,SOTON/O.Q. 392078,8.05,E10,S -431,1,1,"Bjornstrom-Steffansson, Mr. Mauritz Hakan",male,28,0,0,110564,26.55,C52,S -432,1,3,"Thorneycroft, Mrs. Percival (Florence Kate White)",female,,1,0,376564,16.1,,S -433,1,2,"Louch, Mrs. Charles Alexander (Alice Adelaide Slow)",female,42,1,0,SC/AH 3085,26,,S -434,0,3,"Kallio, Mr. Nikolai Erland",male,17,0,0,STON/O 2. 3101274,7.125,,S -435,0,1,"Silvey, Mr. William Baird",male,50,1,0,13507,55.9,E44,S -436,1,1,"Carter, Miss. Lucile Polk",female,14,1,2,113760,120,B96 B98,S -437,0,3,"Ford, Miss. Doolina Margaret ""Daisy""",female,21,2,2,W./C. 6608,34.375,,S -438,1,2,"Richards, Mrs. Sidney (Emily Hocking)",female,24,2,3,29106,18.75,,S -439,0,1,"Fortune, Mr. Mark",male,64,1,4,19950,263,C23 C25 C27,S -440,0,2,"Kvillner, Mr. Johan Henrik Johannesson",male,31,0,0,C.A. 18723,10.5,,S -441,1,2,"Hart, Mrs. Benjamin (Esther Ada Bloomfield)",female,45,1,1,F.C.C. 13529,26.25,,S -442,0,3,"Hampe, Mr. Leon",male,20,0,0,345769,9.5,,S -443,0,3,"Petterson, Mr. Johan Emil",male,25,1,0,347076,7.775,,S -444,1,2,"Reynaldo, Ms. Encarnacion",female,28,0,0,230434,13,,S -445,1,3,"Johannesen-Bratthammer, Mr. Bernt",male,,0,0,65306,8.1125,,S -446,1,1,"Dodge, Master. Washington",male,4,0,2,33638,81.8583,A34,S -447,1,2,"Mellinger, Miss. Madeleine Violet",female,13,0,1,250644,19.5,,S -448,1,1,"Seward, Mr. Frederic Kimber",male,34,0,0,113794,26.55,,S -449,1,3,"Baclini, Miss. Marie Catherine",female,5,2,1,2666,19.2583,,C -450,1,1,"Peuchen, Major. Arthur Godfrey",male,52,0,0,113786,30.5,C104,S -451,0,2,"West, Mr. Edwy Arthur",male,36,1,2,C.A. 34651,27.75,,S -452,0,3,"Hagland, Mr. Ingvald Olai Olsen",male,,1,0,65303,19.9667,,S -453,0,1,"Foreman, Mr. Benjamin Laventall",male,30,0,0,113051,27.75,C111,C -454,1,1,"Goldenberg, Mr. Samuel L",male,49,1,0,17453,89.1042,C92,C -455,0,3,"Peduzzi, Mr. Joseph",male,,0,0,A/5 2817,8.05,,S -456,1,3,"Jalsevac, Mr. Ivan",male,29,0,0,349240,7.8958,,C -457,0,1,"Millet, Mr. Francis Davis",male,65,0,0,13509,26.55,E38,S -458,1,1,"Kenyon, Mrs. Frederick R (Marion)",female,,1,0,17464,51.8625,D21,S -459,1,2,"Toomey, Miss. Ellen",female,50,0,0,F.C.C. 13531,10.5,,S -460,0,3,"O'Connor, Mr. Maurice",male,,0,0,371060,7.75,,Q -461,1,1,"Anderson, Mr. Harry",male,48,0,0,19952,26.55,E12,S -462,0,3,"Morley, Mr. William",male,34,0,0,364506,8.05,,S -463,0,1,"Gee, Mr. Arthur H",male,47,0,0,111320,38.5,E63,S -464,0,2,"Milling, Mr. Jacob Christian",male,48,0,0,234360,13,,S -465,0,3,"Maisner, Mr. Simon",male,,0,0,A/S 2816,8.05,,S -466,0,3,"Goncalves, Mr. Manuel Estanslas",male,38,0,0,SOTON/O.Q. 3101306,7.05,,S -467,0,2,"Campbell, Mr. William",male,,0,0,239853,0,,S -468,0,1,"Smart, Mr. John Montgomery",male,56,0,0,113792,26.55,,S -469,0,3,"Scanlan, Mr. James",male,,0,0,36209,7.725,,Q -470,1,3,"Baclini, Miss. Helene Barbara",female,0.75,2,1,2666,19.2583,,C -471,0,3,"Keefe, Mr. Arthur",male,,0,0,323592,7.25,,S -472,0,3,"Cacic, Mr. Luka",male,38,0,0,315089,8.6625,,S -473,1,2,"West, Mrs. Edwy Arthur (Ada Mary Worth)",female,33,1,2,C.A. 34651,27.75,,S -474,1,2,"Jerwan, Mrs. Amin S (Marie Marthe Thuillard)",female,23,0,0,SC/AH Basle 541,13.7917,D,C -475,0,3,"Strandberg, Miss. Ida Sofia",female,22,0,0,7553,9.8375,,S -476,0,1,"Clifford, Mr. George Quincy",male,,0,0,110465,52,A14,S -477,0,2,"Renouf, Mr. Peter Henry",male,34,1,0,31027,21,,S -478,0,3,"Braund, Mr. Lewis Richard",male,29,1,0,3460,7.0458,,S -479,0,3,"Karlsson, Mr. Nils August",male,22,0,0,350060,7.5208,,S -480,1,3,"Hirvonen, Miss. Hildur E",female,2,0,1,3101298,12.2875,,S -481,0,3,"Goodwin, Master. Harold Victor",male,9,5,2,CA 2144,46.9,,S -482,0,2,"Frost, Mr. Anthony Wood ""Archie""",male,,0,0,239854,0,,S -483,0,3,"Rouse, Mr. Richard Henry",male,50,0,0,A/5 3594,8.05,,S -484,1,3,"Turkula, Mrs. (Hedwig)",female,63,0,0,4134,9.5875,,S -485,1,1,"Bishop, Mr. Dickinson H",male,25,1,0,11967,91.0792,B49,C -486,0,3,"Lefebre, Miss. Jeannie",female,,3,1,4133,25.4667,,S -487,1,1,"Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby)",female,35,1,0,19943,90,C93,S -488,0,1,"Kent, Mr. Edward Austin",male,58,0,0,11771,29.7,B37,C -489,0,3,"Somerton, Mr. Francis William",male,30,0,0,A.5. 18509,8.05,,S -490,1,3,"Coutts, Master. Eden Leslie ""Neville""",male,9,1,1,C.A. 37671,15.9,,S -491,0,3,"Hagland, Mr. Konrad Mathias Reiersen",male,,1,0,65304,19.9667,,S -492,0,3,"Windelov, Mr. Einar",male,21,0,0,SOTON/OQ 3101317,7.25,,S -493,0,1,"Molson, Mr. Harry Markland",male,55,0,0,113787,30.5,C30,S -494,0,1,"Artagaveytia, Mr. Ramon",male,71,0,0,PC 17609,49.5042,,C -495,0,3,"Stanley, Mr. Edward Roland",male,21,0,0,A/4 45380,8.05,,S -496,0,3,"Yousseff, Mr. Gerious",male,,0,0,2627,14.4583,,C -497,1,1,"Eustis, Miss. Elizabeth Mussey",female,54,1,0,36947,78.2667,D20,C -498,0,3,"Shellard, Mr. Frederick William",male,,0,0,C.A. 6212,15.1,,S -499,0,1,"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)",female,25,1,2,113781,151.55,C22 C26,S -500,0,3,"Svensson, Mr. Olof",male,24,0,0,350035,7.7958,,S -501,0,3,"Calic, Mr. Petar",male,17,0,0,315086,8.6625,,S -502,0,3,"Canavan, Miss. Mary",female,21,0,0,364846,7.75,,Q -503,0,3,"O'Sullivan, Miss. Bridget Mary",female,,0,0,330909,7.6292,,Q -504,0,3,"Laitinen, Miss. Kristina Sofia",female,37,0,0,4135,9.5875,,S -505,1,1,"Maioni, Miss. Roberta",female,16,0,0,110152,86.5,B79,S -506,0,1,"Penasco y Castellana, Mr. Victor de Satode",male,18,1,0,PC 17758,108.9,C65,C -507,1,2,"Quick, Mrs. Frederick Charles (Jane Richards)",female,33,0,2,26360,26,,S -508,1,1,"Bradley, Mr. George (""George Arthur Brayton"")",male,,0,0,111427,26.55,,S -509,0,3,"Olsen, Mr. Henry Margido",male,28,0,0,C 4001,22.525,,S -510,1,3,"Lang, Mr. Fang",male,26,0,0,1601,56.4958,,S -511,1,3,"Daly, Mr. Eugene Patrick",male,29,0,0,382651,7.75,,Q -512,0,3,"Webber, Mr. James",male,,0,0,SOTON/OQ 3101316,8.05,,S -513,1,1,"McGough, Mr. James Robert",male,36,0,0,PC 17473,26.2875,E25,S -514,1,1,"Rothschild, Mrs. Martin (Elizabeth L. Barrett)",female,54,1,0,PC 17603,59.4,,C -515,0,3,"Coleff, Mr. Satio",male,24,0,0,349209,7.4958,,S -516,0,1,"Walker, Mr. William Anderson",male,47,0,0,36967,34.0208,D46,S -517,1,2,"Lemore, Mrs. (Amelia Milley)",female,34,0,0,C.A. 34260,10.5,F33,S -518,0,3,"Ryan, Mr. Patrick",male,,0,0,371110,24.15,,Q -519,1,2,"Angle, Mrs. William A (Florence ""Mary"" Agnes Hughes)",female,36,1,0,226875,26,,S -520,0,3,"Pavlovic, Mr. Stefo",male,32,0,0,349242,7.8958,,S -521,1,1,"Perreault, Miss. Anne",female,30,0,0,12749,93.5,B73,S -522,0,3,"Vovk, Mr. Janko",male,22,0,0,349252,7.8958,,S -523,0,3,"Lahoud, Mr. Sarkis",male,,0,0,2624,7.225,,C -524,1,1,"Hippach, Mrs. Louis Albert (Ida Sophia Fischer)",female,44,0,1,111361,57.9792,B18,C -525,0,3,"Kassem, Mr. Fared",male,,0,0,2700,7.2292,,C -526,0,3,"Farrell, Mr. James",male,40.5,0,0,367232,7.75,,Q -527,1,2,"Ridsdale, Miss. Lucy",female,50,0,0,W./C. 14258,10.5,,S -528,0,1,"Farthing, Mr. John",male,,0,0,PC 17483,221.7792,C95,S -529,0,3,"Salonen, Mr. Johan Werner",male,39,0,0,3101296,7.925,,S -530,0,2,"Hocking, Mr. Richard George",male,23,2,1,29104,11.5,,S -531,1,2,"Quick, Miss. Phyllis May",female,2,1,1,26360,26,,S -532,0,3,"Toufik, Mr. Nakli",male,,0,0,2641,7.2292,,C -533,0,3,"Elias, Mr. Joseph Jr",male,17,1,1,2690,7.2292,,C -534,1,3,"Peter, Mrs. Catherine (Catherine Rizk)",female,,0,2,2668,22.3583,,C -535,0,3,"Cacic, Miss. Marija",female,30,0,0,315084,8.6625,,S -536,1,2,"Hart, Miss. Eva Miriam",female,7,0,2,F.C.C. 13529,26.25,,S -537,0,1,"Butt, Major. Archibald Willingham",male,45,0,0,113050,26.55,B38,S -538,1,1,"LeRoy, Miss. Bertha",female,30,0,0,PC 17761,106.425,,C -539,0,3,"Risien, Mr. Samuel Beard",male,,0,0,364498,14.5,,S -540,1,1,"Frolicher, Miss. Hedwig Margaritha",female,22,0,2,13568,49.5,B39,C -541,1,1,"Crosby, Miss. Harriet R",female,36,0,2,WE/P 5735,71,B22,S -542,0,3,"Andersson, Miss. Ingeborg Constanzia",female,9,4,2,347082,31.275,,S -543,0,3,"Andersson, Miss. Sigrid Elisabeth",female,11,4,2,347082,31.275,,S -544,1,2,"Beane, Mr. Edward",male,32,1,0,2908,26,,S -545,0,1,"Douglas, Mr. Walter Donald",male,50,1,0,PC 17761,106.425,C86,C -546,0,1,"Nicholson, Mr. Arthur Ernest",male,64,0,0,693,26,,S -547,1,2,"Beane, Mrs. Edward (Ethel Clarke)",female,19,1,0,2908,26,,S -548,1,2,"Padro y Manent, Mr. Julian",male,,0,0,SC/PARIS 2146,13.8625,,C -549,0,3,"Goldsmith, Mr. Frank John",male,33,1,1,363291,20.525,,S -550,1,2,"Davies, Master. John Morgan Jr",male,8,1,1,C.A. 33112,36.75,,S -551,1,1,"Thayer, Mr. John Borland Jr",male,17,0,2,17421,110.8833,C70,C -552,0,2,"Sharp, Mr. Percival James R",male,27,0,0,244358,26,,S -553,0,3,"O'Brien, Mr. Timothy",male,,0,0,330979,7.8292,,Q -554,1,3,"Leeni, Mr. Fahim (""Philip Zenni"")",male,22,0,0,2620,7.225,,C -555,1,3,"Ohman, Miss. Velin",female,22,0,0,347085,7.775,,S -556,0,1,"Wright, Mr. George",male,62,0,0,113807,26.55,,S -557,1,1,"Duff Gordon, Lady. (Lucille Christiana Sutherland) (""Mrs Morgan"")",female,48,1,0,11755,39.6,A16,C -558,0,1,"Robbins, Mr. Victor",male,,0,0,PC 17757,227.525,,C -559,1,1,"Taussig, Mrs. Emil (Tillie Mandelbaum)",female,39,1,1,110413,79.65,E67,S -560,1,3,"de Messemaeker, Mrs. Guillaume Joseph (Emma)",female,36,1,0,345572,17.4,,S -561,0,3,"Morrow, Mr. Thomas Rowan",male,,0,0,372622,7.75,,Q -562,0,3,"Sivic, Mr. Husein",male,40,0,0,349251,7.8958,,S -563,0,2,"Norman, Mr. Robert Douglas",male,28,0,0,218629,13.5,,S -564,0,3,"Simmons, Mr. John",male,,0,0,SOTON/OQ 392082,8.05,,S -565,0,3,"Meanwell, Miss. (Marion Ogden)",female,,0,0,SOTON/O.Q. 392087,8.05,,S -566,0,3,"Davies, Mr. Alfred J",male,24,2,0,A/4 48871,24.15,,S -567,0,3,"Stoytcheff, Mr. Ilia",male,19,0,0,349205,7.8958,,S -568,0,3,"Palsson, Mrs. Nils (Alma Cornelia Berglund)",female,29,0,4,349909,21.075,,S -569,0,3,"Doharr, Mr. Tannous",male,,0,0,2686,7.2292,,C -570,1,3,"Jonsson, Mr. Carl",male,32,0,0,350417,7.8542,,S -571,1,2,"Harris, Mr. George",male,62,0,0,S.W./PP 752,10.5,,S -572,1,1,"Appleton, Mrs. Edward Dale (Charlotte Lamson)",female,53,2,0,11769,51.4792,C101,S -573,1,1,"Flynn, Mr. John Irwin (""Irving"")",male,36,0,0,PC 17474,26.3875,E25,S -574,1,3,"Kelly, Miss. Mary",female,,0,0,14312,7.75,,Q -575,0,3,"Rush, Mr. Alfred George John",male,16,0,0,A/4. 20589,8.05,,S -576,0,3,"Patchett, Mr. George",male,19,0,0,358585,14.5,,S -577,1,2,"Garside, Miss. Ethel",female,34,0,0,243880,13,,S -578,1,1,"Silvey, Mrs. William Baird (Alice Munger)",female,39,1,0,13507,55.9,E44,S -579,0,3,"Caram, Mrs. Joseph (Maria Elias)",female,,1,0,2689,14.4583,,C -580,1,3,"Jussila, Mr. Eiriik",male,32,0,0,STON/O 2. 3101286,7.925,,S -581,1,2,"Christy, Miss. Julie Rachel",female,25,1,1,237789,30,,S -582,1,1,"Thayer, Mrs. John Borland (Marian Longstreth Morris)",female,39,1,1,17421,110.8833,C68,C -583,0,2,"Downton, Mr. William James",male,54,0,0,28403,26,,S -584,0,1,"Ross, Mr. John Hugo",male,36,0,0,13049,40.125,A10,C -585,0,3,"Paulner, Mr. Uscher",male,,0,0,3411,8.7125,,C -586,1,1,"Taussig, Miss. Ruth",female,18,0,2,110413,79.65,E68,S -587,0,2,"Jarvis, Mr. John Denzil",male,47,0,0,237565,15,,S -588,1,1,"Frolicher-Stehli, Mr. Maxmillian",male,60,1,1,13567,79.2,B41,C -589,0,3,"Gilinski, Mr. Eliezer",male,22,0,0,14973,8.05,,S -590,0,3,"Murdlin, Mr. Joseph",male,,0,0,A./5. 3235,8.05,,S -591,0,3,"Rintamaki, Mr. Matti",male,35,0,0,STON/O 2. 3101273,7.125,,S -592,1,1,"Stephenson, Mrs. Walter Bertram (Martha Eustis)",female,52,1,0,36947,78.2667,D20,C -593,0,3,"Elsbury, Mr. William James",male,47,0,0,A/5 3902,7.25,,S -594,0,3,"Bourke, Miss. Mary",female,,0,2,364848,7.75,,Q -595,0,2,"Chapman, Mr. John Henry",male,37,1,0,SC/AH 29037,26,,S -596,0,3,"Van Impe, Mr. Jean Baptiste",male,36,1,1,345773,24.15,,S -597,1,2,"Leitch, Miss. Jessie Wills",female,,0,0,248727,33,,S -598,0,3,"Johnson, Mr. Alfred",male,49,0,0,LINE,0,,S -599,0,3,"Boulos, Mr. Hanna",male,,0,0,2664,7.225,,C -600,1,1,"Duff Gordon, Sir. Cosmo Edmund (""Mr Morgan"")",male,49,1,0,PC 17485,56.9292,A20,C -601,1,2,"Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy)",female,24,2,1,243847,27,,S -602,0,3,"Slabenoff, Mr. Petco",male,,0,0,349214,7.8958,,S -603,0,1,"Harrington, Mr. Charles H",male,,0,0,113796,42.4,,S -604,0,3,"Torber, Mr. Ernst William",male,44,0,0,364511,8.05,,S -605,1,1,"Homer, Mr. Harry (""Mr E Haven"")",male,35,0,0,111426,26.55,,C -606,0,3,"Lindell, Mr. Edvard Bengtsson",male,36,1,0,349910,15.55,,S -607,0,3,"Karaic, Mr. Milan",male,30,0,0,349246,7.8958,,S -608,1,1,"Daniel, Mr. Robert Williams",male,27,0,0,113804,30.5,,S -609,1,2,"Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue)",female,22,1,2,SC/Paris 2123,41.5792,,C -610,1,1,"Shutes, Miss. Elizabeth W",female,40,0,0,PC 17582,153.4625,C125,S -611,0,3,"Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren)",female,39,1,5,347082,31.275,,S -612,0,3,"Jardin, Mr. Jose Neto",male,,0,0,SOTON/O.Q. 3101305,7.05,,S -613,1,3,"Murphy, Miss. Margaret Jane",female,,1,0,367230,15.5,,Q -614,0,3,"Horgan, Mr. John",male,,0,0,370377,7.75,,Q -615,0,3,"Brocklebank, Mr. William Alfred",male,35,0,0,364512,8.05,,S -616,1,2,"Herman, Miss. Alice",female,24,1,2,220845,65,,S -617,0,3,"Danbom, Mr. Ernst Gilbert",male,34,1,1,347080,14.4,,S -618,0,3,"Lobb, Mrs. William Arthur (Cordelia K Stanlick)",female,26,1,0,A/5. 3336,16.1,,S -619,1,2,"Becker, Miss. Marion Louise",female,4,2,1,230136,39,F4,S -620,0,2,"Gavey, Mr. Lawrence",male,26,0,0,31028,10.5,,S -621,0,3,"Yasbeck, Mr. Antoni",male,27,1,0,2659,14.4542,,C -622,1,1,"Kimball, Mr. Edwin Nelson Jr",male,42,1,0,11753,52.5542,D19,S -623,1,3,"Nakid, Mr. Sahid",male,20,1,1,2653,15.7417,,C -624,0,3,"Hansen, Mr. Henry Damsgaard",male,21,0,0,350029,7.8542,,S -625,0,3,"Bowen, Mr. David John ""Dai""",male,21,0,0,54636,16.1,,S -626,0,1,"Sutton, Mr. Frederick",male,61,0,0,36963,32.3208,D50,S -627,0,2,"Kirkland, Rev. Charles Leonard",male,57,0,0,219533,12.35,,Q -628,1,1,"Longley, Miss. Gretchen Fiske",female,21,0,0,13502,77.9583,D9,S -629,0,3,"Bostandyeff, Mr. Guentcho",male,26,0,0,349224,7.8958,,S -630,0,3,"O'Connell, Mr. Patrick D",male,,0,0,334912,7.7333,,Q -631,1,1,"Barkworth, Mr. Algernon Henry Wilson",male,80,0,0,27042,30,A23,S -632,0,3,"Lundahl, Mr. Johan Svensson",male,51,0,0,347743,7.0542,,S -633,1,1,"Stahelin-Maeglin, Dr. Max",male,32,0,0,13214,30.5,B50,C -634,0,1,"Parr, Mr. William Henry Marsh",male,,0,0,112052,0,,S -635,0,3,"Skoog, Miss. Mabel",female,9,3,2,347088,27.9,,S -636,1,2,"Davis, Miss. Mary",female,28,0,0,237668,13,,S -637,0,3,"Leinonen, Mr. Antti Gustaf",male,32,0,0,STON/O 2. 3101292,7.925,,S -638,0,2,"Collyer, Mr. Harvey",male,31,1,1,C.A. 31921,26.25,,S -639,0,3,"Panula, Mrs. Juha (Maria Emilia Ojala)",female,41,0,5,3101295,39.6875,,S -640,0,3,"Thorneycroft, Mr. Percival",male,,1,0,376564,16.1,,S -641,0,3,"Jensen, Mr. Hans Peder",male,20,0,0,350050,7.8542,,S -642,1,1,"Sagesser, Mlle. Emma",female,24,0,0,PC 17477,69.3,B35,C -643,0,3,"Skoog, Miss. Margit Elizabeth",female,2,3,2,347088,27.9,,S -644,1,3,"Foo, Mr. Choong",male,,0,0,1601,56.4958,,S -645,1,3,"Baclini, Miss. Eugenie",female,0.75,2,1,2666,19.2583,,C -646,1,1,"Harper, Mr. Henry Sleeper",male,48,1,0,PC 17572,76.7292,D33,C -647,0,3,"Cor, Mr. Liudevit",male,19,0,0,349231,7.8958,,S -648,1,1,"Simonius-Blumer, Col. Oberst Alfons",male,56,0,0,13213,35.5,A26,C -649,0,3,"Willey, Mr. Edward",male,,0,0,S.O./P.P. 751,7.55,,S -650,1,3,"Stanley, Miss. Amy Zillah Elsie",female,23,0,0,CA. 2314,7.55,,S -651,0,3,"Mitkoff, Mr. Mito",male,,0,0,349221,7.8958,,S -652,1,2,"Doling, Miss. Elsie",female,18,0,1,231919,23,,S -653,0,3,"Kalvik, Mr. Johannes Halvorsen",male,21,0,0,8475,8.4333,,S -654,1,3,"O'Leary, Miss. Hanora ""Norah""",female,,0,0,330919,7.8292,,Q -655,0,3,"Hegarty, Miss. Hanora ""Nora""",female,18,0,0,365226,6.75,,Q -656,0,2,"Hickman, Mr. Leonard Mark",male,24,2,0,S.O.C. 14879,73.5,,S -657,0,3,"Radeff, Mr. Alexander",male,,0,0,349223,7.8958,,S -658,0,3,"Bourke, Mrs. John (Catherine)",female,32,1,1,364849,15.5,,Q -659,0,2,"Eitemiller, Mr. George Floyd",male,23,0,0,29751,13,,S -660,0,1,"Newell, Mr. Arthur Webster",male,58,0,2,35273,113.275,D48,C -661,1,1,"Frauenthal, Dr. Henry William",male,50,2,0,PC 17611,133.65,,S -662,0,3,"Badt, Mr. Mohamed",male,40,0,0,2623,7.225,,C -663,0,1,"Colley, Mr. Edward Pomeroy",male,47,0,0,5727,25.5875,E58,S -664,0,3,"Coleff, Mr. Peju",male,36,0,0,349210,7.4958,,S -665,1,3,"Lindqvist, Mr. Eino William",male,20,1,0,STON/O 2. 3101285,7.925,,S -666,0,2,"Hickman, Mr. Lewis",male,32,2,0,S.O.C. 14879,73.5,,S -667,0,2,"Butler, Mr. Reginald Fenton",male,25,0,0,234686,13,,S -668,0,3,"Rommetvedt, Mr. Knud Paust",male,,0,0,312993,7.775,,S -669,0,3,"Cook, Mr. Jacob",male,43,0,0,A/5 3536,8.05,,S -670,1,1,"Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright)",female,,1,0,19996,52,C126,S -671,1,2,"Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford)",female,40,1,1,29750,39,,S -672,0,1,"Davidson, Mr. Thornton",male,31,1,0,F.C. 12750,52,B71,S -673,0,2,"Mitchell, Mr. Henry Michael",male,70,0,0,C.A. 24580,10.5,,S -674,1,2,"Wilhelms, Mr. Charles",male,31,0,0,244270,13,,S -675,0,2,"Watson, Mr. Ennis Hastings",male,,0,0,239856,0,,S -676,0,3,"Edvardsson, Mr. Gustaf Hjalmar",male,18,0,0,349912,7.775,,S -677,0,3,"Sawyer, Mr. Frederick Charles",male,24.5,0,0,342826,8.05,,S -678,1,3,"Turja, Miss. Anna Sofia",female,18,0,0,4138,9.8417,,S -679,0,3,"Goodwin, Mrs. Frederick (Augusta Tyler)",female,43,1,6,CA 2144,46.9,,S -680,1,1,"Cardeza, Mr. Thomas Drake Martinez",male,36,0,1,PC 17755,512.3292,B51 B53 B55,C -681,0,3,"Peters, Miss. Katie",female,,0,0,330935,8.1375,,Q -682,1,1,"Hassab, Mr. Hammad",male,27,0,0,PC 17572,76.7292,D49,C -683,0,3,"Olsvigen, Mr. Thor Anderson",male,20,0,0,6563,9.225,,S -684,0,3,"Goodwin, Mr. Charles Edward",male,14,5,2,CA 2144,46.9,,S -685,0,2,"Brown, Mr. Thomas William Solomon",male,60,1,1,29750,39,,S -686,0,2,"Laroche, Mr. Joseph Philippe Lemercier",male,25,1,2,SC/Paris 2123,41.5792,,C -687,0,3,"Panula, Mr. Jaako Arnold",male,14,4,1,3101295,39.6875,,S -688,0,3,"Dakic, Mr. Branko",male,19,0,0,349228,10.1708,,S -689,0,3,"Fischer, Mr. Eberhard Thelander",male,18,0,0,350036,7.7958,,S -690,1,1,"Madill, Miss. Georgette Alexandra",female,15,0,1,24160,211.3375,B5,S -691,1,1,"Dick, Mr. Albert Adrian",male,31,1,0,17474,57,B20,S -692,1,3,"Karun, Miss. Manca",female,4,0,1,349256,13.4167,,C -693,1,3,"Lam, Mr. Ali",male,,0,0,1601,56.4958,,S -694,0,3,"Saad, Mr. Khalil",male,25,0,0,2672,7.225,,C -695,0,1,"Weir, Col. John",male,60,0,0,113800,26.55,,S -696,0,2,"Chapman, Mr. Charles Henry",male,52,0,0,248731,13.5,,S -697,0,3,"Kelly, Mr. James",male,44,0,0,363592,8.05,,S -698,1,3,"Mullens, Miss. Katherine ""Katie""",female,,0,0,35852,7.7333,,Q -699,0,1,"Thayer, Mr. John Borland",male,49,1,1,17421,110.8833,C68,C -700,0,3,"Humblen, Mr. Adolf Mathias Nicolai Olsen",male,42,0,0,348121,7.65,F G63,S -701,1,1,"Astor, Mrs. John Jacob (Madeleine Talmadge Force)",female,18,1,0,PC 17757,227.525,C62 C64,C -702,1,1,"Silverthorne, Mr. Spencer Victor",male,35,0,0,PC 17475,26.2875,E24,S -703,0,3,"Barbara, Miss. Saiide",female,18,0,1,2691,14.4542,,C -704,0,3,"Gallagher, Mr. Martin",male,25,0,0,36864,7.7417,,Q -705,0,3,"Hansen, Mr. Henrik Juul",male,26,1,0,350025,7.8542,,S -706,0,2,"Morley, Mr. Henry Samuel (""Mr Henry Marshall"")",male,39,0,0,250655,26,,S -707,1,2,"Kelly, Mrs. Florence ""Fannie""",female,45,0,0,223596,13.5,,S -708,1,1,"Calderhead, Mr. Edward Pennington",male,42,0,0,PC 17476,26.2875,E24,S -709,1,1,"Cleaver, Miss. Alice",female,22,0,0,113781,151.55,,S -710,1,3,"Moubarek, Master. Halim Gonios (""William George"")",male,,1,1,2661,15.2458,,C -711,1,1,"Mayne, Mlle. Berthe Antonine (""Mrs de Villiers"")",female,24,0,0,PC 17482,49.5042,C90,C -712,0,1,"Klaber, Mr. Herman",male,,0,0,113028,26.55,C124,S -713,1,1,"Taylor, Mr. Elmer Zebley",male,48,1,0,19996,52,C126,S -714,0,3,"Larsson, Mr. August Viktor",male,29,0,0,7545,9.4833,,S -715,0,2,"Greenberg, Mr. Samuel",male,52,0,0,250647,13,,S -716,0,3,"Soholt, Mr. Peter Andreas Lauritz Andersen",male,19,0,0,348124,7.65,F G73,S -717,1,1,"Endres, Miss. Caroline Louise",female,38,0,0,PC 17757,227.525,C45,C -718,1,2,"Troutt, Miss. Edwina Celia ""Winnie""",female,27,0,0,34218,10.5,E101,S -719,0,3,"McEvoy, Mr. Michael",male,,0,0,36568,15.5,,Q -720,0,3,"Johnson, Mr. Malkolm Joackim",male,33,0,0,347062,7.775,,S -721,1,2,"Harper, Miss. Annie Jessie ""Nina""",female,6,0,1,248727,33,,S -722,0,3,"Jensen, Mr. Svend Lauritz",male,17,1,0,350048,7.0542,,S -723,0,2,"Gillespie, Mr. William Henry",male,34,0,0,12233,13,,S -724,0,2,"Hodges, Mr. Henry Price",male,50,0,0,250643,13,,S -725,1,1,"Chambers, Mr. Norman Campbell",male,27,1,0,113806,53.1,E8,S -726,0,3,"Oreskovic, Mr. Luka",male,20,0,0,315094,8.6625,,S -727,1,2,"Renouf, Mrs. Peter Henry (Lillian Jefferys)",female,30,3,0,31027,21,,S -728,1,3,"Mannion, Miss. Margareth",female,,0,0,36866,7.7375,,Q -729,0,2,"Bryhl, Mr. Kurt Arnold Gottfrid",male,25,1,0,236853,26,,S -730,0,3,"Ilmakangas, Miss. Pieta Sofia",female,25,1,0,STON/O2. 3101271,7.925,,S -731,1,1,"Allen, Miss. Elisabeth Walton",female,29,0,0,24160,211.3375,B5,S -732,0,3,"Hassan, Mr. Houssein G N",male,11,0,0,2699,18.7875,,C -733,0,2,"Knight, Mr. Robert J",male,,0,0,239855,0,,S -734,0,2,"Berriman, Mr. William John",male,23,0,0,28425,13,,S -735,0,2,"Troupiansky, Mr. Moses Aaron",male,23,0,0,233639,13,,S -736,0,3,"Williams, Mr. Leslie",male,28.5,0,0,54636,16.1,,S -737,0,3,"Ford, Mrs. Edward (Margaret Ann Watson)",female,48,1,3,W./C. 6608,34.375,,S -738,1,1,"Lesurer, Mr. Gustave J",male,35,0,0,PC 17755,512.3292,B101,C -739,0,3,"Ivanoff, Mr. Kanio",male,,0,0,349201,7.8958,,S -740,0,3,"Nankoff, Mr. Minko",male,,0,0,349218,7.8958,,S -741,1,1,"Hawksford, Mr. Walter James",male,,0,0,16988,30,D45,S -742,0,1,"Cavendish, Mr. Tyrell William",male,36,1,0,19877,78.85,C46,S -743,1,1,"Ryerson, Miss. Susan Parker ""Suzette""",female,21,2,2,PC 17608,262.375,B57 B59 B63 B66,C -744,0,3,"McNamee, Mr. Neal",male,24,1,0,376566,16.1,,S -745,1,3,"Stranden, Mr. Juho",male,31,0,0,STON/O 2. 3101288,7.925,,S -746,0,1,"Crosby, Capt. Edward Gifford",male,70,1,1,WE/P 5735,71,B22,S -747,0,3,"Abbott, Mr. Rossmore Edward",male,16,1,1,C.A. 2673,20.25,,S -748,1,2,"Sinkkonen, Miss. Anna",female,30,0,0,250648,13,,S -749,0,1,"Marvin, Mr. Daniel Warner",male,19,1,0,113773,53.1,D30,S -750,0,3,"Connaghton, Mr. Michael",male,31,0,0,335097,7.75,,Q -751,1,2,"Wells, Miss. Joan",female,4,1,1,29103,23,,S -752,1,3,"Moor, Master. Meier",male,6,0,1,392096,12.475,E121,S -753,0,3,"Vande Velde, Mr. Johannes Joseph",male,33,0,0,345780,9.5,,S -754,0,3,"Jonkoff, Mr. Lalio",male,23,0,0,349204,7.8958,,S -755,1,2,"Herman, Mrs. Samuel (Jane Laver)",female,48,1,2,220845,65,,S -756,1,2,"Hamalainen, Master. Viljo",male,0.67,1,1,250649,14.5,,S -757,0,3,"Carlsson, Mr. August Sigfrid",male,28,0,0,350042,7.7958,,S -758,0,2,"Bailey, Mr. Percy Andrew",male,18,0,0,29108,11.5,,S -759,0,3,"Theobald, Mr. Thomas Leonard",male,34,0,0,363294,8.05,,S -760,1,1,"Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards)",female,33,0,0,110152,86.5,B77,S -761,0,3,"Garfirth, Mr. John",male,,0,0,358585,14.5,,S -762,0,3,"Nirva, Mr. Iisakki Antino Aijo",male,41,0,0,SOTON/O2 3101272,7.125,,S -763,1,3,"Barah, Mr. Hanna Assi",male,20,0,0,2663,7.2292,,C -764,1,1,"Carter, Mrs. William Ernest (Lucile Polk)",female,36,1,2,113760,120,B96 B98,S -765,0,3,"Eklund, Mr. Hans Linus",male,16,0,0,347074,7.775,,S -766,1,1,"Hogeboom, Mrs. John C (Anna Andrews)",female,51,1,0,13502,77.9583,D11,S -767,0,1,"Brewe, Dr. Arthur Jackson",male,,0,0,112379,39.6,,C -768,0,3,"Mangan, Miss. Mary",female,30.5,0,0,364850,7.75,,Q -769,0,3,"Moran, Mr. Daniel J",male,,1,0,371110,24.15,,Q -770,0,3,"Gronnestad, Mr. Daniel Danielsen",male,32,0,0,8471,8.3625,,S -771,0,3,"Lievens, Mr. Rene Aime",male,24,0,0,345781,9.5,,S -772,0,3,"Jensen, Mr. Niels Peder",male,48,0,0,350047,7.8542,,S -773,0,2,"Mack, Mrs. (Mary)",female,57,0,0,S.O./P.P. 3,10.5,E77,S -774,0,3,"Elias, Mr. Dibo",male,,0,0,2674,7.225,,C -775,1,2,"Hocking, Mrs. Elizabeth (Eliza Needs)",female,54,1,3,29105,23,,S -776,0,3,"Myhrman, Mr. Pehr Fabian Oliver Malkolm",male,18,0,0,347078,7.75,,S -777,0,3,"Tobin, Mr. Roger",male,,0,0,383121,7.75,F38,Q -778,1,3,"Emanuel, Miss. Virginia Ethel",female,5,0,0,364516,12.475,,S -779,0,3,"Kilgannon, Mr. Thomas J",male,,0,0,36865,7.7375,,Q -780,1,1,"Robert, Mrs. Edward Scott (Elisabeth Walton McMillan)",female,43,0,1,24160,211.3375,B3,S -781,1,3,"Ayoub, Miss. Banoura",female,13,0,0,2687,7.2292,,C -782,1,1,"Dick, Mrs. Albert Adrian (Vera Gillespie)",female,17,1,0,17474,57,B20,S -783,0,1,"Long, Mr. Milton Clyde",male,29,0,0,113501,30,D6,S -784,0,3,"Johnston, Mr. Andrew G",male,,1,2,W./C. 6607,23.45,,S -785,0,3,"Ali, Mr. William",male,25,0,0,SOTON/O.Q. 3101312,7.05,,S -786,0,3,"Harmer, Mr. Abraham (David Lishin)",male,25,0,0,374887,7.25,,S -787,1,3,"Sjoblom, Miss. Anna Sofia",female,18,0,0,3101265,7.4958,,S -788,0,3,"Rice, Master. George Hugh",male,8,4,1,382652,29.125,,Q -789,1,3,"Dean, Master. Bertram Vere",male,1,1,2,C.A. 2315,20.575,,S -790,0,1,"Guggenheim, Mr. Benjamin",male,46,0,0,PC 17593,79.2,B82 B84,C -791,0,3,"Keane, Mr. Andrew ""Andy""",male,,0,0,12460,7.75,,Q -792,0,2,"Gaskell, Mr. Alfred",male,16,0,0,239865,26,,S -793,0,3,"Sage, Miss. Stella Anna",female,,8,2,CA. 2343,69.55,,S -794,0,1,"Hoyt, Mr. William Fisher",male,,0,0,PC 17600,30.6958,,C -795,0,3,"Dantcheff, Mr. Ristiu",male,25,0,0,349203,7.8958,,S -796,0,2,"Otter, Mr. Richard",male,39,0,0,28213,13,,S -797,1,1,"Leader, Dr. Alice (Farnham)",female,49,0,0,17465,25.9292,D17,S -798,1,3,"Osman, Mrs. Mara",female,31,0,0,349244,8.6833,,S -799,0,3,"Ibrahim Shawah, Mr. Yousseff",male,30,0,0,2685,7.2292,,C -800,0,3,"Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert)",female,30,1,1,345773,24.15,,S -801,0,2,"Ponesell, Mr. Martin",male,34,0,0,250647,13,,S -802,1,2,"Collyer, Mrs. Harvey (Charlotte Annie Tate)",female,31,1,1,C.A. 31921,26.25,,S -803,1,1,"Carter, Master. William Thornton II",male,11,1,2,113760,120,B96 B98,S -804,1,3,"Thomas, Master. Assad Alexander",male,0.42,0,1,2625,8.5167,,C -805,1,3,"Hedman, Mr. Oskar Arvid",male,27,0,0,347089,6.975,,S -806,0,3,"Johansson, Mr. Karl Johan",male,31,0,0,347063,7.775,,S -807,0,1,"Andrews, Mr. Thomas Jr",male,39,0,0,112050,0,A36,S -808,0,3,"Pettersson, Miss. Ellen Natalia",female,18,0,0,347087,7.775,,S -809,0,2,"Meyer, Mr. August",male,39,0,0,248723,13,,S -810,1,1,"Chambers, Mrs. Norman Campbell (Bertha Griggs)",female,33,1,0,113806,53.1,E8,S -811,0,3,"Alexander, Mr. William",male,26,0,0,3474,7.8875,,S -812,0,3,"Lester, Mr. James",male,39,0,0,A/4 48871,24.15,,S -813,0,2,"Slemen, Mr. Richard James",male,35,0,0,28206,10.5,,S -814,0,3,"Andersson, Miss. Ebba Iris Alfrida",female,6,4,2,347082,31.275,,S -815,0,3,"Tomlin, Mr. Ernest Portage",male,30.5,0,0,364499,8.05,,S -816,0,1,"Fry, Mr. Richard",male,,0,0,112058,0,B102,S -817,0,3,"Heininen, Miss. Wendla Maria",female,23,0,0,STON/O2. 3101290,7.925,,S -818,0,2,"Mallet, Mr. Albert",male,31,1,1,S.C./PARIS 2079,37.0042,,C -819,0,3,"Holm, Mr. John Fredrik Alexander",male,43,0,0,C 7075,6.45,,S -820,0,3,"Skoog, Master. Karl Thorsten",male,10,3,2,347088,27.9,,S -821,1,1,"Hays, Mrs. Charles Melville (Clara Jennings Gregg)",female,52,1,1,12749,93.5,B69,S -822,1,3,"Lulic, Mr. Nikola",male,27,0,0,315098,8.6625,,S -823,0,1,"Reuchlin, Jonkheer. John George",male,38,0,0,19972,0,,S -824,1,3,"Moor, Mrs. (Beila)",female,27,0,1,392096,12.475,E121,S -825,0,3,"Panula, Master. Urho Abraham",male,2,4,1,3101295,39.6875,,S -826,0,3,"Flynn, Mr. John",male,,0,0,368323,6.95,,Q -827,0,3,"Lam, Mr. Len",male,,0,0,1601,56.4958,,S -828,1,2,"Mallet, Master. Andre",male,1,0,2,S.C./PARIS 2079,37.0042,,C -829,1,3,"McCormack, Mr. Thomas Joseph",male,,0,0,367228,7.75,,Q -830,1,1,"Stone, Mrs. George Nelson (Martha Evelyn)",female,62,0,0,113572,80,B28, -831,1,3,"Yasbeck, Mrs. Antoni (Selini Alexander)",female,15,1,0,2659,14.4542,,C -832,1,2,"Richards, Master. George Sibley",male,0.83,1,1,29106,18.75,,S -833,0,3,"Saad, Mr. Amin",male,,0,0,2671,7.2292,,C -834,0,3,"Augustsson, Mr. Albert",male,23,0,0,347468,7.8542,,S -835,0,3,"Allum, Mr. Owen George",male,18,0,0,2223,8.3,,S -836,1,1,"Compton, Miss. Sara Rebecca",female,39,1,1,PC 17756,83.1583,E49,C -837,0,3,"Pasic, Mr. Jakob",male,21,0,0,315097,8.6625,,S -838,0,3,"Sirota, Mr. Maurice",male,,0,0,392092,8.05,,S -839,1,3,"Chip, Mr. Chang",male,32,0,0,1601,56.4958,,S -840,1,1,"Marechal, Mr. Pierre",male,,0,0,11774,29.7,C47,C -841,0,3,"Alhomaki, Mr. Ilmari Rudolf",male,20,0,0,SOTON/O2 3101287,7.925,,S -842,0,2,"Mudd, Mr. Thomas Charles",male,16,0,0,S.O./P.P. 3,10.5,,S -843,1,1,"Serepeca, Miss. Augusta",female,30,0,0,113798,31,,C -844,0,3,"Lemberopolous, Mr. Peter L",male,34.5,0,0,2683,6.4375,,C -845,0,3,"Culumovic, Mr. Jeso",male,17,0,0,315090,8.6625,,S -846,0,3,"Abbing, Mr. Anthony",male,42,0,0,C.A. 5547,7.55,,S -847,0,3,"Sage, Mr. Douglas Bullen",male,,8,2,CA. 2343,69.55,,S -848,0,3,"Markoff, Mr. Marin",male,35,0,0,349213,7.8958,,C -849,0,2,"Harper, Rev. John",male,28,0,1,248727,33,,S -850,1,1,"Goldenberg, Mrs. Samuel L (Edwiga Grabowska)",female,,1,0,17453,89.1042,C92,C -851,0,3,"Andersson, Master. Sigvard Harald Elias",male,4,4,2,347082,31.275,,S -852,0,3,"Svensson, Mr. Johan",male,74,0,0,347060,7.775,,S -853,0,3,"Boulos, Miss. Nourelain",female,9,1,1,2678,15.2458,,C -854,1,1,"Lines, Miss. Mary Conover",female,16,0,1,PC 17592,39.4,D28,S -855,0,2,"Carter, Mrs. Ernest Courtenay (Lilian Hughes)",female,44,1,0,244252,26,,S -856,1,3,"Aks, Mrs. Sam (Leah Rosen)",female,18,0,1,392091,9.35,,S -857,1,1,"Wick, Mrs. George Dennick (Mary Hitchcock)",female,45,1,1,36928,164.8667,,S -858,1,1,"Daly, Mr. Peter Denis ",male,51,0,0,113055,26.55,E17,S -859,1,3,"Baclini, Mrs. Solomon (Latifa Qurban)",female,24,0,3,2666,19.2583,,C -860,0,3,"Razi, Mr. Raihed",male,,0,0,2629,7.2292,,C -861,0,3,"Hansen, Mr. Claus Peter",male,41,2,0,350026,14.1083,,S -862,0,2,"Giles, Mr. Frederick Edward",male,21,1,0,28134,11.5,,S -863,1,1,"Swift, Mrs. Frederick Joel (Margaret Welles Barron)",female,48,0,0,17466,25.9292,D17,S -864,0,3,"Sage, Miss. Dorothy Edith ""Dolly""",female,,8,2,CA. 2343,69.55,,S -865,0,2,"Gill, Mr. John William",male,24,0,0,233866,13,,S -866,1,2,"Bystrom, Mrs. (Karolina)",female,42,0,0,236852,13,,S -867,1,2,"Duran y More, Miss. Asuncion",female,27,1,0,SC/PARIS 2149,13.8583,,C -868,0,1,"Roebling, Mr. Washington Augustus II",male,31,0,0,PC 17590,50.4958,A24,S -869,0,3,"van Melkebeke, Mr. Philemon",male,,0,0,345777,9.5,,S -870,1,3,"Johnson, Master. Harold Theodor",male,4,1,1,347742,11.1333,,S -871,0,3,"Balkic, Mr. Cerin",male,26,0,0,349248,7.8958,,S -872,1,1,"Beckwith, Mrs. Richard Leonard (Sallie Monypeny)",female,47,1,1,11751,52.5542,D35,S -873,0,1,"Carlsson, Mr. Frans Olof",male,33,0,0,695,5,B51 B53 B55,S -874,0,3,"Vander Cruyssen, Mr. Victor",male,47,0,0,345765,9,,S -875,1,2,"Abelson, Mrs. Samuel (Hannah Wizosky)",female,28,1,0,P/PP 3381,24,,C -876,1,3,"Najib, Miss. Adele Kiamie ""Jane""",female,15,0,0,2667,7.225,,C -877,0,3,"Gustafsson, Mr. Alfred Ossian",male,20,0,0,7534,9.8458,,S -878,0,3,"Petroff, Mr. Nedelio",male,19,0,0,349212,7.8958,,S -879,0,3,"Laleff, Mr. Kristo",male,,0,0,349217,7.8958,,S -880,1,1,"Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)",female,56,0,1,11767,83.1583,C50,C -881,1,2,"Shelley, Mrs. William (Imanita Parrish Hall)",female,25,0,1,230433,26,,S -882,0,3,"Markun, Mr. Johann",male,33,0,0,349257,7.8958,,S -883,0,3,"Dahlberg, Miss. Gerda Ulrika",female,22,0,0,7552,10.5167,,S -884,0,2,"Banfield, Mr. Frederick James",male,28,0,0,C.A./SOTON 34068,10.5,,S -885,0,3,"Sutehall, Mr. Henry Jr",male,25,0,0,SOTON/OQ 392076,7.05,,S -886,0,3,"Rice, Mrs. William (Margaret Norton)",female,39,0,5,382652,29.125,,Q -887,0,2,"Montvila, Rev. Juozas",male,27,0,0,211536,13,,S -888,1,1,"Graham, Miss. Margaret Edith",female,19,0,0,112053,30,B42,S -889,0,3,"Johnston, Miss. Catherine Helen ""Carrie""",female,,1,2,W./C. 6607,23.45,,S -890,1,1,"Behr, Mr. Karl Howell",male,26,0,0,111369,30,C148,C -891,0,3,"Dooley, Mr. Patrick",male,32,0,0,370376,7.75,,Q diff --git a/examples/sdk/titanic/datapreprocessing.py b/examples/sdk/titanic/datapreprocessing.py deleted file mode 100644 index 3e93bc9fc..000000000 --- a/examples/sdk/titanic/datapreprocessing.py +++ /dev/null @@ -1,73 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="dataprocessing") -def dataprocessing(train_df, test_df): - import numpy as np - - data = [train_df, test_df] - for dataset in data: - dataset['relatives'] = dataset['SibSp'] + dataset['Parch'] - dataset.loc[dataset['relatives'] > 0, 'not_alone'] = 0 - dataset.loc[dataset['relatives'] == 0, 'not_alone'] = 1 - dataset['not_alone'] = dataset['not_alone'].astype(int) - train_df['not_alone'].value_counts() - - # This does not contribute to a person survival probability - train_df = train_df.drop(['PassengerId'], axis=1) - - import re - deck = {"A": 1, "B": 2, "C": 3, "D": 4, "E": 5, "F": 6, "G": 7, "U": 8} - data = [train_df, test_df] - - for dataset in data: - dataset['Cabin'] = dataset['Cabin'].fillna("U0") - dataset['Deck'] = dataset['Cabin'].map(lambda x: re.compile("([a-zA-Z]+)").search(x).group()) - dataset['Deck'] = dataset['Deck'].map(deck) - dataset['Deck'] = dataset['Deck'].fillna(0) - dataset['Deck'] = dataset['Deck'].astype(int) - # we can now drop the cabin feature - train_df = train_df.drop(['Cabin'], axis=1) - test_df = test_df.drop(['Cabin'], axis=1) - - data = [train_df, test_df] - - for dataset in data: - mean = train_df["Age"].mean() - std = test_df["Age"].std() - is_null = dataset["Age"].isnull().sum() - # compute random numbers between the mean, std and is_null - rand_age = np.random.randint(mean - std, mean + std, size = is_null) - # fill NaN values in Age column with random values generated - age_slice = dataset["Age"].copy() - age_slice[np.isnan(age_slice)] = rand_age - dataset["Age"] = age_slice - dataset["Age"] = train_df["Age"].astype(int) - train_df["Age"].isnull().sum() - - train_df['Embarked'].describe() - - # fill with most common value - common_value = 'S' - data = [train_df, test_df] - - for dataset in data: - dataset['Embarked'] = dataset['Embarked'].fillna(common_value) - - train_df.info() - - return train_df, test_df diff --git a/examples/sdk/titanic/feature_engineering.py b/examples/sdk/titanic/feature_engineering.py deleted file mode 100644 index 3851510de..000000000 --- a/examples/sdk/titanic/feature_engineering.py +++ /dev/null @@ -1,109 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="featureengineering") -def featureengineering(train_df, test_df): - PREDICTION_LABEL = "Survived" - - data = [train_df, test_df] - - for dataset in data: - dataset['Fare'] = dataset['Fare'].fillna(0) - dataset['Fare'] = dataset['Fare'].astype(int) - - # Titles features - data = [train_df, test_df] - titles = {"Mr": 1, "Miss": 2, "Mrs": 3, "Master": 4, "Rare": 5} - - for dataset in data: - # extract titles - dataset['Title'] = dataset.Name.str.extract(' ([A-Za-z]+)\.', expand=False) - # replace titles with a more common title or as Rare - dataset['Title'] = dataset['Title'].replace(['Lady', 'Countess','Capt', 'Col','Don', 'Dr', - 'Major', 'Rev', 'Sir', 'Jonkheer', 'Dona'], 'Rare') - dataset['Title'] = dataset['Title'].replace('Mlle', 'Miss') - dataset['Title'] = dataset['Title'].replace('Ms', 'Miss') - dataset['Title'] = dataset['Title'].replace('Mme', 'Mrs') - # convert titles into numbers - dataset['Title'] = dataset['Title'].map(titles) - # filling NaN with 0, to get safe - dataset['Title'] = dataset['Title'].fillna(0) - train_df = train_df.drop(['Name'], axis=1) - test_df = test_df.drop(['Name'], axis=1) - - # Sex into numeric - genders = {"male": 0, "female": 1} - data = [train_df, test_df] - - for dataset in data: - dataset['Sex'] = dataset['Sex'].map(genders) - - # Drop ticket feature - train_df = train_df.drop(['Ticket'], axis=1) - test_df = test_df.drop(['Ticket'], axis=1) - - # Embarked into numeric - ports = {"S": 0, "C": 1, "Q": 2} - data = [train_df, test_df] - - for dataset in data: - dataset['Embarked'] = dataset['Embarked'].map(ports) - - # Age into categories - data = [train_df, test_df] - for dataset in data: - dataset['Age'] = dataset['Age'].astype(int) - dataset.loc[ dataset['Age'] <= 11, 'Age'] = 0 - dataset.loc[(dataset['Age'] > 11) & (dataset['Age'] <= 18), 'Age'] = 1 - dataset.loc[(dataset['Age'] > 18) & (dataset['Age'] <= 22), 'Age'] = 2 - dataset.loc[(dataset['Age'] > 22) & (dataset['Age'] <= 27), 'Age'] = 3 - dataset.loc[(dataset['Age'] > 27) & (dataset['Age'] <= 33), 'Age'] = 4 - dataset.loc[(dataset['Age'] > 33) & (dataset['Age'] <= 40), 'Age'] = 5 - dataset.loc[(dataset['Age'] > 40) & (dataset['Age'] <= 66), 'Age'] = 6 - dataset.loc[ dataset['Age'] > 66, 'Age'] = 6 - - # Fare into categories - data = [train_df, test_df] - - for dataset in data: - dataset.loc[ dataset['Fare'] <= 7.91, 'Fare'] = 0 - dataset.loc[(dataset['Fare'] > 7.91) & (dataset['Fare'] <= 14.454), 'Fare'] = 1 - dataset.loc[(dataset['Fare'] > 14.454) & (dataset['Fare'] <= 31), 'Fare'] = 2 - dataset.loc[(dataset['Fare'] > 31) & (dataset['Fare'] <= 99), 'Fare'] = 3 - dataset.loc[(dataset['Fare'] > 99) & (dataset['Fare'] <= 250), 'Fare'] = 4 - dataset.loc[ dataset['Fare'] > 250, 'Fare'] = 5 - dataset['Fare'] = dataset['Fare'].astype(int) - - # Build new features - - # Age times class - data = [train_df, test_df] - for dataset in data: - dataset['Age_Class']= dataset['Age']* dataset['Pclass'] - - # Fare per person - for dataset in data: - dataset['Fare_Per_Person'] = dataset['Fare']/(dataset['relatives']+1) - dataset['Fare_Per_Person'] = dataset['Fare_Per_Person'].astype(int) - # Let's take a last look at the training set, before we start training the models. - train_df.head(10) - - # Finalize data - train_labels = train_df[PREDICTION_LABEL] - train_df = train_df.drop(PREDICTION_LABEL, axis=1) - - return train_df, train_labels diff --git a/examples/sdk/titanic/loaddata.py b/examples/sdk/titanic/loaddata.py deleted file mode 100644 index b8dd6fc98..000000000 --- a/examples/sdk/titanic/loaddata.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="loaddata") -def loaddata(): - import pandas as pd - - data_path = "data/" - - test_df = pd.read_csv(data_path + "test.csv") - train_df = pd.read_csv(data_path + "train.csv") - - return train_df, test_df diff --git a/examples/sdk/titanic/logistic_regression.py b/examples/sdk/titanic/logistic_regression.py deleted file mode 100644 index 7eeaa337f..000000000 --- a/examples/sdk/titanic/logistic_regression.py +++ /dev/null @@ -1,29 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="logisticregression") -def logistic_regression(train_df, train_labels): - from sklearn.linear_model import LogisticRegression - - logreg = LogisticRegression(solver='lbfgs', max_iter=110) - logreg.fit(train_df, train_labels) - acc_log = round(logreg.score(train_df, train_labels) * 100, 2) - print("Logistic Regression: %s" % acc_log) - return acc_log - - - diff --git a/examples/sdk/titanic/main.py b/examples/sdk/titanic/main.py deleted file mode 100644 index ad52fb9f9..000000000 --- a/examples/sdk/titanic/main.py +++ /dev/null @@ -1,48 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import pipeline - -# data functions -from loaddata import loaddata -from feature_engineering import featureengineering -from datapreprocessing import dataprocessing - -# models -from svm import svm -from randomforest import randomforest -from logistic_regression import logistic_regression - -# end -from results import results - - -@pipeline( - name="titanic", - experiment="test" -) -def titanic_pipeline(): - train, test = loaddata() - train_proc, test_proc = dataprocessing(train, test) - train_feat, train_labels = featureengineering(train_proc, test_proc) - - rf_acc = randomforest(train_feat, train_labels) - svm_acc = svm(train_feat, train_labels) - lg_acc = logistic_regression(train_feat, train_labels) - - results(svm_acc, lg_acc, rf_acc) - - -if __name__ == "__main__": - titanic_pipeline() diff --git a/examples/sdk/titanic/randomforest.py b/examples/sdk/titanic/randomforest.py deleted file mode 100644 index ad3a7fd7e..000000000 --- a/examples/sdk/titanic/randomforest.py +++ /dev/null @@ -1,26 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="randomforest") -def randomforest(train_df, train_labels): - from sklearn.ensemble import RandomForestClassifier - - random_forest = RandomForestClassifier(n_estimators=100) - random_forest.fit(train_df, train_labels) - acc_random_forest = round(random_forest.score(train_df, train_labels) * 100, 2) - print("Random Forest accuracy: %s" % acc_random_forest) - return acc_random_forest diff --git a/examples/sdk/titanic/results.py b/examples/sdk/titanic/results.py deleted file mode 100644 index 3d4329c8d..000000000 --- a/examples/sdk/titanic/results.py +++ /dev/null @@ -1,28 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="results") -def results(acc_linear_svc, acc_log, acc_random_forest): - import pandas as pd - - results = pd.DataFrame({ - 'Model': ['Support Vector Machines', 'logistic Regression', - 'Random Forest'], - 'Score': [acc_linear_svc, acc_log, acc_random_forest]}) - result_df = results.sort_values(by='Score', ascending=False) - result_df = result_df.set_index('Score') - print(result_df) diff --git a/examples/sdk/titanic/svm.py b/examples/sdk/titanic/svm.py deleted file mode 100644 index 33aa5900b..000000000 --- a/examples/sdk/titanic/svm.py +++ /dev/null @@ -1,26 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from kale.sdk import step - - -@step(name="svm") -def svm(train_df, train_labels): - from sklearn.svm import SVC - - linear_svc = SVC(gamma='auto') - linear_svc.fit(train_df, train_labels) - acc_linear_svc = round(linear_svc.score(train_df, train_labels) * 100, 2) - print("Support Vector Classifier accuracy: %s" % acc_linear_svc) - return acc_linear_svc From 78fc5a3f78c4340209dcc1a0edf091662124b8c3 Mon Sep 17 00:00:00 2001 From: Stefano Fioravanzo Date: Mon, 2 Feb 2026 14:51:06 +0100 Subject: [PATCH 2/7] chore: Remove SDK module Remove the backend/kale/sdk/ module which provided Python decorator-based pipeline definition: - api.py: @pipeline, @step, and @artifact decorators - __init__.py: Module exports The SDK enabled writing pipelines using Python decorators instead of Jupyter notebooks. This workflow is being removed in Kale 2.0 to focus exclusively on the notebook-based approach. BREAKING CHANGE: The kale.sdk module is no longer available. Users should migrate to the notebook-based workflow. Signed-off-by: Stefano Fioravanzo --- backend/kale/sdk/__init__.py | 21 ----- backend/kale/sdk/api.py | 146 ----------------------------------- 2 files changed, 167 deletions(-) delete mode 100644 backend/kale/sdk/__init__.py delete mode 100644 backend/kale/sdk/api.py diff --git a/backend/kale/sdk/__init__.py b/backend/kale/sdk/__init__.py deleted file mode 100644 index 8ba994706..000000000 --- a/backend/kale/sdk/__init__.py +++ /dev/null @@ -1,21 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -from kale.common import logutils - -from .api import artifact as artifact, pipeline as pipeline, step as step - -logutils.get_or_create_logger(module=__name__, name="sdk") -del logutils diff --git a/backend/kale/sdk/api.py b/backend/kale/sdk/api.py deleted file mode 100644 index 917d9fb34..000000000 --- a/backend/kale/sdk/api.py +++ /dev/null @@ -1,146 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - - -import argparse -import contextlib -import logging -import os -import sys - -from kale import Artifact, Compiler, PipelineConfig, PythonProcessor, Step, StepConfig -from kale.common import utils - -log = logging.getLogger(__name__) - - -def step(**kwargs): - """Decorator used to declare a pipeline step.""" - config = StepConfig(**kwargs) - - def _step(func): - return Step(source=func, **config.to_dict()) - - return _step - - -def pipeline(**kwargs): - """Decorator used to declare a pipeline.""" - # XXX: Translate some of the input arguments because the PipelineConfig - # field names reflect the metadata passed by the Notebook. Here we want - # to provide a more user friendly API with simpler argument names. - _map = { - "name": "pipeline_name", - "experiment": "experiment_name", - "description": "pipeline_description", - } - for old, new in _map.items(): - with contextlib.suppress(KeyError): - kwargs[new] = kwargs.pop(old) - - def _pipeline(func): - # do_kwargs correspond to pipeline parameters - def _do(*args, **do_kwargs): - if not utils.main_source_lives_in_cwd(): - # XXX: See arrikto/dev#671 for more details - raise RuntimeError( - "Kale does not yet support running a pipeline when" - " Python's current working directory is different from the" - " location of the source script. You are now running" - f" `python {sys.argv[0]}`. Consider moving into the source script" - f" directory with `cd {os.path.dirname(sys.argv[0])}` and running `python {os.path.basename(sys.argv[0])}`," - " instead.\nPlease reach out to the Arrikto team in case" - " you need more information and assistance." - ) - - if args: - raise RuntimeError( - "Positional arguments found in pipeline" - f" function call `{func.__name__}`. Please provide just" - " keyword arguments." - ) - - cli_args = _parse_cli_args() - - config = PipelineConfig(**kwargs) - - processor = PythonProcessor(func, config) - pipeline_obj = processor.run() - pipeline_obj.override_pipeline_parameters_from_kwargs(**do_kwargs) - - if cli_args.kfp: - if cli_args.dry_run: - return Compiler(pipeline_obj).compile() - else: - return Compiler(pipeline_obj).compile_and_run() - else: # run the pipeline locally - return pipeline_obj.run() - - return _do - - return _pipeline - - -def _parse_cli_args(): - """Parse CLI arguments.""" - parser = argparse.ArgumentParser(description="Run Kale Pipeline") - parser.add_argument( - "-K", "--kfp", action="store_true", help="Compile the pipeline to KFP DSL and deploy it" - ) - parser.add_argument( - "-D", - "--dry-run", - action="store_true", - help=("Compile the pipeline to KFP DSL. Requires --kfp."), - ) - return parser.parse_args() - - -def artifact(name: str, path: str): - """Decorate a step to create a KFP HTML artifact. - - Apply this decorator to a step to create a Kubeflow Pipelines artifact - (https://www.kubeflow.org/docs/pipelines/sdk/output-viewer/). - In case the path does not point to a valid file, the step will fail with - an error. - - To generate more than one artifact per step, apply the same decorator - multiple time, as shown in the example below. - - ```python - @artifact(name="artifact1", path="./figure.html") - @artifact(name="artifact2", path="./plot.html") - @step(name="artifact-generator") - def foo(): - # ... - # save something to plot.html and figure.html - # ... - ``` - - **Note**: Currently the only supported format is HTML. - - Args: - name: Artifact name - path: Absolute path to an HTML file - """ - - def _(step: Step): - if not isinstance(step, Step): - raise ValueError( - "You should decorate functions that are decorated with the @step decorator!" - ) - step.artifacts.append(Artifact(name, path)) - return step - - return _ From 066745f82642240d836210564580d9a29fc307bc Mon Sep 17 00:00:00 2001 From: Stefano Fioravanzo Date: Mon, 2 Feb 2026 14:51:20 +0100 Subject: [PATCH 3/7] chore: Remove Python processor and template Remove the PythonProcessor and its associated template: - processors/pyprocessor.py: Processor that converted decorated Python functions into Pipeline objects - templates/py_function_template.jinja2: Jinja2 template for generating KFP components from Python functions The PythonProcessor enabled the SDK workflow where users could define pipelines using @pipeline and @step decorators. This is being removed in Kale 2.0 to focus exclusively on the notebook-based workflow. BREAKING CHANGE: PythonProcessor is no longer available. Signed-off-by: Stefano Fioravanzo --- backend/kale/processors/pyprocessor.py | 170 ------------------ .../templates/py_function_template.jinja2 | 40 ----- 2 files changed, 210 deletions(-) delete mode 100644 backend/kale/processors/pyprocessor.py delete mode 100644 backend/kale/templates/py_function_template.jinja2 diff --git a/backend/kale/processors/pyprocessor.py b/backend/kale/processors/pyprocessor.py deleted file mode 100644 index da4a59da0..000000000 --- a/backend/kale/processors/pyprocessor.py +++ /dev/null @@ -1,170 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import ast -from collections.abc import Callable -import inspect -from inspect import Parameter -import logging - -from kale import step as step_module -from kale.common import astutils -from kale.pipeline import PipelineConfig -from kale.step import PipelineParam, Step - -from .baseprocessor import BaseProcessor - -log = logging.getLogger(__name__) - - -def _no_op(): - pass - - -class PythonProcessor(BaseProcessor): - """Convert annotated Python code to a Pipeline object.""" - - id = "py" - no_op_step = Step(name="no_op", source=_no_op) - - _ALLOWED_ARG_KINDS = (Parameter.POSITIONAL_OR_KEYWORD,) - - def __init__(self, pipeline_function: Callable, config: PipelineConfig = None, **kwargs): - self.pipeline_fn = pipeline_function - # self.pipeline.origin = PipelineOrigin.PYTHON - - # Will be populated during processing - self._steps_input_vars = None - self._steps_return_vars = None - - super().__init__(config=config, **kwargs) - - fn_source = astutils.get_function_source(self.pipeline_fn) - self.validate(fn_source) - self.process(fn_source) - - def validate(self, fn_source: str): - """Run static analysis over the source of the @pipeline fn.""" - self._validate_function_body(fn_source) - self._fn_accepts_only_kwargs() - self._fn_args_ensure_supported_types() - return self - - def process(self, fn_source: str): - """Validates and processes the input pipeline function.""" - self._steps_return_vars = astutils.link_fns_to_return_vars(fn_source) - self._steps_input_vars = astutils.link_fns_to_inputs_vars(fn_source) - self.pipeline.pipeline_parameters = self._get_fn_kwargs() - return self - - def to_pipeline(self): - """Generate the Pipeline object.""" - # Execute the pipeline function to create the steps and build the graph - __old_execution_handler = step_module.execution_handler - step_module.execution_handler = self._register_step_handler - - # Now the steps inside the pipeline function will be called one after - # the other. Each call will create a new Step object that will - # call the registration handler to bind itself to the Pipeline object. - self.pipeline_fn() - - step_module.execution_handler = __old_execution_handler - - def _register_step_handler(self, step: Step, *args, **kwargs): - log.info(f"Registering Step '{step.name}'") - - self.pipeline.add_step(step) - - step.outs = self._steps_return_vars.get(step.source.__name__, []) - step.ins = self._steps_input_vars.get(step.source.__name__, []) - - _params_names = set(self.pipeline.pipeline_parameters) - if set(step.outs).intersection(_params_names): - raise RuntimeError( - "Some steps' return values are overriding" - " pipeline arguments. Make sure that pipeline" - " arguments are used uniquely across the" - " pipeline." - ) - - # a step can consume a subset of the pipeline's parameters - consumed_params = set(step.ins).intersection(_params_names) - step.parameters = {k: self.pipeline.pipeline_parameters[k] for k in consumed_params} - - self._link_step(step) - - # The step's execution handler will return to the main user's script. - # Need to return a fixture to fill the return values. - return (None for _ in step.outs) - - def _link_step(self, step: Step): - ins_left = set(step.ins.copy()) - ins_left.difference_update(set(self.pipeline.pipeline_parameters)) - for anc_step in reversed(list(self.pipeline.steps)): - if ins_left.intersection(set(anc_step.outs)): - self.pipeline.add_dependency(anc_step, step) - ins_left.difference_update(set(anc_step.outs)) - - def _validate_function_body(self, fn_source: str): - tree = ast.parse(fn_source) - - for node in tree.body: - func_node = None - if isinstance(node, ast.Assign): - if not isinstance(node.value, ast.Call): - raise RuntimeError("ast.Assign value is not a ast.Call node") - func_node = node.value - if isinstance(node, ast.Expr): - if not isinstance(node.value, ast.Call): - raise RuntimeError("ast.Expr value is not a ast.Call node") - func_node = node.value - if isinstance(node, ast.Call): - func_node = node - if not func_node: - raise RuntimeError(f"Node {node} is not valid.") - - fn_name = func_node.func.id - if any(not isinstance(arg, ast.Name) for arg in func_node.args): - raise ValueError(f"Function '{fn_name}' is called with some constant arguments") - - def _fn_accepts_only_kwargs(self): - signature = inspect.signature(self.pipeline_fn) - for param in signature.parameters.values(): - if param.kind not in self._ALLOWED_ARG_KINDS: - raise RuntimeError( - "All pipeline function arguments must be either positional or keyword" - ) - if param.default == Parameter.empty: - raise RuntimeError("All pipeline function arguments must have a default value") - - def _fn_args_ensure_supported_types(self): - signature = inspect.signature(self.pipeline_fn) - for param in signature.parameters.values(): - # In _fn_accepts_only_kwargs(), we have validated that the - # parameters are in _ALLOWED_ARG_KINDS and they have defaults - # FIXME: Ensure we support all the KFP-supported types - # https://github.com/kubeflow/pipelines/blob/9af3e79c10b9bb1ac1adc7bf8c1354a16fa7b461/sdk/python/kfp/components/_data_passing.py#L107-L116 - if not isinstance(param.default, (int, float, str, bool)): - raise RuntimeError( - "Pipeline parameters must be of primitive" - " types: int, float, str, or bool. Pipeline" - f" parameter {param.name} is of type {type(param.default)}" - ) - - def _get_fn_kwargs(self) -> dict[str, PipelineParam]: - kwargs = {} - signature = inspect.signature(self.pipeline_fn) - for param in signature.parameters.values(): - kwargs[param.name] = PipelineParam(type(param.default).__name__, param.default) - return kwargs diff --git a/backend/kale/templates/py_function_template.jinja2 b/backend/kale/templates/py_function_template.jinja2 deleted file mode 100644 index 92b7fe60f..000000000 --- a/backend/kale/templates/py_function_template.jinja2 +++ /dev/null @@ -1,40 +0,0 @@ -def {{ step.name }}({%- for arg in step.pps_names -%} - {{ arg }}: {{ (step.pps_types)[loop.index-1] }} - {%- if loop.index < step.pps_names|length -%}, - {%- endif -%} - {%- endfor -%}): -{%- if step.ins|length == 0 and step.outs|length == 0 and step.source|length == 0 %} - pass -{%- else %} - - - {% if step.config.timeout %}from kale.common.runutils import ttl as _kale_ttl{% endif %} - from kale.marshal.decorator import marshal as _kale_marshal - from kale.common.runutils import link_artifacts as _kale_link_artifacts - - _kale_pipeline_parameters = { -{%- if step.pps_names|length %} - {%- for arg in step.pps_names -%} - "{{ arg }}": {{ arg }} - {%- if loop.index < step.pps_names|length -%}, - {%- endif -%} - {%- endfor -%} -{%- endif %}} - - {% if step.config.timeout %}@_kale_ttl({{ step.config.timeout }}){% endif %} - @_kale_marshal({{ step.ins }}, {{ step.outs }}, _kale_pipeline_parameters, "{{ marshal_path }}") -{{ step.rendered_source|indent(4, True) }} - - {{ step.source.__name__ }}() - - _kale_artifacts = { -{%- if step.artifacts|length %} - {%- for artifact in step.artifacts -%} - "{{ artifact.name }}": "{{ artifact.path }}" - {%- if loop.index < step.pps_names|length -%}, - {%- endif -%} - {%- endfor -%} -{%- endif %}} - - _kale_link_artifacts(_kale_artifacts) -{%- endif %} From 4bde41330505647a75a7e6448d32e1008de294c8 Mon Sep 17 00:00:00 2001 From: Stefano Fioravanzo Date: Mon, 2 Feb 2026 14:51:42 +0100 Subject: [PATCH 4/7] chore: Remove PythonProcessor from package exports Update import statements to remove PythonProcessor references: - processors/__init__.py: Remove PythonProcessor import - kale/__init__.py: Remove PythonProcessor from imports The package now only exports NotebookProcessor for pipeline creation. Signed-off-by: Stefano Fioravanzo --- backend/kale/__init__.py | 3 +-- backend/kale/processors/__init__.py | 1 - 2 files changed, 1 insertion(+), 3 deletions(-) diff --git a/backend/kale/__init__.py b/backend/kale/__init__.py index 909fbac86..11331d5d2 100644 --- a/backend/kale/__init__.py +++ b/backend/kale/__init__.py @@ -65,7 +65,7 @@ class Artifact(NamedTuple): from .compiler import Compiler from .pipeline import Pipeline, PipelineConfig, VolumeConfig -from .processors import NotebookConfig, NotebookProcessor, PythonProcessor +from .processors import NotebookConfig, NotebookProcessor from .step import Step, StepConfig __all__ = [ @@ -73,7 +73,6 @@ class Artifact(NamedTuple): "Artifact", "NotebookConfig", "NotebookProcessor", - "PythonProcessor", "Step", "StepConfig", "Pipeline", diff --git a/backend/kale/processors/__init__.py b/backend/kale/processors/__init__.py index 9357c0103..8de5ff734 100644 --- a/backend/kale/processors/__init__.py +++ b/backend/kale/processors/__init__.py @@ -13,4 +13,3 @@ # limitations under the License. from .nbprocessor import NotebookConfig as NotebookConfig, NotebookProcessor as NotebookProcessor -from .pyprocessor import PythonProcessor as PythonProcessor From 4defe3ff09c9d49606e7255421d72c77d6b7eaa0 Mon Sep 17 00:00:00 2001 From: Stefano Fioravanzo Date: Mon, 2 Feb 2026 14:52:11 +0100 Subject: [PATCH 5/7] refactor: Simplify compiler to notebook-only workflow Remove Python processor template selection logic from the compiler: - Remove PY_FN_TEMPLATE constant (py_function_template.jinja2) - Remove PIPELINE_ORIGIN dictionary that mapped processor.id to templates - Remove conditional check for processor.id == "nb" - Always use NB_FN_TEMPLATE for component generation The compiler now exclusively supports notebook-based pipeline generation, simplifying the code and removing the unused Python processor code path. Signed-off-by: Stefano Fioravanzo --- backend/kale/compiler.py | 16 ++++++---------- 1 file changed, 6 insertions(+), 10 deletions(-) diff --git a/backend/kale/compiler.py b/backend/kale/compiler.py index 0cf4903d2..59f81e16b 100644 --- a/backend/kale/compiler.py +++ b/backend/kale/compiler.py @@ -27,10 +27,8 @@ log = logging.getLogger(__name__) -PY_FN_TEMPLATE = "py_function_template.jinja2" NB_FN_TEMPLATE = "nb_function_template.jinja2" PIPELINE_TEMPLATE = "pipeline_template.jinja2" -PIPELINE_ORIGIN = {"nb": NB_FN_TEMPLATE, "py": PY_FN_TEMPLATE} KFP_DSL_ARTIFACT_IMPORTS = [ "Dataset", @@ -111,7 +109,7 @@ def generate_dsl(self): return pipeline_code def generate_lightweight_component(self, step: Step): - """Generate Python code using the function template.""" + """Generate Python code using the notebook function template.""" step_source_raw = step.source def _encode_source(s): @@ -120,14 +118,12 @@ def _encode_source(s): [line.encode("unicode_escape").decode("utf-8") for line in s.splitlines()] ) - if self.pipeline.processor.id == "nb": - # Since the code will be wrapped in triple quotes inside the - # template, we need to escape triple quotes as they will not be - # escaped by encode("unicode_escape"). - step.source = [re.sub(r"'''", "\\'\\'\\'", _encode_source(s)) for s in step_source_raw] + # Since the code will be wrapped in triple quotes inside the + # template, we need to escape triple quotes as they will not be + # escaped by encode("unicode_escape"). + step.source = [re.sub(r"'''", "\\'\\'\\'", _encode_source(s)) for s in step_source_raw] - _template_filename = PIPELINE_ORIGIN.get(self.pipeline.processor.id) - template = self._get_templating_env().get_template(_template_filename) + template = self._get_templating_env().get_template(NB_FN_TEMPLATE) # Separate parameters with and without defaults for proper ordering params_without_defaults = [f"{step.name}_html_report: Output[HTML]"] From 1bfd7bc1b94881d77c6cdd5e028f89a5abeab022 Mon Sep 17 00:00:00 2001 From: Stefano Fioravanzo Date: Wed, 4 Feb 2026 09:15:23 +0100 Subject: [PATCH 6/7] refactor: Remove BaseProcessor and inline into NotebookProcessor With PythonProcessor removed, the BaseProcessor abstract class is no longer needed. Inline its logic directly into NotebookProcessor: - run() method - _post_pipeline() method - _configure_poddefaults() method - _apply_steps_defaults() method Signed-off-by: Stefano Fioravanzo --- backend/kale/processors/baseprocessor.py | 74 ------------------------ backend/kale/processors/nbprocessor.py | 57 +++++++++++++++--- 2 files changed, 49 insertions(+), 82 deletions(-) delete mode 100644 backend/kale/processors/baseprocessor.py diff --git a/backend/kale/processors/baseprocessor.py b/backend/kale/processors/baseprocessor.py deleted file mode 100644 index 789fa0ac9..000000000 --- a/backend/kale/processors/baseprocessor.py +++ /dev/null @@ -1,74 +0,0 @@ -# Copyright 2026 The Kubeflow Authors. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -from abc import ABC, abstractmethod -import logging - -from kale.common import kfutils -from kale.pipeline import Pipeline, PipelineConfig, Step - -log = logging.getLogger(__name__) - - -class BaseProcessor(ABC): - """Provides basic tools for processors to generate a Pipeline object.""" - - id: str - no_op_step: Step - config_cls = PipelineConfig - - def __init__( - self, config: PipelineConfig | None = None, skip_validation: bool = False, **kwargs - ): - self.config = config - if not config and not skip_validation: - self.config = self.config_cls(**kwargs) - self.pipeline = Pipeline(self.config) if self.config else None - - def run(self) -> Pipeline: - """Process the source into a Pipeline object.""" - self.to_pipeline() - self._post_pipeline() - return self.pipeline - - @abstractmethod - def to_pipeline(self): - """A processor class is supposed to extend this method.""" - pass - - def _post_pipeline(self): - # keep reference to original processor, so the pipeline knows - # what backend generated it. - if self.pipeline: - self.pipeline.processor = self - self._configure_poddefaults() - self._apply_steps_defaults() - - def _configure_poddefaults(self): - # FIXME: We should reconsider the implementation of - # https://github.com/kubeflow-kale/kale/pull/175/files to - # avoid using an RPC and always detect PodDefaults here. - _pod_defaults_labels = {} - try: - _pod_defaults_labels = kfutils.find_poddefault_labels() - except Exception as e: - log.warning("Could not retrieve PodDefaults. Reason: %s", e) - self.pipeline.config.steps_defaults["labels"] = { - **self.pipeline.config.steps_defaults.get("labels", {}), - **_pod_defaults_labels, - } - - def _apply_steps_defaults(self): - for step in self.pipeline.steps: - step.config.update(self.pipeline.config.steps_defaults) diff --git a/backend/kale/processors/nbprocessor.py b/backend/kale/processors/nbprocessor.py index 67b6ebcae..a5b50ad2c 100644 --- a/backend/kale/processors/nbprocessor.py +++ b/backend/kale/processors/nbprocessor.py @@ -12,18 +12,19 @@ # See the License for the specific language governing permissions and # limitations under the License. +import logging import os import re from typing import Any import nbformat as nb -from kale.common import astutils, flakeutils, graphutils, utils +from kale.common import astutils, flakeutils, graphutils, kfutils, utils from kale.config import Field -from kale.pipeline import PipelineConfig +from kale.pipeline import Pipeline, PipelineConfig from kale.step import PipelineParam, Step -from .baseprocessor import BaseProcessor +log = logging.getLogger(__name__) # fixme: Change the name of this key to `kale_metadata` KALE_NB_METADATA_KEY = "kubeflow_notebook" @@ -168,19 +169,25 @@ def _parse_steps_defaults(self, steps_defaults): return result -class NotebookProcessor(BaseProcessor): +class NotebookProcessor: """Convert a Notebook to a Pipeline object.""" - id = "nb" - config_cls = NotebookConfig no_op_step = Step(name="no_op", source=[]) - def __init__(self, nb_path: str, nb_metadata_overrides: dict[str, Any] | None = None, **kwargs): + def __init__( + self, + nb_path: str, + nb_metadata_overrides: dict[str, Any] | None = None, + config: NotebookConfig | None = None, + skip_validation: bool = False, + **kwargs, + ): """Instantiate a new NotebookProcessor. Args: nb_path: Path to source notebook nb_metadata_overrides: Override notebook config settings + config: Optional pre-built NotebookConfig skip_validation: Set to True in order to skip the notebook's metadata validation. This is useful in case the NotebookProcessor is used to parse a part of the notebook @@ -194,13 +201,47 @@ def __init__(self, nb_path: str, nb_metadata_overrides: dict[str, Any] | None = nb_metadata.update({"notebook_path": nb_path}) if nb_metadata_overrides: nb_metadata.update(nb_metadata_overrides) - super().__init__(**{**kwargs, **nb_metadata}) + + # Initialize config and pipeline (previously in BaseProcessor) + self.config = config + if not config and not skip_validation: + self.config = NotebookConfig(**{**kwargs, **nb_metadata}) + self.pipeline = Pipeline(self.config) if self.config else None def _read_notebook(self): if not os.path.exists(self.nb_path): raise ValueError(f"NotebookProcessor could not find a notebook at path {self.nb_path}") return nb.read(self.nb_path, as_version=nb.NO_CONVERT) + def run(self) -> Pipeline: + """Process the notebook into a Pipeline object.""" + self.to_pipeline() + self._post_pipeline() + return self.pipeline + + def _post_pipeline(self): + """Post-process the pipeline after conversion.""" + if self.pipeline: + self.pipeline.processor = self + self._configure_poddefaults() + self._apply_steps_defaults() + + def _configure_poddefaults(self): + """Detect and configure PodDefaults labels.""" + _pod_defaults_labels = dict() + try: + _pod_defaults_labels = kfutils.find_poddefault_labels() + except Exception as e: + log.warning("Could not retrieve PodDefaults. Reason: %s", e) + self.pipeline.config.steps_defaults["labels"] = { + **self.pipeline.config.steps_defaults.get("labels", dict()), + **_pod_defaults_labels} + + def _apply_steps_defaults(self): + """Apply default configuration to all pipeline steps.""" + for step in self.pipeline.steps: + step.config.update(self.pipeline.config.steps_defaults) + def to_pipeline(self): """Convert an annotated Notebook to a Pipeline object.""" (pipeline_parameters_source, pipeline_metrics_source, imports_and_functions) = ( From b6b15cdcdfb8ed84c19fc33be73b0ba82032ee87 Mon Sep 17 00:00:00 2001 From: Stefano Fioravanzo Date: Thu, 5 Feb 2026 22:26:03 +0100 Subject: [PATCH 7/7] style: Apply ruff lint fixes for modern Python type annotations Signed-off-by: Stefano Fioravanzo --- backend/kale/common/astutils.py | 29 +++++++++----------------- backend/kale/common/kfputils.py | 2 +- backend/kale/processors/nbprocessor.py | 7 ++++--- 3 files changed, 15 insertions(+), 23 deletions(-) diff --git a/backend/kale/common/astutils.py b/backend/kale/common/astutils.py index f77f23864..26a50f96d 100644 --- a/backend/kale/common/astutils.py +++ b/backend/kale/common/astutils.py @@ -59,13 +59,13 @@ def get_list_tuple_names(node): Returns: a list of all names of the tuple """ - assert isinstance(node, (ast.Tuple, ast.List)) + assert isinstance(node, ast.Tuple | ast.List) names = [] for _n in node.elts: - if isinstance(_n, (ast.Tuple, ast.List)): + if isinstance(_n, ast.Tuple | ast.List): # recursive call names.extend(get_list_tuple_names(_n)) - elif isinstance(_n, (ast.Name,)): + elif isinstance(_n, ast.Name): names.append(_n.id) return names @@ -135,21 +135,18 @@ def get_marshal_candidates(code): for node in walk(block, stop_at=contexts): if isinstance(node, contexts): names.add(node.name) - if isinstance(node, (ast.Name,)): + if isinstance(node, ast.Name): names.add(node.id) if isinstance( node, - ( - ast.Import, - ast.ImportFrom, - ), + ast.Import | ast.ImportFrom, ): for _n in node.names: if _n.asname is None: names.add(_n.name) else: names.add(_n.asname) - if isinstance(node, (ast.Tuple, ast.List)): + if isinstance(node, ast.Tuple | ast.List): names.update(get_list_tuple_names(node)) return names @@ -171,7 +168,7 @@ def parse_functions(code): tree = ast.parse(code) for block in tree.body: for node in walk(block, stop_at=(ast.FunctionDef,), ignore=(ast.ClassDef,)): - if isinstance(node, (ast.FunctionDef,)): + if isinstance(node, ast.FunctionDef): fn_name = node.name fns[fn_name] = astor.to_source(node) return fns @@ -208,7 +205,7 @@ def get_function_calls(code): # a function call. We check the attribute func to be ast.Name # because it could also be a ast.Attribute node, in case of # function calls like obj.foo() - if isinstance(node, (ast.Call,)) and isinstance(node.func, (ast.Name,)): + if isinstance(node, ast.Call) and isinstance(node.func, ast.Name): fns.add(node.func.id) return fns @@ -230,10 +227,7 @@ def get_function_and_class_names(code): for node in walk(block): if isinstance( node, - ( - ast.FunctionDef, - ast.ClassDef, - ), + ast.FunctionDef | ast.ClassDef, ): names.add(node.name) return names @@ -256,10 +250,7 @@ def parse_assignments_expressions(code): if ( isinstance( targets[0], - ( - ast.Tuple, - ast.List, - ), + ast.Tuple | ast.List, ) or len(targets) > 1 ): diff --git a/backend/kale/common/kfputils.py b/backend/kale/common/kfputils.py index 811c21ac7..3b45c5692 100644 --- a/backend/kale/common/kfputils.py +++ b/backend/kale/common/kfputils.py @@ -298,7 +298,7 @@ def generate_mlpipeline_metrics(metrics): """ metadata = [] for name, value in metrics.items(): - if not isinstance(value, (int, float)): + if not isinstance(value, int | float): try: value = float(value) except ValueError: diff --git a/backend/kale/processors/nbprocessor.py b/backend/kale/processors/nbprocessor.py index a5b50ad2c..c80596eee 100644 --- a/backend/kale/processors/nbprocessor.py +++ b/backend/kale/processors/nbprocessor.py @@ -228,14 +228,15 @@ def _post_pipeline(self): def _configure_poddefaults(self): """Detect and configure PodDefaults labels.""" - _pod_defaults_labels = dict() + _pod_defaults_labels = {} try: _pod_defaults_labels = kfutils.find_poddefault_labels() except Exception as e: log.warning("Could not retrieve PodDefaults. Reason: %s", e) self.pipeline.config.steps_defaults["labels"] = { - **self.pipeline.config.steps_defaults.get("labels", dict()), - **_pod_defaults_labels} + **self.pipeline.config.steps_defaults.get("labels", {}), + **_pod_defaults_labels, + } def _apply_steps_defaults(self): """Apply default configuration to all pipeline steps."""