{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"___\n",
"\n",
" 
\n",
"___"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Distribution Plots\n",
"\n",
"Let's discuss some plots that allow us to visualize the distribution of a data set. These plots are:\n",
"\n",
"* distplot\n",
"* jointplot\n",
"* pairplot\n",
"* rugplot\n",
"* kdeplot"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"___\n",
"## Imports"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import seaborn as sns\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Data\n",
"Seaborn comes with built-in data sets!"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"tips = sns.load_dataset('tips')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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" | \n",
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