From 5129ac8d226f5389bf899c152fc9ceb824aaa475 Mon Sep 17 00:00:00 2001 From: herguejuan Date: Wed, 25 Mar 2020 17:26:09 -0600 Subject: [PATCH 1/4] Modificando archivo About-me a proposito --- module-1/lab-resolving-git-conflicts/your-code/about-me.md | 1 + 1 file changed, 1 insertion(+) diff --git a/module-1/lab-resolving-git-conflicts/your-code/about-me.md b/module-1/lab-resolving-git-conflicts/your-code/about-me.md index 30a999d..584f19f 100755 --- a/module-1/lab-resolving-git-conflicts/your-code/about-me.md +++ b/module-1/lab-resolving-git-conflicts/your-code/about-me.md @@ -5,3 +5,4 @@ Ut porttitor iaculis tellus bibendum euismod. Morbi porta, ante nec tempus porta Suspendisse ut malesuada ex. Nulla ultricies nisl et nisi rhoncus sollicitudin. Vestibulum maximus iaculis ligula, nec commodo nunc ullamcorper nec. Duis quis condimentum sapien. Cras vestibulum interdum felis eu auctor. Quisque semper, magna at dapibus faucibus, felis risus semper ligula, id aliquam lectus ligula vel nisi. In hac habitasse platea dictumst. Donec arcu sapien, suscipit ac dictum et, imperdiet id tortor. Maecenas ornare sodales interdum. Mauris dictum felis eu eros vestibulum cursus. Phasellus accumsan, turpis ut malesuada sollicitudin, augue leo venenatis ante, vel convallis tellus diam sit amet lacus. Aenean eu mauris eros. Praesent ante lacus, gravida sit amet tellus nec, laoreet ultrices lacus. Integer commodo semper vestibulum. Fusce felis massa, consectetur facilisis rutrum nec, pulvinar et nisi. Morbi fermentum ultricies tortor, vehicula ultrices eros elementum a. Duis ornare aliquam facilisis. Proin aliquam tincidunt odio vitae dignissim. Sed malesuada lacinia massa, nec blandit urna auctor elementum. Duis auctor non tortor in consequat. Mauris id vestibulum risus. In eget erat sed lacus efficitur viverra sed eu est. Aliquam interdum consequat molestie. Aliquam metus nisi, blandit non semper ut, blandit vel leo. Cras dictum turpis erat, sed iaculis ligula facilisis dapibus. Aliquam posuere dignissim fermentum. Praesent at neque sit amet lectus ornare iaculis. Curabitur id urna quis lorem varius ultrices eu sit amet sapien. Curabitur maximus volutpat suscipit. Proin imperdiet elementum lacus a eleifend. Sed tempor lacus posuere diam vehicula iaculis. +Agregando cualquier cosa From 484a78b6127d01a89eeedc8029eacf60ecfda819 Mon Sep 17 00:00:00 2001 From: herguejuan Date: Wed, 15 Apr 2020 03:53:20 -0500 Subject: [PATCH 2/4] Descartar cambios --- .../lab-web-scraping/your-code/main.ipynb | 105 +++++++++++++++--- 1 file changed, 87 insertions(+), 18 deletions(-) diff --git a/module-1/lab-web-scraping/your-code/main.ipynb b/module-1/lab-web-scraping/your-code/main.ipynb index d2d7553..0785805 100755 --- a/module-1/lab-web-scraping/your-code/main.ipynb +++ b/module-1/lab-web-scraping/your-code/main.ipynb @@ -40,7 +40,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -51,9 +51,9 @@ "# from lxml import html\n", "# from lxml.html import fromstring\n", "# import urllib.request\n", - "# from urllib.request import urlopen\n", + "from urllib.request import urlopen\n", "# import random\n", - "# import re\n", + "import re\n", "# import scrapy" ] }, @@ -66,7 +66,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -76,11 +76,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ - "#your code" + "github_html=requests.get(url).text\n", + "soup = BeautifulSoup(github_html, \"html.parser\")" ] }, { @@ -134,11 +135,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "['Product', 'Platform', 'Support', 'Company']" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "#your code" + "def elimina(t):\n", + " t = re.sub(' ','',t)\n", + " t = re.sub('\\n\\n',' ',t)\n", + " return t.strip()\n", + "\n", + "dev2 = [d.text for d in soup.find_all('h2')]\n", + "dev2 = list(map(elimina, dev2))\n", + "\n", + "dev2" ] }, { @@ -152,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -162,11 +182,59 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "#your code" + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Trending',\n", + " 'zylo117 - Yet-Another-EfficientDet-Pytorch',\n", + " 'shengqiangzhang - examples-of-web-crawlers',\n", + " 'Mascobot - pandemic-ventilator-2.0',\n", + " 'twintproject - twint',\n", + " 'satwikkansal - wtfpython',\n", + " 'tiangolo - fastapi',\n", + " 'diofeher - bbb-v2',\n", + " 'matterport - Mask_RCNN',\n", + " 'alievk - avatarify',\n", + " 'vt-vl-lab - 3d-photo-inpainting',\n", + " 'leisurelicht - wtfpython-cn',\n", + " 'lindawangg - COVID-Net',\n", + " 'grantmcconnaughey - cookiecutter-django-vue-graphql-aws',\n", + " 'awslabs - aws-data-wrangler',\n", + " 'toandaominh1997 - EfficientDet.Pytorch',\n", + " 'DP-3T - reference_implementation',\n", + " 'encode - django-rest-framework',\n", + " 'lazyprogrammer - machine_learning_examples',\n", + " 'allenai - longformer',\n", + " 'eragonruan - text-detection-ctpn',\n", + " 'tensorflow - hub',\n", + " 'darkarp - chromepass',\n", + " 'junyanz - pytorch-CycleGAN-and-pix2pix',\n", + " 'ansible - ansible',\n", + " 'Azure - azure-sdk-for-python']" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#your code\n", + "github_html_py = requests.get(url).text\n", + "soup_py = BeautifulSoup(github_html_py, \"html.parser\")\n", + "\n", + "def limpia(t):\n", + " t = re.sub(' ','',t)\n", + " t = re.sub('\\n','',t)\n", + " t = re.sub('/',' - ',t)\n", + " return t\n", + "\n", + "repository = [r.text for r in soup_py.find_all('h1')]\n", + "repository = list(map(limpia, repository))\n", + "repository" ] }, { @@ -178,7 +246,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -192,7 +260,8 @@ "metadata": {}, "outputs": [], "source": [ - "#your code" + "disney_html = requests.get(url).text\n", + "soup_disney = BeautifulSoup(disney_html, \"html.parser\")" ] }, { @@ -630,7 +699,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.2" + "version": "3.7.6" } }, "nbformat": 4, From 3bbd85e5ad8c769af29c77b52c66f6bc67ff2110 Mon Sep 17 00:00:00 2001 From: herguejuan Date: Fri, 17 Apr 2020 14:18:23 -0500 Subject: [PATCH 3/4] quitando cambios --- .../pymongo-tester-checkpoint.ipynb | 6 + .../starter_code/pymongo-tester.ipynb | 1355 +++++++++++++++++ .../challenge-1-checkpoint.ipynb | 391 +++++ 3 files changed, 1752 insertions(+) create mode 100644 module-2/lab-advance-querying-mongo/starter_code/.ipynb_checkpoints/pymongo-tester-checkpoint.ipynb create mode 100644 module-2/lab-advance-querying-mongo/starter_code/pymongo-tester.ipynb create mode 100755 module-2/lab-matplotlib-seaborn/your-code/.ipynb_checkpoints/challenge-1-checkpoint.ipynb diff --git a/module-2/lab-advance-querying-mongo/starter_code/.ipynb_checkpoints/pymongo-tester-checkpoint.ipynb b/module-2/lab-advance-querying-mongo/starter_code/.ipynb_checkpoints/pymongo-tester-checkpoint.ipynb new file mode 100644 index 0000000..7fec515 --- /dev/null +++ b/module-2/lab-advance-querying-mongo/starter_code/.ipynb_checkpoints/pymongo-tester-checkpoint.ipynb @@ -0,0 +1,6 @@ +{ + "cells": [], + "metadata": {}, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module-2/lab-advance-querying-mongo/starter_code/pymongo-tester.ipynb b/module-2/lab-advance-querying-mongo/starter_code/pymongo-tester.ipynb new file mode 100644 index 0000000..bce3bb6 --- /dev/null +++ b/module-2/lab-advance-querying-mongo/starter_code/pymongo-tester.ipynb @@ -0,0 +1,1355 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#import pymongo\n", + "#cliente = pymongo.MongoClient()\n", + "#cliente.list_databases.names()\n", + "\n", + "#nueva_base = cliente.nueva_base\n", + "#nueva_base.list_collection_names()\n", + "\n", + "#db.createCollection('test');" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import pymongo" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "cliente = pymongo.MongoClient()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Test', 'admin', 'config', 'local', 'nueva_db']" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cliente.list_database_names()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "nueva_base2 = cliente.nueva_base2" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Test', 'admin', 'config', 'local', 'nueva_db']" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cliente.list_database_names()" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "coleccion = nueva_base2.coleccion" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nueva_base2.list_collection_names()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dic1 = {'nombre':'Juan', 'edad':27}\n", + "\n", + "coleccion.insert_one(dic1)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27}]" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Test', 'admin', 'config', 'local', 'nueva_base2', 'nueva_db']" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cliente.list_database_names()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['coleccion']" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nueva_base2.list_collection_names()" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27}]" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dic2 = {'nombre':'anai', 'edad':24}\n", + "coleccion.insert_one(dic2)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24}]" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30}]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dic3 = {'nombre':'Angel', 'edad':30}\n", + "coleccion.insert_one(dic3)\n", + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25}]" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dic4 = {'nombre':'Diana', 'edad':25}\n", + "coleccion.insert_one(dic4)\n", + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20}]" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dic5 = {'nombre':'Belen', 'edad':20 }\n", + "coleccion.insert_one(dic5)\n", + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['coleccion']" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "nueva_base2.list_collection_names()" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20}]" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30}]" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find().limit(3))" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.insert_one({'_id':1, 'nombre':'José Juan', 'edad':28})" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28}]" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.insert_one({'_id':2, 'nombre':'Yona', 'edad':35})" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35}]" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(list(coleccion.find()))" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25}]" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find().limit(4))" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "7" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(list(coleccion.find()))" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 58, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.insert_many([\n", + " {'_id':3,'nombre':'Esteban', 'edad':45, 'altura':1.7},\n", + " {'_id':4,'nombre':'Alicia', 'edad':34, 'altura':1.5},\n", + " {'_id':5,'nombre':'Luz', 'edad':18, 'altura':1.65}\n", + "])" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65}]" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': 1, 'nombre': 'José Juan', 'edad': 28}]" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find({'edad':28}))" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5}]" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find({'edad':{'$gte':30}}))" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7}]" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find({'edad':{'$gte':35}}))" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find({'Edad':{'$gte':35}}))" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65}]" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find({'altura':{'$gte':1.51}}))" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65}]" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find().sort('edad',-1))" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e99030aa359803eff02b8d9'), 'nombre': 'anai', 'edad': 24},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5}]" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find().sort('nombre',-1))" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.delete_one({'nombre':'anai'})" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65}]" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.insert_one({'nomre':'Anai', 'edad':24, 'altura':1.45})" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45}]" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45}]" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find().sort('nombre',-1))" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35}]" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find().sort('nombre',1))" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35}]" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find().sort('nombre'))" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.update_one({'_id':'5e990c68a359803eff02b8dd'}, {'$set':{'_id':0}})" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45}]" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 90, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.update_one({'nombre':'Anai'}, {'$set':{'nombre':'Argelia Anai'}})" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'), 'nombre': 'Juan', 'edad': 27},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45}]" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 92, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.update_one({'nombre':'Juan'}, {'$set':{'nombre':'José Juan'}})" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'),\n", + " 'nombre': 'José Juan',\n", + " 'edad': 27},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45}]" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.update_one({'nombre':'Anai'}, {'$set':{'nombre':'Argelia Anai'}})" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'),\n", + " 'nombre': 'José Juan',\n", + " 'edad': 27},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45}]" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.delete_one({'nombre':'Anai'}) # borrar un elemento" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'),\n", + " 'nombre': 'José Juan',\n", + " 'edad': 27},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45}]" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.delete_one({'nombre':'Anai'}) # borrar un elemento" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.delete_one({'nombre':'Anai'}) # borrar un elemento" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "coleccion.delete_one({'nombre':'Anai'}) # borrar un elemento" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'_id': ObjectId('5e98fec6a359803eff02b8d8'),\n", + " 'nombre': 'José Juan',\n", + " 'edad': 27},\n", + " {'_id': ObjectId('5e99034ba359803eff02b8da'), 'nombre': 'Angel', 'edad': 30},\n", + " {'_id': ObjectId('5e9903a2a359803eff02b8db'), 'nombre': 'Diana', 'edad': 25},\n", + " {'_id': ObjectId('5e9903fda359803eff02b8dc'), 'nombre': 'Belen', 'edad': 20},\n", + " {'_id': 1, 'nombre': 'José Juan', 'edad': 28},\n", + " {'_id': 2, 'nombre': 'Yona', 'edad': 35},\n", + " {'_id': 3, 'nombre': 'Esteban', 'edad': 45, 'altura': 1.7},\n", + " {'_id': 4, 'nombre': 'Alicia', 'edad': 34, 'altura': 1.5},\n", + " {'_id': 5, 'nombre': 'Luz', 'edad': 18, 'altura': 1.65},\n", + " {'_id': ObjectId('5e990c68a359803eff02b8dd'),\n", + " 'nomre': 'Anai',\n", + " 'edad': 24,\n", + " 'altura': 1.45}]" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(coleccion.find())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/module-2/lab-matplotlib-seaborn/your-code/.ipynb_checkpoints/challenge-1-checkpoint.ipynb b/module-2/lab-matplotlib-seaborn/your-code/.ipynb_checkpoints/challenge-1-checkpoint.ipynb new file mode 100755 index 0000000..c522b6f --- /dev/null +++ b/module-2/lab-matplotlib-seaborn/your-code/.ipynb_checkpoints/challenge-1-checkpoint.ipynb @@ -0,0 +1,391 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Before you start :\n", + " - These exercises are related to the Exploratory data analysis using matplotlib and seaborn.\n", + " - Keep in mind that you need to use some of the functions you learned in the previous lessons.\n", + " - The datasets for Challenge 2 and 3 are provided in the `your-code` folder of this lab.\n", + " - Elaborate your codes and outputs as much as you can.\n", + " - Try your best to answer the questions and complete the tasks and most importantly enjoy the process!!!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Challenge 1" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Import all the libraries that are necessary." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# import libraries here\n", + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Define data." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "x = np.arange(0,100)\n", + "y = x*2\n", + "z = x**2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot (x,y) and (x,z) on the axes.\n", + "\n", + "#### There are 2 ways of doing this. Do in both ways.\n", + "\n", + "*Hint: Check out the `nrows`, `ncols`, and `index` arguments of [subplots](https://matplotlib.org/api/_as_gen/matplotlib.pyplot.subplot.html)*\n", + "\n", + "#### Also, play around with the linewidth and style. Use the ones you're most happy with." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# your code here-1st way\n", + "plt.subplot(1,2,1)\n", + "plt.plot(x,y,lw=3,color=\"b\", ls='--')\n", + "plt.subplot(1,2,2)\n", + "plt.plot(x,z,lw=3, color=\"r\",ls='-')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# your code here-2st way (call `subplots` only once not using the `index` parameter)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Augmenting your previous code, resize your previous plot.\n", + "\n", + "*Hint: Add the `figsize` argument in `plt.subplots()`*" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# your code here\n", + "fig,axes=plt.subplots(1,2)\n", + "axes[0].plot(x,y,color=\"b\", lw=3, ls='--')\n", + "axes[1].plot(x,z,color=\"r\", lw=3, ls='-')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Augmenting your previous code, label your axes.\n", + "\n", + "*Hint: call `set_xlabel` and `set_ylabel`*" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'z')" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# your code here\n", + "fig, axes = plt.subplots(nrows=1, ncols=2,figsize=(12,2))\n", + "\n", + "axes[0].plot(x,y,color=\"blue\", lw=5)\n", + "axes[0].set_xlabel('x')\n", + "axes[0].set_ylabel('y')\n", + "\n", + "axes[1].plot(x,z,color=\"red\", lw=3, ls='--')\n", + "axes[1].set_xlabel('x')\n", + "axes[1].set_ylabel('z')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Plot both `y=x^2` and `y=exp(x)` in the same plot using normal and logarithmic scale.\n", + "\n", + "*Hint: Use `set_xscale` and `set_yscale`*" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Logarithmic scale (y)')" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# your code here\n", + "fig, axes = plt.subplots(1, 2, figsize=(10,4))\n", + " \n", + "axes[0].plot(x, x**2,x, np.exp(x))\n", + "axes[0].set_title(\"Normal scale\")\n", + "\n", + "axes[1].plot(x, x**2,x, np.exp(x))\n", + "axes[1].set_yscale(\"log\")\n", + "axes[1].set_title(\"Logarithmic scale (y)\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### In the vehicles data set that you have downloaded, use the vehicles.csv file. In this exercise we will conduct some exploratory data analysis using one plot each of scatter plot, box plot, histogram, and bar chart. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Scatter Plot\n", + "\n", + "Please provide a scatter plot between \"Combined MPG\" as X variable and \n", + "\"Highway MPG\" as Y variable" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# your code here\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Box Whisker Plot\n", + "\n", + "Please provide a box plot of the variable \"CO2 Emission Grams/mile\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# your code here\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Histogram\n", + "\n", + "Please provide a histogram of the Fuel Barrels/Year" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# your code here\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Bar Chart\n", + "\n", + "Please provide a bar chart of the Fuel Type on the X axis and \"City MPG\" on the Y axis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# your code here\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From cbb805cf37334caa160d15b6e6412a59f534d004 Mon Sep 17 00:00:00 2001 From: herguejuan Date: Tue, 12 May 2020 23:11:38 -0500 Subject: [PATCH 4/4] Subiendo Lab supervised learning evaluation --- .../.ipynb_checkpoints/main-checkpoint.ipynb | 1770 +++++++++++++++++ .../your-code/main.ipynb | 1371 ++++++++++++- .../your-code/mushrooms.sav | Bin 0 -> 607811 bytes 3 files changed, 3083 insertions(+), 58 deletions(-) create mode 100755 module-3/lab-supervised-learning-evaluation/your-code/.ipynb_checkpoints/main-checkpoint.ipynb create mode 100644 module-3/lab-supervised-learning-evaluation/your-code/mushrooms.sav diff --git a/module-3/lab-supervised-learning-evaluation/your-code/.ipynb_checkpoints/main-checkpoint.ipynb b/module-3/lab-supervised-learning-evaluation/your-code/.ipynb_checkpoints/main-checkpoint.ipynb new file mode 100755 index 0000000..779a229 --- /dev/null +++ b/module-3/lab-supervised-learning-evaluation/your-code/.ipynb_checkpoints/main-checkpoint.ipynb @@ -0,0 +1,1770 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "# Before your start:\n", + "- Read the README.md file\n", + "- Comment as much as you can and use the resources in the README.md file\n", + "- Happy learning!" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# Import your libraries:\n", + "\n", + "import numpy as np\n", + "import pandas as pd" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Challenge 1 - Explore The Data\n", + "\n", + "This lesson will explore the creation of a machine learning pipeline from beggining to end. We will save our model and use the model to make predictions on data outside of our training sample. Let's start by loading the dataset which can be obtained from [Kaggle](https://www.kaggle.com/uciml/mushroom-classification) and [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/mushroom)." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# Loading the data\n", + "\n", + "mushrooms = pd.read_csv('../mushrooms.csv')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This dataset contains information about different types of mushrooms. Our response variable indicates whether a mushroom is poisonous. \n", + "\n", + "#### We will create a model to predict whether a mushroom is poisonous (the `class` column) using the information in all other columns.\n", + "\n", + "Let's print the `head()` of this dataset to see what columns we have in our data." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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5 rows × 23 columns

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" + ], + "text/plain": [ + " class cap-shape cap-surface cap-color bruises odor gill-attachment \\\n", + "0 p x s n t p f \n", + "1 e x s y t a f \n", + "2 e b s w t l f \n", + "3 p x y w t p f \n", + "4 e x s g f n f \n", + "\n", + " gill-spacing gill-size gill-color ... stalk-surface-below-ring \\\n", + "0 c n k ... s \n", + "1 c b k ... s \n", + "2 c b n ... s \n", + "3 c n n ... s \n", + "4 w b k ... s \n", + "\n", + " stalk-color-above-ring stalk-color-below-ring veil-type veil-color \\\n", + "0 w w p w \n", + "1 w w p w \n", + "2 w w p w \n", + "3 w w p w \n", + "4 w w p w \n", + "\n", + " ring-number ring-type spore-print-color population habitat \n", + "0 o p k s u \n", + "1 o p n n g \n", + "2 o p n n m \n", + "3 o p k s u \n", + "4 o e n a g \n", + "\n", + "[5 rows x 23 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here:\n", + "mushrooms.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### It looks like the columns in this dataset are coded. \n", + "\n", + "Let's examine the column types using `dtypes` to confirm this. " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "class object\n", + "cap-shape object\n", + "cap-surface object\n", + "cap-color object\n", + "bruises object\n", + "odor object\n", + "gill-attachment object\n", + "gill-spacing object\n", + "gill-size object\n", + "gill-color object\n", + "stalk-shape object\n", + "stalk-root object\n", + "stalk-surface-above-ring object\n", + "stalk-surface-below-ring object\n", + "stalk-color-above-ring object\n", + "stalk-color-below-ring object\n", + "veil-type object\n", + "veil-color object\n", + "ring-number object\n", + "ring-type object\n", + "spore-print-color object\n", + "population object\n", + "habitat object\n", + "dtype: object" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here:\n", + "mushrooms.dtypes" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this dataset, each column (feature) of the mushroom is represented by a single-character code. It would be best if we can obtain a dictionary of these codes so that we know what possible codes each column has and what each code represents. This dictionary can be obtained from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/mushroom). In the table below, we print the code dictionary for you to reference.\n", + "\n", + "| Features | Codes |\n", + "|---|---|\n", + "| classes | edible=e, poisonous=p |\n", + "| cap-shape | bell=b,conical=c,convex=x,flat=f,knobbed=k,sunken=s |\n", + "| cap-surface | fibrous=f,grooves=g,scaly=y,smooth=s |\n", + "| cap-color | brown=n,buff=b,cinnamon=c,gray=g,green=r,pink=p,purple=u,red=e,white=w,yellow=y |\n", + "| bruises | bruises=t,no=f |\n", + "| odor | almond=a,anise=l,creosote=c,fishy=y,foul=f,musty=m,none=n,pungent=p,spicy=s |\n", + "| gill-attachment | attached=a,descending=d,free=f,notched=n |\n", + "| gill-spacing | close=c,crowded=w,distant=d |\n", + "| gill-size | broad=b,narrow=n |\n", + "| gill-color | black=k,brown=n,buff=b,chocolate=h,gray=g, green=r,orange=o,pink=p,purple=u,red=e,white=w,yellow=y |\n", + "| stalk-shape | enlarging=e,tapering=t |\n", + "| stalk-root | bulbous=b,club=c,cup=u,equal=e,rhizomorphs=z,rooted=r,missing=? |\n", + "| stalk-surface-above-ring | fibrous=f,scaly=y,silky=k,smooth=s |\n", + "| stalk-surface-below-ring | fibrous=f,scaly=y,silky=k,smooth=s |\n", + "| stalk-color-above-ring | brown=n,buff=b,cinnamon=c,gray=g,orange=o,pink=p,red=e,white=w,yellow=y |\n", + "| stalk-color-below-ring | brown=n,buff=b,cinnamon=c,gray=g,orange=o,pink=p,red=e,white=w,yellow=y |\n", + "| veil-type | partial=p,universal=u |\n", + "| veil-color | brown=n,orange=o,white=w,yellow=y |\n", + "| ring-number | none=n,one=o,two=t |\n", + "| ring-type | cobwebby=c,evanescent=e,flaring=f,large=l,none=n,pendant=p,sheathing=s,zone=z |\n", + "| spore-print-color | black=k,brown=n,buff=b,chocolate=h,green=r,orange=o,purple=u,white=w,yellow=y |\n", + "| population | abundant=a,clustered=c,numerous=n,scattered=s,several=v,solitary=y |\n", + "| habitat | grasses=g,leaves=l,meadows=m,paths=p,urban=u,waste=w,woods=d\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**The columns in the mushrooms dataset seem to be correlated**. We suspect this because many columns seem to have dependencies. For example, if `ring-number` is `n` (none), `ring-type` must be `n` (none) too. Only when `ring-number` is `o` (one) or `t` (two) `ring-type` can be values other than `n`. Other columns may have inter-dependencies too but we can't tell right now. \n", + "\n", + "Why are we concerned about the variable correlations (also called *multicollinearity*)? It's because if they are strongly correlated, we shouldn't use the linear regression algorithm as the machine learning model. The prediction of the linear regression model is known to be unstable and inaccurate if the variables are strongly correlated. You can read more about why [here](https://en.wikipedia.org/wiki/Multicollinearity#Consequences_of_multicollinearity).\n", + "\n", + "So far it's just our suspicion that the variables are strongly correlated. We need to verify that. Since all the columns are categorical, we cannot use a correlation matrix to examine the degrees of correlations. There are several ways to test whether categorical variables are correlated. The first way is to convert the categorical values to ordinal, then calcualte the correlation matrix with the numerical values. The second way is to use a [Chi-Square test of independence](https://onlinecourses.science.psu.edu/stat500/node/56/) to find out whether there is correlation between each pair of variables. We will use the second way in this lab. So read the explanation of Chi-Square test of independence to understand what it does.\n", + "\n", + "We will begin with the first 2 variables (`cap-shape` and `cap-surface`). Our **null hypothesis of the Chi-Square test of independence is that the two variables are independent** and the **alternative hypothesis is that they are not independent**. To perform Chi-Squre test of independence, we first create a contingency table of those two features using Pandas' [`crosstab`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.crosstab.html) function, then use Scipy's [`chi2_contingency`](https://docs.scipy.org/doc/scipy-0.15.1/reference/generated/scipy.stats.chi2_contingency.html) to test the variable independence from the contingency table.\n", + "\n", + "#### In the following cell, create a contingency table of `cap-surface` and `cap-shape`. Assign this table to the variable `ct`." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + "cap-shape b c f k s x\n", + "cap-surface \n", + "f 52 0 1016 60 32 1160\n", + "g 1 1 1 1 0 0\n", + "s 244 0 820 418 0 1074\n", + "y 155 3 1315 349 0 1422" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here:\n", + "ct=pd.crosstab(mushrooms['cap-surface'], mushrooms['cap-shape'])\n", + "ct" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's import the chi quare test:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "from scipy.stats import chi2_contingency" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the following cell perform the chi square test on the contingency table using the function you just imported. This function wil return a tuple with 4 values. The second value in the tuple is the p-value for our test. Print the p-value and interpret the result - is the null hypothesis rejected? " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.635777687474967e-206" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here:\n", + "chi2_contingency(ct)[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "# Your comment here\n", + "#Se puede rechazar H0, el p-value es casi cero" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Now let's create a p-value matrix for all variables.\n", + "\n", + "In the cell below, create a 2-dimensional matrix of all pairwise tests for each two features. Print the matrix and interpret the results.\n", + "\n", + "Below is an example of what your matrix should look like:\n", + "![corr df](../corr_df.png)\n", + "\n", + "*Hint: Use loop inside loop to perform pairwise tests for each two features.*" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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classcap-shapecap-surfacecap-colorbruisesodorgill-attachmentgill-spacinggill-sizegill-color...stalk-surface-below-ringstalk-color-above-ringstalk-color-below-ringveil-typeveil-colorring-numberring-typespore-print-colorpopulationhabitat
class0.000000e+001.196457e-1035.518427e-686.055815e-780.000000e+000.000000e+005.501707e-315.022978e-2160.000000e+000.0...0.000000e+000.00.000000e+001.03.320973e-414.235758e-820.000000e+000.000000e+000.000000e+000.0
cap-shape1.196457e-1030.000000e+004.635778e-2061.249975e-2201.811119e-1120.000000e+003.135646e-401.879772e-105.169179e-2090.0...1.911102e-560.02.928263e-2211.01.661712e-2522.331652e-1321.793004e-2860.000000e+000.000000e+000.0
cap-surface5.518427e-684.635778e-2060.000000e+001.237998e-2431.359844e-315.624295e-2785.758186e-783.831131e-2013.449797e-1350.0...9.621957e-1450.00.000000e+001.03.845602e-896.790342e-323.975737e-2561.076398e-2630.000000e+000.0
cap-color6.055815e-781.249975e-2201.237998e-2430.000000e+002.347626e-770.000000e+007.290466e-1023.859462e-2740.000000e+000.0...0.000000e+000.00.000000e+001.06.121524e-1000.000000e+000.000000e+000.000000e+000.000000e+000.0
bruises0.000000e+001.811119e-1121.359844e-312.347626e-770.000000e+000.000000e+008.033466e-354.139756e-1605.662661e-2430.0...0.000000e+000.00.000000e+001.02.125442e-311.193039e-090.000000e+000.000000e+002.217266e-1560.0
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5 rows × 23 columns

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" + ], + "text/plain": [ + " class cap-shape cap-surface cap-color \\\n", + "class 0.000000e+00 1.196457e-103 5.518427e-68 6.055815e-78 \n", + "cap-shape 1.196457e-103 0.000000e+00 4.635778e-206 1.249975e-220 \n", + "cap-surface 5.518427e-68 4.635778e-206 0.000000e+00 1.237998e-243 \n", + "cap-color 6.055815e-78 1.249975e-220 1.237998e-243 0.000000e+00 \n", + "bruises 0.000000e+00 1.811119e-112 1.359844e-31 2.347626e-77 \n", + "\n", + " bruises odor gill-attachment gill-spacing \\\n", + "class 0.000000e+00 0.000000e+00 5.501707e-31 5.022978e-216 \n", + "cap-shape 1.811119e-112 0.000000e+00 3.135646e-40 1.879772e-10 \n", + "cap-surface 1.359844e-31 5.624295e-278 5.758186e-78 3.831131e-201 \n", + "cap-color 2.347626e-77 0.000000e+00 7.290466e-102 3.859462e-274 \n", + "bruises 0.000000e+00 0.000000e+00 8.033466e-35 4.139756e-160 \n", + "\n", + " gill-size gill-color ... stalk-surface-below-ring \\\n", + "class 0.000000e+00 0.0 ... 0.000000e+00 \n", + "cap-shape 5.169179e-209 0.0 ... 1.911102e-56 \n", + "cap-surface 3.449797e-135 0.0 ... 9.621957e-145 \n", + "cap-color 0.000000e+00 0.0 ... 0.000000e+00 \n", + "bruises 5.662661e-243 0.0 ... 0.000000e+00 \n", + "\n", + " stalk-color-above-ring stalk-color-below-ring veil-type \\\n", + "class 0.0 0.000000e+00 1.0 \n", + "cap-shape 0.0 2.928263e-221 1.0 \n", + "cap-surface 0.0 0.000000e+00 1.0 \n", + "cap-color 0.0 0.000000e+00 1.0 \n", + "bruises 0.0 0.000000e+00 1.0 \n", + "\n", + " veil-color ring-number ring-type spore-print-color \\\n", + "class 3.320973e-41 4.235758e-82 0.000000e+00 0.000000e+00 \n", + "cap-shape 1.661712e-252 2.331652e-132 1.793004e-286 0.000000e+00 \n", + "cap-surface 3.845602e-89 6.790342e-32 3.975737e-256 1.076398e-263 \n", + "cap-color 6.121524e-100 0.000000e+00 0.000000e+00 0.000000e+00 \n", + "bruises 2.125442e-31 1.193039e-09 0.000000e+00 0.000000e+00 \n", + "\n", + " population habitat \n", + "class 0.000000e+00 0.0 \n", + "cap-shape 0.000000e+00 0.0 \n", + "cap-surface 0.000000e+00 0.0 \n", + "cap-color 0.000000e+00 0.0 \n", + "bruises 2.217266e-156 0.0 \n", + "\n", + "[5 rows x 23 columns]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here:\n", + "res=[]\n", + "for e in mushrooms.columns:\n", + " p_valor=[]\n", + " for f in mushrooms.columns:\n", + " p_valor.append(chi2_contingency(pd.crosstab(mushrooms[e], mushrooms[f]))[1])\n", + " res.append(p_valor)\n", + "\n", + " p_matrix=pd.DataFrame(res)\n", + "p_matrix.columns=mushrooms.columns\n", + "p_matrix.index=mushrooms.columns\n", + "p_matrix.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "# Your comment here\n", + "\n", + "#Los elementos son dependientes uno de otro" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We verified the variables are highly correlated from the pairwise Chi-Square test of independence.\n", + "\n", + "#### The next step in model generation is to ensure there is no missing data and handle any missing data if they exist.\n", + "\n", + "In the next cell, check to see if there is any missing data in each column of the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "class 0\n", + "cap-shape 0\n", + "cap-surface 0\n", + "cap-color 0\n", + "bruises 0\n", + "odor 0\n", + "gill-attachment 0\n", + "gill-spacing 0\n", + "gill-size 0\n", + "gill-color 0\n", + "stalk-shape 0\n", + "stalk-root 0\n", + "stalk-surface-above-ring 0\n", + "stalk-surface-below-ring 0\n", + "stalk-color-above-ring 0\n", + "stalk-color-below-ring 0\n", + "veil-type 0\n", + "veil-color 0\n", + "ring-number 0\n", + "ring-type 0\n", + "spore-print-color 0\n", + "population 0\n", + "habitat 0\n", + "dtype: int64" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here:\n", + "p_matrix.isnull().sum()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Since there is no work to be done to clean up missing data, the next step is to create dummy variables. \n", + "\n", + "Most machine learning algorithms cannot work with non-numeric data, so we will need to transform our data. Use the [`get_dummies` function](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.get_dummies.html) to transform the data. Make sure to remove one dummy column per variable using the `drop_first=True` option." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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class_pcap-shape_ccap-shape_fcap-shape_kcap-shape_scap-shape_xcap-surface_gcap-surface_scap-surface_ycap-color_c...population_npopulation_spopulation_vpopulation_yhabitat_ghabitat_lhabitat_mhabitat_phabitat_uhabitat_w
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" + ], + "text/plain": [ + " class_p cap-shape_c cap-shape_f cap-shape_k cap-shape_s cap-shape_x \\\n", + "0 1 0 0 0 0 1 \n", + "1 0 0 0 0 0 1 \n", + "2 0 0 0 0 0 0 \n", + "3 1 0 0 0 0 1 \n", + "4 0 0 0 0 0 1 \n", + "\n", + " cap-surface_g cap-surface_s cap-surface_y cap-color_c ... \\\n", + "0 0 1 0 0 ... \n", + "1 0 1 0 0 ... \n", + "2 0 1 0 0 ... \n", + "3 0 0 1 0 ... \n", + "4 0 1 0 0 ... \n", + "\n", + " population_n population_s population_v population_y habitat_g \\\n", + "0 0 1 0 0 0 \n", + "1 1 0 0 0 1 \n", + "2 1 0 0 0 0 \n", + "3 0 1 0 0 0 \n", + "4 0 0 0 0 1 \n", + "\n", + " habitat_l habitat_m habitat_p habitat_u habitat_w \n", + "0 0 0 0 1 0 \n", + "1 0 0 0 0 0 \n", + "2 0 1 0 0 0 \n", + "3 0 0 0 1 0 \n", + "4 0 0 0 0 0 \n", + "\n", + "[5 rows x 96 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here:\n", + "dummie=pd.get_dummies(mushrooms, columns=mushrooms.columns,drop_first=True)\n", + "dummie.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Our final data exploration task is to prepare the data for modeling by splitting it to predictor, response, train and test. \n", + "\n", + "We will do this using the [`train_test_split` function from scikit-learn](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html). In the cell below, split the data to `X_train`, `X_test`, `y_train`, and `y_test` using this function. Select 80% of the data for the training sample and the rest for the test sample." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.model_selection import train_test_split\n", + "\n", + "# Your code here:\n", + "X=dummie.drop(columns='class_p')\n", + "y=dummie['class_p']\n", + "X_train, X_test, y_train, y_test=train_test_split(X, y, test_size=0.2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Challenge 2 - Creating and Saving Our Model\n", + "\n", + "Determining whether a mushroom is poisonous is a classification task. There are multiple classification models we can choose from.\n", + "However, since we have determined that there are many columns that are not indepdendent, this limits our choice of model. One model we will not consider is logistic regression. Two potential choices for this modeling task are [random forest](https://en.wikipedia.org/wiki/Random_forest) and [SVM](https://en.wikipedia.org/wiki/Support_vector_machine).\n", + "\n", + "Let's start with Random Forest. We think of random forest as a voting algorithm. We generate many decision trees by sampling both rows and columns in our dataset. Each one of these trees produces a decision. We let all the trees \"vote\" and the aggregate decision that they produce gives us the final decision for our algorithm (in this case, they will vote whether each mushroom is poisonous or edible). To learn more about random forests, click [here](https://onlinecourses.science.psu.edu/stat857/node/179/).\n", + "\n", + "In the cell below, we will import and initialize a random forest from scikit-learn ([documentation](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html)). Assign the initialized model to `mushroom_rf`. For now, we will just use the default settings for the random forest classifier, so there is no need to pass any arguments to the function." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "# Your code here:\n", + "mushroom_rf=RandomForestClassifier(n_estimators=100)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In the cell below, fit the model to the training data." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here:\n", + "mushroom_rf=mushroom_rf.fit(X_train, y_train)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Next, let's evaluate the model. One of the most straightforward ways to evaluate a classification model is using a confusion matrix. \n", + "\n", + "The confusion matrix shows us the true positives, false positives, false negatives and true negatives in the data. Our goal is to maximize the true positives and true negatives (the observations that are correctly classified) and minimize the false positives and false negatives.\n", + "\n", + "In the cell below, we'll start by generating predictions for the test data using the `predict` function. " + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1 1 1 ... 1 0 0]\n", + "Test: 1.00\n", + "\n" + ] + } + ], + "source": [ + "# Your code here:\n", + "y_pred=mushroom_rf.predict(X_test)\n", + "score=mushroom_rf.score(X_test, y_test)\n", + "print (y_pred)\n", + "print ('Test: {:.2f}\\n'.format(score))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now we'll import the `confusion_matrix` function ([documentation](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html)) and compute the [confusion matrix](https://en.wikipedia.org/wiki/Confusion_matrix) by comparing the observed data (`y_test`) and the predicted data that you found in the cell above." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[862, 0],\n", + " [ 0, 763]])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "\n", + "from sklearn.metrics import confusion_matrix\n", + "\n", + "# Your code here:\n", + "confusion=confusion_matrix(y_test, y_pred)\n", + "confusion" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Bonus Challenge 1 - Use a Different ML Algorithm to Evaluate Model\n", + "\n", + "Repeat the steps here to predict and evaluate the model but instead use gradient boosted classification. Your end result should be a confusion matrix comparing the predicted and observed y values for the test sample. You can read more about gradient boosting [here](http://blog.kaggle.com/2017/01/23/a-kaggle-master-explains-gradient-boosting/).\n", + "\n", + "To calculate the gradient boosted classfication, use the [`GradientBoostingClassifier` of Scikit-Learn](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html)." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Entrenamiento: 1.00\n", + "Test: 1.00\n", + "\n", + "[[862 0]\n", + " [ 2 761]]\n" + ] + } + ], + "source": [ + "from sklearn.ensemble import GradientBoostingClassifier\n", + "\n", + "# Your code here:\n", + "gb=GradientBoostingClassifier().fit(X_train, y_train)\n", + "print ('Entrenamiento: {:.2f}'.format(gb.score(X_train, y_train))) \n", + "print ('Test: {:.2f}\\n'.format(gb.score(X_test, y_test)))\n", + "y_pred=gb.predict(X_test)\n", + "confusion_gb=confusion_matrix(y_test, y_pred)\n", + "print (confusion_gb)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Challenge 3 - Producing Individual Predictions and Saving The Model\n", + "\n", + "One of the most important goals of machine learning models is to act as something like a prediction black box. We would like to pass an observation to the model and get back a prediction as an output. Let's do this in the next cells using the `predict` function. What we want to do is to pick a random mushroom and generate a prediction that will tell us whether it is poisonous.\n", + "\n", + "#### In the next cell, create a function called `get_random_data` that accepts a dataset and returns a random row from the dataset." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "from random import seed\n", + "from random import randint\n", + "\n", + "def get_random_data(dataset):\n", + " \"\"\"\n", + " Returns a random row of a dataset\n", + " \n", + " Args:\n", + " dataset [dataframe]: a Pandas dataframe containing a dataset\n", + " \n", + " Returns:\n", + " A random row in the dataset\n", + " \"\"\"\n", + " # Your code here\n", + " return dataset.drop(columns='class_p').sample()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Call `get_random_data` to obtain a random row from the test dataset. Assign the returned row to `random_mushroom` and print." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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cap-shape_ccap-shape_fcap-shape_kcap-shape_scap-shape_xcap-surface_gcap-surface_scap-surface_ycap-color_ccap-color_e...population_npopulation_spopulation_vpopulation_yhabitat_ghabitat_lhabitat_mhabitat_phabitat_uhabitat_w
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" + ], + "text/plain": [ + " cap-shape_c cap-shape_f cap-shape_k cap-shape_s cap-shape_x \\\n", + "7514 0 0 0 0 1 \n", + "\n", + " cap-surface_g cap-surface_s cap-surface_y cap-color_c cap-color_e \\\n", + "7514 0 0 0 0 0 \n", + "\n", + " ... population_n population_s population_v population_y habitat_g \\\n", + "7514 ... 1 0 0 0 1 \n", + "\n", + " habitat_l habitat_m habitat_p habitat_u habitat_w \n", + "7514 0 0 0 0 0 \n", + "\n", + "[1 rows x 95 columns]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Your code here\n", + "random_mushroom=get_random_data(dummie)\n", + "random_mushroom" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### In the cell below, use the `predict` function to generate a prediction for this random mushroom. Is the random mushroom poisonous? Compare this to the true y value." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test aleatorio\n", + "Probabilidad comestible: 0.998458\n", + "Probabilidad venenoso : 0.001542\n", + "[ True]\n" + ] + } + ], + "source": [ + "# Your code here:\n", + "print ('Test aleatorio')\n", + "print ('Probabilidad comestible: {:.6f}'.format(gb.predict_proba(random_mushroom)[0][0]))\n", + "print ('Probabilidad venenoso : {:.6f}'.format(gb.predict_proba(random_mushroom)[0][1]))\n", + "\n", + "# sera verdadera la prediccion si este print sale True\n", + "print (dummie.iloc[random_mushroom.index[0]].class_p==gb.predict(random_mushroom))" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "# Your comment here\n", + "\n", + "#Los datos presentan un 99% de prob de ser un hongo comestible" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Our final step is to save our model. \n", + "\n", + "Do this in the cell below using [pickling](https://docs.python.org/3/library/pickle.html). Import the pickle library and save the `mushroom_rf` model as a pickle file using `pickle.dump()`. Name your file `mushrooms.sav`" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "import pickle\n", + "\n", + "# Your code here:\n", + "out=open('mushrooms.sav','wb')\n", + "pickle.dump(mushroom_rf, out)\n", + "out.close()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Bonus Challenge 2 - Heatmap to Visualize Data Correlation\n", + "\n", + "Practice generating a heatmap to visualize the pairwise column correlations. You can do one of the following two things (or both if you like):\n", + "\n", + "* Create a heatmap using the p-value matrix for the pairwise Chi-Square test of independence. \n", + "\n", + "* Use Scikit-Learn's `LabelEncoder` ([documentation](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelEncoder.html)) to transform the raw categorical variables to ordinal. Then calculate the correlation matrix using the ordinal values.\n", + "\n", + "If you're scratching your hairs off, refer to [this example for the first way](https://towardsdatascience.com/the-search-for-categorical-correlation-a1cf7f1888c9) and [this example for the second way](https://www.kaggle.com/haimfeld87/analysis-and-classification-of-mushrooms). " + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "# Your code here\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn import preprocessing\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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classcap-shapecap-surfacecap-colorbruisesodorgill-attachmentgill-spacinggill-sizegill-color...stalk-surface-below-ringstalk-color-above-ringstalk-color-below-ringveil-typeveil-colorring-numberring-typespore-print-colorpopulationhabitat
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" + ], + "text/plain": [ + " class cap-shape cap-surface cap-color bruises odor \\\n", + "class 0 11 12 6 0 0 \n", + "cap-shape 3 0 5 3 4 0 \n", + "cap-surface 6 6 0 2 7 1 \n", + "cap-color 5 4 4 0 5 0 \n", + "bruises 0 10 14 7 0 0 \n", + "\n", + " gill-attachment gill-spacing gill-size gill-color ... \\\n", + "class 11 5 0 0 ... \n", + "cap-shape 9 15 3 0 ... \n", + "cap-surface 6 6 5 0 ... \n", + "cap-color 4 3 0 0 ... \n", + "bruises 10 9 1 0 ... \n", + "\n", + " stalk-surface-below-ring stalk-color-above-ring \\\n", + "class 0 0 \n", + "cap-shape 6 0 \n", + "cap-surface 4 0 \n", + "cap-color 0 0 \n", + "bruises 0 0 \n", + "\n", + " stalk-color-below-ring veil-type veil-color ring-number \\\n", + "class 0 0 9 6 \n", + "cap-shape 2 0 2 4 \n", + "cap-surface 0 0 5 10 \n", + "cap-color 0 0 4 0 \n", + "bruises 0 0 11 11 \n", + "\n", + " ring-type spore-print-color population habitat \n", + "class 0 0 0 0 \n", + "cap-shape 1 0 0 0 \n", + "cap-surface 2 1 0 0 \n", + "cap-color 0 0 0 0 \n", + "bruises 0 0 3 0 \n", + "\n", + "[5 rows x 23 columns]" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "heat_matrix=p_matrix.apply(preprocessing.LabelEncoder().fit_transform)\n", + "heat_matrix.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ], + "text/plain": [ + " class_p cap-shape_c cap-shape_f cap-shape_k cap-shape_s cap-shape_x \\\n", + "0 1 0 0 0 0 1 \n", + "1 0 0 0 0 0 1 \n", + "2 0 0 0 0 0 0 \n", + "3 1 0 0 0 0 1 \n", + "4 0 0 0 0 0 1 \n", + "\n", + " cap-surface_g cap-surface_s cap-surface_y cap-color_c ... \\\n", + "0 0 1 0 0 ... \n", + "1 0 1 0 0 ... \n", + "2 0 1 0 0 ... \n", + "3 0 0 1 0 ... \n", + "4 0 1 0 0 ... \n", + "\n", + " population_n population_s population_v population_y habitat_g \\\n", + "0 0 1 0 0 0 \n", + "1 1 0 0 0 1 \n", + "2 1 0 0 0 0 \n", + "3 0 1 0 0 0 \n", + "4 0 0 0 0 1 \n", + "\n", + " habitat_l habitat_m habitat_p habitat_u habitat_w \n", + "0 0 0 0 1 0 \n", + "1 0 0 0 0 0 \n", + "2 0 1 0 0 0 \n", + "3 0 0 0 1 0 \n", + "4 0 0 0 0 0 \n", + "\n", + "[5 rows x 96 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here:\n" + "# Your code here:\n", + "dummie=pd.get_dummies(mushrooms, columns=mushrooms.columns,drop_first=True)\n", + "dummie.head()" ] }, { @@ -261,13 +1090,16 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "\n", - "# Your code here:\n" + "# Your code here:\n", + "X=dummie.drop(columns='class_p')\n", + "y=dummie['class_p']\n", + "X_train, X_test, y_train, y_test=train_test_split(X, y, test_size=0.2)" ] }, { @@ -286,13 +1118,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "from sklearn.ensemble import RandomForestClassifier\n", "\n", - "# Your code here:\n" + "# Your code here:\n", + "mushroom_rf=RandomForestClassifier(n_estimators=100)" ] }, { @@ -304,11 +1137,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ - "# Your code here:\n" + "# Your code here:\n", + "mushroom_rf=mushroom_rf.fit(X_train, y_train)" ] }, { @@ -324,11 +1158,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[1 1 1 ... 1 0 0]\n", + "Test: 1.00\n", + "\n" + ] + } + ], "source": [ - "# Your code here:\n" + "# Your code here:\n", + "y_pred=mushroom_rf.predict(X_test)\n", + "score=mushroom_rf.score(X_test, y_test)\n", + "print (y_pred)\n", + "print ('Test: {:.2f}\\n'.format(score))" ] }, { @@ -340,13 +1188,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([[862, 0],\n", + " [ 0, 763]])" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ + "\n", "from sklearn.metrics import confusion_matrix\n", "\n", - "# Your code here:\n" + "# Your code here:\n", + "confusion=confusion_matrix(y_test, y_pred)\n", + "confusion" ] }, { @@ -362,13 +1225,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Entrenamiento: 1.00\n", + "Test: 1.00\n", + "\n", + "[[862 0]\n", + " [ 2 761]]\n" + ] + } + ], "source": [ "from sklearn.ensemble import GradientBoostingClassifier\n", "\n", - "# Your code here:\n" + "# Your code here:\n", + "gb=GradientBoostingClassifier().fit(X_train, y_train)\n", + "print ('Entrenamiento: {:.2f}'.format(gb.score(X_train, y_train))) \n", + "print ('Test: {:.2f}\\n'.format(gb.score(X_test, y_test)))\n", + "y_pred=gb.predict(X_test)\n", + "confusion_gb=confusion_matrix(y_test, y_pred)\n", + "print (confusion_gb)\n" ] }, { @@ -384,7 +1265,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -402,7 +1283,7 @@ " A random row in the dataset\n", " \"\"\"\n", " # Your code here\n", - " return None" + " return dataset.drop(columns='class_p').sample()" ] }, { @@ -414,11 +1295,108 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " cap-shape_c cap-shape_f cap-shape_k cap-shape_s cap-shape_x \\\n", + "7514 0 0 0 0 1 \n", + "\n", + " cap-surface_g cap-surface_s cap-surface_y cap-color_c cap-color_e \\\n", + "7514 0 0 0 0 0 \n", + "\n", + " ... population_n population_s population_v population_y habitat_g \\\n", + "7514 ... 1 0 0 0 1 \n", + "\n", + " habitat_l habitat_m habitat_p habitat_u habitat_w \n", + "7514 0 0 0 0 0 \n", + "\n", + "[1 rows x 95 columns]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "# Your code here\n" + "# Your code here\n", + "random_mushroom=get_random_data(dummie)\n", + "random_mushroom" ] }, { @@ -430,20 +1408,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test aleatorio\n", + "Probabilidad comestible: 0.998458\n", + "Probabilidad venenoso : 0.001542\n", + "[ True]\n" + ] + } + ], "source": [ - "# Your code here:\n" + "# Your code here:\n", + "print ('Test aleatorio')\n", + "print ('Probabilidad comestible: {:.6f}'.format(gb.predict_proba(random_mushroom)[0][0]))\n", + "print ('Probabilidad venenoso : {:.6f}'.format(gb.predict_proba(random_mushroom)[0][1]))\n", + "\n", + "# sera verdadera la prediccion si este print sale True\n", + "print (dummie.iloc[random_mushroom.index[0]].class_p==gb.predict(random_mushroom))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, "outputs": [], "source": [ - "# Your comment here" + "# Your comment here\n", + "\n", + "#Los datos presentan un 99% de prob de ser un hongo comestible" ] }, { @@ -457,13 +1454,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ + "\n", "import pickle\n", "\n", - "# Your code here:\n" + "# Your code here:\n", + "out=open('mushrooms.sav','wb')\n", + "pickle.dump(mushroom_rf, out)\n", + "out.close()\n" ] }, { @@ -483,11 +1484,265 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ - "# Your code here" + "# Your code here\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn import preprocessing\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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classcap-shapecap-surfacecap-colorbruisesodorgill-attachmentgill-spacinggill-sizegill-color...stalk-surface-below-ringstalk-color-above-ringstalk-color-below-ringveil-typeveil-colorring-numberring-typespore-print-colorpopulationhabitat
class0111260011500...0000960000
cap-shape30534091530...6020241000
cap-surface6602716650...40005102100
cap-color5440504300...0000400000
bruises0101470010910...000011110030
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5 rows × 23 columns

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" + ], + "text/plain": [ + " class cap-shape cap-surface cap-color bruises odor \\\n", + "class 0 11 12 6 0 0 \n", + "cap-shape 3 0 5 3 4 0 \n", + "cap-surface 6 6 0 2 7 1 \n", + "cap-color 5 4 4 0 5 0 \n", + "bruises 0 10 14 7 0 0 \n", + "\n", + " gill-attachment gill-spacing gill-size gill-color ... \\\n", + "class 11 5 0 0 ... \n", + "cap-shape 9 15 3 0 ... \n", + "cap-surface 6 6 5 0 ... \n", + "cap-color 4 3 0 0 ... \n", + "bruises 10 9 1 0 ... \n", + "\n", + " stalk-surface-below-ring stalk-color-above-ring \\\n", + "class 0 0 \n", + "cap-shape 6 0 \n", + "cap-surface 4 0 \n", + "cap-color 0 0 \n", + "bruises 0 0 \n", + "\n", + " stalk-color-below-ring veil-type veil-color ring-number \\\n", + "class 0 0 9 6 \n", + "cap-shape 2 0 2 4 \n", + "cap-surface 0 0 5 10 \n", + "cap-color 0 0 4 0 \n", + "bruises 0 0 11 11 \n", + "\n", + " ring-type spore-print-color population habitat \n", + "class 0 0 0 0 \n", + "cap-shape 1 0 0 0 \n", + "cap-surface 2 1 0 0 \n", + "cap-color 0 0 0 0 \n", + "bruises 0 0 3 0 \n", + "\n", + "[5 rows x 23 columns]" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "heat_matrix=p_matrix.apply(preprocessing.LabelEncoder().fit_transform)\n", + "heat_matrix.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(15,15))\n", + "sns.heatmap(heat_matrix.corr(),annot=True)\n", + "plt.yticks(rotation=0)\n", + "plt.xticks(rotation=75)\n", + "plt.title('HeatMap Correlation')\n", + "plt.show();\n" ] } ], @@ -507,7 +1762,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.1" + "version": "3.7.6" } }, "nbformat": 4, diff --git a/module-3/lab-supervised-learning-evaluation/your-code/mushrooms.sav b/module-3/lab-supervised-learning-evaluation/your-code/mushrooms.sav new file mode 100644 index 0000000000000000000000000000000000000000..8cf2f32e067dd2fb13dde1b420e4184310251732 GIT binary patch literal 607811 zcmcG%2Ygk<5-@%!LZlgr6s3d^Ap%0^ojnkGAcRW`JtPD!NXb215RmAl1yI4Lpa=?) zqLGIh!GeOms0diVfJhU_Re6f#DK_LOPye%LXEwX%`hMS%@B5$M{q3BY+1Xxa_UsLn z%b0uT%*@Ho>{gkx=Vs1IpPAWe($qOl=Ghw&fQoy=> zNuW%2plp0;Iz$<$3`8fprNaGj 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