matplotlib-demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Effectively using matplotlib\n",
    "\n",
    "From a tutorial on the eeenterneeet.\n",
    "http://pbpython.com/effective-matplotlib.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import FuncFormatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>account number</th>\n",
       "      <th>name</th>\n",
       "      <th>sku</th>\n",
       "      <th>quantity</th>\n",
       "      <th>unit price</th>\n",
       "      <th>ext price</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>740150</td>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>B1-20000</td>\n",
       "      <td>39</td>\n",
       "      <td>86.69</td>\n",
       "      <td>3380.91</td>\n",
       "      <td>2014-01-01 07:21:51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>714466</td>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>S2-77896</td>\n",
       "      <td>-1</td>\n",
       "      <td>63.16</td>\n",
       "      <td>-63.16</td>\n",
       "      <td>2014-01-01 10:00:47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>218895</td>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>B1-69924</td>\n",
       "      <td>23</td>\n",
       "      <td>90.70</td>\n",
       "      <td>2086.10</td>\n",
       "      <td>2014-01-01 13:24:58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>307599</td>\n",
       "      <td>Kassulke, Ondricka and Metz</td>\n",
       "      <td>S1-65481</td>\n",
       "      <td>41</td>\n",
       "      <td>21.05</td>\n",
       "      <td>863.05</td>\n",
       "      <td>2014-01-01 15:05:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>412290</td>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>S2-34077</td>\n",
       "      <td>6</td>\n",
       "      <td>83.21</td>\n",
       "      <td>499.26</td>\n",
       "      <td>2014-01-01 23:26:55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   account number                         name       sku  quantity  \\\n",
       "0          740150                   Barton LLC  B1-20000        39   \n",
       "1          714466              Trantow-Barrows  S2-77896        -1   \n",
       "2          218895                    Kulas Inc  B1-69924        23   \n",
       "3          307599  Kassulke, Ondricka and Metz  S1-65481        41   \n",
       "4          412290                Jerde-Hilpert  S2-34077         6   \n",
       "\n",
       "   unit price  ext price                 date  \n",
       "0       86.69    3380.91  2014-01-01 07:21:51  \n",
       "1       63.16     -63.16  2014-01-01 10:00:47  \n",
       "2       90.70    2086.10  2014-01-01 13:24:58  \n",
       "3       21.05     863.05  2014-01-01 15:05:22  \n",
       "4       83.21     499.26  2014-01-01 23:26:55  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(\"https://github.com/chris1610/pbpython/blob/master/data/sample-salesv3.xlsx?raw=true\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "top_10 = (df.groupby('name')['ext price', 'quantity'].agg({'ext price': 'sum', 'quantity': 'count'})\n",
    "            .sort_values(by='ext price', ascending=False))[:10].reset_index()\n",
    "top_10.rename(columns={'name': 'Name', 'ext price': 'Sales', 'quantity': 'Purchases'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Sales</th>\n",
       "      <th>Purchases</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kulas Inc</td>\n",
       "      <td>137351.96</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>White-Trantow</td>\n",
       "      <td>135841.99</td>\n",
       "      <td>86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Trantow-Barrows</td>\n",
       "      <td>123381.38</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerde-Hilpert</td>\n",
       "      <td>112591.43</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Fritsch, Russel and Anderson</td>\n",
       "      <td>112214.71</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Barton LLC</td>\n",
       "      <td>109438.50</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Will LLC</td>\n",
       "      <td>104437.60</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Koepp Ltd</td>\n",
       "      <td>103660.54</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Frami, Hills and Schmidt</td>\n",
       "      <td>103569.59</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Keeling LLC</td>\n",
       "      <td>100934.30</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Name      Sales  Purchases\n",
       "0                     Kulas Inc  137351.96         94\n",
       "1                 White-Trantow  135841.99         86\n",
       "2               Trantow-Barrows  123381.38         94\n",
       "3                 Jerde-Hilpert  112591.43         89\n",
       "4  Fritsch, Russel and Anderson  112214.71         81\n",
       "5                    Barton LLC  109438.50         82\n",
       "6                      Will LLC  104437.60         74\n",
       "7                     Koepp Ltd  103660.54         82\n",
       "8      Frami, Hills and Schmidt  103569.59         72\n",
       "9                   Keeling LLC  100934.30         74"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'seaborn-darkgrid',\n",
       " u'seaborn-notebook',\n",
       " u'classic',\n",
       " u'seaborn-ticks',\n",
       " u'grayscale',\n",
       " u'bmh',\n",
       " u'seaborn-talk',\n",
       " u'dark_background',\n",
       " u'ggplot',\n",
       " u'fivethirtyeight',\n",
       " u'_classic_test',\n",
       " u'seaborn-colorblind',\n",
       " u'seaborn-deep',\n",
       " u'seaborn-whitegrid',\n",
       " u'seaborn-bright',\n",
       " u'seaborn-poster',\n",
       " u'seaborn-muted',\n",
       " u'seaborn-paper',\n",
       " u'seaborn-white',\n",
       " u'seaborn-pastel',\n",
       " u'seaborn-dark',\n",
       " u'seaborn',\n",
       " u'seaborn-dark-palette']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.style.available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use('ggplot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10f4c8710>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VK1c4ceJERaNVWUm+ZcuW4eTkxA8//FBrfde2X3/9FS8vL3777bca78toNNZ4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\nAEAiHgCARDwAAIl4AAAS8QAAJOIBAEgWXnLMJcazc4kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ea7fd10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IM888Q0hICHB1VfuIESMIDw+/qTZWrVrF4MGDK6SelStX4ufnx4ABA0rsHzJk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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fa36d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setting fig and ax makes it easier to customize the plots\n",
    "fig, ax = plt.subplots(figsize=(5,6))\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "ax.set_xlim([-10000, 140000])\n",
    "ax.set(title=\"2014 Revenue\", xlabel='Total Revenue', ylabel='Customer')\n",
    "ax.legend().set_visible(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tick formatting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def currency(x, pos):\n",
    "    \"\"\"\n",
    "    The two args are the value and the tick position\n",
    "    \"\"\"\n",
    "    if x >= 1000000:\n",
    "        return '${:1.1f}M'.format(x*1e-6)\n",
    "    return '${:1.0f}K'.format(x*1e-3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KXg/yzDPPEBISAlxZjT5s2DDCw8NvqI2VK1cycODAcqlnxYoV+Pn50a9fvxL7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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f5fa710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setting fig and ax makes it easier to customize the plots\n",
    "fig, ax = plt.subplots(figsize=(5,6))\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "ax.set_xlim([-10000, 140000])\n",
    "ax.set(title=\"2014 Revenue\", xlabel='Total Revenue', ylabel='Customer')\n",
    "\n",
    "# Using a tick formatting function\n",
    "formatter = FuncFormatter(currency)\n",
    "ax.xaxis.set_major_formatter(formatter)\n",
    "\n",
    "ax.legend().set_visible(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Annotations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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c3NyAkssiGRkZ6PV6Dh06pLb1MNbW1ty7d09dbt26Nfv37wfgxIkT5OfL1MdC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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10fd54ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Setting fig and ax makes it easier to customize the plots\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# Plot the data and get the average\n",
    "top_10.plot(kind='barh', y=\"Sales\", x=\"Name\", ax=ax)\n",
    "avg = top_10['Sales'].mean()\n",
    "\n",
    "# Set limits and labels\n",
    "ax.set_xlim([-10000, 140000])\n",
    "ax.set(title=\"2014 Revenue\", xlabel='Total Revenue', ylabel='Customer')\n",
    "\n",
    "# Add a line for the average\n",
    "ax.axvline(x=avg, color='b', label='Average', linestyle='--', linewidth=1)\n",
    "\n",
    "# Annotate new customers\n",
    "for cust in [3, 5, 8]:\n",
    "    ax.text(115000, cust, \"New Customer\")\n",
    "\n",
    "# Using a tick formatting function\n",
    "formatter = FuncFormatter(currency)\n",
    "ax.xaxis.set_major_formatter(formatter)\n",
    "\n",
    "# Hides the legend\n",
    "ax.legend().set_visible(False)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using figures and sublots "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VMjIyyMvLY8SIEYSGhpKcnMwXX3yBs7MzGRkZdOjQgfHjx2M0Vl5jFxcX8/nn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\nhFAkKYKEEEIIoUhSBAkhhBBCkf4Xjrq21cx4PBMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110505490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get the figure and the axes\n",
    "fig, (ax0, ax1) = plt.subplots(nrows=1, ncols=2, sharey=True, figsize=(7,4))\n",
    "\n",
    "# Plot on the first axes\n",
    "top_10.plot(kind='barh', y='Sales', x='Name', ax=ax0)\n",
    "ax.set_xlim([-10000, 140000])\n",
    "ax.set(title=\"2014 Revenue\", xlabel='Total Revenue', ylabel='Customers')\n",
    "\n",
    "# Format currency values\n",
    "formatter = FuncFormatter(currency)\n",
    "ax0.xaxis.set_major_formatter(formatter)\n",
    "\n",
    "# Plot the average as a vertical line\n",
    "avg = top_10['Sales'].mean()\n",
    "ax0.axvline(x=avg, color='b', label='Average', linestyle='--', linewidth=1)\n",
    "\n",
    "\n",
    "# Repeat for the unit plot\n",
    "top_10.plot(kind='barh', y=\"Purchases\", x=\"Name\", ax=ax1)\n",
    "avg = top_10['Purchases'].mean()\n",
    "ax1.set(title='Units', xlabel='Total Units', ylabel='')\n",
    "ax1.axvline(x=avg, color='b', label='Average', linestyle='--', linewidth=1)\n",
    "\n",
    "# Title the figure \n",
    "fig.suptitle('2014 Sales Analysis', fontsize=14, fontweight='bold')\n",
    "\n",
    "# Hide the legends\n",
    "ax1.legend().set_visible(False)\n",
    "ax0.legend().set_visible(False)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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   },
   "outputs": [],
   "source": []
  }
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