4 - Exploratory Plotting.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next step in exploratory data analysis is plotting. Let's go through the world's fastest introduction to the core plotting library in Python, **matplotlib**.\n",
    "\n",
    "We are going to look briefly at some of the underlying concepts in matplotlib to aid in orientation. Having a mental model of how matplotlib works will greatly aid your ability to unlock the power of matplotlib. That said, one of the best ways to make great plots and to customize matplotlib is to go to the [gallery](https://matplotlib.org/gallery.html), find a plot that you want to emulate, and read the code. Another recent but great resource is the [python graph gallery](https://python-graph-gallery.com/)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are two interfaces available when working with matplotlib -- an interactive interface and an object-oriented interface. Both are available through the `matplotlib.pyplot` namespace.\n",
    "\n",
    "When working interactively, matplotlib maintains a global state for your current plot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, let's set some Notebook display options. For more information on this, check [here](http://ipython.readthedocs.io/en/stable/interactive/plotting.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the canonical import for matplotlib."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's use the interactive interface."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bfRdJJLSVeRxvfrmVZz5cT+1axvQxfbhxYIyGKIWwKhW1c24NkODjLCIhb8PeXCbMTmZNVjYX92jJ9DF9aNOkgb9jiZ/pokuRAFBc6uGVzzbz54830qheHZ6/oR9X943WECUBVNQifrc2K5uJiclk7MllVN9opo7qRfNGGqIk/0dFLeInBcVlPLd8A7NWZBIVUY9ZtyRwaa9W/o4lAUhFLeIHX2ceZFJiMlsP5nPjoBgevLIHjetriJIcn4papBrlFpYwc0kG767cTofm4fzjzsGc21lDlOTkVNQi1eTjjL1MmZPK3iOF3Hl+R+6/tDsNwnRnoZyailrExw4eLeIPC9OZt2YX3VtF8PIvzqFf+6b+jiU1iIpaxEeccyxI3s3U+WnkFpZw34iu/M+FXQiro9u/5fSoqEV8YE9OIQ/NTWH5un30bd+Up8bG0711hL9jSQ2lohbxIucc732bxROL1lHi8fDQyJ7cPqwjtXX7t5wFFbWIl2w7mMekxBS+yjzI0E7NmTk2jg7NNURJzp6KWuQslXkcb3yxhWeWradurVrMuDaOGwa21+3f4jUqapGzsH5PLhMSk1mblc2Ini2ZNjqO1k3q+zuWBBkVtcgZKC718OInm3jp0000rl+XP9/Yn6vi2+gsWnxCRS1ymtZkZTNh9lo27D3K6H7RPDKqN5ENw/wdS4KYilqkigqKy/jjsvW8/sUWWjWuz+u3JXBxDw1REt9TUYtUwZebDzApMYXth/L5+eAYHryiBxEaoiTVREUtchJHCkuYsXgd//wmi9jm4bw3fghDOjX3dywJMSpqkRNYnr6XKXNT2J9bxF0XdOK+Ed00REn8QkUtcowDR4t4bEE6C9buokfrCGbdkkB8Ow1REv9RUYtUcM4xb80uHluQRl5RGb+7tBt3De+sIUridypqEWBXdgEPzU3l44x99I8pH6LUtZWGKElgUFFLSPN4HP/4Zjszl2RQ5nE8clUvbj03VkOUJKCoqCVkbTmQx6TEZFZuOcR5XVow49o42keG+zuWyI+oqCXklJZ5+NvnW3j2ow2E1anFU2Pj+WlCO93+LQFLRS0hZd3uI0xMTCZ5Rw4/6dWKx0f3oVVjDVGSwKailpBQVFrGXz7exMufbqZpeF1e/PkAroxrrbNoqRFU1BL0Vm87zMTEZDbtO8q1A9ry8MheNNMQJalBVNQStPKLS3n6w/W8+eVW2jSuzxu3D+Si7i39HUvktKmoJSh9vvEAk5KS2XG4gFuGdmDC5T1oVE9/3aVm0t9cCSo5+SVMX5zO+6t20KlFQ96/ayiDOkb6O5bIWVFRS9BYmrqHh+elciivmF9f2JnfXtKV+nU1RElqPhW11Hj7c4uYOj+NRSm76dWmMW/cNpA+bZv4O5aI16iopcZyzpH03U7+sDCdguIyHrisO+Mv6ETd2hqiJMFFRS010s7sAiYnpfDZhv2c06EZT46Np0vLRv6OJeITVS5qM6sNrAJ2Oueu8l0kkRPzeBzvrNzGk0sycMBjV/fm5iEdqKUhShLETueM+rfAOqCxj7KInNTm/UeZlJjMt1sPc37XFjwxRkOUJDRUqajNrB0wEpgO3O/TRCLHKCnzMGtFJs8t30iDurV55qd9GTugrW7/lpBR1TPq54AJwAknqZvZeGA8QExMzNknEwFSd+YwMTGZtF1HuKJPax67pjctIzRESULLKYvazK4C9jnnVpvZhSfazzn3GvAaQEJCgvNaQglJhSVl/PnjjbzyWSbNwsN4+aYBXBHXxt+xRPyiKmfUw4CrzexKoD7Q2Mzecc79wrfRJFSt2nqICYnJZO7P46fntGPKyJ40DdcQJQldpyxq59yDwIMAFWfUv1dJiy8cLSrl6aUZvP31NqKbNODtcYO4oFuUv2OJ+J2uo5aA8NmG/UxOSmFXTgG3Do3lgcu601BDlESA0yxq59ynwKc+SSIhKTu/mMcXriPxux10jmrIB3cNJSFWQ5REKtMpi/jNkpTdPDwvjcP5xdxzURfuubiLhiiJHIeKWqrdviOFPDIvjaVpe+gd3Zi3xg2kd7SGKImciIpaqo1zjg9W72DawnQKSz1MvLwHd57fkToaoiRyUipqqRZZh/KZPCeFFRsPMCg2kplj4+gUpSFKIlWhohafKvM43v5qK09/uB4DHr+mNzcN1hAlkdOhohaf2bQvl4mJKazedpjh3aJ44to42jZt4O9YIjWOilq8rqTMw6ufbeaFf28ivF5tnv1ZX8b01xAlkTOlohavStmRwwOz15KxJ5eR8W2YOqo3URH1/B1LpEZTUYtXFJaU8dzyjcxakUnzhmG8evM5XNa7tb9jiQQFFbWctZWZB5mUlMKWA3lcn9CeySN70qRBXX/HEgkaKmo5Y7mFJTy1dD1//3ob7SMb8O4dgxnWpYW/Y4kEHRW1nJFP1u9jSlIKu48UMm5YR35/WTfCw/TXScQX9G+WnJZDecU8vjCdOd/vpGvLRiT++lwGxDTzdyyRoKailipxzrEoZTePzksjp6CEey/pyt0XdaZeHQ1REvE1FbWc0t4jhTw0N5WP0vcS364J79wxmJ5t9MvoRaqLilpOyDnH+6uymLZoHcWlHiZf2YNxwzRESaS6qajluLYfzGdSUjJfbj7I4I6RPDk2ntgWDf0dSyQkqajlB8o8jje/3MozH66ndi1j2ug+/HxQjIYoifiRilr+14a9uUyYncyarGwu6h7F9DFxRGuIkojfqaiF4lIPL3+6mb98spFG9erw/A39uLpvtIYoiQQIFXWIW5uVzcTEZDL25DKqbzRTR/WieSMNURIJJCrqEFVQXMaflm/grysyiYqox6xbEri0Vyt/xxKR41BRh6CvNh/kwaRkth7M58ZB7Xnwyp40rq8hSiKBSkUdQo4UljBzSQb/WLmdmMhw/nHHYM7VECWRgKeiDhH/XreXKXNS2ZdbyJ3nd+T+S7vTIEy3f4vUBCrqIHfwaBGPLUhn/tpddG8VwSs3n0O/9k39HUtEToOKOkg555i/dhePLUgnt7CE+0Z05X8u7EJYHd3+LVLTqKiD0O6cAh6ak8q/M/bRt31TnhobT/fWEf6OJSJnSEUdRDwex3vfZjFj8TpKPB4eGtmT24d1pLZu/xap0VTUQWLrgTwmJSXzdeYhhnZqzsyxcXRoriFKIsFARV3DlZZ5eP2LLfxx2QbCatdi5rVxXD+wvW7/FgkiKuoaLGPPESbOTmbtjhxG9GzJtNFxtG5S39+xRMTLVNQ1UFFpGS9+spmXPtlEkwZ1+fON/bkqvo3OokWClIq6hvl++2EmJiazYe9RRveL5pFRvYlsGObvWCLiQyrqGiK/uJQ/LtvA619soXXj+rx+WwIX99AQJZFQcMqiNrP2wNtAa8ADvOace97XweT/fLnpAJOSUth+KJ9fDIlh4uU9iNAQJZGQUZUz6lLgd86578wsAlhtZh8559J9nC3k5RSUMGPxOt77NovY5uG8N34IQzo193csEalmpyxq59xuYHfF17lmtg5oC6iofeij9L08NDeF/blF3DW8E/9vRDfq19UQJZFQdFpr1GYWC/QHVh5n23hgPEBMTIwXooWmA0eLmDo/jYXJu+nROoJZtyQQ305DlERCWZWL2swaAYnAfc65I8dud869BrwGkJCQ4LyWMEQ455i7ZiePLUgnv6iM313ajbuGd9YQJRGpWlGbWV3KS/pd51ySbyOFnl3ZBUyZk8In6/fTP6Z8iFLXVhqiJCLlqnLVhwF/A9Y55571faTQ4fE43v1mO08uyaDM43jkql7cem6shiiJyA9U5Yx6GHAzkGJmayqem+ycW+y7WMEvc/9RJiWm8M3WQ5zXpQUzro2jfWS4v2OJSACqylUfnwM6xfOS0jIPf/18C3/6aANhdWrx1Nh4fprQTrd/i8gJ6c7EapS+6wgTEteSuvMIP+nVisdH96FVYw1REpGTU1FXg6LSMv7y8SZe/nQzTcPr8tJNA7iiT2udRYtIlaiofWz1tvIhSpv2HeXaAW15eGQvmmmIkoicBhW1j+QVlfLMsvW8+eVWops04M3bB3Jh95b+jiUiNZCK2gdWbNzPg0kp7DhcwC1DOzDh8h40qqcftYicGbWHF+XklzB9cTrvr9pBpxYNef+uoQzqGOnvWCJSw6movWRp6h4enpfKobxifn1hZ357SVcNURIRr1BRn6V9uYVMnZ/G4pQ99GrTmDduG0iftk38HUtEgoiK+gw550j6bid/WJhOQUkZD1zWnfEXdKJubQ1REhHvUlGfgR2H85k8J5X/bNjPOR2a8eTYeLq0bOTvWCISpFTUp8HjcbyzchtPLsnAAY9d3Zubh3SgloYoiYgPqairaPP+o0xKTObbrYc5v2sLnhijIUoiUj1U1KdQUuZh1opMnlu+kQZ1a/PMT/sydkBb3f4tItVGRX0SqTtzmJiYTNquI1wZ15qpV/emZYSGKIlI9VJRH0dhSRkv/Hsjr/4nk2bhYbzyiwFc3qeNv2OJSIhSUR9j1dZDTEhMJnN/Hj89px0PjexFk/C6/o4lIiFMRV3haFEpTy/N4O2vtxHdpAFvjxvEBd2i/B1LRERFDfDZhv1MTkphV04Btw6N5YHLutNQQ5REJECEdBtl5xfz+MJ1JH63g85RDZn9q6Gc00FDlEQksIRsUS9O2c0j81LJzi/hnou6cM/FXTRESUQCUsgV9b4jhTwyL42laXvo07Yxb40bRO9oDVESkcAVMkXtnOOD1TuYtjCdwlIPEy/vwZ3nd6SOhiiJSIALiaLOOpTP5DkprNh4gEGxkcwcG0enKA1REpGaIaiLuszjePurrTz94XoMePya3tw0WEOURKRmCdqi3rQvlwmzk/luezYXdo9i+pg42jZt4O9YIiKnLeiKuqTMw6ufbeaFf28ivF5t/nR9X0b30xAlEam5gqqoU3bk8MDstWTsyWVkfBseu7o3LRrV83csEZGzEhRFXVhSxnPLNzJrRSbNG4bx6s3ncFnv1v6OJSLiFTW+qFdmHmRSUgpbDuRxfUJ7Jo/sSZMGGqIkIsGjxhZ1bmEJTy7N4J2vt9M+sgHv3jGYYV1a+DuWiIjX1cii/iRjH1PmpLD7SCG/PK8jv/tJN8LDauS3IiJySjWq3Q7lFfP4wnTmfL+Tri0bkfjrcxkQ08zfsUREfKpGFLVzjoXJu5k6P42cghLuvaQrd1/UmXp1NERJRIJfwBf13iOFTJmTyvJ1e4lv14R37hhMzzaN/R1LRKTaBGxRO+f417dZTF+8juJSD5Ov7MG4YRqiJCKhp0pFbWaXA88DtYG/Oudm+jLU9oP5TEpK5svNBxncMZInx8YT26KhLw8pIhKwTlnUZlYbeBG4FNgBfGtm851z6d4OU+ZxvPHFFp5Ztp46tWoxfUwfbhwYoyFKIhLSqnJGPQjY5JzLBDCz94BrAK8WdU5+Cbe+8Q1rsrK5uEdLpo/pQ5smGqIkIlKVom4LZFV6vAMYfOxOZjYeGA8QExNz2kEaN6hDh+bh3D4slqv7RmuIkohIhaoU9fEa0/3oCedeA14DSEhI+NH2Ux7EjOdv6H+6LxMRCXpVuYRiB9C+0uN2wC7fxBERkWNVpai/BbqaWUczCwNuAOb7NpaIiPzXKZc+nHOlZnYP8CHll+e97pxL83kyEREBqngdtXNuMbDYx1lEROQ4dJufiEiAU1GLiAQ4FbWISIBTUYuIBDhz7rTvTTn1m5rtB7Z5/Y1FRIJXB+dc1PE2+KSoRUTEe7T0ISIS4FTUIiIBTkUtIhLgVNRS45hZezPbYmaRFY+bVTzucIL9x5iZM7MeVXjvBDN7wduZRc6GPkyUGsnMJgBdnHPjzexVYKtzbsYJ9n0faAP82zk3tRpjiniFzqilpvoTMMTM7gPOA/54vJ3MrBEwDPgl5ZMf//v8GDNbbuXamNkGM2ttZhea2cKKfYab2ZqKf743swjff1siP6ailhrJOVcCPEB5Yd/nnCs+wa6jgaXOuQ3AITMbUPH6OcAe4G5gFvCoc27PMa/9PXC3c64fcD5Q4P3vROTUVNRSk10B7Ab6nGSfG4H3Kr5+r+Lxf/0GeBAocs798ziv/QJ41szuBZo650rPPrLI6avSmFORQGNm/TX6U7MAAAD0SURBVIBLgSHA52b2nnNu9zH7NAcuBvqYmaN8nrozswmu/MOZtoAHaGVmtZxznsqvd87NNLNFwJXA12Y2wjmX4fvvTuSHdEYtNY6V/+bjlylf8tgOPA08c5xdrwPeds51cM7FOufaA1uA88ysDvAG8HNgHXD/cY7T2TmX4px7ElgFnPKqERFfUFFLTXQnsN0591HF45eAHmY2/Jj9bgTmHPNcIuXlPBlY4ZxbQXlJ32FmPY/Z9z4zSzWztZSvTy/x5jchUlW6PE9EJMDpjFpEJMCpqEVEApyKWkQkwKmoRUQCnIpaRCTAqahFRAKcilpEJMD9f+WcSyHR9k0QAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(range(10), range(10))\n",
    "\n",
    "plt.xlabel(\"X Axis\")\n",
    "plt.xticks([])\n",
    "plt.title(\"The Image Title\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I don't *really* recommend using the interactive interface in practice or for anything serious. \n",
    "\n",
    "Alternatively, you can use the object-oriented interface. This usually entails a call to **plt.subplots**.\n",
    "\n",
    "This call returns instances of two objects -- a Figure object and an Axes object. Understanding the [anatomy of a matplotlib plot](http://matplotlib.org/faq/usage_faq.html#parts-of-a-figure) and these two underlying concepts will help unlock the power of **matplotlib**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Figure is the object that contains the Axes. To be concrete, we'll turn the figure color gray."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.set_facecolor('gray')\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Axes contain the plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax.scatter(\n",
    "    (.25, .25, .75, .75), (.25, .75, .25, .75), \n",
    "    s=64**2,\n",
    "    c=['red', 'green', 'blue', 'orange']\n",
    ")\n",
    "\n",
    "ax.set_xticks([])\n",
    "ax.set_yticks([])\n",
    "\n",
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Figure can contain multiple Axes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Line 2')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=2, ncols=1, figsize=(10, 12))\n",
    "\n",
    "axes[0].plot(range(10), range(10))\n",
    "axes[1].plot(range(10), range(10, 0, -1))\n",
    "\n",
    "axes[0].set_title(\"Line 1\")\n",
    "axes[1].set_title(\"Line 2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## High-Level Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One of the reasons that this abstraction and the distinction between figures and axes can be useful is in understanding how to operate with some higher-level plotting libraries like **pandas** and **seaborn**.\n",
    "\n",
    "Pandas itself has a plotting API that utilizes matplotlib under the hood. Let's take a look at some of this functionality using the canonical Titanic dataset with information on passenger survival in this famous shipwreck."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "titanic = pd.read_csv(\"data/titanic.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we know, bar plots can be useful for displaying and comparing measurable quantities, such as counts or volumes. Let's say we want to make a bar plot of the number of survivors by the class of their ticket. \n",
    "\n",
    "Pandas provides access to all of the plotting functionality through the **DataFrame.plot** attribute. The plot attribute is exposed on GroupBy objects as well. Here, we'll group by the class of the ticket and then call `...plot.bar` to get a nice bar plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qgwtsvr5+YK+V5LapNgGHLGQvmrUlVfULgKrakuQ44PIkL6D/V2roqWVXVe0GHklyT1U9DFBVjyZ5fJF7W3CG+/AdApwA/GxSPcC3F74dzcKPkyyrqg0A3RX8G4G1wG8vbmuagV8meVZVPQK8fE8xyXMBw10DuwbYf09A9Ery9YVvR7PwDmBXb6GqdgHvSPKvi9OSZuE1VfUYQFX1hvm+wKrFaWnxOOYuSQ3yVkhJapDhLkkNMtylSZIcl+Saxe5DGoThLkkNMty1V0gyluTOJOuS3Jbk8iTPSvKKJN9O8r0kNyZ5zqTjlnfbb+1ej+7qx3b7b+jeb2mSZyf5UvdeG5Ocsji/reStkNq7HA2cWlXfSrIWOAM4DTilqm5K8hvAo5OOuZOJW+x2JXkd8PfAn3bHfbyqLupmG1sCnAQ8WFVvgP+7v1paFIa79ib3V9W3uuXPAWcD26rqJoA9TzQmv/Iw6nOBdUmWMjHJ+75d/TvA2UkOB75QVXd3j7+fn+RDwDVV9d/z/htJU3BYRnuTyQ91PNynNtnfAl+rqpcAfww8E6CqPg+8iYkr/a8keW1V/YCJJyNvB/4hyQeG2bw0G4a79iajSV7ZLa8EbgCe3/MVsc9JMvl/s88FHuiW37mnmOQo4N6q+icmJn9/aZLnA49U1eeA8wG/RVKLxnDX3mQTsKr7crcDgU8ApwCfSPI9Jr4m9pmTjvkwE1fh32JiXH2PU4CNSTYALwY+y8T3z9zY1c4G/m4+fxnpyfj1A9ordF/he003vCI1zyt3SWqQV+6S1CCv3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KD/hePYEijWJKB5QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (titanic.groupby('pclass')\n",
    "      .survived.sum()\n",
    "      .plot.bar())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that pandas returned to us the matplotlib axes. We could go on and customize these axes should we so desire. Let's rotate **tick labels**, for example.\n",
    "\n",
    "Note that each axes holds a reference to the figure, which we use to display in the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for label in ax.xaxis.get_ticklabels():\n",
    "    label.set_rotation(0)\n",
    "    \n",
    "ax.figure"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also use this pattern to plot multiple things on an axes using a mix of pure matplotlib and higher-level plotting packages."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This plot is a little small. One trick I like to use is explicitly passing in an axes that I have already created. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "\n",
    "ax = (titanic.groupby('pclass')\n",
    "      .survived.sum()\n",
    "      .plot.bar(ax=ax))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then we might want to make the tick and axes labels bigger. We could do this by munging the axes or we could take advantage of the matplotlib style context manager."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "font_config = {\n",
    "    'font.size': 16,\n",
    "}\n",
    "\n",
    "with plt.style.context(font_config):\n",
    "    fig, ax = plt.subplots(figsize=(12, 6))\n",
    "\n",
    "    ax = (titanic.groupby('pclass')\n",
    "          .survived.sum()\n",
    "          .plot.bar(ax=ax))\n",
    "    \n",
    "    for tick in ax.xaxis.get_ticklabels():\n",
    "        tick.set_rotation(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also set matplotlib style state globally using the `rc` function. See here for more information. TODO: add link."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rc('font', size=16)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a few more interesting bar plots we can make using pandas. We might want to see the number of survivors broken down with class by gender, and plot it as a horizontal bar chart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 6))\n",
    "\n",
    "ax = (titanic.groupby(['sex', 'pclass'])\n",
    "      .survived.sum().plot.barh(ax=ax))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can look use a cross-tab of the those who did and did not survive by class and gender to make a stacked bar chart, which is a little more economical."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>False</th>\n",
       "      <th>True</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>female</th>\n",
       "      <td>5</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>118</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">2</th>\n",
       "      <th>female</th>\n",
       "      <td>12</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>146</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">3</th>\n",
       "      <th>female</th>\n",
       "      <td>110</td>\n",
       "      <td>106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>418</td>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "survived       False  True \n",
       "pclass sex                 \n",
       "1      female      5    139\n",
       "       male      118     61\n",
       "2      female     12     94\n",
       "       male      146     25\n",
       "3      female    110    106\n",
       "       male      418     75"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "death_counts = pd.crosstab([titanic.pclass, titanic.sex], titanic.survived.astype(bool))\n",
    "death_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dVNMqUhlxTwLOIJnxn0XyZeAiYFdJwyJifUb1p4CLJZVFxJo8xmlmZnnIKZlK6gB0iIjKjLKDSZ4c89eIeKnA8WUbSnJq+dW6KqWzxOtJZqa/z6O/7sDIqhm3pK1I7rN9PiLOTOvMlDQKGE2aTNP6G2eMkjqSzCIXA0cCk2uJu4IkgU6MiAszyt8GngEOofrv0i+RJPk9gL9n7esE4ASAjj22zHngZmbWcLn+ZvpH4A9VHyT9GPgLcAXJrOvAAsZWk77AyqpF9utwDTAMGJPnc1afzTp1PTd9z749aC7J75cbSfq+pOckfQJUktw61J2678X9BsnfyTRJnapewHPASpJZcKaq09t9s3cUETdGxJCIGNKxa886ujQzs3zlmkyHAtMzPp9F8qSYnsC9wDkFiqs2ZSQXQNVK0qUkM7LjIuLRPPvLTsTr6igvy4jhEOBOklPMPwT2IVl2cWlmvRr0Sd/fAT7PevXgiyUcq6xO37vUMw4zM2tCuf5m2of0XtL0YeD9gWsi4lNJN5N1YVATWE5yhW6NJJ1DclvMzyJiahPHUpcjgHciYlxVQXoLS69aWySWp+8HsWnCztxepWp/yxoRo5mZFUiuyXQlX8yORgDLIqLq98v11D3rKoS5QImkbSJiQeYGST8juVDnnBaw2H5XklO7mcYCHetpNxPYAGwbETMb0E/VohRv5RaemZkVUq7J9O/AeEmVJPd7Zp7y3R5YUGOrwnkqfd87sy9JR5BcaTsD+KukoRltVkbEGxl1nwAqIqKiCeOcARwmaTLwELAn8DPgk7oaRcS7ki4DrpG0E/AksIbk99hvAL+LiP/JaLIPsDAi/tkEYzAzswbKNZn+F/Aw8ADJ7SETMrb9AHi2MGHVLCLmS3qe5KrWezM2jSR5gs3I9JXpSZJZdJVuQK23phTITSQJ8DiS1ZpeIIk5++EAm4iIX0h6Ezg5fQXwf8DjwD+yqo8C7ihc2GZm1hiKiNwbSb3TBRwyywYDH9a0gEIhSRpHcntKeUSsyrFtN5LfIsdExF1NEF6zkbQPyZmCnSPi7brqlpbvEOXH/Lp5ArNq/DxTs9ZL0osRMaQhdXO9mhfYuBJSdtlrTZ1IU1NJLoI6qRFth5EsrnB3QSMqjvHALfUlUjMza3o5r4BUG0lHk8xM870dpU4RsV7ScSQLFeTadiawc+Gjal6SykgWbLipIfUHb92T2ZNGNW1QVgvPLM3ag4IlU5KF10PS68DFEXFnAfddTUTMAmY11f5bunTpwOZ4qICZmTVAo07z1mI/kotsHgL+s4D7NTMza9EKNjONiCfTP06vs6KZmVkbU5CZqaTsZe7MzMzajZySafqczbMyPg+WtABYIml2+lQVMzOzdiXXmelP+WJxdYBfkazqcyrJYve+KMbMzNqdXH8z3Zb0MWSSegLDgcMiYrqk5cClBY7PzMysxct1ZtqRZCF2gK+RLHX3RPr5//jiEWJmZmbtRq7J9B8k68FC8pixv2cs6dcX+KhQgZmZmbUWuZ7mvRKYKukYkueKjs7Yth/wao2tzMzM2rCckmlE3C7pfZJHf70QEU9lbF5M8jQZMzOzdiXnRRsi4hngmRrKLyhIRGZmZq1MrveZDpP07YzPvSX9UdJrkq6U1LHwIZqZmbVsuV6ANAnYM+PzFcC3gLeBnwC/KFBcZmZmrUauyXRnYDaApBLge8BpEfFd4Bwgzychm5mZtT65JtPuwMr0z3sD3UieEgPwvySLOpiZmbUruSbThcBu6Z+/CcyJiCXp5y8Bq2psZWZm1oblejXvH4FLJI0g+a008wrePUgWdbAW5rWFK6gY/3Ct2+eXtcOz8xNWFDsCM2tDck2mE4A1wFCSi5F+lbFtN+BPhQnLzMys9ch10Yb1wMW1bDusIBGZmZm1MgV5OLiZmVl7lvMKSJIOBn4M7ASUZW+PiAEFiMvMzKzVyHUFpG8B04GuwCCSZ5u+D/QjeTTbkw3cz9WSHsz4PETSjZLmSlol6X1J0yT1zyW+rD66SZoqaYmkkPTrxu6rqUiaL2lKI9qdJulVST6zYGbWAuT6j/F5wG9JruQFODciRgBfIXnW6V/q24GkgcCJwMSM4iPSffw3yS0340muDp4tqV+OMVY5GTgSOBP4KjC5kftpia4neXbsMcUOxMzMcj/NOwg4n2QWGlXtI+JtSRNIku1d9ezjVOCViJidUXZZRCzNrCTpb8A84Pi0z1ztDHwQEbc2om2LFhGrJd1K8kXh5mLHY2bW3uU6M90AVEZEAEupvuLRB8DAuhpLKgXGALdnlmcn0rTsvbSPrXOMEUkBjAP6pad4I703FklbSLpO0kJJa9NTyydktR+Xthkm6S5Jn0paLOnn6faRkl6S9C9JL0jaM6v9QZKmS1qUnraeI+mMhjwIQFL/9BT30jS+lyUdXkPVO4BdJA3L9fiYmVlh5TozfQuoSP88Gzg1nUFWAmcA8+tpPxTYHHi6vo4k7UxyKvPNHGOE5LTuBJJ7X6sS0RuSegB/A7qk2+cBBwPXSSqNiKuz9nMLcCtwI8mD0C+RtDnJae6Lgc+Ay4H7JA2MiHVpuwHA48DVJPflDkn725LkFHZtY+4HPAcsAU4j+TLxA+AeSYdFRObzYl8mWdpxJPD3GvZ1AnACQMceW9bWpZmZFUCuyXQayelTSFY/egxYkH5eT/0L3Q8lOT38al2VJHUi+V1wKfD7HGMkImZJWgasjYhZGfs9D9gOGBwRVas1PZYmyAskXRcRlRm7mhoRv0zbPkGSmE8HdoyIeWl5B+B+kgT+ZNr/9Rl9iuTLQ2fgTEm/iIgNtYQ+ARAwPCKWp2WPpEn2QjIevh4RGyS9SnJMazoGN5J8CaC0fIeo9WCZmVnecl204bcZf35R0mCSmVFX4LGIeKOeXfQFVmbM4GpzDTAMGBURH+cSYz1Gksz85qUJu8ojwI+AXaie6DdeUBURlZLeAXpWJdLU3PR944VSkspJEuNIkjFn9tUH+LCO+KYDK2qI7wpJPSJiZUb5UmDHWvZlZmbNJOf7TDNFxALgdzk0KQPW1lVB0qUkpyePiYhH8wivJn2A7YHPa9neO+tzdiJfV0sZpPfcpjPVB0iS6ASSZLsaOIzkMXWb3JubFd/R6au2+DKT6WqSU9ZmZlZEeSXTRlhO8nSZGkk6h+Q3xZ9FxNQm6n8JcEot298qQB8DSX4jHRsRt1UVSjqkAW2Xk5wSvqyW7R9kfe4FLGtMkGZmVjj1JlNJVbfBNERERF37nAuUSNomndVm9vMz4CLgnBouBCqUGcBPgfczHh1XaF3T942z3/RB6kc1oO0Mkt9eX4+I1Q2o3x94PucIzcysoBoyM72QhifT+jyVvu/NFxcuIekI4NckyeSvkjIvqlmZ+VtseiFQRURUNKL/ySRXxz4taTLJTLQbyf2z+0bEdxqxz2xvAu8BF0taT5JUT2tg2/NJkuNTkq4huTr6S8CuwICIOK6qYnrR1I7AlQWI2czM8lBvMo2ICYXqLCLmS3oeOAS4N2PTSJKrWEemr0xPAiMyPnej9gt46ut/RXpf5vnA2ST3sH5CklTvacw+a+hjnaTDSC6iuhX4CPgDybKLN9XT9n1JVbfRXEJyK81yYA7JbTqZRpH8XvvnQsRtZmaNp2T9hQZWTk5Xdo6If9WwrRuwLiJqu7inqt444DdAeUSsyinYpI+PgTERUd9KS22apL8AyyJibH11S8t3iPJjal+a2A8HNzPblKQXI2JIg+rmmExvBTpFxCb/+kq6jSSZHrdpy2r1OgKvAX+IiJxOUUr6Bsn6vV+p417NNk/S7sAsYNeIeKe++kOGDInZs2fXV83MmtGaNWtYunQpa9asobKysv4GVjAlJSX06dOHHj161Fkvl2Sa69W8I4Czatn2AHBFfTuIiPWSjiNZyD4nETGTLxaNaM+2Ao5tSCI1s5ZnxYoVLF68mC233JKtttqKTp06kazvYk0tIli9ejULFy4EqDehNlSuybQPya0lNVkKfLkhO0lXJZpVb0WrUUTMKHYMZtZ4y5YtY5tttqFr1671V7aCkkTXrl3Zeuut+eCDDwqWTHNd6H4JMLiWbYNJLpYxM7M6rFu3ji5dvN5KMXXp0oXPP6/zEp+c5JpMHwLOk/T/MgvTZQXPAR6ssZWZmVXj07rFVejjn+tp3vOBbwAvSnqB5F7RrUnuG50HnFvQ6MzMzFqBnGamEbEM2Au4lOS+0N3T94uBvdLtZmZm7Uqup3mJiE9IVt05g+TU7pnAryLCN+6ZmbUzI0aMYMSIEc3a5/z585HElClTmrXfuuS80L2k80kSafeM4s8kXRERFxUsMjMza/GuvfbaYofQIuSUTCVNBM4jeezaHcBiktthjgQmSupUyOUHzcysea1fv56IoFOnhqWHXXbZpYkjah1yPc17PHBVRJwQEX+NiNfT9+NJFpE/ofAhmplZtrfffpvDDz+cPn36UFZWxrbbbsvo0aOprKxkypQpSGL+/PnV2kyYMGGTq1glcc455zBp0iT69+9P586deeGFF+jUqRNXX73pA7wuu+wySkpKWLp0KVD9NO+iRYsa3A7g3nvvZejQoXTt2pXNN9+c0aNH8/7771drt2rVKk466SR69+5N9+7dOfTQQ1mwYEH27osu12TaE3iklm0z0u1mZtbEvv3tb7Nw4UKuu+46HnnkESZNmkRpaSkbNuS+0uqUKVN4+OGHufLKK3n44YcZMGAABx54IFOnbvpY6dtuu42RI0ey5ZZbbrKtvLy8we2uv/56vvvd77LLLrtw9913c8MNNzBnzhyGDx/Op59+urHdiSeeyO9+9ztOP/107r33XnbaaSd++MMWuJ54RDT4BfwV+Hkt234O/DWX/fnVPK8999wzzKzleOONN/Jqv3Tp0gDi/vvvr3H7zTffHEDMmzevWvkFF1wQyT/7XwCivLw8Vq1aVa38tttuCyDmzp27seyll14KIO68886NZcOHD4/hw4fn1O7TTz+NHj16xLHHHlutz3nz5kVJSUlMnjw5IiLmzp0bHTp0iEsvvbRavR//+McBxM0331zj+Buqvr8HYHY08N/ZXGemPwOOk3SWpApJXdL3/wKOA/5TUoeqV/6p3szMsvXu3ZsBAwYwfvx4brrpJv7xj3/ktb+RI0dusiLT4YcfTvfu3avNMqdOnUrPnj059NBDa91XQ9o9++yzrFy5kqOOOorKysqNr2222YZBgwbx1FPJo6+fe+45NmzYwPe///1qfRxxxBF5jbcp5JrwXgUGApOAd4HP0vdL0/LXSB6G/TnJszbNzKzAJDFz5kyGDBnCz3/+c3bccUcGDBjAdddd16j9lZeXb1LWtWtXvvvd7zJt2jQigvXr1/PHP/6R0aNHU1ZWVuu+GtJuyZJkifcDDzyQkpKSaq/XXnuN5cuTlWkXLVoEwJe/XH3Z9+zPLUGut8ZcCDT8mW1mZtYkBgwYwK233kpE8Morr3DNNddw0kknUVFRsTFprVtXfU5TlaSy1ba03tixY7nlllt45plnWL16NYsWLWLs2HofoVxvu969ewPJb7Vf+cpXNmm/2WabAV8k+cWLFzNgwICN2xcvXlxvDM0tp2Qavu3FzKxFkcTuu+/Or371K37/+98zZ84cvva1rwEwZ84cdtxxRwAqKyt59NFHc9r3fvvtxzbbbMPUqVNZvXo1FRUV7Lvvvnm3GzZsGJttthnvvPMOxxxzTK372WeffejQoQN33XUX48eP31h+xx135DSO5pDzog1mZlZcr776Kqeccgo/+MEP2H777Vm/fj1TpkyhU6dO7L///uy2224MHDiQs846iw0bNlBaWsq1117L2rVrc+qnQ4cOHHXUUdxwww18/vnnnHbaaQ1aIL6+dj169OCKK67g5JNPZunSpXzzm9+kZ8+eLFy4kCeffJIRI0bwwx/+cOOVu+effz4bNmxgr732YubMmUyfPj3nY9bUnEzbgdcWrqBi/MPFDqNVmV/WAi+9rzLBK3e2d1tttRXbbrstv/rVr1iwYAFlZWUMHjyYhx56iD333BOA+++/n5NPPplx48bRq1cvTj31VPbZZx8mTpyYU19jx47lsssuA2DMmDEFa3fiiSfSr18/rrjiCn0Zpu0AABXFSURBVG6//XY+//xztt56a77+9a+z++67b6x3ww030L17d6688krWrVvH/vvvz+23375x9t1SKLn619qy0vIdovyYXxc7jFbFydSa0ptvvsnOO+9c7DDavfr+HiS9GBFDGrIv375iZmaWJydTMzOzPDmZmpmZ5alVJlNJV0t6MKvsEkmPSlouKSSNK1J4DSZpXBprRY7tukhaJGl000RmZma5aHXJVNJA4EQg+5K0nwJdgIeaPahmFhGrgcuBSyWVFDseM7P2rtUlU+BU4JWImJ1V3jMi9gV+WYSYimEK0A84vMhxmJm1e60qmUoqBcYAt2dvi4jcnztUd1/zJd0maayktyStlvS0pB0kdZN0Q3pKebGkqyR1ymhbJmmypDmSPpP0oaQHJQ1qYN/HS3pF0hpJyyT9XlKvrPF+TPI4vB8VctxmZpa7VpVMgaHA5sDTzdTf14GTgLOBY0gW878HmAZ8ChwB3AicTvUHo5cCmwEXAaOAnwBlwCxJW9XVoaRJwLXAY8ChwFnASOAvkjpmVX8KGC5pk1WnJZ0gabak2etX+b5EM7Om1NpWQBpKstD+q83UX3dgZESsAEgT4W+A5yPizLTOTEmjgNEkSZC0/sYZY5oEHwEWA0cCk2vqLL0Q6SxgYkRcmFH+NvAMcAhwX0aTl4DOwB7A3zP3FRE3kiR6Sst38MocZmZNqLXNTPsCKyOiuR7v9mxVIk3NTd8fyao3l+T3y40kfV/Sc5I+ASqBf5Ek553q6O8bJH8n0yR1qnoBzwErSWbKmZam730bOiAzMyu81jYzLQNyW6k5Px9nfV5XR/nGU62SDgHuBG4huep4GbABmJ5ZrwZ90vd3atneO+vz6vS9S3ZFM2udir2O9vxJoxrVbsqUKRx77LE1bps5cyYHHnhgvfuoqKhgxIgRTJkypVExFFNrS6bLgS8VO4gGOAJ4JyLGVRWkt7D0qrVFouphgwexacLO3F6lan/LGhGjmVnB/elPf2KbbbapVrbLLrsUKZrm09qS6VygRNI2EbGg2MHUoSvJqd1MY4HsC4iyzSSZwW4bETMb0E//9P2t3MIzM2sau+++O9tvv32xw2h2re0306fS972zN0gaLul7JFe+AgyR9L20LLPeE5LmN22YzAAGpbfHHCDpv4ALgU/qahQR7wKXAddIulzSqLT9OEnTJO2X1WQfYGFE/LNJRmFmVgCPPvoo3/rWtygvL6dr167suuuuXHXVVaxfv77Odh9++CHHHHMMffv2pbS0lPLycr797W+zZMmSjXVWrVrF2WefTf/+/encuTP9+/fn4osvZsOGgt4tWa9WNTONiPmSnie5qvXerM0TgeEZn09OXwCZT7PtBnzYZEEmbiK5IOk4ktWaXiCJ+c/1NYyIX0h6ky/iD+D/gMeBf2RVHwW0vEfOm1m7tX79eiorvzgxJ4l//vOfHHDAAfz0pz+lrKyM2bNnM2HCBJYuXcqkSZNq3dfYsWN57733uOKKK+jXrx+LFy/m8ccfZ9WqVQBUVlZy8MEH88Ybb3DeeecxePBgZs2axS9/+Us++ugjrrrqqiYfb5VWlUxT1wG/kXRyRKyqKoyIEfU1lNQN2I1k4Yc6RURFDWVPUD0xV5WPy/q8ATg3fWWqyKo3hWQlo+z9TQWm1hWfpH1I7nu9sa56ZmbNadCg6mvT/Nu//RvPPPPMxs8Rwb777su6deu48sorueSSS+jQoeaTpM8++yyXXHIJRx111May0aO/WJL8j3/8I8888wxPPvkkX/96crPDAQccAMDEiRM5++yz6dOnD82hNSbTqcB/kSymcGWObYcB7wJ3FzqoIhgP3BIRbxc7EDOzKn/+85+rXYC02WabsWjRIiZMmMCMGTP44IMPqs1clyxZwlZb1byWzV577cUVV1xBRLD//vuz6667In0xn5kxYwbbbbcdw4YNq7bPgw46iHPPPZdZs2Zx6KGHNsEoN9XqkmlErJd0HMlCBbm2nQm0+sfbpysevURyOrleg7fuyexGXu7efnnVKLPG2HXXXatdgLRhwwb22WcfPvjgAyZMmMCgQYPo0qUL9913HxdffDFr1qypdV933nknEydO5PLLL+fUU0+lvLycH//4x5x77rl06NCBJUuW8N5771FSUvPzPpYvz74Boum0umQKEBGzgFnFjqNYImINyQVNZmYt2rvvvsvs2bOZOnUqY8Z88Qvbgw8+WEerRJ8+ffjtb3/Lb3/7W9566y1uueUWLrjgArbcckt+8pOf0Lt3b/r3789dd91VY/uKiopCDaNerTKZmplZ61B1sVDm7PHzzz9n2rRpOe1np5124pJLLuH6669nzpw5AIwcOZJ77rmH7t27b/JbbXNzMjUzsyaz8847s91223HOOefQsWNHSkpKmDy5xuXJq1mxYgUHHnggRx11FIMGDaKkpIT777+fjz/+mIMOOgiAo446iptvvpkDDjiAM844g912241169bx7rvv8sADD3DffffRtWvXph4i4GRqZtaiNHY5v5aqc+fO3Hffffznf/4nRx99NL169eK4445j22235fjjj6+1XVlZGXvssQc33XQT7733Hh06dGCnnXZi2rRpfOc73wGS2e4jjzzCpEmTuPHGG5k3bx7dunVj4MCBjBo1is6dOzfXMFGEHyjS1g0ZMiRmz85+lrqZFcubb77Jzju3+mshW736/h4kvRgRQxqyr9a2ApKZmVmL42RqZmaWJydTMzOzPDmZmpmZ5cnJ1MzMLE9OpmZmZnlyMjUzM8uTk6mZmVmenEzNzMzy5GRqZmaWJ6/Na2bWkkzoWeT+c3+Wb+YDu2uz3XbbMX/+/EYE1Do4mZqZWV6effbZap8PP/xwdtttNyZMmLCxrLS0tJmjal5Opu3AawtXUDH+4Y2f55f9sIjRtCON+IZv1hoNHTq02ufS0lK22GKLTcozrV+/noigU6e2kYb8m6mZmTU5SZxzzjlMmjSJ/v3707lzZ1577TWmTJmCpE1OAU+YMGGT08eVlZVceumlDBo0iNLSUvr27csZZ5zBmjVrmnEkNWsbXwnMzKzFmzJlCgMGDODKK6+kW7du9O3bl1deeaXB7ceMGcODDz7I2WefzbBhw3jzzTc577zzmD9/Pvfcc08TRl4/J1MzM2sWEcGjjz5Kly5dcm779NNPc+edd3LLLbdw9NFHA3DggQfSq1cvxowZw8svv8zuu+9e6JAbrCineSVdLenBrLJLJD0qabmkkDQuzz66SZoqaUm6v1/nFXQTkDRf0pRGtDtN0quSfJrezFqNkSNHNiqRAsyYMYPOnTvz3e9+l8rKyo2vgw46CICnnnqqkKHmrNn/MZY0EDgRmJi16adAF+ChAnV1MnAkcCbwVWBygfbbElwP9AGOKXYgZmYNVV5e3ui2S5YsYd26dXTv3p2SkpKNrz59+gCwfPnyQoXZKMU4zXsq8EpEzM4q7xkRGyRtDxxdgH52Bj6IiFsLsK8WJSJWS7qV5IvCzcWOx8ysIWq6H7WsrAyAdevWVSvPTo69e/emrKyMp59+usZ99+3bt0BRNk6zzkwllQJjgNuzt0XEhgL2E8A4oF96ijckjUi3bSHpOkkLJa2VNFfSCVntx6Vthkm6S9KnkhZL+nm6faSklyT9S9ILkvbMan+QpOmSFklaJWmOpDMkdWxA7P0lTZO0NI3vZUmH11D1DmAXScMad5TMzIpvu+22A2DOnDkbyyorK3n00Uer1Rs5ciRr1qxhxYoVDBkyZJNXsZNpc89MhwKbAzV/tSicrwITgN2AqkT0hqQewN9ITidPAOYBBwPXSSqNiKuz9nMLcCtwIzAauETS5sC3gIuBz4DLgfskDYyIqq9WA4DHgauBNcCQtL8tgfG1BS2pH/AcsAQ4DVgK/AC4R9JhEfFARvWXgZXASODvDTwuZmYtyl577cXAgQM566yz2LBhA6WlpVx77bWsXbu2Wr0RI0Zw5JFH8r3vfY/TTz+dvffemw4dOjB//nymT5/OZZddxo477likURQnmQbwalN2EhGzJC0D1kbErKpySecB2wGDI+IfafFjaYK8QNJ1EVGZsaupEfHLtO0TJIn5dGDHiJiXlncA7idJ4E+m/V+f0adIvjx0Bs6U9Is6ZuETAAHDI6LqHMcjaZK9ENiYTNNT4q+SHNNNpLPtEwA69tiy1mNlZi1MO1vso1OnTtx///2cfPLJjBs3jl69enHqqaeyzz77MHFi9UtrbrvtNq6++mr+8Ic/cPHFF1NaWkpFRQUHH3wwX/7yl4s0gkRzJ9O+wMqMGVxzG0ky85snKXPsjwA/AnaheqL/S9UfIqJS0jskv+3Oy6gzN33vV1UgqZwkMY4kGXNmX32AD+uIbzqwoob4rpDUIyJWZpQvBWr8KhYRN5LMqCkt3yFq6c/MrOBqWoM3ovZ/hr7yla/wxBNPbFKeuRwhQIcOHTjllFM45ZRT8oyw8Jo7mZYBa+ut1XT6ANsDn9eyvXfW54+zPq+rpQySsVXNVB8gSaITSJLtauAw4JyqenXEdzS1X4DVm+TUbpXVJKeszcysiJo7mS4HvtTMfWb3vwSo7WvNWwXoYyDJb6RjI+K2qkJJhzSg7XKSU8KX1bL9g6zPvYBljQnSzMwKp7mT6VygRNI2EbGgmfsGmEFyP+v7EbGkifromr5vnP1KKgGOakDbGSS/vb4eEasbUL8/8HzOEZqZWUE1dzKtWqJib6BaMpU0nORq163SoiGSPgOIiLsz6j0BVERERSP6n0xydezTkiaTzES7AYOAfSPiO43YZ7Y3gfeAiyWtJ0mqpzWw7fkkyfEpSdcA80lm8rsCAyLiuKqK6UVTOwJXFiBmMzPLQ7Mm04iYL+l54BDg3qzNE4HhGZ9PTl+QXOFapRu1X8BTX/8r0vsyzwfOBrYGPiFJqgVZJTki1kk6DLiG5Laaj4A/AO8DN9XT9n1JVbfRXELy5WI5MIfkNp1Mo0h+r/1zIeI2M7PGK8YKSNcBv5F0ckSsqiqMiBH1NZTUjeTe0TH11Y2IGutExMckM8VaZ4sRMQWYUkP5JjFGxHyqJ3si4mXgazXs+ndZ9Spq2N8CkiuL6zMG+FPGLTRm1opERI0rAlnzqOvq4sYoxkLpU4GFwEmNaDsMeBe4u76KbZmk3YH92HR9YzNrBTp37szq1Q25LMKayurVqykpKSnY/pp9ZhoR6yUdB+zRiLYzSdbcbe+2Ao6NiHcaUnnw1j2ZPWlURkn7uincrKXZYostWLBgAVtssQWbbbYZnTp18iy1mUQEq1evZuHChQVd6KEozzNNVyWaVW9Fq1FEzCh2DGbWeD179qS0tJSlS5eyfPlyKisr629kBVNSUsKXv/xlevToUbB9+uHgZmZFUFZWRr9+/eqvaK2CHy5tZmaWJydTMzOzPDmZmpmZ5cnJ1MzMLE9OpmZmZnlyMjUzM8uTCr2kkrU8kj6lMI+Xa822wI+ra+/HoL2PH3wMILdjsF1EbNmQir7PtH14KyKGFDuIYpI028egfR+D9j5+8DGApjsGPs1rZmaWJydTMzOzPDmZtg83FjuAFsDHwMegvY8ffAygiY6BL0AyMzPLk2emZmZmeXIyNTMzy5OTaRslqZ+kuyWtkLRS0r2Sti12XIUgaRtJV0t6VtIqSSGpooZ6X5L0O0nLJP1L0mOSBtdQr0zSFZIWSVqd7vfrzTGWxpD0PUn3SHovjfctSZdK2iyrXlsd/8GS/irpQ0lrJS2QdJekXbLqtcnx10bSjPT/hYuyytvkcZA0Ih1v9uuTrHrNM/6I8KuNvYCuwD+AOcBhwHeA14B3gW7Fjq8A4xsBLAamA48AAVRk1RHwNLAAOBIYCTxJcrP2Nll1pwGfAMcDBwD3AquB3Ys91lrGPwu4CzgKGA6cmsY/C+jQDsZ/JHAF8L10/GOB14GVJDfZt+nx13FMFqX/L1yUUd5mj0P670AAPwWGZryGFGP8RT8gfjXJf2SnAOuB7TPK+gOVwOnFjq8A4+uQ8ecfUXMy/U5avl9GWU/gI+C/M8p2S+sdm1HWiWTFqAeKPdZaxr9lDWVHp+PYv62Pv5ZjslM6jjPa2/iBzYEP02SRnUzb7HHISKYH1lGn2cbv07xt06HArIh4p6ogIuYBfyP5j6tVi4gNDah2KPBBRPxPRrsVwINUPwaHAp8Dd2bUqwTuAA6WVFqQoAsoIpbWUPxC+r51+t5mx1+L5en75+l7exr/5cDrEfHHGra1p+NQk2Ybv5Np2/QVklO82V4HdqmhvC2q6xhsK6l7Rr15EbGqhnqdge2bLsSCGp6+v5m+t/nxS+ooqbOkHYAbSGZnd6Sb2/z4ASR9jeSsxEm1VGkPx2GapPWSlku6PevakGYbv5Np29QL+LiG8o+ALzVzLMVS1zGAL45DffV6FTiugpO0NXAh8FhEzE6L28P4nwPWAm8D/4/kFPeSdFubH7+kEpIvEVdGRG0PsmjLx2EFcBXJTz37A78EDgSeldQnrdNs4/dC921XTatxqNmjKB7RsGPQ0HotUvrN+n6S38OPzdxE2x//WKAHMAA4E5gp6WsRMZ/2Mf6zgS7AxXXUabPHISJeAl7KKHpS0lPA88DPgHNpxvF7Zto2fUzN36S+RM3fvtqij6j9GMAXx6G+eh/VsK1FkFQGPECSTA6OiAUZm9v8+CPizYh4Lv2t8ACgOzA+3dymx5+eyjwHOA8olbS5pM3TzVWfO9LGj0O2iPhfkjMVe6VFzTZ+J9O26XWS3wCy7QK80cyxFEtdx+D9iPgso15/SV1rqLcOeIcWKD3Fdw+wN/CtiHgtq0qbHn+2iPiEJNaq37ba+vgHAGXAbSQJoeoFySz9Y2Awbf841CRzltls43cybZseAIZKGlBVoGRRg39Lt7UHDwBbS6q6MAdJPYBDqH4MHgBKgNEZ9ToBPwAejYi1zRNuw0nqQHJP3AHAdyJiVg3V2uz4ayLpy8Agknupoe2P/2VgvxpekCTY/UgSQFs/DtVIGgLsSPJ7OjTn+It9r5BfhX8B3Uj+R3qN5PLvQ4FXgH8C3YsdX4HG+L30dR3Jt9CfpJ+Hp9s7AH8H/g84AjgYeILkdE2/rH3dQfJN/kckCepuYA2wR7HHWcvYq8Z8EdVvVh9KeiN6Gx//n0lOb36HJGmcCMwlueF+x7Y+/nqOTfZ9pm32OJB8obwI+HeSC5DOIFmM4X1gi+Yef9EPiF9N9h/atiSnAVcCnwL3kbWwQWt+pf9o1PR6IqNOL+AP6f84q4DHgd1q2FcX4Fckt1asIflWO6LYY6xj7PPrGP+EdjD+s4EX0+S5iuTG+huy//tuq+Ov59hUS6Zt+TgAPwdeJbmq9/M0Yd4IlBdj/H4Em5mZWZ78m6mZmVmenEzNzMzy5GRqZmaWJydTMzOzPDmZmpmZ5cnJ1MzMLE9OpmZmZnlyMjUzM8vT/wdZZThaQ1TquQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = death_counts.plot.barh(stacked=True) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also look at the survival *rate* of the groups, by adjusting for the number of people in each group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (death_counts.div(death_counts.sum(1), axis=0)\n",
    "      .plot.barh(stacked=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This, obviously, isn't quite what we want for the legend. We might Consider increasing the margin at the bottom and making the legend horizontal. Let's go ahead and clean up the labels too."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1514a870fa0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = (death_counts.div(death_counts.sum(1), axis=0)\n",
    "      .plot.barh(stacked=True))\n",
    "\n",
    "ax.margins(x=0)\n",
    "ax.set_ylim(-1.75, 5.5)\n",
    "\n",
    "ax.legend(loc=(.15, .05), ncol=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Health Inspection Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take a look back at the Chicago Health Inspection data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "from load_data import dta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "dta = dta.drop([\"violations\"], axis='columns').join(\n",
    "    dta.violations.str.split(\"|\", expand=True)\n",
    "        .unstack()\n",
    "        .dropna()\n",
    "        .str.strip()\n",
    "        .reset_index(level=0, drop=True)\n",
    "        .to_frame()\n",
    "        .rename(columns={0: 'violations'}),\n",
    "    how='right'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One thing we may wonder is if the violations are fairly evenly distributed or if some are much more common than others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "violation_num = dta.violations.str.extract(\"(\\d+)(?=\\.)\", expand=False).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(14, 10))\n",
    "\n",
    "ax = violation_num.groupby(violation_num).size().plot.bar(ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercise:\n",
    "\n",
    "See if there are any meaningful differences in the number of violations by quarter. Recall that you can use the `dt` accessor for datetime functionality on a Series."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# %load solutions/violation_by_quarter.py\n",
    "quarter = (dta.inspection_date.dt.month - 1) // 3\n",
    "\n",
    "quarter_size = dta.groupby((quarter, violation_num)).size()\n",
    "\n",
    "axes = quarter_size.unstack(level=0).plot.bar(\n",
    "    figsize=(14, 8),\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting Geographic Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One the most interesting features that we have here are geographical. There are a few options for plotting maps in Python (and in Notebooks).\n",
    "\n",
    "The first thing we can try is plotting with matplotlib only. If you don't need much else, this can work really well to get a sense of how things are, if your data are sufficiently dense."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 101975 entries, 2015577 to 2456811\n",
      "Data columns (total 15 columns):\n",
      " #   Column           Non-Null Count   Dtype         \n",
      "---  ------           --------------   -----         \n",
      " 0   dba_name         101975 non-null  object        \n",
      " 1   aka_name         101756 non-null  object        \n",
      " 2   license_         101972 non-null  float64       \n",
      " 3   facility_type    101888 non-null  category      \n",
      " 4   risk             101975 non-null  category      \n",
      " 5   address          101975 non-null  object        \n",
      " 6   city             101887 non-null  object        \n",
      " 7   state            101947 non-null  object        \n",
      " 8   zip              101945 non-null  object        \n",
      " 9   inspection_date  101975 non-null  datetime64[ns]\n",
      " 10  inspection_type  101975 non-null  category      \n",
      " 11  results          101975 non-null  category      \n",
      " 12  latitude         101727 non-null  float64       \n",
      " 13  longitude        101727 non-null  float64       \n",
      " 14  violations       101975 non-null  object        \n",
      "dtypes: category(4), datetime64[ns](1), float64(3), object(7)\n",
      "memory usage: 12.3+ MB\n"
     ]
    }
   ],
   "source": [
    "dta.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "dta = dta.dropna(subset=[\"latitude\", \"longitude\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with plt.style.context({\n",
    "    'axes.facecolor': 'black',\n",
    "   }):\n",
    "    fig, ax = plt.subplots(figsize=(16, 12))\n",
    "\n",
    "    ax = dta.plot.scatter(x='longitude', y='latitude', color='white', s=.02, alpha=.6, ax=ax)\n",
    "    ax.xaxis.set_ticklabels([])\n",
    "    ax.yaxis.set_ticklabels([])\n",
    "    ax.set_xlabel('')\n",
    "    ax.set_ylabel('')\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A few things to note. First, we used a context manager again to set some style that we know we wanted to adhere to. Second, we used the `DataFrame.plot.scatter` method."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Suppose we thought there may be some geographic clustering to the restaurant incident reporting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x864 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = plt.cm.get_cmap('RdYlBu')\n",
    "\n",
    "\n",
    "with plt.style.context({\n",
    "    'axes.facecolor': 'black',\n",
    "    'legend.facecolor': 'inherit',\n",
    "    'legend.markerscale': 32,\n",
    "    'text.color': 'white',\n",
    "   }):\n",
    "    fig, ax = plt.subplots(figsize=(16, 12))\n",
    "\n",
    "    grouper = dta.groupby('facility_type')\n",
    "    for i, (name, group) in enumerate(grouper):\n",
    "        if len(group) < 5000:\n",
    "            continue\n",
    "        ax = group.plot.scatter(x='longitude', y='latitude', s=.2, color=cmap(i), alpha=.6, ax=ax, label=name)\n",
    "    ax.xaxis.set_ticklabels([])\n",
    "    ax.yaxis.set_ticklabels([])\n",
    "    ax.set_xlabel('')\n",
    "    ax.set_ylabel('')\n",
    "    ax.set_xticks([])\n",
    "    ax.set_yticks([])\n",
    "    ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we attempt to uncover some more detail from our map, by plotting the different types of estbalishments using different colors. We use matplotlib's **color maps** under the `plt.cmap` namespace to do this. We also add a **legend** and style it. In general, you use the `label` argument to add a name to plot element and the call `legend` on the axes to display it.\n",
    "\n",
    "Incidentally, the matplotlib documentation has a [fantastic page](https://matplotlib.org/users/colormaps.html) about choosing color maps purposefully for different situations."
   ]
  },
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   "source": [
    "For some more fine-grained control over maps, you may want to check out packages like [cartopy](http://scitools.org.uk/cartopy/), [folium](http://python-visualization.github.io/folium/), and [bqplot](https://github.com/bloomberg/bqplot)."
   ]
  }
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