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Exploring the Kaggle Titanic dataset with seaborn.
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"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Exploring the *Titanic* dataset with `seaborn`"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<div style=\"width:100%; text-align:center\">\n",
"<img src=http://blogs.westword.com/showandtell/titanic.jpg width=500px>\n",
"</div>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Kaggle has a nice [dataset](https://www.kaggle.com/c/titanic-gettingStarted) with information about passengers on the *Titanic*. It's meant as an introduction to predictive models -- here, predicting who survived the sinking. Let's explore it using [seaborn](http://stanford.edu/~mwaskom/software/seaborn/). This notebook mostly demonstrates features in development for version 0.3. Please [get in touch](https://github.com/mwaskom/seaborn/issues/new) if you have ideas for how they could be improved."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import numpy as np\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"sns.set(style=\"nogrid\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First we load in the data and take a look"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"url = \"https://raw.github.com/mattdelhey/kaggle-titanic/master/Data/train.csv\"\n",
"titanic = pd.read_csv(url)\n",
"titanic.info()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 891 entries, 0 to 890\n",
"Data columns (total 11 columns):\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(4), object(5)"
]
}
],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"titanic.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>survived</th>\n",
" <th>pclass</th>\n",
" <th>name</th>\n",
" <th>sex</th>\n",
" <th>age</th>\n",
" <th>sibsp</th>\n",
" <th>parch</th>\n",
" <th>ticket</th>\n",
" <th>fare</th>\n",
" <th>cabin</th>\n",
" <th>embarked</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> Braund, Mr. Owen Harris</td>\n",
" <td> male</td>\n",
" <td> 22</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> A/5 21171</td>\n",
" <td> 7.2500</td>\n",
" <td> NaN</td>\n",
" <td> S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
" <td> female</td>\n",
" <td> 38</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> PC 17599</td>\n",
" <td> 71.2833</td>\n",
" <td> C85</td>\n",
" <td> C</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 1</td>\n",
" <td> 3</td>\n",
" <td> Heikkinen, Miss. Laina</td>\n",
" <td> female</td>\n",
" <td> 26</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> STON/O2. 3101282</td>\n",
" <td> 7.9250</td>\n",
" <td> NaN</td>\n",
" <td> S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
" <td> female</td>\n",
" <td> 35</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 113803</td>\n",
" <td> 53.1000</td>\n",
" <td> C123</td>\n",
" <td> S</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> Allen, Mr. William Henry</td>\n",
" <td> male</td>\n",
" <td> 35</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 373450</td>\n",
" <td> 8.0500</td>\n",
" <td> NaN</td>\n",
" <td> S</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 11 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 3,
"text": [
" survived pclass name \\\n",
"0 0 3 Braund, Mr. Owen Harris \n",
"1 1 1 Cumings, Mrs. John Bradley (Florence Briggs Th... \n",
"2 1 3 Heikkinen, Miss. Laina \n",
"3 1 1 Futrelle, Mrs. Jacques Heath (Lily May Peel) \n",
"4 0 3 Allen, Mr. William Henry \n",
"\n",
" sex age sibsp parch ticket fare cabin embarked \n",
"0 male 22 1 0 A/5 21171 7.2500 NaN S \n",
"1 female 38 1 0 PC 17599 71.2833 C85 C \n",
"2 female 26 0 0 STON/O2. 3101282 7.9250 NaN S \n",
"3 female 35 1 0 113803 53.1000 C123 S \n",
"4 male 35 0 0 373450 8.0500 NaN S \n",
"\n",
"[5 rows x 11 columns]"
]
}
],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's do little bit of processing to make some different variables that might be more interesting to plot. Since this notebook is focused on visualization, we're going to do this without much comment."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def woman_child_or_man(passenger):\n",
" age, sex = passenger\n",
" if age < 16:\n",
" return \"child\"\n",
" else:\n",
" return dict(male=\"man\", female=\"woman\")[sex]"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"titanic[\"class\"] = titanic.pclass.map({1: \"First\", 2: \"Second\", 3: \"Third\"})\n",
"titanic[\"who\"] = titanic[[\"age\", \"sex\"]].apply(woman_child_or_man, axis=1)\n",
"titanic[\"adult_male\"] = titanic.who == \"man\"\n",
"titanic[\"deck\"] = titanic.cabin.str[0].map(lambda s: np.nan if s == \"T\" else s)\n",
"titanic[\"embark_town\"] = titanic.embarked.map({\"C\": \"Cherbourg\", \"Q\": \"Queenstown\", \"S\": \"Southampton\"})\n",
"titanic[\"alive\"] = titanic.survived.map({0: \"no\", 1: \"yes\"})\n",
"titanic[\"alone\"] = ~(titanic.parch + titanic.sibsp).astype(bool)\n",
"titanic = titanic.drop([\"name\", \"ticket\", \"cabin\"], axis=1)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"titanic.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>survived</th>\n",
" <th>pclass</th>\n",
" <th>sex</th>\n",
" <th>age</th>\n",
" <th>sibsp</th>\n",
" <th>parch</th>\n",
" <th>fare</th>\n",
" <th>embarked</th>\n",
" <th>class</th>\n",
" <th>who</th>\n",
" <th>adult_male</th>\n",
" <th>deck</th>\n",
" <th>embark_town</th>\n",
" <th>alive</th>\n",
" <th>alone</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> male</td>\n",
" <td> 22</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 7.2500</td>\n",
" <td> S</td>\n",
" <td> Third</td>\n",
" <td> man</td>\n",
" <td> True</td>\n",
" <td> NaN</td>\n",
" <td> Southampton</td>\n",
" <td> no</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> female</td>\n",
" <td> 38</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 71.2833</td>\n",
" <td> C</td>\n",
" <td> First</td>\n",
" <td> woman</td>\n",
" <td> False</td>\n",
" <td> C</td>\n",
" <td> Cherbourg</td>\n",
" <td> yes</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td> 1</td>\n",
" <td> 3</td>\n",
" <td> female</td>\n",
" <td> 26</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 7.9250</td>\n",
" <td> S</td>\n",
" <td> Third</td>\n",
" <td> woman</td>\n",
" <td> False</td>\n",
" <td> NaN</td>\n",
" <td> Southampton</td>\n",
" <td> yes</td>\n",
" <td> True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td> 1</td>\n",
" <td> 1</td>\n",
" <td> female</td>\n",
" <td> 35</td>\n",
" <td> 1</td>\n",
" <td> 0</td>\n",
" <td> 53.1000</td>\n",
" <td> S</td>\n",
" <td> First</td>\n",
" <td> woman</td>\n",
" <td> False</td>\n",
" <td> C</td>\n",
" <td> Southampton</td>\n",
" <td> yes</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td> 0</td>\n",
" <td> 3</td>\n",
" <td> male</td>\n",
" <td> 35</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 8.0500</td>\n",
" <td> S</td>\n",
" <td> Third</td>\n",
" <td> man</td>\n",
" <td> True</td>\n",
" <td> NaN</td>\n",
" <td> Southampton</td>\n",
" <td> no</td>\n",
" <td> True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 15 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": [
" survived pclass sex age sibsp parch fare embarked class \\\n",
"0 0 3 male 22 1 0 7.2500 S Third \n",
"1 1 1 female 38 1 0 71.2833 C First \n",
"2 1 3 female 26 0 0 7.9250 S Third \n",
"3 1 1 female 35 1 0 53.1000 S First \n",
"4 0 3 male 35 0 0 8.0500 S Third \n",
"\n",
" who adult_male deck embark_town alive alone \n",
"0 man True NaN Southampton no False \n",
"1 woman False C Cherbourg yes False \n",
"2 woman False NaN Southampton yes True \n",
"3 woman False C Southampton yes False \n",
"4 man True NaN Southampton no True \n",
"\n",
"[5 rows x 15 columns]"
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Finally set up a palette dictionary for some of the plots."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"pal = dict(man=\"#4682B4\", woman=\"#CD5C5C\", child=\"#2E8B57\", male=\"#6495ED\", female=\"#F08080\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 7
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Who were the *Titanic* passengers?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Before getting to the main question (who survived), let's take a look at the dataset to get a sense for how the observations are distributed into the different levels of our factors of interest."
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"How many men, women, and children are in our sample?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First let's count the number of males and females, ignoring age."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"sex\", data=titanic, palette=pal);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x1097b3590>"
]
}
],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Then we can look at how this is distributed into the three classes."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", data=titanic, hue=\"sex\", palette=pal);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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avny5IiIiFBUVpby8vOabGADQalz1SCgrK0t//vOf5e/vL0kqLS1Venq60tPTGx5z8uRJ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\nIUIAAGOIEADAGCIEADCGCAEAjPlf17IOmL4VwREAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10973a8d0>"
]
}
],
"prompt_number": 9
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also have a separate classification that splits off children (recall, this is going to be relevant because of the \"women and children first\" policy followed during the evacuation)."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"who\", data=titanic, palette=pal);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x109757690>"
]
}
],
"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", data=titanic, hue=\"who\", palette=pal);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x1097cd310>"
]
}
],
"prompt_number": 11
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Finally, we made a variable that indicates whether a passanger was an adult male."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"adult_male\", data=titanic, palette=\"Blues\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x109759b50>"
]
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", data=titanic, hue=\"adult_male\", palette=\"Blues\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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/c393F8t374uPj9ewYcMUFBSkoKAgDR8+XNXV1dq1a5cWL16srKwso3NfS0aN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\nRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x109738910>"
]
}
],
"prompt_number": 13
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next let's look at the distribution of ages within the groups we defined above."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg = sns.FacetGrid(titanic, hue=\"sex\", aspect=3, palette=pal)\n",
"fg.map(sns.kdeplot, \"age\", shade=True)\n",
"fg.set(xlim=(0, 80));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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ng7wSNZ8op8r3b4kjZZAsdC2EEAOBdH+IHhOpraX95ZdRBw/GPndut0HYMOGl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\npDTBYvxokX4AAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10976d790>"
]
}
],
"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg = sns.FacetGrid(titanic, hue=\"who\", aspect=3, palette=pal)\n",
"fg.map(sns.kdeplot, \"age\", shade=True)\n",
"fg.set(xlim=(0, 80));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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z74+bUbtx7YBOgVU/upbwUNN5n9PS0sL69et57bXXePrppykuLmbz5s08/fTT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\n/wDIHClnn8q7ggAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1096d6d50>"
]
}
],
"prompt_number": 15
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"How many first, second, and third class passengers are in our sample?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Although have some information about the distribution into classes from the sex plots, let's directly visualize it an then see how the classes break down by age."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", data=titanic, palette=\"BuPu_d\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x1096ed490>"
]
}
],
"prompt_number": 16
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg = sns.FacetGrid(titanic, hue=\"class\", aspect=3, palette=\"BuPu_d\")\n",
"fg.map(sns.kdeplot, \"age\", shade=True)\n",
"fg.set(xlim=(0, 80));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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S1d5Fv6UfAK1WS4DJiDnQjDnQjCkoCK1PGHq9lqQYX7Taqd84RXGrnD/SimPE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\nb3wDp9NJUVER99xzD4cOHRo/x4fhNy0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T5LL5Ad9Ht+q43E7cHidO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\n/n9UXH7BeNJRHwAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1096f4410>"
]
}
],
"prompt_number": 17
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Finally let's look at the breakdown by age and sex."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg = sns.FacetGrid(titanic, col=\"sex\", row=\"class\", hue=\"sex\", size=2.5, aspect=2.5, palette=pal)\n",
"fg.map(sns.kdeplot, \"age\", shade=True)\n",
"fg.map(sns.rugplot, \"age\")\n",
"sns.despine(left=True)\n",
"fg.set(xlim=(0, 80));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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4p07VOksRkWtUVa3Nn7c38NaeEFErNj3wKxO8Gr27RnVPcTEjK0D+cJvth8K8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2ZbqPVa16B3vE56b4OBvW2kJRukJRskxXafgV+6fKInhBBdhWazYRsypLmFOHj4MOaBAzSVlYVa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\nhw9HdzrjHY74hs65TGrqTV5fXc/QvlYOng7wl81es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"text": [
"<matplotlib.figure.Figure at 0x109740550>"
]
}
],
"prompt_number": 18
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Where were our passenger's cabins?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also have information about what deck each passgener's cabin was on, which may be relevant."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"deck\", data=titanic, palette=\"PuBu_d\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x109740750>"
]
}
],
"prompt_number": 19
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"How did the decks break down by class for the passengers we have data about?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"deck\", hue=\"class\", data=titanic, palette=\"BuPu_d\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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IZs+ereHDhys6OlqS9PDDD6tr165asGCBRo4cqd69e8tut2vixImSftriCgwM\n1PPPP69p06apsrLSm28L8Hl8dQUAwBhsKQEAjEGUAADGIEoAAGMQJQCAMYgSAMAYRAkAYAyiBAAw\nxv8H6O5Fku+jfEwAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10b9d9a10>"
]
}
],
"prompt_number": 20
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that we're missing a lot of deck data for the second and third class passengers, which will be important to keep in mind later."
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"How much did they pay for their tickets?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since we have data about fares, let's see how those broke down by classes."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from seaborn import linearmodels\n",
"reload(linearmodels)\n",
"reload(sns)\n",
"sns.set(style=\"nogrid\")"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", \"fare\", data=titanic, palette=\"BuPu_d\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAWEAAAFhCAYAAACh/xvXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x10b97a6d0>"
]
}
],
"prompt_number": 22
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.violinplot(titanic[\"fare\"], titanic[\"class\"], color=\"BuPu_d\").set_ylim(0, 600)\n",
"sns.despine(left=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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AggUL0l2SiEirltIW+UMPPcSLL75Ibm4uZWVlXH755dx+++2UlpYyceJELr30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\nrisnGK4kNyeXm2+5mbFjx2K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dO8u0kuVIhw+Yaxz0Fg6Hqauro76+vulWV1dHKBRq+hJZ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\nAMBiXye80GtUVlD6AAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c116d10>"
]
}
],
"prompt_number": 23
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are some extreme outliers in the first class distribution; let's winsorize those to get a better sense for how much each class paid."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"titanic[\"fare_winsor\"] = titanic.fare.map(lambda f: min(f, 200))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 24
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.violinplot(titanic[\"fare_winsor\"], titanic[\"class\"], color=\"BuPu_d\").set_ylim(0, 250)\n",
"sns.despine(left=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Or7gsaTAbrJgz549obW3VOg4RUUK6YJE///zzCIVC2LFjB+bMmYMhQ4bgo48+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\nYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c146e50>"
]
}
],
"prompt_number": 25
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"How did the fares break down by deck? Let's look both at the mean and the distribution."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"deck\", \"fare\", data=titanic, palette=\"PuBu_d\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x1093dd910>"
]
}
],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.violinplot(titanic[\"fare_winsor\"], titanic[\"deck\"], color=\"PuBu_d\")\n",
"sns.despine(left=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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lSQIkCRyn/FZLQnrTa4LPyMgIRxwkQkmShG3btoMzxoBh+jfgw7AcOKMV27Ky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\nrPjrX2VvPxyKi4uxc2c24q9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kHzqIEfP+A/pY+Yf++yptxgJY0sbgt8//TrWDdcjA1GOC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\nRIIXBEEQBCf0/5t7UtUgOHmbAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c135790>"
]
}
],
"prompt_number": 27
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It might make more sense to plot the median fare, since the distributions aren't normal."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"deck\", \"fare\", data=titanic, palette=\"PuBu_d\", estimator=np.median);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10c1706d0>"
]
}
],
"prompt_number": 28
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also look at a regression of fare on age to see if older passengers paid more. We'll use robust methods here too, which will accound for the skewed distribution on fare."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.regplot(\"age\", \"fare\", data=titanic, robust=True, ci=None, color=\"seagreen\")\n",
"sns.despine();"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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CnGFTWDp2tg+qFRf6/fZ/8PGx7bhVNwPj+/C3b/+nBL0QAUZuocQ1eT37Uwrr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\n+4bfAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c1346d0>"
]
}
],
"prompt_number": 29
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Where did the passengers come from?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The *Titanic* passengers embarked at one of three ports before the voyage."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", data=titanic, hue=\"embark_town\", palette=\"Set2\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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AamoqLi4uJCcnExUVhc1mIyUlhbZt2zZb0yIiIheqQYHXpUsX1q9fD0BAQABf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\n8ERExBAUeCIiYgj/D/XGtg0Uj0eQAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x109692990>"
]
}
],
"prompt_number": 30
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Who was traveling with family members?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also have some data, although it's not coded very well, about the number of parents/children and the numbe of siblings/spouses on board for each passenger."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", data=titanic, hue=\"parch\", palette=\"BuGn\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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0+OOP+7nXHV94eLjeeustPfHEE3rnnXc0bNgwHTx4UK+88orGjh0ru92uzMxM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\nRFgAAIwICwCAEWEBADAiLAAARv8f7czo4OxgEV8AAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c153ed0>"
]
}
],
"prompt_number": 31
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", data=titanic, hue=\"sibsp\", palette=\"YlGn\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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iNWvWfKXtK6+84tOYfCbtgyuL67Bjx46WH/633367srKyNG/ePG3evFmpqanK\nyMjQAw88II/Ho6VLl+rPf/6z1q9fH+CqO76IiAj99a9/1S9+8QudOnVKI0aM0N69e/X+++8rMzNT\ndrtd2dnZqq2tlcfj0Q9/+EONGjVKiYmJ2rp1qyRp/vz5Sk1NVWpqql599VVJUk5Ojp588kllZWVp\nxIgROnjwoCRpzZo1GjlypLKystolkLqKv6/a93g8OnbsmCZPnqykpCQtXrxYknT33Xfr6NGjWrRo\nkSZMmKC0tDQdOXJEzz//vJKSkjR16lTjlQf8h7BohY8++uhLt6FOnz7d8t7Jkyf129/+Vi+//LL+\n+7//W//+7/+u0tJSTZkyRbW1tVq4cKEyMzM1a9asAJ5B5zBw4EBt3bpVu3fv1pgxYxQfH6/CwkI9\n/vjj+tnPfqbt27dr8uTJWr58uQoKCnT+/HmVl5dr+/bt2r9/v4qKilRTU6M9e/Zo165dev311/XB\nBx/IYrFo8ODB+uMf/6innnpKa9eu1WeffaYVK1aovLxcb731liwWC7/JtoH6+noVFBSotLRUP/3p\nTyX944rBYrFo+PDh2r17ty5fvtzyOW7atEkXL14MZNldCrehWmHYsGFfug31xXvXN998s6KioiRJ\nL7/8spYtW6ZXX31V8fHxuu+++8Szj/5TXV2tiIgIvfbaa5KkiooKZWVlqaGhQbNnz5YkNTU1KTY2\nVmFhYRo9erQkKTIyUkuWLNGLL76ojIwMSVJISIhSU1P10UcfSZISExMlSbfddpt2796t48ePKz4+\nXlarVdLVLW34LP0vISFBVqtVVqtVISFf/bE0dOjVvZeOHDmi73znO5KkHj16KDk5mc+jnXBlcR2+\n+I/0ixsmrl27VosWLdKOHTvk8Xj05ptvtuzAi+tXWVmpuXPnqqmpSZIUGxurqKgoxcbG6le/+pW2\nb98uh8Ohe++9V/Hx8dq3b58kyel0avLkyYqPj9euXbskXQ2VsrIyxcbGfukYf/9sY2Nj9eGHH6qu\nrk4ej0d79+7lyqINmP5O//7+8OHDVV5eLrfbrcbGRh08eJDPo51wZdEK//yP8ou3JL74XkpKiqZM\nmaKwsDCFhYVp6tSpqqur0/vvv69XX31VeXl57Vp3ZzN9+nQdPnxYycnJCg0Nldvt1osvvqhBgwbp\n4Ycf1pUrV2SxWPSLX/xCMTExKi4uVkZGhq5cuaJFixZp4sSJ2rFjh8aMGaPGxkY98MADLVcUX/w8\nLRaLbr5/iudzAAACvElEQVT5Zi1cuFDp6enq3bt3yxUGrt8//13/8+tf13bEiBGaNm2aUlJS1K9f\nP918883tUyzYGwoAYMZtKACAEWEBADAiLAAARoQFAMCIsAAAGBEWAAAjwgKd0t13383usIAfERbo\nlNjDCfAvwgKdwn/8x39o6NChGj58uFauXNnyenNzs3JzczVmzBhFR0dr8uTJqq+vV21tre655x4l\nJSUpKSlJhYWFkq7u63XXXXdp5MiRevLJJwN1OsANh+0+0OFt2rRJZWVl+uCDD9TY2Kj09HTV19fL\n4/GorKxMPXr0UFlZmTwejzIzM/XWW2/p4sWLGjJkiIqKinTkyBHl5+dr8uTJ+slPfqJPP/1UQUFB\nmjt3rk6fPq0BAwYE+hSBgCMs0OHt3LlTDzzwQMuupQcPHpTdbpfFYlFGRoZ69+6t1atX68iRIzp2\n7JguXbqkMWPG6Nlnn9WpU6d0zz33aOHChQoODtaYMWOUlJSkadOmae7cuQQF8P9xGwodntVq/dIO\nwDU1Nbp06ZI8Ho+2bt2qf/mXf1FoaKgeffRR2Ww2eTwexcTE6MiRI/rBD36g0tJSpaSkSJK2bNmi\nNWvWyOPxKCsrSzt37gzUaQE3FMICHZ7NZtPmzZt15coVXb58WRMnTtSpU6ckSX/605/03e9+VzNn\nztQtt9yinTt36sqVK1qzZo2ef/55ZWdna/Xq1Tp37pzOnz+v+Ph4JSQkaPHixZowYYLef//9AJ8d\ncGPgNhQ6vPvuu0/79+/XyJEj5Xa7NW/ePP3ud7+TxWJRbm6uvv/972vz5s269dZbNW3aNNXU1GjB\nggV68MEHdeedd8pqtWrx4sXq06ePnnjiCSUnJ+umm27S7bffrpycnECfHnBDYItyAIARt6EAAEaE\nBQDAiLAAABgRFgAAI8ICAGBEWAAAjAgLAIDR/wOIqxQ3+52TagAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10b976210>"
]
}
],
"prompt_number": 32
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We defined a variable that just measures whether someone was traveling alone, i.e. without family."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"alone\", data=titanic, palette=\"Greens\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x109678810>"
]
}
],
"prompt_number": 33
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"What made people survive the sinking?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<div style=\"width:100%; text-align:center\">\n",
"<i>Iceberg, dead ahead!</i><br><br>\n",
"<img src=http://upload.wikimedia.org/wikipedia/en/b/bb/Titanic_breaks_in_half.jpg width=500px>\n",
"</div>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we have a feel for the characteristics of our sample, let's get down to the main question and ask what factors seem to predict whether our passengers survived. But first, one more count plot just to see how many of our passengers perished in the sinking."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"alive\", data=titanic, palette=\"OrRd_d\");"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10c135950>"
]
}
],
"prompt_number": 34
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"What classes had the survivors traveled in?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"It's part of popular lore that the third-class (or steerage) passengers fared much more poorly than their wealthier shipmates. Is this borne out in the data?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", \"survived\", data=titanic).set(ylim=(0, 1))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 35,
"text": [
"<seaborn.axisgrid.FacetGrid at 0x10c134ed0>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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gfz5LxZXbPuGjM2MIE5FRG/FIH7y/LAx/mNbaokg9VYol7xzAtn35+sGPzooh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\nRAIxhImIBGIIExEJ9P8BOUNZoutBNTAAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c134fd0>"
]
}
],
"prompt_number": 35
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also of course know that women were given high priority during the evacuation, and we saw above that Third class was disproportionately male. Maybe that's driving the class effect?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", \"survived\", data=titanic, hue=\"sex\", palette=pal).set(ylim=(0, 1));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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z5XF/pR8/NzeXZcuW8fjjj/Pqq68yf/58Xn/9dd58801++OEHVqxYwYYNG/D7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\nREQsoQASERFL/H+r9w/jQW5BKQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10c146b10>"
]
}
],
"prompt_number": 36
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nope, in general it was not good to be a male *or* to be in steerage."
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"What effect did \"women and children first\" have?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Were they at least successful in evacuating the children?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg = sns.factorplot(\"class\", \"survived\", data=titanic, hue=\"who\", col=\"who\", palette=pal, aspect=.4)\n",
"fg.set(ylim=(0, 1))\n",
"fg.despine(left=True)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 37,
"text": [
"<seaborn.axisgrid.FacetGrid at 0x10c105e10>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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SOv7OK5B8xKnLmmu0nYj3c122AwpayVmSAslH9Iu5jPA29Yt4Zebosp2ItwuJ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\nggJJREQ8ggJJREQ8ggJJREQ8wv8HEerlZv6nErYAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c12df50>"
]
}
],
"prompt_number": 37
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pretty good for first and second class (although the precise estimates are unreliable because there weren't that many children traveling in the upper classes. It's actually the case that every second-class child survived, though).\n",
"\n",
"We suspect that the best way to predict survival is to look at whether a passenger was an adult male and what class he or she was in."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"class\", \"survived\", data=titanic, hue=\"adult_male\", palette=\"Blues\").set(ylim=(0, 1))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 38,
"text": [
"<seaborn.axisgrid.FacetGrid at 0x10c585550>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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udmw4ceJE37+LL76Y5557jk8++eRsX6uIiF8YhoGpYQK+dczDAxBuMZHQzPxI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\n3eOYdWk6KfWHHItI26ZAEb/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7XC6mT59ORkYGvXv3ZsqUKdTW1lJeXs4ll1zCiBEjGDFi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\n8QsFioiI+IUCRURE/EKBIiIifvH/Acz1u/cDiXPAAAAAAElFTkSuQmCC\n",
"text": [
"<matplotlib.figure.Figure at 0x10c1bd890>"
]
}
],
"prompt_number": 38
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Another way to plot the same data emphasizes the different outcomes for men and other passengers even more dramatically."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg = sns.factorplot(\"adult_male\", \"survived\", data=titanic, col=\"class\", hue=\"class\",\n",
" aspect=.33, palette=\"BuPu_d\")\n",
"fg.set(ylim=(0, 1))\n",
"fg.despine(left=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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sW7fOEvU4tKR5M3HpfDlqq+pQWV6NsEkhcpdkV0Kj/HD1fB3qK1rQ1a4zjTIk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\nAUtEJBEGLBGRRBiwREQSYcASEUnk/wcT+nr9bSajeAAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10c134f10>"
]
}
],
"prompt_number": 39
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Did age matter in general?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also ask whether age as a contiunous variable mattered. We'll draw logistic regression plots, first jittering the survival datapoints to get a sense of the distribution."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.lmplot(\"age\", \"survived\", titanic, logistic=True, y_jitter=.05);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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k39FBdN1ziZyMzv4M4aBJIhZiKOVZdFJK6qoi1CQmliIDNFZHCJkGtuNlCwgp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\nWYCiuJN9mqqQMW2srFtD11Re3npywIiRkw1dnGqM5UYbqqIwY0Ipty8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"text": [
"<matplotlib.figure.Figure at 0x1099d57d0>"
]
}
],
"prompt_number": 40
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can also plot the same data with the survival observations grouped into discrete bins."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.lmplot(\"age\", \"survived\", titanic, logistic=True, x_bins=4, truncate=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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UhTaTQUZifASKy+3wKIrm3c48HgUbdp1sFsAAoAKIjjBiQI8YZO8uxI4DJdh9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\nrkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10c1b8510>"
]
}
],
"prompt_number": 41
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"How did age interact with sex and class?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We know that sex is important, though, so we probably want to separate out these predictions for men and women."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"age_bins = [15, 30, 45, 60]\n",
"sns.lmplot(\"age\", \"survived\", titanic, hue=\"sex\",\n",
" palette=pal, x_bins=age_bins, logistic=True).set(xlim=(0, 80));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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lWWhoaMCjjz6K888/H1VVVaitrcW7776LpUuXQimFsrIyPPHEEwgEAn22u8/w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\nRESOY/gQEZHj/n8zfxMOO264YwAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1099db5d0>"
]
}
],
"prompt_number": 42
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Class is imporant too, let's see whether it interacts with the age variable as well."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.lmplot(\"age\", \"survived\", titanic, hue=\"class\",\n",
" palette=\"BuPu_d\", x_bins=age_bins, logistic=True).set(xlim=(0, 80));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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7G9m39gTuLh+bXqnm8JbTzLxjLEWjs5M1mmvKqrsWPbOkUCiMz+OPVXkIBBFC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\n6es6g5bMPC1BfxiP0080FEEk6I1QZ9A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Yesd0fG1B6ve1JBZ5erKdLF43NSnzJ1l5Hm68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\nJCIiRimIRETEKAWRiIgY9QUyl4VZoQfbEQAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10c59c950>"
]
}
],
"prompt_number": 43
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Because the above plot is rather busy, it might make sense to split the three classes onto separate facets."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.lmplot(\"age\", \"survived\", titanic, col=\"class\", hue=\"class\",\n",
" palette=\"BuPu_d\", x_bins=4, logistic=True, size=3).set(xlim=(0, 80));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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2k6fnX/K+DYpCMKAR8Ed6Em1WKzHx589HdLsiK7qcm9kthgerw8y0ZTlMWZxF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\nrkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10c59d590>"
]
}
],
"prompt_number": 44
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Did it matter what passengers paid, or where they stayed?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We know that class matters, but we can also use the `fare` variable as a proxy for a contiuous measure of wealth."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.lmplot(\"fare_winsor\", \"survived\", titanic, x_bins=4, logistic=True, truncate=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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P31BCEoiNZl1fpWAIU7MkSQIFJRUAghPADpcH/9j0PfJOFAEARvRvi3vHdFVU2UlJkqAP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\n5mHd9pP8pUTUQgQshHft2oV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"text": [
"<matplotlib.figure.Figure at 0x10b9f44d0>"
]
}
],
"prompt_number": 45
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Perhaps it mattered what deck each passenger's cabin was on?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"deck\", \"survived\", data=titanic, palette=\"PuBu_d\", join=False);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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TTY9Up4KCAt14440+t0VHRxua5tK1bNlS27dvNz2GX2f/fJx1zz336IknnjA4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\nfhoAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10b9d7250>"
]
}
],
"prompt_number": 46
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"deck\", \"survived\", data=titanic, col=\"class\", size=3, palette=\"PuBu_d\", join=False);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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WAFAmhMJJ6HGyN4FarRbTp09HUFAQQkNDkZmZqTceGxuLwMBABAcHY8aMGRB8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\nYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x1099ea5d0>"
]
}
],
"prompt_number": 47
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Did family members increase the odds of survival?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Although the way our data on family members was coded, we don't know for sure what sort of companions these passengers had, but it's worth asking how they influenced survival."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.lmplot(\"parch\", \"survived\", titanic, x_estimator=np.mean, logistic=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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50qDsNJw3MHYXPDp7nYawruuYPXs2br31Vtx4440YOXIkNK3j8tOuKi8vh6qq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\nAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1096f4ed0>"
]
}
],
"prompt_number": 48
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.lmplot(\"parch\", \"survived\", titanic, hue=\"sex\", x_estimator=np.mean, logistic=True, palette=pal);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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9kyeukg6ijteIQiGv8am4JecbHdbtS7LnVCp9qXDsYB/LpweZIuXSBS3r4VNW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\nOe2lKXQAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x10c113ed0>"
]
}
],
"prompt_number": 49
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.lmplot(\"sibsp\", \"survived\", titanic, x_estimator=np.mean, logistic=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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Xv8ZNN910wu9D1hhu3LGUUk1f7nO8C/iGLpwvp9IXAY1g1kM6EpeNDVqzt5ty\nu0RMqtCHyxm95nLfp25sSyfnuL6imqZv4575zaid5HilYDCIDRs24Oqrr8aWLVtQW1trnAuFQli2\nbBmam5vhdDrh8/k4My+PZcYdJyUF4fSFPIaxdRx2m7HeRYamaelecySn59zZG0MiqaD94ADaDw7k\nvE75BE9WMOsjNLizyak5ZgjfeuutAPTe63XXXYeqqqpTfrPGxkY0NzcjGAwCANatW4f169cjEolg\nxYoVWL58ORYvXgyHw4Fzzjln3O3gUYj0Reg9UFUNoZiEWEKGqmgsVYwBgiCg2O9Csd+Fs2dk95oV\ndPbGjHA+1B3FoSNhhGMyevrj6OmP4y8fDfaanQ69LDKp0o/JFfq/kyr88LF0d1xMHScsCIJR2siY\nPXu2cXvFihVYsWLFSb02jW02m4AJfhcm+F2IJWSEoxKSsgpRZBiPNQ67mNVrrjGOD0SSONQdMXrM\nh7oj6OiJQpJV7O0IYW9HKOd1SopcxoXATGmjqswLOy/e5jB1nDARoG8d5HU7IKcUhKMSookUhHGy\n1nE+y/Sas2vNmQknh7qjOJwJ6O4I+sNJ9KU/sqdpizYB1WW+dG/Zh4npcC4pGr+7aJs6Tpjyy2iP\ni3bY9THHJQG9VBGJSZwenWeGm3AC6DtoZ8YyZ3YzOdytT9PO3M/mddn1QK70YVJ6Qf5JFX54xsGF\nQFPHCVN+MWtctCAIKPa5UOxzIRKTeJGnAPg8DsyZVoI50wanaauaht7+uBHOB7v1skZ3XxyxZAq7\nD/YP2dW8NODO6TFPrPChusxXUCWNEUO4srLytI0Tpvxj9rhov9eJsvSMvIzhhjJS/rEJAipKvKgo\n8eJv5lQaxyVZQUdvFIeO6L3lTE85FJVwNJTA0VAC77YPljRsNgHVpd6cYJ5YoY9tzsdf4COG8FNP\nPYW77rrLjLYQDVExwYuKCV5E4zJiSdaOC5HTIWJadQDTqnN3Lw/HpHQ5I5ouZwyWNA73RHG4J4q2\nDwYXOHI5RNSU+zCxIruk4UOR1zmmv2eOa1H3e++9F3V1dfB4BnsoixcvHtWGEWW4XXa4XXaUahoi\ncQmRmIzUONwnb7wp8joxZ1op5kwbXD9G1TT0DiSMWnMmmDuPxpCUlWFHafg9Dr23XD7Ya55Y7oPX\nPTaG0I0Ywr29vdi0aRM2bdqUc/yT94lGmyAIKPK6UOR1ISmlEI5KiHG9inHFlrVh6zlZCxylFBVd\nvTEc7ok2Q3WJAAAVOklEQVQYIzUOd0fQM5BAJC4P2RsQACYUuTCxfDCUJ1X4UV3mM31/wBFDePPm\nzSY0g+jEZHaRNtarSMjQwFLFeGUXbfqwt0o/zss6nkimcLgnio6edEmjJ4qOnggGIhL6w0n0h5M5\nS4MKAMomeNLh7ENNuR+Tyn2oKvPCYR+dcB4xhOvr64ccEwQBr7zyyqg0iOhEZNarmFDkYqmChnC7\n7JgxqRgzJhXnHI/EZb233BM1ShqHeyKIJVLGrMAduwdXoNMvKurhXJPVe64sPfXJJyOG8N13323c\nlmUZv/vd71BSUvIpzyAyX3apIp6QEY7JSEgKZ+TRsPweB2ZPLcHsrJ1OMmtpZGYCZoL5cE8USUkx\nNm/NXujIZhNQWeIxQrmmXK89V5Z4jrtMNmIIX3zxxTn3v/jFL+L888/Hfffdd5yfLpG5PG4HPJ+Y\nkcfFg2gk2WtpZM8K1DQNfaEkDvXkhnNHTzS9Op2+FdX2rNcSbQKqSr3pUPZhcqUfNeX+Yd93xBDe\nv39/TmPee+89HD169FOeQXTyPjrQh2f/9KFxf8t7HZg7veSkar2fnJEXjXPxIDpxgiCgtNiN0mI3\n5s8c3Lw1M1Kjw6g168PmOnv1cM4Mo9uWfvxlwRnDvv6IIbx48WLjB0AQBFRUVODhhx8+9c+M6BP+\nuqcHD/1mG3oGEsax5zfvBqDhq8vmnfTrZs/I4+JBdLpkj9TI3opKVTX0DMT1oXO9ehD3hRLHfJ0R\nQ/iZZ55BS0sL7rjjDixbtgxvv/02otHo6fksiLI8v7k9J4ABQAPw8p8PYNmFM1E+wTP8E08AFw+i\n0abXib2oLPEC0MP50/74GrFy/K1vfQsLFy7Ec889B6/Xi+3bt2PNmjWnq71Eho8PDwx7fCAqoeUv\nh07re2VKFZMr/Zjgd8FuE6By9SCywIghrKoqLrroIrz44ov48pe/jKlTp0JRFDPaRuOM81PGYY7W\nAuGCIMDvdaKqzIeKrDUrGMhklhFD2Ov14qGHHsLLL7+MK664Av/2b/+GoqLxud07ja6zsnZ3yDap\nwo+LPjt51N8/e2zxBL8LLocIVdFOejsvouMxYgg/9dRTiMVieO6551BaWorOzk48/fTTZrSNxpmv\nXnEW5s3MDeJivxM3Xn7WqM1WOhaXw47yCR5MrvKj2O/UyxWqamobaHwQtDz+NS8IAnspBUZRNTzz\nx5145k+7AAB3f70OCz9Tbcp7f/DxUXzvP14HADz4jQvxmTNKc84riopQVEJcSkHhrDw6ATYBxxwn\nzO8iGlNEm4DPzh3cVNbndlrYmlyiaENJwJ2eEeWFxynqO5Gr7AjQySv8vUOIRkFmAaFSALGEjFhc\nRlxSONyNThhDmOgUZcYea+n1jmPxFKSUwnIFHReGMNFpkr2IEOvHdLwYwkSjIFM/LgEQT6YQjcuI\nc3smGgZDmGiUeVx2eFx2o1wRjaUgpbh2BekYwkQmyS5XZNauiEspaCq4sts4xhAmskBm7QogPboi\nkUIimQLAQB5vGMJEFsuMrgA43G08YggTjSHZw92icb2HHJdSp7yPGY1dDGGiMSizupvf64SqDo4/\nlhWOPy40pv5vqqqKlStXYtGiRaivr0d7e3vO+fXr1+Nzn/scLrjgAtx2221cF4II+iLhAZ8L1elN\nJL1uO2wCoHBBoYJgagg3NTVBkiS0trZizZo1WL16tXEuHo/jrrvuwubNm/HGG29gYGAAL7zwgpnN\nIxrzRNGGkiI3asr9qCnzweuyA9C4wlseM7Uc0dLSgoaGBgBAXV0d2trajHNutxtvvvkm3G43ACCV\nSsHjOfXtbIgKlcMuoiQgogTuwQkhiRQEGy/o5RNTQzgUCiEQCBj3RVGEqupTOjObiALAww8/jGg0\niiVLlpjZPKK8lT0hJBqXEY3LSMoKRF7QG/NMDeFAIIBwOGzczwRw9v3vfe972L17N37729+a2TSi\ngpB9QU9RNYSiSSSSKciKCpEX9MYkU/9XgsEgNm7cCADYsmULamtrc87feuutSCaTeP75542yBBGd\nHNEmGPXj6lIfPE4RANc/HmtM7Qk3NjaiubkZwWAQALBu3TqsX78ekUgECxcuxC9/+UssXrwYl1xy\nCQB9p+cvfelLZjaRqCA5HYMz9LIXFIIA2Fg/tpSpISwIAtauXZtzbPbs2cZt7uJMNPqy68exhIxo\nPIWErMDGGXqW4GQNonFKEAT4PE74PPqEkGhCnxDCC3rmYggTEWy2rAXp0zP04pyhZwqGMBHlEG0C\nin0uFPtyA1lKsYc8GhjCRHRMwwVyIsGSxenEECZKk3lh+FNlB3JmUaF4IoVkSuVFvVPAX2U07mma\nhqf/uBM/W7/dOPbrje+jL5y0sFVjW2ZRoaoyH6ZU+jHB74LTboOqalC58NYJYQjTuPe719rxbPOH\n6OlPGMfe29OLnz29zcJW5Y/MLL2KEi8mV/pRFnDD5RChaVxY6HgwhGnce/2dQxhuEtl77T3Ysbvb\n/AblMUEQ4HU7UD7Bg8mVRaiY4DVm6nHpzeExhGlc0zQNvQOJYc/JioY9BwdMblFhcbvsKC32YFJF\nkbH0pk0AFIWBnMELczSuCYKAsmL3sEHsEAXMmFxsQasKU2bpTQBQVA3RuIREUkFSUgDb+J0+zZ4w\njXsXLpiE4TY4njezHLWzKsxv0Dggpi/sVZZ6MblKryO7HXrZYrzVkdkTpnHv7xbPRCyRQvNb+4yL\nc/NmlOHb151rccvGh0wdObPjtCQr+nrIkgIppcBmEwp6+Bt7wjTuCYKA6y6di29f+1nj2A2XnYWS\nIpeFrRq/nA4RJQE3qst9mFxZhAl+F1zpXnKqAGvJ7AkTpTlE0eom0CfYbJlF6vX7iqIimtB3DUlK\nClRNy/vF6hnCRJQ3RNGGgG/wLxQ5pSCWTCEpKZBlPZTzbcEhhjAR5S2HXUSxXQR8+n1JVhCX8iuU\nGcJEVDCcDhFOx/ChLMljs3zBECaigvXJUJZTCuJJfRU4WVYgKxrsFq8GxxAmonHDYRfhsA9egFUU\nFbGkjKSkQkopSKVU04fEMYSJaNwSRVt6RxH9vqJqSCT10ReSrEBKaRBGeTNUhjARUZpoy+y7p9/X\nNA1xSUFSSkGSFciyCk3TYDuNJQyGMBHRMQiCAK/LDq9rMCozF/vkdG85pWinVMJgCBMRnQDjYl9a\nbglDhSyrgHD8Q+MYwkREp+CTJQwASEopvbecUvXxyuqxe8kMYSKi08zltMPlHIxX7VO2fBpbo5aJ\niArQp9WLGcJERBZiCBMRWYghTERkIYYwEZGFTA9hVVWxcuVKLFq0CPX19Whvbx/ymFgshmAwiA8/\n/NDs5hERmcr0EG5qaoIkSWhtbcWaNWuwevXqnPNtbW1YvHgxPv7444LeV4qICLAghFtaWtDQ0AAA\nqKurQ1tbW855SZLQ1NSEOXPmmN00IiLTmT5ZIxQKIRAIGPdFUYSqqsYUv0WLFpndJCIiy5jeEw4E\nAgiHw8b97AAmIhpvTE+/YDCIjRs3AgC2bNmC2tpas5tARDRmmF6OaGxsRHNzM4LBIABg3bp1WL9+\nPSKRCFasWGF2c4iILGV6CAuCgLVr1+Ycmz179pDHbdq0yawmERFZhsVYIiILMYSJiCzEECYishBD\nmIjIQgxhIiILMYSJiCzEECYishBDmIjIQgxhIiILMYSJiCxk+rRlopFMqS6C1203bhMVMoYwjTl+\njwOP37nUuE1UyBjCNCYxfGm8YE2YiMhCDGEiIgsxhImILMQQJiKyEEOYiMhCDGEiIgsxhImILMQQ\nJiKyEEOYiMhCDGEiIgsxhImILMQQJiKyEEOYiMhCDGEiIgsxhImILMQQJiKyEEOYiMhCpu6soaoq\nbr/9duzYsQMulwuPPfYYZs6caZzfsGED7rvvPtjtdtx88834+te/bmbziEz3/se9eLHlYxzujsLv\ndaDu7GpcHjwDgiBY3bSC8tc9PXix5WN09MRQ5HXg/DH0dTY1hJuamiBJElpbW7F161asXr0aTU1N\nAABZlvGP//iPaGtrg9frRTAYxJVXXonKykozm0hkmnc+6sZPn9qGvnDSOPaXj7rR2RvF1/9uvoUt\nKyzbP+zCz9e/PeTr3HU0hq9dOc/ClulMLUe0tLSgoaEBAFBXV4e2tjbj3AcffIBZs2ahuLgYDocD\nF1xwAV577TUzm0dkqt+9ujsnGABA04BN2w6iuy9mUasKz/++tmfI11nVgE3bDqB3IG5RqwaZGsKh\nUAiBQMC4L4oiVFU1zhUXFxvnioqKMDAwYGbziEyjaRr2Hg4Pey4UldD6bofJLSpMqqrh48OhYc8N\nRMbG19nUckQgEEA4PPiNp6oqbDb990BxcXHOuXA4jJKSEjObR+PclOoieN124/ZoEgQBbqd4zPMB\nn3NU33+8EAR86te5yGv9rt6m9oSDwSA2btwIANiyZQtqa2uNc3PnzsVHH32Evr4+SJKE1157DZ//\n/OfNbB6Nc36PA4/fuRSP37kUfs/o/3CePbNs2OPTqotw4YJJo/7+44EgCJg3s3zYc9Oqi3DhOdZ/\nnU3tCTc2NqK5uRnBYBAAsG7dOqxfvx6RSAQrVqzAT3/6U1x66aVQVRVf+9rXUFNTY2bziEwJ34yv\nXnE2Onuj2LG7B5qmH6sq9eKmK86GXeTo0dPl5mVnobM3infbB7/ONWVe3LzsbIhj4OssaFqmWflH\nEATkcfOJoGkaWnd04KOD/Qh4HWj4/HR43db/iVxoVFVDy47DaD80gIDPgYbPjZ2vM0OYiMhC1vfF\niYjGMYYwEZGFGMJERBZiCBMRWYghTERkIYYwEZGFGMJERBZiCBMRWYghTERkIYYwEZGFGMJERBZi\nCBMRWYghTERkIYYwEZGFGMJERBZiCBMRWYghTERkIYYwEZGFGMJERBZiCBMRWYghTERkIYYwEZGF\nGMJERBZiCBMRWYghTERkIYYwEZGFGMJERBZiCBMRWYghTERkIVNDOB6P48tf/jIWL16Myy+/HD09\nPcM+rru7G7Nnz4YkSWY2j4jIdKaG8Nq1a3HOOefgtddeww033IAf/vCHQx7zxz/+EUuXLsWRI0fM\nbBoRkSVMDeGWlhY0NDQAABoaGvCnP/1pyGNEUcTLL7+MkpISM5tGRGQJ+2i98OOPP46f//znOceq\nqqoQCAQAAEVFRRgYGBjyvCVLloxWk4iIxh7NRFdddZX21ltvaZqmaf39/dq8efOO+djp06dryWTy\nU1/voosu0gDwgx/84MeY/7j77ruHzbFR6wkPJxgMYuPGjTjvvPPw+9//HosXLz6l19u8efPpaRgR\nkUUETdM0s94sHo/jxhtvREdHB1wuF55++mlUVlbiZz/7GWbNmoVly5YZj50xYwZ27twJp9NpVvOI\niExnaggTEVEuTtYgIrIQQ5iIyEIMYSIiCzGEiYgsxBA+TqqqYuXKlVi0aBHq6+vR3t5udZNGlSzL\n+MpXvoLFixejrq4OGzZssLpJpjhy5AimTJmCXbt2Wd2UUXf//fdj0aJFOO+88/CrX/3K6uaMKlVV\ncfPNN+OCCy7A4sWL8eGHH1rdJAND+Dg1NTVBkiS0trZizZo1WL16tdVNGlVPPfUUKioq8Nprr+EP\nf/gDvvGNb1jdpFEnyzJuvfVW+Hw+q5sy6jZv3ow333wTra2t2Lx5M/bs2WN1k0bVSy+9hGg0ijfe\neAM/+MEP8M///M9WN8nAED5O2ete1NXVoa2tzeIWja6rr74a9957LwC9F2G3mzqvxxLf/e53cdtt\nt6Gmpsbqpoy6l156CfPnz8eXvvQlLFu2DFdeeaXVTRpVHo8HAwMD0DQNAwMDY2r+QeH/ZJ0moVDI\nWPcC0BcaUlUVNlth/h7L9AbD4TCuvvpq/OhHP7K4RaPriSeeQEVFBZYuXYr7778fhT58vru7GwcO\nHMALL7yAPXv24Morr8TOnTutbtaoCQaDSCQSmDt3Lnp7e8dUea0wE2QUBAIBhMNh434hB3DGgQMH\ncMkll+CGG27ANddcY3VzRtW6devQ3NyM+vp6vPPOO7jxxhvR1dVldbNGTXl5OZYuXQq73Y7Zs2fD\n7XYfc33vQvDggw8iGAziww8/NP5/x8p65YWdIqdRZt0LANiyZQtqa2stbtHo6urqwtKlS/Hggw/i\npptusro5o+7VV1/F5s2bsWnTJixYsAC//vWvUVVVZXWzRs0FF1yAP/zhDwCAw4cPIxqNoqyszOJW\njZ5oNGr8JVtSUgJZlqEoisWt0rEccZwaGxvR3NyMYDAIQO85FbIf//jHGBgYwL333mvUhn//+9/D\n7XZb3DI6HS6//HK89tprOP/886GqKh555BEIgmB1s0bNd7/7XXz1q1/FhRdeCFmWcf/998Pj8Vjd\nLABcO4KIyFIsRxARWYghTERkIYYwEZGFGMJERBZiCBMRWYghTERkIYYwjTuXX345Ojo68MQTT2DV\nqlVWN4fGOU7WoHHnxRdfBICCnpxA+YM9YSpoBw8exEUXXYTzzjsPdXV12LJlC6ZPn459+/YBAN5/\n/31ccMEFmD9/Pu68804A+mJNl19+ORYuXIiFCxcai71cfPHFWLVqFc4991ycffbZaG5utuzzosLB\nnjAVtF/+8pdYtmwZvvOd7+DVV19FS0uL0QPWNA179uzB9u3b4ff7cckll2Djxo3o6enBGWecgRdf\nfBE7d+7EunXrsGzZMgiCgFQqhW3btuGdd97BZZddhv3794+LZT5p9LAnTAVtyZIleOihh3D99dfj\n0KFDuOOOO4xzgiDgqquuQklJCRwOB/7hH/4BL7/8MhYtWoSmpiY0NjbijTfeMHrIALBy5UoAwIIF\nC1BTU4O//OUvpn9OVFgYwlTQFi1ahPfffx+XXnopnn32WSxbtiznvCiKxm1VVeFwODBr1izs3LkT\n119/PV5//XWcf/75n/p4olPBEKaC9v3vfx9PPvkkbrjhBjz88MN4++23jXOapmHDhg0Ih8NIJBJ4\n5plnsGTJEvzXf/0X7r77bvz93/89/vM//xNHjhzBwMAAAH3bJwBoa2tDf38/5s+fb8nnRYWDxSwq\naHfccQeuu+46PPHEExBFEWvXrsU//dM/AdDLEXPmzMGll16KgYEBLF++HEuWLEFdXR2uvfZa1NbW\nwuFw4J577kFxcTEAYPfu3Tj33HMhCAKeffZZjrCgU8alLImOU319PR544IGc8gTRqWI5gojIQuwJ\nExFZiD1hIiILMYSJiCzEECYishBDmIjIQgxhIiIL/f+g/Pt7AQ5+kwAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x10b9a5e50>"
]
}
],
"prompt_number": 50
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We also have a more interpretable `alone` variable (although it's reasonable to assume that this is going to be confounded with age)."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"sns.factorplot(\"alone\", \"survived\", data=titanic).set(ylim=(0, 1));"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
"<matplotlib.figure.Figure at 0x10b98e2d0>"
]
}
],
"prompt_number": 51
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Did traveling alone have a greater effect depending on what class you were in?"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fg = sns.factorplot(\"alone\", \"survived\", data=titanic, col=\"class\", hue=\"class\",\n",
" aspect=.33, palette=\"BuPu_d\")\n",
"fg.set(ylim=(0, 1))\n",
"fg.despine(left=True);"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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