From fd10061a0b074e4a67fae767358cb89a81bce5ab Mon Sep 17 00:00:00 2001 From: Mohammad Date: Wed, 24 Jan 2018 14:03:15 -0600 Subject: [PATCH] sync --- .ipynb_checkpoints/titanic-checkpoint.ipynb | 1832 +++++++++++++++++++ titanic.ipynb | 1832 +++++++++++++++++++ 2 files changed, 3664 insertions(+) create mode 100644 .ipynb_checkpoints/titanic-checkpoint.ipynb create mode 100644 titanic.ipynb diff --git a/.ipynb_checkpoints/titanic-checkpoint.ipynb b/.ipynb_checkpoints/titanic-checkpoint.ipynb new file mode 100644 index 0000000..cf51545 --- /dev/null +++ b/.ipynb_checkpoints/titanic-checkpoint.ipynb @@ -0,0 +1,1832 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from itertools import combinations\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.metrics import confusion_matrix\n", + "from sklearn.model_selection import train_test_split\n", + "from pandas.plotting import scatter_matrix\n", + "%matplotlib inline\n", + "\n", + "pd.options.display.max_colwidth = 100" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df = pd.read_csv('data.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
1211Cumings, Mrs. John Bradley (Florence Briggs Thayer)female38.010PC 1759971.2833C85C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
4503Allen, Mr. William Henrymale35.0003734508.0500NaNS
\n", + "
" + ], + "text/plain": [ + " PassengerId Survived Pclass \\\n", + "0 1 0 3 \n", + "1 2 1 1 \n", + "2 3 1 3 \n", + "3 4 1 1 \n", + "4 5 0 3 \n", + "\n", + " Name Sex Age SibSp \\\n", + "0 Braund, Mr. Owen Harris male 22.0 1 \n", + "1 Cumings, Mrs. John Bradley (Florence Briggs Thayer) female 38.0 1 \n", + "2 Heikkinen, Miss. Laina female 26.0 0 \n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n", + "4 Allen, Mr. William Henry male 35.0 0 \n", + "\n", + " Parch Ticket Fare Cabin Embarked \n", + "0 0 A/5 21171 7.2500 NaN S \n", + "1 0 PC 17599 71.2833 C85 C \n", + "2 0 STON/O2. 3101282 7.9250 NaN S \n", + "3 0 113803 53.1000 C123 S \n", + "4 0 373450 8.0500 NaN S " + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
countmeanstdmin25%50%75%max
PassengerId891.0446.000000257.3538421.00223.5000446.0000668.5891.0000
Survived891.00.3838380.4865920.000.00000.00001.01.0000
Pclass891.02.3086420.8360711.002.00003.00003.03.0000
Age714.029.69911814.5264970.4220.125028.000038.080.0000
SibSp891.00.5230081.1027430.000.00000.00001.08.0000
Parch891.00.3815940.8060570.000.00000.00000.06.0000
Fare891.032.20420849.6934290.007.910414.454231.0512.3292
\n", + "
" + ], + "text/plain": [ + " count mean std min 25% 50% 75% \\\n", + "PassengerId 891.0 446.000000 257.353842 1.00 223.5000 446.0000 668.5 \n", + "Survived 891.0 0.383838 0.486592 0.00 0.0000 0.0000 1.0 \n", + "Pclass 891.0 2.308642 0.836071 1.00 2.0000 3.0000 3.0 \n", + "Age 714.0 29.699118 14.526497 0.42 20.1250 28.0000 38.0 \n", + "SibSp 891.0 0.523008 1.102743 0.00 0.0000 0.0000 1.0 \n", + "Parch 891.0 0.381594 0.806057 0.00 0.0000 0.0000 0.0 \n", + "Fare 891.0 32.204208 49.693429 0.00 7.9104 14.4542 31.0 \n", + "\n", + " max \n", + "PassengerId 891.0000 \n", + "Survived 1.0000 \n", + "Pclass 3.0000 \n", + "Age 80.0000 \n", + "SibSp 8.0000 \n", + "Parch 6.0000 \n", + "Fare 512.3292 " + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 891 entries, 0 to 890\n", + "Data columns (total 12 columns):\n", + "PassengerId 891 non-null int64\n", + "Survived 891 non-null int64\n", + "Pclass 891 non-null int64\n", + "Name 891 non-null object\n", + "Sex 891 non-null object\n", + "Age 714 non-null float64\n", + "SibSp 891 non-null int64\n", + "Parch 891 non-null int64\n", + "Ticket 891 non-null object\n", + "Fare 891 non-null float64\n", + "Cabin 204 non-null object\n", + "Embarked 889 non-null object\n", + "dtypes: float64(2), int64(5), object(5)\n", + "memory usage: 83.6+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df = df.fillna(99)" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 891 entries, 0 to 890\n", + "Data columns (total 12 columns):\n", + "PassengerId 891 non-null int64\n", + "Survived 891 non-null int64\n", + "Pclass 891 non-null int64\n", + "Name 891 non-null object\n", + "Sex 891 non-null object\n", + "Age 891 non-null float64\n", + "SibSp 891 non-null int64\n", + "Parch 891 non-null int64\n", + "Ticket 891 non-null object\n", + "Fare 891 non-null float64\n", + "Cabin 891 non-null object\n", + "Embarked 891 non-null object\n", + "dtypes: float64(2), int64(5), object(5)\n", + "memory usage: 83.6+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
countmeanstdmin25%50%75%max
PassengerId891.0446.000000257.3538421.00223.5000446.0000668.5891.0000
Survived891.00.3838380.4865920.000.00000.00001.01.0000
Pclass891.02.3086420.8360711.002.00003.00003.03.0000
Age891.043.46596030.5686080.4222.000032.000054.099.0000
SibSp891.00.5230081.1027430.000.00000.00001.08.0000
Parch891.00.3815940.8060570.000.00000.00000.06.0000
Fare891.032.20420849.6934290.007.910414.454231.0512.3292
\n", + "
" + ], + "text/plain": [ + " count mean std min 25% 50% 75% \\\n", + "PassengerId 891.0 446.000000 257.353842 1.00 223.5000 446.0000 668.5 \n", + "Survived 891.0 0.383838 0.486592 0.00 0.0000 0.0000 1.0 \n", + "Pclass 891.0 2.308642 0.836071 1.00 2.0000 3.0000 3.0 \n", + "Age 891.0 43.465960 30.568608 0.42 22.0000 32.0000 54.0 \n", + "SibSp 891.0 0.523008 1.102743 0.00 0.0000 0.0000 1.0 \n", + "Parch 891.0 0.381594 0.806057 0.00 0.0000 0.0000 0.0 \n", + "Fare 891.0 32.204208 49.693429 0.00 7.9104 14.4542 31.0 \n", + "\n", + " max \n", + "PassengerId 891.0000 \n", + "Survived 1.0000 \n", + "Pclass 3.0000 \n", + "Age 99.0000 \n", + "SibSp 8.0000 \n", + "Parch 6.0000 \n", + "Fare 512.3292 " + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['S', 'C', 'Q', 99], dtype=object)" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.Embarked.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [], + "source": [ + "df['Sex'] = df.Sex.map({'male':1, 'female':2})\n", + "df['Embarked'] = df.Embarked.map({'C':1, 'Q':2, 'S':3, 99:9})" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 1, 2, 9], dtype=int64)" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.Embarked.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarkedCabin_L
0103Braund, Mr. Owen Harris122.010A/5 211717.25009939
1211Cumings, Mrs. John Bradley (Florence Briggs Thayer)238.010PC 1759971.2833C851C
2313Heikkinen, Miss. Laina226.000STON/O2. 31012827.92509939
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)235.01011380353.1000C1233C
4503Allen, Mr. William Henry135.0003734508.05009939
5603Moran, Mr. James199.0003308778.45839929
6701McCarthy, Mr. Timothy J154.0001746351.8625E463E
7803Palsson, Master. Gosta Leonard12.03134990921.07509939
8913Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)227.00234774211.13339939
91012Nasser, Mrs. Nicholas (Adele Achem)214.01023773630.07089919
101113Sandstrom, Miss. Marguerite Rut24.011PP 954916.7000G63G
111211Bonnell, Miss. Elizabeth258.00011378326.5500C1033C
121303Saundercock, Mr. William Henry120.000A/5. 21518.05009939
131403Andersson, Mr. Anders Johan139.01534708231.27509939
141503Vestrom, Miss. Hulda Amanda Adolfina214.0003504067.85429939
151612Hewlett, Mrs. (Mary D Kingcome)255.00024870616.00009939
161703Rice, Master. Eugene12.04138265229.12509929
171812Williams, Mr. Charles Eugene199.00024437313.00009939
181903Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)231.01034576318.00009939
192013Masselmani, Mrs. Fatima299.00026497.22509919
\n", + "
" + ], + "text/plain": [ + " PassengerId Survived Pclass \\\n", + "0 1 0 3 \n", + "1 2 1 1 \n", + "2 3 1 3 \n", + "3 4 1 1 \n", + "4 5 0 3 \n", + "5 6 0 3 \n", + "6 7 0 1 \n", + "7 8 0 3 \n", + "8 9 1 3 \n", + "9 10 1 2 \n", + "10 11 1 3 \n", + "11 12 1 1 \n", + "12 13 0 3 \n", + "13 14 0 3 \n", + "14 15 0 3 \n", + "15 16 1 2 \n", + "16 17 0 3 \n", + "17 18 1 2 \n", + "18 19 0 3 \n", + "19 20 1 3 \n", + "\n", + " Name Sex Age SibSp \\\n", + "0 Braund, Mr. Owen Harris 1 22.0 1 \n", + "1 Cumings, Mrs. John Bradley (Florence Briggs Thayer) 2 38.0 1 \n", + "2 Heikkinen, Miss. Laina 2 26.0 0 \n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) 2 35.0 1 \n", + "4 Allen, Mr. William Henry 1 35.0 0 \n", + "5 Moran, Mr. James 1 99.0 0 \n", + "6 McCarthy, Mr. Timothy J 1 54.0 0 \n", + "7 Palsson, Master. Gosta Leonard 1 2.0 3 \n", + "8 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) 2 27.0 0 \n", + "9 Nasser, Mrs. Nicholas (Adele Achem) 2 14.0 1 \n", + "10 Sandstrom, Miss. Marguerite Rut 2 4.0 1 \n", + "11 Bonnell, Miss. Elizabeth 2 58.0 0 \n", + "12 Saundercock, Mr. William Henry 1 20.0 0 \n", + "13 Andersson, Mr. Anders Johan 1 39.0 1 \n", + "14 Vestrom, Miss. Hulda Amanda Adolfina 2 14.0 0 \n", + "15 Hewlett, Mrs. (Mary D Kingcome) 2 55.0 0 \n", + "16 Rice, Master. Eugene 1 2.0 4 \n", + "17 Williams, Mr. Charles Eugene 1 99.0 0 \n", + "18 Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) 2 31.0 1 \n", + "19 Masselmani, Mrs. Fatima 2 99.0 0 \n", + "\n", + " Parch Ticket Fare Cabin Embarked Cabin_L \n", + "0 0 A/5 21171 7.2500 99 3 9 \n", + "1 0 PC 17599 71.2833 C85 1 C \n", + "2 0 STON/O2. 3101282 7.9250 99 3 9 \n", + "3 0 113803 53.1000 C123 3 C \n", + "4 0 373450 8.0500 99 3 9 \n", + "5 0 330877 8.4583 99 2 9 \n", + "6 0 17463 51.8625 E46 3 E \n", + "7 1 349909 21.0750 99 3 9 \n", + "8 2 347742 11.1333 99 3 9 \n", + "9 0 237736 30.0708 99 1 9 \n", + "10 1 PP 9549 16.7000 G6 3 G \n", + "11 0 113783 26.5500 C103 3 C \n", + "12 0 A/5. 2151 8.0500 99 3 9 \n", + "13 5 347082 31.2750 99 3 9 \n", + "14 0 350406 7.8542 99 3 9 \n", + "15 0 248706 16.0000 99 3 9 \n", + "16 1 382652 29.1250 99 2 9 \n", + "17 0 244373 13.0000 99 3 9 \n", + "18 0 345763 18.0000 99 3 9 \n", + "19 0 2649 7.2250 99 1 9 " + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Cabin_L'] = df['Cabin'].astype(str).str[0]\n", + "df.head(20)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['9', 'C', 'E', 'G', 'D', 'A', 'B', 'F', 'T'], dtype=object)" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.Cabin_L.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarkedCabin_L
0103Braund, Mr. Owen Harris122.010A/5 211717.25009939
1211Cumings, Mrs. John Bradley (Florence Briggs Thayer)238.010PC 1759971.2833C8513
2313Heikkinen, Miss. Laina226.000STON/O2. 31012827.92509939
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)235.01011380353.1000C12333
4503Allen, Mr. William Henry135.0003734508.05009939
5603Moran, Mr. James199.0003308778.45839929
6701McCarthy, Mr. Timothy J154.0001746351.8625E4635
7803Palsson, Master. Gosta Leonard12.03134990921.07509939
8913Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)227.00234774211.13339939
91012Nasser, Mrs. Nicholas (Adele Achem)214.01023773630.07089919
\n", + "
" + ], + "text/plain": [ + " PassengerId Survived Pclass \\\n", + "0 1 0 3 \n", + "1 2 1 1 \n", + "2 3 1 3 \n", + "3 4 1 1 \n", + "4 5 0 3 \n", + "5 6 0 3 \n", + "6 7 0 1 \n", + "7 8 0 3 \n", + "8 9 1 3 \n", + "9 10 1 2 \n", + "\n", + " Name Sex Age SibSp \\\n", + "0 Braund, Mr. Owen Harris 1 22.0 1 \n", + "1 Cumings, Mrs. John Bradley (Florence Briggs Thayer) 2 38.0 1 \n", + "2 Heikkinen, Miss. Laina 2 26.0 0 \n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) 2 35.0 1 \n", + "4 Allen, Mr. William Henry 1 35.0 0 \n", + "5 Moran, Mr. James 1 99.0 0 \n", + "6 McCarthy, Mr. Timothy J 1 54.0 0 \n", + "7 Palsson, Master. Gosta Leonard 1 2.0 3 \n", + "8 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) 2 27.0 0 \n", + "9 Nasser, Mrs. Nicholas (Adele Achem) 2 14.0 1 \n", + "\n", + " Parch Ticket Fare Cabin Embarked Cabin_L \n", + "0 0 A/5 21171 7.2500 99 3 9 \n", + "1 0 PC 17599 71.2833 C85 1 3 \n", + "2 0 STON/O2. 3101282 7.9250 99 3 9 \n", + "3 0 113803 53.1000 C123 3 3 \n", + "4 0 373450 8.0500 99 3 9 \n", + "5 0 330877 8.4583 99 2 9 \n", + "6 0 17463 51.8625 E46 3 5 \n", + "7 1 349909 21.0750 99 3 9 \n", + "8 2 347742 11.1333 99 3 9 \n", + "9 0 237736 30.0708 99 1 9 " + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Cabin_L'] = df.Cabin_L.map({'A':1, 'B':2, 'C':3, 'D':4, 'E':5, 'F':6, 'G':7, 'T':8, '9':9})\n", + "df.head(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 891 entries, 0 to 890\n", + "Data columns (total 13 columns):\n", + "PassengerId 891 non-null int64\n", + "Survived 891 non-null int64\n", + "Pclass 891 non-null int64\n", + "Name 891 non-null object\n", + "Sex 891 non-null int64\n", + "Age 891 non-null float64\n", + "SibSp 891 non-null int64\n", + "Parch 891 non-null int64\n", + "Ticket 891 non-null object\n", + "Fare 891 non-null float64\n", + "Cabin 891 non-null object\n", + "Embarked 891 non-null int64\n", + "Cabin_L 891 non-null int64\n", + "dtypes: float64(2), int64(8), object(3)\n", + "memory usage: 90.6+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 1, 2, 9], dtype=int64)" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.Embarked.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtMAAALCCAYAAAAcfl8PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGtNJkiRJkiRJ0kn+H+o6Y54HVjjHAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "scatter_matrix(df, alpha=0.2, figsize =(12,12))\n", + "None" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
CombosScore
0Pclass0.679453
1Sex0.786496
2Age0.616147
3SibSp0.616147
4Parch0.607156
\n", + "
" + ], + "text/plain": [ + " Combos Score\n", + "0 Pclass 0.679453\n", + "1 Sex 0.786496\n", + "2 Age 0.616147\n", + "3 SibSp 0.616147\n", + "4 Parch 0.607156" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from itertools import combinations\n", + "rows = []\n", + "for i in range(1,9):\n", + " combos = list(combinations(['Pclass', 'Sex', 'Age', 'SibSp',\n", + " 'Parch', 'Fare', 'Cabin_L', 'Embarked'],i))\n", + " for j,com in enumerate(combos):\n", + " y = df.Survived\n", + " X = pd.DataFrame(df, columns=com)\n", + " # X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, shuffle=True, random_state=22)\n", + " model = LogisticRegression(fit_intercept=True)\n", + " score = cross_val_score(model, X, y, cv=20, scoring='accuracy').mean()\n", + " s = ', '.join(com)\n", + " rows.append({'Score':score, 'Combos':s,})\n", + " # print('score:', score, 'columns:', s)\n", + "df1 = pd.DataFrame(rows)\n", + "df1.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Combos Pclass, Sex, Age, Parch, Embarked\n", + "Score 0.804801\n", + "Name: 168, dtype: object" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df1.iloc[df1.Score.idxmax()]" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "y = df.Survived\n", + "X = pd.DataFrame(df, columns=['Pclass', 'Sex', 'Age', 'Parch', 'Embarked'])" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, shuffle=True, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "model = LogisticRegression(fit_intercept=True).fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.79661016949152541" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.score(X_test, y_test) " + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.69565217, 0.86956522, 0.77777778, 0.77777778, 0.8 ,\n", + " 0.8 , 0.77777778, 0.86666667, 0.84444444, 0.77272727,\n", + " 0.79545455, 0.70454545, 0.81818182, 0.86363636, 0.84090909,\n", + " 0.81818182, 0.84090909, 0.81818182, 0.72727273, 0.88636364])" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cross_val_score(model, X, y, cv=20, scoring='accuracy')" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "y_hat = model.predict(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[148, 27],\n", + " [ 33, 87]], dtype=int64)" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "confusion_matrix(y_test, y_hat)" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "recall = 87/(87+33)\n", + "precision = 87/(87+27)" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.725" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "recall" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.7631578947368421" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "precision" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.28660899, 0.38695415, 0.02744571, 0.22330864, 0.35202229,\n", + " 0.3183973 , 0.22058658, 0.5152139 , 0.4269109 , 0.31089887,\n", + " 0.42062783, 0.41032367, 0.22799713, 0.52878289, 0.32953313,\n", + " 0.32364799, 0.46026791, 0.45804272, 0.21096577, 0.51529824])" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "#model = LinearRegression()\n", + "model = LinearRegression(fit_intercept=True)\n", + "cross_val_score(model, X, y, cv=20, scoring='r2')" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.34807231728595672" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cross_val_score(model, X, y, cv=10, scoring='r2').mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-0.15122351, 0.51797586, -0.00135754, -0.03163365, -0.04193267])" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.fit(X,y).coef_" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.21044598408017504" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.fit(X,y).intercept_" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Please input Ticket Class: 1\n", + "Please input Sex: 1\n", + "Please input Age: 20\n", + "Please input Parents/Children: 0\n", + "Please input where Embarked: 2\n", + "0.4661821940801749\n" + ] + } + ], + "source": [ + "b = 0.21044598408017504 # y intercept\n", + "Pclass_coef = -0.15122351\n", + "Sex_coef = 0.51797586\n", + "Age_coef = -0.00135754\n", + "Parch_coef = -0.03163365\n", + "Embarked_coef = -0.04193267\n", + "\n", + "Pclass_input = user_str = input('Please input Ticket Class: ')\n", + "Sex_input = user_str = input('Please input Sex: ')\n", + "Age_input = user_str = input('Please input Age: ')\n", + "Parch_input = user_str = input('Please input Parents/Children: ')\n", + "Embarked_input = user_str = input('Please input where Embarked: ')\n", + "\n", + "y_hat = b + (Pclass_coef*int(Pclass_input)) + (Sex_coef*int(Sex_input)) + (Age_coef*int(Age_input)) + (Parch_coef*int(Parch_input)) + (Embarked_coef*int(Embarked_input))\n", + "\n", + "print(y_hat)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "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": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/titanic.ipynb b/titanic.ipynb new file mode 100644 index 0000000..cf51545 --- /dev/null +++ b/titanic.ipynb @@ -0,0 +1,1832 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from itertools import combinations\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.metrics import confusion_matrix\n", + "from sklearn.model_selection import train_test_split\n", + "from pandas.plotting import scatter_matrix\n", + "%matplotlib inline\n", + "\n", + "pd.options.display.max_colwidth = 100" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df = pd.read_csv('data.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarked
0103Braund, Mr. Owen Harrismale22.010A/5 211717.2500NaNS
1211Cumings, Mrs. John Bradley (Florence Briggs Thayer)female38.010PC 1759971.2833C85C
2313Heikkinen, Miss. Lainafemale26.000STON/O2. 31012827.9250NaNS
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)female35.01011380353.1000C123S
4503Allen, Mr. William Henrymale35.0003734508.0500NaNS
\n", + "
" + ], + "text/plain": [ + " PassengerId Survived Pclass \\\n", + "0 1 0 3 \n", + "1 2 1 1 \n", + "2 3 1 3 \n", + "3 4 1 1 \n", + "4 5 0 3 \n", + "\n", + " Name Sex Age SibSp \\\n", + "0 Braund, Mr. Owen Harris male 22.0 1 \n", + "1 Cumings, Mrs. John Bradley (Florence Briggs Thayer) female 38.0 1 \n", + "2 Heikkinen, Miss. Laina female 26.0 0 \n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) female 35.0 1 \n", + "4 Allen, Mr. William Henry male 35.0 0 \n", + "\n", + " Parch Ticket Fare Cabin Embarked \n", + "0 0 A/5 21171 7.2500 NaN S \n", + "1 0 PC 17599 71.2833 C85 C \n", + "2 0 STON/O2. 3101282 7.9250 NaN S \n", + "3 0 113803 53.1000 C123 S \n", + "4 0 373450 8.0500 NaN S " + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
countmeanstdmin25%50%75%max
PassengerId891.0446.000000257.3538421.00223.5000446.0000668.5891.0000
Survived891.00.3838380.4865920.000.00000.00001.01.0000
Pclass891.02.3086420.8360711.002.00003.00003.03.0000
Age714.029.69911814.5264970.4220.125028.000038.080.0000
SibSp891.00.5230081.1027430.000.00000.00001.08.0000
Parch891.00.3815940.8060570.000.00000.00000.06.0000
Fare891.032.20420849.6934290.007.910414.454231.0512.3292
\n", + "
" + ], + "text/plain": [ + " count mean std min 25% 50% 75% \\\n", + "PassengerId 891.0 446.000000 257.353842 1.00 223.5000 446.0000 668.5 \n", + "Survived 891.0 0.383838 0.486592 0.00 0.0000 0.0000 1.0 \n", + "Pclass 891.0 2.308642 0.836071 1.00 2.0000 3.0000 3.0 \n", + "Age 714.0 29.699118 14.526497 0.42 20.1250 28.0000 38.0 \n", + "SibSp 891.0 0.523008 1.102743 0.00 0.0000 0.0000 1.0 \n", + "Parch 891.0 0.381594 0.806057 0.00 0.0000 0.0000 0.0 \n", + "Fare 891.0 32.204208 49.693429 0.00 7.9104 14.4542 31.0 \n", + "\n", + " max \n", + "PassengerId 891.0000 \n", + "Survived 1.0000 \n", + "Pclass 3.0000 \n", + "Age 80.0000 \n", + "SibSp 8.0000 \n", + "Parch 6.0000 \n", + "Fare 512.3292 " + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 891 entries, 0 to 890\n", + "Data columns (total 12 columns):\n", + "PassengerId 891 non-null int64\n", + "Survived 891 non-null int64\n", + "Pclass 891 non-null int64\n", + "Name 891 non-null object\n", + "Sex 891 non-null object\n", + "Age 714 non-null float64\n", + "SibSp 891 non-null int64\n", + "Parch 891 non-null int64\n", + "Ticket 891 non-null object\n", + "Fare 891 non-null float64\n", + "Cabin 204 non-null object\n", + "Embarked 889 non-null object\n", + "dtypes: float64(2), int64(5), object(5)\n", + "memory usage: 83.6+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "df = df.fillna(99)" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 891 entries, 0 to 890\n", + "Data columns (total 12 columns):\n", + "PassengerId 891 non-null int64\n", + "Survived 891 non-null int64\n", + "Pclass 891 non-null int64\n", + "Name 891 non-null object\n", + "Sex 891 non-null object\n", + "Age 891 non-null float64\n", + "SibSp 891 non-null int64\n", + "Parch 891 non-null int64\n", + "Ticket 891 non-null object\n", + "Fare 891 non-null float64\n", + "Cabin 891 non-null object\n", + "Embarked 891 non-null object\n", + "dtypes: float64(2), int64(5), object(5)\n", + "memory usage: 83.6+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
countmeanstdmin25%50%75%max
PassengerId891.0446.000000257.3538421.00223.5000446.0000668.5891.0000
Survived891.00.3838380.4865920.000.00000.00001.01.0000
Pclass891.02.3086420.8360711.002.00003.00003.03.0000
Age891.043.46596030.5686080.4222.000032.000054.099.0000
SibSp891.00.5230081.1027430.000.00000.00001.08.0000
Parch891.00.3815940.8060570.000.00000.00000.06.0000
Fare891.032.20420849.6934290.007.910414.454231.0512.3292
\n", + "
" + ], + "text/plain": [ + " count mean std min 25% 50% 75% \\\n", + "PassengerId 891.0 446.000000 257.353842 1.00 223.5000 446.0000 668.5 \n", + "Survived 891.0 0.383838 0.486592 0.00 0.0000 0.0000 1.0 \n", + "Pclass 891.0 2.308642 0.836071 1.00 2.0000 3.0000 3.0 \n", + "Age 891.0 43.465960 30.568608 0.42 22.0000 32.0000 54.0 \n", + "SibSp 891.0 0.523008 1.102743 0.00 0.0000 0.0000 1.0 \n", + "Parch 891.0 0.381594 0.806057 0.00 0.0000 0.0000 0.0 \n", + "Fare 891.0 32.204208 49.693429 0.00 7.9104 14.4542 31.0 \n", + "\n", + " max \n", + "PassengerId 891.0000 \n", + "Survived 1.0000 \n", + "Pclass 3.0000 \n", + "Age 99.0000 \n", + "SibSp 8.0000 \n", + "Parch 6.0000 \n", + "Fare 512.3292 " + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe().T" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['S', 'C', 'Q', 99], dtype=object)" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.Embarked.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [], + "source": [ + "df['Sex'] = df.Sex.map({'male':1, 'female':2})\n", + "df['Embarked'] = df.Embarked.map({'C':1, 'Q':2, 'S':3, 99:9})" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 1, 2, 9], dtype=int64)" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.Embarked.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarkedCabin_L
0103Braund, Mr. Owen Harris122.010A/5 211717.25009939
1211Cumings, Mrs. John Bradley (Florence Briggs Thayer)238.010PC 1759971.2833C851C
2313Heikkinen, Miss. Laina226.000STON/O2. 31012827.92509939
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)235.01011380353.1000C1233C
4503Allen, Mr. William Henry135.0003734508.05009939
5603Moran, Mr. James199.0003308778.45839929
6701McCarthy, Mr. Timothy J154.0001746351.8625E463E
7803Palsson, Master. Gosta Leonard12.03134990921.07509939
8913Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)227.00234774211.13339939
91012Nasser, Mrs. Nicholas (Adele Achem)214.01023773630.07089919
101113Sandstrom, Miss. Marguerite Rut24.011PP 954916.7000G63G
111211Bonnell, Miss. Elizabeth258.00011378326.5500C1033C
121303Saundercock, Mr. William Henry120.000A/5. 21518.05009939
131403Andersson, Mr. Anders Johan139.01534708231.27509939
141503Vestrom, Miss. Hulda Amanda Adolfina214.0003504067.85429939
151612Hewlett, Mrs. (Mary D Kingcome)255.00024870616.00009939
161703Rice, Master. Eugene12.04138265229.12509929
171812Williams, Mr. Charles Eugene199.00024437313.00009939
181903Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)231.01034576318.00009939
192013Masselmani, Mrs. Fatima299.00026497.22509919
\n", + "
" + ], + "text/plain": [ + " PassengerId Survived Pclass \\\n", + "0 1 0 3 \n", + "1 2 1 1 \n", + "2 3 1 3 \n", + "3 4 1 1 \n", + "4 5 0 3 \n", + "5 6 0 3 \n", + "6 7 0 1 \n", + "7 8 0 3 \n", + "8 9 1 3 \n", + "9 10 1 2 \n", + "10 11 1 3 \n", + "11 12 1 1 \n", + "12 13 0 3 \n", + "13 14 0 3 \n", + "14 15 0 3 \n", + "15 16 1 2 \n", + "16 17 0 3 \n", + "17 18 1 2 \n", + "18 19 0 3 \n", + "19 20 1 3 \n", + "\n", + " Name Sex Age SibSp \\\n", + "0 Braund, Mr. Owen Harris 1 22.0 1 \n", + "1 Cumings, Mrs. John Bradley (Florence Briggs Thayer) 2 38.0 1 \n", + "2 Heikkinen, Miss. Laina 2 26.0 0 \n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) 2 35.0 1 \n", + "4 Allen, Mr. William Henry 1 35.0 0 \n", + "5 Moran, Mr. James 1 99.0 0 \n", + "6 McCarthy, Mr. Timothy J 1 54.0 0 \n", + "7 Palsson, Master. Gosta Leonard 1 2.0 3 \n", + "8 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) 2 27.0 0 \n", + "9 Nasser, Mrs. Nicholas (Adele Achem) 2 14.0 1 \n", + "10 Sandstrom, Miss. Marguerite Rut 2 4.0 1 \n", + "11 Bonnell, Miss. Elizabeth 2 58.0 0 \n", + "12 Saundercock, Mr. William Henry 1 20.0 0 \n", + "13 Andersson, Mr. Anders Johan 1 39.0 1 \n", + "14 Vestrom, Miss. Hulda Amanda Adolfina 2 14.0 0 \n", + "15 Hewlett, Mrs. (Mary D Kingcome) 2 55.0 0 \n", + "16 Rice, Master. Eugene 1 2.0 4 \n", + "17 Williams, Mr. Charles Eugene 1 99.0 0 \n", + "18 Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele) 2 31.0 1 \n", + "19 Masselmani, Mrs. Fatima 2 99.0 0 \n", + "\n", + " Parch Ticket Fare Cabin Embarked Cabin_L \n", + "0 0 A/5 21171 7.2500 99 3 9 \n", + "1 0 PC 17599 71.2833 C85 1 C \n", + "2 0 STON/O2. 3101282 7.9250 99 3 9 \n", + "3 0 113803 53.1000 C123 3 C \n", + "4 0 373450 8.0500 99 3 9 \n", + "5 0 330877 8.4583 99 2 9 \n", + "6 0 17463 51.8625 E46 3 E \n", + "7 1 349909 21.0750 99 3 9 \n", + "8 2 347742 11.1333 99 3 9 \n", + "9 0 237736 30.0708 99 1 9 \n", + "10 1 PP 9549 16.7000 G6 3 G \n", + "11 0 113783 26.5500 C103 3 C \n", + "12 0 A/5. 2151 8.0500 99 3 9 \n", + "13 5 347082 31.2750 99 3 9 \n", + "14 0 350406 7.8542 99 3 9 \n", + "15 0 248706 16.0000 99 3 9 \n", + "16 1 382652 29.1250 99 2 9 \n", + "17 0 244373 13.0000 99 3 9 \n", + "18 0 345763 18.0000 99 3 9 \n", + "19 0 2649 7.2250 99 1 9 " + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Cabin_L'] = df['Cabin'].astype(str).str[0]\n", + "df.head(20)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['9', 'C', 'E', 'G', 'D', 'A', 'B', 'F', 'T'], dtype=object)" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.Cabin_L.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
PassengerIdSurvivedPclassNameSexAgeSibSpParchTicketFareCabinEmbarkedCabin_L
0103Braund, Mr. Owen Harris122.010A/5 211717.25009939
1211Cumings, Mrs. John Bradley (Florence Briggs Thayer)238.010PC 1759971.2833C8513
2313Heikkinen, Miss. Laina226.000STON/O2. 31012827.92509939
3411Futrelle, Mrs. Jacques Heath (Lily May Peel)235.01011380353.1000C12333
4503Allen, Mr. William Henry135.0003734508.05009939
5603Moran, Mr. James199.0003308778.45839929
6701McCarthy, Mr. Timothy J154.0001746351.8625E4635
7803Palsson, Master. Gosta Leonard12.03134990921.07509939
8913Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)227.00234774211.13339939
91012Nasser, Mrs. Nicholas (Adele Achem)214.01023773630.07089919
\n", + "
" + ], + "text/plain": [ + " PassengerId Survived Pclass \\\n", + "0 1 0 3 \n", + "1 2 1 1 \n", + "2 3 1 3 \n", + "3 4 1 1 \n", + "4 5 0 3 \n", + "5 6 0 3 \n", + "6 7 0 1 \n", + "7 8 0 3 \n", + "8 9 1 3 \n", + "9 10 1 2 \n", + "\n", + " Name Sex Age SibSp \\\n", + "0 Braund, Mr. Owen Harris 1 22.0 1 \n", + "1 Cumings, Mrs. John Bradley (Florence Briggs Thayer) 2 38.0 1 \n", + "2 Heikkinen, Miss. Laina 2 26.0 0 \n", + "3 Futrelle, Mrs. Jacques Heath (Lily May Peel) 2 35.0 1 \n", + "4 Allen, Mr. William Henry 1 35.0 0 \n", + "5 Moran, Mr. James 1 99.0 0 \n", + "6 McCarthy, Mr. Timothy J 1 54.0 0 \n", + "7 Palsson, Master. Gosta Leonard 1 2.0 3 \n", + "8 Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg) 2 27.0 0 \n", + "9 Nasser, Mrs. Nicholas (Adele Achem) 2 14.0 1 \n", + "\n", + " Parch Ticket Fare Cabin Embarked Cabin_L \n", + "0 0 A/5 21171 7.2500 99 3 9 \n", + "1 0 PC 17599 71.2833 C85 1 3 \n", + "2 0 STON/O2. 3101282 7.9250 99 3 9 \n", + "3 0 113803 53.1000 C123 3 3 \n", + "4 0 373450 8.0500 99 3 9 \n", + "5 0 330877 8.4583 99 2 9 \n", + "6 0 17463 51.8625 E46 3 5 \n", + "7 1 349909 21.0750 99 3 9 \n", + "8 2 347742 11.1333 99 3 9 \n", + "9 0 237736 30.0708 99 1 9 " + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Cabin_L'] = df.Cabin_L.map({'A':1, 'B':2, 'C':3, 'D':4, 'E':5, 'F':6, 'G':7, 'T':8, '9':9})\n", + "df.head(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 891 entries, 0 to 890\n", + "Data columns (total 13 columns):\n", + "PassengerId 891 non-null int64\n", + "Survived 891 non-null int64\n", + "Pclass 891 non-null int64\n", + "Name 891 non-null object\n", + "Sex 891 non-null int64\n", + "Age 891 non-null float64\n", + "SibSp 891 non-null int64\n", + "Parch 891 non-null int64\n", + "Ticket 891 non-null object\n", + "Fare 891 non-null float64\n", + "Cabin 891 non-null object\n", + "Embarked 891 non-null int64\n", + "Cabin_L 891 non-null int64\n", + "dtypes: float64(2), int64(8), object(3)\n", + "memory usage: 90.6+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([3, 1, 2, 9], dtype=int64)" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.Embarked.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAtMAAALCCAYAAAAcfl8PAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGtNJkiRJkiRJ0kn+H+o6Y54HVjjHAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "scatter_matrix(df, alpha=0.2, figsize =(12,12))\n", + "None" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
CombosScore
0Pclass0.679453
1Sex0.786496
2Age0.616147
3SibSp0.616147
4Parch0.607156
\n", + "
" + ], + "text/plain": [ + " Combos Score\n", + "0 Pclass 0.679453\n", + "1 Sex 0.786496\n", + "2 Age 0.616147\n", + "3 SibSp 0.616147\n", + "4 Parch 0.607156" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from itertools import combinations\n", + "rows = []\n", + "for i in range(1,9):\n", + " combos = list(combinations(['Pclass', 'Sex', 'Age', 'SibSp',\n", + " 'Parch', 'Fare', 'Cabin_L', 'Embarked'],i))\n", + " for j,com in enumerate(combos):\n", + " y = df.Survived\n", + " X = pd.DataFrame(df, columns=com)\n", + " # X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, shuffle=True, random_state=22)\n", + " model = LogisticRegression(fit_intercept=True)\n", + " score = cross_val_score(model, X, y, cv=20, scoring='accuracy').mean()\n", + " s = ', '.join(com)\n", + " rows.append({'Score':score, 'Combos':s,})\n", + " # print('score:', score, 'columns:', s)\n", + "df1 = pd.DataFrame(rows)\n", + "df1.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Combos Pclass, Sex, Age, Parch, Embarked\n", + "Score 0.804801\n", + "Name: 168, dtype: object" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df1.iloc[df1.Score.idxmax()]" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "y = df.Survived\n", + "X = pd.DataFrame(df, columns=['Pclass', 'Sex', 'Age', 'Parch', 'Embarked'])" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, shuffle=True, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "model = LogisticRegression(fit_intercept=True).fit(X_train, y_train)" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.79661016949152541" + ] + }, + "execution_count": 88, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.score(X_test, y_test) " + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.69565217, 0.86956522, 0.77777778, 0.77777778, 0.8 ,\n", + " 0.8 , 0.77777778, 0.86666667, 0.84444444, 0.77272727,\n", + " 0.79545455, 0.70454545, 0.81818182, 0.86363636, 0.84090909,\n", + " 0.81818182, 0.84090909, 0.81818182, 0.72727273, 0.88636364])" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cross_val_score(model, X, y, cv=20, scoring='accuracy')" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "y_hat = model.predict(X_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[148, 27],\n", + " [ 33, 87]], dtype=int64)" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "confusion_matrix(y_test, y_hat)" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "recall = 87/(87+33)\n", + "precision = 87/(87+27)" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.725" + ] + }, + "execution_count": 93, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "recall" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.7631578947368421" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "precision" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0.28660899, 0.38695415, 0.02744571, 0.22330864, 0.35202229,\n", + " 0.3183973 , 0.22058658, 0.5152139 , 0.4269109 , 0.31089887,\n", + " 0.42062783, 0.41032367, 0.22799713, 0.52878289, 0.32953313,\n", + " 0.32364799, 0.46026791, 0.45804272, 0.21096577, 0.51529824])" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.linear_model import LinearRegression\n", + "#model = LinearRegression()\n", + "model = LinearRegression(fit_intercept=True)\n", + "cross_val_score(model, X, y, cv=20, scoring='r2')" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.34807231728595672" + ] + }, + "execution_count": 100, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cross_val_score(model, X, y, cv=10, scoring='r2').mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-0.15122351, 0.51797586, -0.00135754, -0.03163365, -0.04193267])" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.fit(X,y).coef_" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.21044598408017504" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "model.fit(X,y).intercept_" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Please input Ticket Class: 1\n", + "Please input Sex: 1\n", + "Please input Age: 20\n", + "Please input Parents/Children: 0\n", + "Please input where Embarked: 2\n", + "0.4661821940801749\n" + ] + } + ], + "source": [ + "b = 0.21044598408017504 # y intercept\n", + "Pclass_coef = -0.15122351\n", + "Sex_coef = 0.51797586\n", + "Age_coef = -0.00135754\n", + "Parch_coef = -0.03163365\n", + "Embarked_coef = -0.04193267\n", + "\n", + "Pclass_input = user_str = input('Please input Ticket Class: ')\n", + "Sex_input = user_str = input('Please input Sex: ')\n", + "Age_input = user_str = input('Please input Age: ')\n", + "Parch_input = user_str = input('Please input Parents/Children: ')\n", + "Embarked_input = user_str = input('Please input where Embarked: ')\n", + "\n", + "y_hat = b + (Pclass_coef*int(Pclass_input)) + (Sex_coef*int(Sex_input)) + (Age_coef*int(Age_input)) + (Parch_coef*int(Parch_input)) + (Embarked_coef*int(Embarked_input))\n", + "\n", + "print(y_hat)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "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": "3.6.3" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +}