{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"___\n",
"\n",
" \n",
"___"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Categorical Data Plots\n",
"\n",
"Now let's discuss using seaborn to plot categorical data! There are a few main plot types for this:\n",
"\n",
"* factorplot\n",
"* boxplot\n",
"* violinplot\n",
"* stripplot\n",
"* swarmplot\n",
"* barplot\n",
"* countplot\n",
"\n",
"Let's go through examples of each!"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import seaborn as sns\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"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", "