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chriswl/ggplot examples

Created November 7, 2013 13:50
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  1. chriswl created this gist Nov 7, 2013.
    217 changes: 217 additions & 0 deletions ggplot examples
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    {
    "metadata": {
    "name": ""
    },
    "nbformat": 3,
    "nbformat_minor": 0,
    "worksheets": [
    {
    "cells": [
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "# import sys\n",
    "# # sys.path.append('/usr/lib/python2.7/dist-packages/gtk-2.0/')\n",
    "# sys.path.append('/usr/lib/python2.7/dist-packages/')\n",
    "# import cairo"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "# print(sys.path)\n",
    "\n",
    "# import matplotlib\n",
    "# matplotlib.use('GTK3Agg')\n",
    "# %pylab --no-import-all\n",
    "\n",
    "# import scipy\n",
    "from ggplot import *\n",
    "\n",
    "# matplotlib.matplotlib_fname()"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "meat"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "a = aes(x='index')\n",
    "a.DEFAULT_ARGS"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "df = pd.DataFrame({\n",
    " \"x\": np.arange(0, 100),\n",
    " \"y\": np.arange(0, 100),\n",
    " \"z\": np.arange(0, 100)\n",
    "})\n",
    "\n",
    "df['cat'] = np.where(df.x*2 > 50, 'blah', 'blue')\n",
    "df['cat'] = np.where(df.y > 50, 'hello', df.cat)\n",
    "df['cat2'] = np.where(df.y < 15, 'one', 'two')\n",
    "df['y'] = np.sin(df.y)\n",
    "\n",
    "gg = ggplot(aes(x=\"x\", y=\"z\", color=\"cat\", alpha=0.2), data=df)"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "gg"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "gg = ggplot(aes(x=\"x\", color=\"c\"), data=pd.DataFrame({\"x\": np.random.normal(0, 1, 10000), \"c\": [\"blue\" if i%2==0 else \"red\" for i in range(10000)]}))\n",
    "gg"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "#print gg + geom_density() + xlab(\"x label\") + ylab(\"y label\")\n",
    "gg = ggplot(aes(x=\"x\", y=\"y\", shape=\"cat2\", color=\"cat\"), data=df)\n",
    "#print gg + geom_point() + facet_wrap(x=\"cat\", y=\"cat2\")\n",
    "#print gg + geom_point() + facet_wrap(y=\"cat2\") + ggtitle(\"My Single Facet\")\n",
    "#print gg + stat_smooth(color=\"blue\") + ggtitle(\"My Smoothed Chart\")\n",
    "#print gg + geom_histogram() + ggtitle(\"My Histogram\")\n",
    "#print gg + geom_point() + geom_vline(x=50, ymin=-10, ymax=10)\n",
    "#print gg + geom_point() + geom_hline(y=50, xmin=-10, xmax=10)\n",
    "df['z'] = df['y'] + 100\n",
    "gg = ggplot(aes(x='x', ymax='y', ymin='z'), data=df)\n",
    "#print gg + geom_bar() + facet_wrap(x=\"cat2\")\n",
    "#print gg + geom_area() + facet_wrap(x=\"cat2\")\n",
    "gg = ggplot(aes(x='x', ymax='y', ymin='z', color=\"cat2\"), data=df)\n",
    "#print gg + geom_area()\n",
    "df['x'] = np.random.randint(0, 10, 100)\n",
    "df['y'] = np.random.randint(0, 10, 100)\n",
    "gg = ggplot(aes(x='x', y='y', shape='cat', color='cat2'), data=df)\n",
    "#print df.head()\n",
    "#print gg + geom_point()"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "meat_lng = pd.melt(meat[['date', 'beef', 'pork', 'broilers']], id_vars='date')\n",
    "ggplot(aes(x='date', y='value', colour='variable'), data=meat_lng) + \\\n",
    " geom_point() + \\\n",
    " stat_smooth(color='red')"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
    "## Meat"
    ]
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "meat_lng = pd.melt(meat, id_vars=['date'])\n",
    "\n",
    "p = ggplot(aes(x='date', y='value'), data=meat_lng)\n",
    "print(p) "
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "print p + geom_point() + \\\n",
    " stat_smooth(colour=\"red\") + \\\n",
    " facet_wrap(\"variable\")"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "print p + geom_histogram()+ facet_wrap()\n",
    "p = ggplot(diamonds, aes(x='price'))"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "p = p + geom_density() + \\\n",
    " facet_grid(\"cut\", \"clarity\")\n",
    "print(p)"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    },
    {
    "cell_type": "code",
    "collapsed": false,
    "input": [
    "p = ggplot(diamonds, aes(x='carat', y='price'))\n",
    "print(p + geom_point(alpha=0.25) + \\\n",
    " facet_grid(\"cut\", \"clarity\"))"
    ],
    "language": "python",
    "metadata": {},
    "outputs": []
    }
    ],
    "metadata": {}
    }
    ]
    }