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Created Matrixplot
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‎PythonDataScience/Self/.ipynb_checkpoints/SeabornMatrixPlot-checkpoint.ipynb‎

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{
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‎PythonDataScience/Self/SeabornMatrixPlot.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"import seaborn as sns\n",
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"%matplotlib inline\n",
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"tips = sns.load_dataset(\"tips\")\n",
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"flights = sns.load_dataset(\"flights\")"
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]
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},
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{
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"cell_type": "code",
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>year</th>\n",
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" <th>month</th>\n",
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" <th>passengers</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>1949</td>\n",
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" <td>January</td>\n",
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" <td>112</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>1949</td>\n",
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" <td>February</td>\n",
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" <td>118</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>1949</td>\n",
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" <td>March</td>\n",
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" <td>132</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>1949</td>\n",
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" <td>April</td>\n",
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" <td>129</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>4</th>\n",
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" <td>1949</td>\n",
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" <td>May</td>\n",
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" <td>121</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" year month passengers\n",
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"0 1949 January 112\n",
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"1 1949 February 118\n",
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"2 1949 March 132\n",
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"3 1949 April 129\n",
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"4 1949 May 121"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"tips.head()"
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]
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},
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"display_name": "Python [conda root]",
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"language": "python",
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"name": "conda-root-py"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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