diff --git a/SET Assignment2.ipynb b/SET Assignment2.ipynb new file mode 100644 index 0000000..e8028ed --- /dev/null +++ b/SET Assignment2.ipynb @@ -0,0 +1,993 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "SETAssignment2.ipynb", + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "nf8JtyyGzdDR" + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "from sklearn.linear_model import LinearRegression\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import train_test_split" + ] + }, + { + "cell_type": "code", + "source": [ + "df = pd.read_csv(\"Nutrition__Physical_Activity__and_Obesity_-_Behavioral_Risk_Factor_Surveillance_System.csv\")\n", + "df.head()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 704 + }, + "id": "9OHwTfqT0WWh", + "outputId": "1b61eac6-4ca1-43e7-a962-8e7444c74bff" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "\n", + "
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YearStartYearEndLocationAbbrLocationDescDatasourceClassTopicQuestionData_Value_UnitData_Value_TypeData_ValueData_Value_AltData_Value_Footnote_SymbolData_Value_FootnoteLow_Confidence_LimitHigh_Confidence_LimitSample_SizeTotalAge(years)EducationGenderIncomeRace/EthnicityGeoLocationClassIDTopicIDQuestionIDDataValueTypeIDLocationIDStratificationCategory1Stratification1StratificationCategoryId1StratificationID1
020112011ALAlabamaBehavioral Risk Factor Surveillance SystemObesity / Weight StatusObesity / Weight StatusPercent of adults aged 18 years and older who ...NaNValue32.032.0NaNNaN30.533.57304.0TotalNaNNaNNaNNaNNaN(32.84057112200048, -86.63186076199969)OWSOWS1Q036VALUE1.0TotalTotalOVROVERALL
120112011ALAlabamaBehavioral Risk Factor Surveillance SystemObesity / Weight StatusObesity / Weight StatusPercent of adults aged 18 years and older who ...NaNValue32.332.3NaNNaN29.934.72581.0NaNNaNNaNMaleNaNNaN(32.84057112200048, -86.63186076199969)OWSOWS1Q036VALUE1.0GenderMaleGENMALE
220112011ALAlabamaBehavioral Risk Factor Surveillance SystemObesity / Weight StatusObesity / Weight StatusPercent of adults aged 18 years and older who ...NaNValue31.831.8NaNNaN30.033.64723.0NaNNaNNaNFemaleNaNNaN(32.84057112200048, -86.63186076199969)OWSOWS1Q036VALUE1.0GenderFemaleGENFEMALE
320112011ALAlabamaBehavioral Risk Factor Surveillance SystemObesity / Weight StatusObesity / Weight StatusPercent of adults aged 18 years and older who ...NaNValue33.633.6NaNNaN29.937.61153.0NaNNaNLess than high schoolNaNNaNNaN(32.84057112200048, -86.63186076199969)OWSOWS1Q036VALUE1.0EducationLess than high schoolEDUEDUHS
420112011ALAlabamaBehavioral Risk Factor Surveillance SystemObesity / Weight StatusObesity / Weight StatusPercent of adults aged 18 years and older who ...NaNValue32.832.8NaNNaN30.235.62402.0NaNNaNHigh school graduateNaNNaNNaN(32.84057112200048, -86.63186076199969)OWSOWS1Q036VALUE1.0EducationHigh school graduateEDUEDUHSGRAD
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YearStartYearEndData_Value_UnitData_ValueData_Value_AltLow_Confidence_LimitHigh_Confidence_LimitSample_SizeLocationID
count5490.0000005490.0000000.05048.0000005048.0000005048.000005048.0000005048.0000005489.000000
mean2012.2300552012.230055NaN31.08686631.08686626.4916436.3111132009.5342715.814903
std1.0945831.094583NaN10.55968210.55968210.2547211.5821359466.8161153.773033
min2011.0000002011.000000NaN0.9000000.9000000.300003.00000050.0000001.000000
25%2011.0000002011.000000NaN23.70000023.70000019.4000028.200000494.0000004.000000
50%2012.0000002012.000000NaN30.40000030.40000025.7000036.000000994.0000006.000000
75%2013.0000002013.000000NaN37.20000037.20000032.8250042.8000001995.0000009.000000
max2015.0000002015.000000NaN72.30000072.30000067.9000083.200000398316.00000059.000000
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Sample_Size LocationID\n", + "count 5490.000000 5490.000000 ... 5048.000000 5489.000000\n", + "mean 2012.230055 2012.230055 ... 2009.534271 5.814903\n", + "std 1.094583 1.094583 ... 9466.816115 3.773033\n", + "min 2011.000000 2011.000000 ... 50.000000 1.000000\n", + "25% 2011.000000 2011.000000 ... 494.000000 4.000000\n", + "50% 2012.000000 2012.000000 ... 994.000000 6.000000\n", + "75% 2013.000000 2013.000000 ... 1995.000000 9.000000\n", + "max 2015.000000 2015.000000 ... 398316.000000 59.000000\n", + "\n", + "[8 rows x 9 columns]" + ] + }, + "metadata": {}, + "execution_count": 28 + } + ] + }, + { + "cell_type": "code", + "source": [ + "wrangled = df[df['StratificationID1'] == 'OVERALL'][['LocationDesc','Data_Value', 'Question', \"YearStart\" ]]\n", + "question = wrangled[wrangled['Question'] == 'Percent of adults who engage in no leisure-time physical activity'][['LocationDesc','Data_Value', 'Question', \"YearStart\" ]]\n", + "x_all = question[question['YearStart'] == 2014][['LocationDesc','Data_Value' ]]\n", + "x = question[question['YearStart'] == 2014][['Data_Value' ]].values\n", + "x" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "nfvngUQ_0j3A", + "outputId": "1dd16745-028c-4eaa-b7be-f9250b989bde" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([[27.6],\n", + " [19.2],\n", + " [21.2],\n", + " [30.7],\n", + " [21.7],\n", + " [16.4],\n", + " [20.6],\n", + " [24.9]])" + ] + }, + "metadata": {}, + "execution_count": 29 + } + ] + }, + { + "cell_type": "code", + "source": [ + "wrangled = df[df['StratificationID1'] == 'OVERALL'][['LocationDesc','Data_Value', 'Question', \"YearStart\" ]]\n", + "year = wrangled[wrangled['Question'] == 'Percent of adults aged 18 years and older who have obesity'][['LocationDesc','Data_Value', 'Question', \"YearStart\" ]]\n", + "y_all = year[year['YearStart'] == 2014][['LocationDesc','Data_Value' ]]\n", + "y = year[year['YearStart'] == 2014][['Data_Value' ]].values\n", + "y" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ZSaSh-4A0mhY", + "outputId": "e691505b-f468-48a5-90fc-fcb08b7ac38e" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([[33.5],\n", + " [29.7],\n", + " [28.9],\n", + " [35.9],\n", + " [24.7],\n", + " [21.3],\n", + " [26.3],\n", + " [30.7]])" + ] + }, + "metadata": {}, + "execution_count": 30 + } + ] + }, + { + "cell_type": "code", + "source": [ + "x = x.reshape(-1, 1)\n", + "x" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "3X4tOzIZ0qfB", + "outputId": "f609deec-1dcc-4fb1-9f1f-3fa641da9693" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([[27.6],\n", + " [19.2],\n", + " [21.2],\n", + " [30.7],\n", + " [21.7],\n", + " [16.4],\n", + " [20.6],\n", + " [24.9]])" + ] + }, + "metadata": {}, + "execution_count": 31 + } + ] + }, + { + "cell_type": "code", + "source": [ + "y = y.reshape(-1, 1)\n", + "y" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "odnC_Qad0s4f", + "outputId": "2a690e65-9ec0-4363-c68f-08c415934a77" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "array([[33.5],\n", + " [29.7],\n", + " [28.9],\n", + " [35.9],\n", + " [24.7],\n", + " [21.3],\n", + " [26.3],\n", + " [30.7]])" + ] + }, + "metadata": {}, + "execution_count": 32 + } + ] + }, + { + "cell_type": "code", + "source": [ + "x_train, x_test, y_train, y_test = train_test_split(x, y, train_size=.8, test_size=.2, random_state=100)" + ], + "metadata": { + "id": "FcsS4k1m0vSK" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "print(f'X Train Data shape{x_train.shape}')\n", + "print(f'y Train Data shape{y_train.shape}')\n", + "print(f'X Test Data shape{x_test.shape}')\n", + "print(f'y Test Data shape{y_test.shape}')" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "-6qRaxN00xx5", + "outputId": "f5e9fe50-2599-41d0-8323-5ee03c40af41" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "X Train Data shape(6, 1)\n", + "y Train Data shape(6, 1)\n", + "X Test Data shape(2, 1)\n", + "y Test Data shape(2, 1)\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "plt.scatter(x_train, y_train, color='orange')\n", + "plt.xlabel('% Adults with reporting no leisure Physical Activity')\n", + "plt.ylabel('% of Adults who have Obesity')\n", + "plt.title('Physical Data')\n", + "plt.show()" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 295 + }, + "id": "PQfW9bb500zu", + "outputId": "e370fad2-0b49-486f-e2e1-de4d9876efa9" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "source": [ + "lm = LinearRegression()\n", + "lm.fit(x_train, y_train)\n", + "y_predict = lm.predict(x_test)" + ], + "metadata": { + "id": "TFQqD_Sf029n" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "print(f'Train Accuracy {round(lm.score(x_train, y_train)* 100,2)}%')\n", + "print(f'Test Accuracy {round(lm.score(x_test, y_test)* 100,2)}%')" + ], + "metadata": { + "id": "Eh3xosm4056N", + "outputId": "9c685099-321c-4a29-9767-41450044cacd", + "colab": { + "base_uri": "https://localhost:8080/" + } + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Train Accuracy 96.51%\n", + "Test Accuracy -134.64%\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "plt.scatter(x_train, y_train, color='orange')\n", + "plt.xlabel('% Adults with reporting no leisure Physical Activity')\n", + "plt.ylabel('% of Adults who have Obesity')\n", + "plt.title('Physical Data')\n", + "plt.show()" + ], + "metadata": { + "id": "jBbc59fY08WU", + "outputId": "eebc0794-8e18-47ea-c031-c60739d1bead", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 295 + } + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + } + } + ] + }, + { + "cell_type": "code", + "source": [ + "" + ], + "metadata": { + "id": "1B5LoqKA0-d9" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file diff --git a/Student assignment updates.txt b/Student assignment updates.txt index 9979d7c..cbc9235 100644 --- a/Student assignment updates.txt +++ b/Student assignment updates.txt @@ -1,2 +1,4 @@ Write your name and PRN no +Pratibha Maind +2019BTECS00088 Hello Updated