{ "metadata": { "name": "", "signature": "sha256:104e85e9af7a590adeb8564daf4e352e16e3d03f0b827610d1b13bb9b24dda8a" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "# The normal imports\n", "import numpy as np\n", "from numpy.random import randn\n", "import pandas as pd\n", "\n", "# Import the stats library from numpy\n", "from scipy import stats\n", "\n", "# These are the plotting modules adn libraries we'll use:\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "# Command so that plots appear in the iPython Notebook\n", "%matplotlib inline" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "# Now we'll learn how ot visualize multiple regression with lmplot()\n", "\n", "# Luckily, Seaborn comes with an example dataset to use as a pandas DataFrame\n", "tips = sns.load_dataset(\"tips\")" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "# Preview\n", "tips.head()" ], "language": "python", "metadata": {}, "outputs": [ { "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", "