{
"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": {},
"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": {},
"outputs": [],
"source": [
"tips = sns.load_dataset('tips')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
| \n", " | total_bill | \n", "tip | \n", "sex | \n", "smoker | \n", "day | \n", "time | \n", "size | \n", "
|---|---|---|---|---|---|---|---|
| 0 | \n", "16.99 | \n", "1.01 | \n", "Female | \n", "No | \n", "Sun | \n", "Dinner | \n", "2 | \n", "
| 1 | \n", "10.34 | \n", "1.66 | \n", "Male | \n", "No | \n", "Sun | \n", "Dinner | \n", "3 | \n", "
| 2 | \n", "21.01 | \n", "3.50 | \n", "Male | \n", "No | \n", "Sun | \n", "Dinner | \n", "3 | \n", "
| 3 | \n", "23.68 | \n", "3.31 | \n", "Male | \n", "No | \n", "Sun | \n", "Dinner | \n", "2 | \n", "
| 4 | \n", "24.59 | \n", "3.61 | \n", "Female | \n", "No | \n", "Sun | \n", "Dinner | \n", "4 | \n", "