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"cells": [
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"cell_type": "markdown",
"metadata": {},
"source": [
"# Using Seaborn To Visualize A Pandas Dataframe\n",
"\n",
"- **Author:** [Chris Albon](http://www.chrisalbon.com/), [@ChrisAlbon](https://twitter.com/chrisalbon)\n",
"- **Date:** -\n",
"- **Repo:** [Python 3 code snippets for data science](https://github.com/chrisalbon/code_py)\n",
"- **Note:**"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Preliminaries"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import pandas as pd\n",
"%matplotlib inline\n",
"import random\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 25
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df = pd.DataFrame()\n",
"\n",
"df['x'] = random.sample(range(1, 100), 25)\n",
"df['y'] = random.sample(range(1, 100), 25)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.head()"
],
"language": "python",
"metadata": {},
"outputs": [
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