Created
November 14, 2013 22:56
-
-
Save aseyboldt/7475835 to your computer and use it in GitHub Desktop.
boxplot
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"metadata": { | |
"name": "" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ | |
{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [ | |
"%matplotlib inline\n", | |
"\n", | |
"import pandas as pd\n", | |
"\n", | |
"df = pd.DataFrame({'X': [1, 0, 1, 0],\n", | |
" 'Y': [1, 0, 1, 0],\n", | |
" 'Z': [1, 0, 1, 0],\n", | |
" #'M': [1, 0, 1, 0],\n", | |
" 'B': list(\"XXYY\")}, \n", | |
" index=list(\"UUVV\"))\n", | |
"print df\n", | |
"axes = df.boxplot(by='B')\n", | |
"\n", | |
"# just for readability\n", | |
"axes[0,0].figure.tight_layout()" | |
], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"output_type": "stream", | |
"stream": "stdout", | |
"text": [ | |
" B X Y Z\n", | |
"U X 1 1 1\n", | |
"U X 0 0 0\n", | |
"V Y 1 1 1\n", | |
"V Y 0 0 0\n" | |
] | |
}, | |
{ | |
"metadata": {}, | |
"output_type": "display_data", | |
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEfCAYAAAAUfVINAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", | |
"text": [ | |
"<matplotlib.figure.Figure at 0x3da3c10>" | |
] | |
} | |
], | |
"prompt_number": 2 | |
}, | |
{ | |
"cell_type": "code", | |
"collapsed": false, | |
"input": [], | |
"language": "python", | |
"metadata": {}, | |
"outputs": [] | |
} | |
], | |
"metadata": {} | |
} | |
] | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment