ch_06/3-customizing_visualizations.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Customizing visualizations\n",
    "\n",
    "## About the Data\n",
    "In this notebook, we will be working with 2 datasets:\n",
    "- Facebook's stock price throughout 2018 (obtained using the [`stock_analysis` package](https://github.com/stefmolin/stock-analysis))\n",
    "- Earthquake data from September 18, 2018 - October 13, 2018 (obtained from the US Geological Survey (USGS) using the [USGS API](https://earthquake.usgs.gov/fdsnws/event/1/))\n",
    "\n",
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "fb = pd.read_csv(\n",
    "    'data/fb_stock_prices_2018.csv', index_col='date', parse_dates=True\n",
    ")\n",
    "\n",
    "quakes = pd.read_csv('data/earthquakes.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding reference lines\n",
    "### Horizontal reference lines\n",
    "`axhline()` adds horizontal lines. We simply specify the y value to draw the horizontal line at with the `y` parameter. Optionally, we can provide:\n",
    "- `label` for a string that will show up in the legend\n",
    "- `color` for the color of the reference line\n",
    "- `linestyle` for the type of line to draw\n",
    "\n",
    "We will draw reference lines for support and resistance using the [`stock_analysis` package](https://github.com/stefmolin/stock-analysis) that we will build in chapter 7. To get these metrics, we need to create a `StockAnalyzer` object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from stock_analysis import StockAnalyzer\n",
    "\n",
    "fb_analyzer = StockAnalyzer(fb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the `fb_analyzer` we can use the `support()` and `resistance()` methods to get the values we seek:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(124.4566666666667, 138.5266666666667)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "support, resistance = (\n",
    "    getattr(fb_analyzer, stat)(level=3) for stat in ['support', 'resistance']\n",
    ")\n",
    "support, resistance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have the values, we can add our reference lines with `plt.axhline()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7dae23a36e10>"
      ]
     },
     "execution_count": 4,
     "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": [
    "fb.close['2018-12'].plot(title='FB Closing Price December 2018')\n",
    "plt.axhline(\n",
    "    y=resistance, color='r', linestyle='--',\n",
    "    label=f'resistance (${resistance:,.2f})'\n",
    ")\n",
    "plt.axhline(\n",
    "    y=support, color='g', linestyle='--',\n",
    "    label=f'support (${support:,.2f})'\n",
    ")\n",
    "plt.ylabel('price ($)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vertical reference lines\n",
    "For vertical lines, we use `axvline()` and provide the `x` parameter for where to draw it. The `std_from_mean_kde()` function draws vertical reference lines using `axvline()` at each standard deviation from the mean (1-3) and the mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[0;31mSignature:\u001b[0m \u001b[0mstd_from_mean_kde\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mSource:\u001b[0m   \n",
       "\u001b[0;32mdef\u001b[0m \u001b[0mstd_from_mean_kde\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m\"\"\"\u001b[0m\n",
       "\u001b[0;34m    Plot the KDE along with vertical reference lines\u001b[0m\n",
       "\u001b[0;34m    for each standard deviation from the mean.\u001b[0m\n",
       "\u001b[0;34m    \u001b[0m\n",
       "\u001b[0;34m    Parameters:\u001b[0m\n",
       "\u001b[0;34m        - data: `pandas.Series` with numeric data\u001b[0m\n",
       "\u001b[0;34m    \u001b[0m\n",
       "\u001b[0;34m    Returns:\u001b[0m\n",
       "\u001b[0;34m        Matplotlib `Axes` object.\u001b[0m\n",
       "\u001b[0;34m    \"\"\"\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mmean_mag\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstd_mean\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'kde'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxvline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmean_mag\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'b'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'mean'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mcolors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'green'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'orange'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'red'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mmultipliers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0msigns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'-'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'+'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mlinestyles\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m':'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'-.'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'--'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;32mfor\u001b[0m \u001b[0msign\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmultiplier\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstyle\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mitertools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mproduct\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m        \u001b[0msigns\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmultipliers\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlinestyles\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m        \u001b[0madjustment\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmultiplier\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mstd_mean\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m        \u001b[0;32mif\u001b[0m \u001b[0msign\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'-'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m            \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmean_mag\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0madjustment\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m            \u001b[0mlabel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'{} {}{}{}'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m                \u001b[0;34mr'$\\mu$'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m                \u001b[0;34mr'$\\pm$'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m                \u001b[0mmultiplier\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m                \u001b[0;34mr'$\\sigma$'\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m            \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m        \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m            \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmean_mag\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0madjustment\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m            \u001b[0mlabel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m        \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxvline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlinestyle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstyle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0.5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlegend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0;32mreturn\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mFile:\u001b[0m      ~/Hands-On-Data-Analysis-with-Pandas-2nd-edition/ch_06/viz.py\n",
       "\u001b[0;31mType:\u001b[0m      function\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from viz import std_from_mean_kde\n",
    "std_from_mean_kde??"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note, we need to import it from the `viz.py` module, before we can use it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'mb earthquake magnitude')"
      ]
     },
     "execution_count": 6,
     "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": [
    "from viz import std_from_mean_kde\n",
    "\n",
    "ax = std_from_mean_kde(\n",
    "    quakes.query(\n",
    "        'magType == \"mb\" and parsed_place == \"Indonesia\"'\n",
    "    ).mag\n",
    ")\n",
    "ax.set_title('mb magnitude distribution in Indonesia')\n",
    "ax.set_xlabel('mb earthquake magnitude')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Shading regions\n",
    "We can use `axhspan()` and `axvspan()` to shade horizontal and vertical regions, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Price ($)')"
      ]
     },
     "execution_count": 7,
     "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 = fb.close.plot(title='FB Closing Price')\n",
    "ax.axhspan(support, resistance, alpha=0.2)\n",
    "plt.ylabel('Price ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rather than filling in a rectangular region, we can fill between two curves using `plt.fill_between()`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'FB differential between high and low price Q4 2018')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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X79DiOqVUwsUssBhjPgL2+Sy+CfijMabO3maXvXwW8Iwxps4YswXYCEyNVdo8Th5eFNF+H2/Yw69fW40xJuS2c1ZV8vmmvRGdJxzb99fw85dX8vyi7TE/l1JKBRPvOpbhwAwR+UJE5onIFHt5P8C7Xe92e1kbInKDiCwSkUW7d++OKjGj+3anZ9eMiPZ96ottPPzJlpDbvb2qkvmb9zkKQpFqajb88LnlVNc28uzCMpqbY3cupZQKJd6BJQ3IB6YDPwaeExHnNeiAMeYhY8xkY8zkwsLCqBKTkiLMKAm/OMzj7rfW8u6anQHX7zlUx8LSfVQerGXr3thV+v/r4818scXKHJZXHeHjjXtidi6llAol3oFlO/CSsSwAmoECoBzo77Vdsb0s5k4e0To4ZWekkped7mhfY+C2Z5ayescBv+v/u2YnnszD/M2xKQ5bs+Mgf5m7vtWyp7/YFpNzKaWUE/EOLK8ApwCIyHAgA9gDvAZcKiKZIjIYKAEWxCNBM0qOBhYR+N9Lj2XWBL+lcH7V1Ddx7exF7DxY22ad9yCWsQosry4vp6GpddHXu2t3squ6bXqUUioeYtnc+Gngc2CEiGwXkWuBR4AhdhPkZ4Cr7NzLauA5YA3wDnCzMSYubXQLumUypl93AH5x7jGcPqoX547tE9YxKg/Wcu1jC6mpPzqfy4EjDXy26WiRVKzqWdZWVLdZ1thseGGxVuIrpRIjlq3CLjPG9DHGpBtjio0xDxtj6o0x3zLGjDHGTDTGvO+1/d3GmKHGmBHGmLdjlS5/Th5eyGVT+3PtiYMBmDwwj6KczLCOsar8ILc/s6yl4vz9dTtb5SRiVc+yZsdBv8u1El8plSidtue9t8umDuDOWWPwtCNISRHOGdM77OPMXbOTe95ZB/ify8Xt4rBd1bXsOeR/9OWte2u0El8plRAaWIDivGzSU1u/FeEWh3n886PNPPLJFuZ92bYptNuBJVBuxePPc9ZprkUpFXcaWAKYPCifwjCLwzzufGNNmxkpwf16Fn/1K95WlR/k1Tj1+ldKKQ8NLAGkRlgcFozb9SxrKoLnWAD+/M56aht0rDKlVPxoYAki0uKwYNwsDlvj039m0sA8uqS3HmJtx4FaHv201LVzKqVUKBpYgpgSRXFYIG4FliP1TWzZc7jVsulD8hlc0LXNtg9+sJG9ASr5lVLKbWmJTkAyS00RZo3vy78djAkWTGFOJrurrR92Tz1LmCPZtLF+ZzW+9fLTBvdk274jbYrIqusa+dlLK63ha0QQrM6ggiACKfZzBPr26MKJUQxzo5RSGlhCuPXUEl5ZtiNgs95Q+uV2YUy/7sxZbY0pVnmwltK9NX5zFuHwbRGWliJMGpjHkm37/W4/d81O5gYZ18yjKCeTL35+WtSBTynVeWlRWAg9stO54/xREe8/ZVAefXO7tFoWqDgsnOC1pqJ1/crY4h50zUxjaGG38BPpZVd1XcjWZkopFYwGFgfOH9eHmSMiG0l56uCe9PMJLP7mZ9lzqI4Z93zAX+audzTjpG+OZdrgngAMKYwuJwT47YOjlFJOaWBxQET43awxbVpcOTF1cF6bwDJ/8942/VneWlnBkYYmHnh/I2fcNy/ocPzNzYZ1la1zFdOG5AMwpCC6HAvAvC93hd7IZbGcr0YpFV8aWBzqn5/ND88cHtY++V0zGFrYrU1R2K7qOjb7tOh6bdmOlufb9x/huscXcd1jiyjb17bfy9Z9NdR45WpSxBrfDKBLRmqbQBauRaX7OVTXGHpDF5XGcL4apVR8aWAJw7UnDubHZ41wvP3kgXmICP3y2v7Qe9ezbN9fw6KtbSvd3127kzPum8ff3t9AXePRQOJbDDamXw9yso7OIRNtcVhjs+HTOI8ztrysigM1DXE9p1IqNjSwhEFEuPmUYfzziklkZ4QuFps62Cqe6tk1g8y01m/1/M37Wp6/vrwi4DFqG5q5d+6XnPPXj/lkg/Vj71txP80+j0e0FfgQ/3qWfYfrWRVgwjSlVPuigSUCZ43uzQs3Hk/fHllBt/MEFhHxW4HvqVd4bfmONvv62rznMN96+AtufmpJq6AEMH1Iz1avhxa5EFjW745rvUdVTT0ryzWwKNURaGCJ0Ki+3Xn1lhOZOCDX7/quGamM6tO95bVvPcueQ3Vs2n2YDTurWetgzC+PN1dUsNir2EzEGjDT21AXWoaVVx1h0+7DoTd0yf6aBg0sSnUQGliiUJiTyVPXT+eiY9tOZTxxYB5pXkPx981tm7v5fPNeR7mVYEb16U6PLumtlrlRFAbxLQ7bX1PPag0sSnUIGliilJWeyl++Pp6fnD0S787qU31yEf1ys9vsO39T9IHlOJ9iMLB6z3fLjH5QhQ/Xx6/ZcVVNA6V7azhYqxX4SrV3GlhcICLcNHMoD10xuaVSf4pPhbq/HMvcNZVRD6N/6sgiv+lxozjsiy37eOSTLXy8YTeVB2pjWueyv6YegFWaa1Gq3dPA4qIzRvXixZuOZ3BBVyb0z221zl/fkoam6H6oczLT2tSveERaHOad66pvbObON9ZwxcMLmP6H9/j7BxsjOqYTVXZTYw0sSrV/Glhcdkyf7rx524lk+fTS99eXJVozhheQkeb/Eobbl2Vk7xx+/9WxPHb11IDbvLcudkVjnhzLynLnDRmUUslJRzeOgeyMtm9r7xBNkyNx6sheAdc5ybGkpwpnj+nDlccNbOnMWVPfSIrQZkh+gGVlVew5VEdBN3fnqKlrbGoZScBfjmVd5UFG9u7eZrlSKjlpjiVOMtNSKXJx0jARgg6MGawvS+/uWfzgjOF8+tNTeeCyY5kyKL9lmPzsjDSGBdjXGPhwvfstxaq8etxv2XOYaq8K/NI9h/nGP+e3zGejlEp+GljiyLcvSzTGF+cGzTkM7JlNis+UKscN6ck/Lp/IJz85hdtOK6Eox38uamy/3IDHfW9t6DldwuUpBvNY7TVkzX3vfsmBIw3c/96Xrp9XKRUbGljiKNrBIb35aw3mLTMtlf752fTunsVNM4fy7g9O5ukbpnPO2D6t+tf4M7Zf4GKnj77cTX1jc0RpDmT/4dZNjD3FYWsrDrY0x356QRkbdx1y9bxKqdjQOpY4crMCP1RgAXjoiskMK+pGqm/WJYSxxT0Crjtc38SCLftcnb64yifH4umB/5e5X+Jp4dzUbPjj2+v491WTXTuvUio2NMcSR6HGFnOqV/dMRvcNXZk9ondO2EEFYFSfHm2K0by9t87d4rD9PqMaryw/wOKt+3nXp9jt3bU7+SLA7JuhaMdLpeJHA0scuVXHcurIopjOSd8lI5WSopyA699bu8vVzpK+dSxb9hzmrjfX+N3292+tpdlfk7UgNu0+xGOflkaaPKVUmDSwxJEbRWGpKcK5Y/u4kJrgghWHbdtX4+oAlb5FYcbA0m1Vfrddvv0Ar68IbxicV5eW88qycp2lUqk40cASR9FW3s8oKeDt781gRkngZsZuGdsvcGABeN/F4jDforBQ/vTOemobmkJviDXl8SvLdrBp92HWhDGKtFIqchpY4qhHl3S6OpggzNfggq48fNVkHr9mKsN7BS6ictOYEIHFzf4svjmWUMqrjvD456WOtl1aVsU2e3rnaAf8VEo5o4EljkQkrHqWnMw0fnneMcy5/SROO6ZXTOtVfI3q0z1oxf+ysioam9xpdhxujgXgb+9vdBSQXl1a3vL89WU7wq6fUUqFTwNLnDkJLCkCl00dwAc/nsl1M4YEHA8slqwK/MC992vqm1i/s9qVc/lW3jtxsLaRB94PPihmQ1Mzb6w4Ou3zjgO1LPKaJE0pFRsaWOIsVAX+9CH5vHHrDP5w0VjXx+QKV6h6liUu/UjvPxx+YAF4/PNStu4N3Ijgk4172Otz7NeWlwfYWinlFg0scTakIPCow/d+bTxPXz+dUQ76qMRDsJZhQKspkiPV3Gw4cCSyPiYNTYY/zVkfcP0rS9sGkTdXVNDgUhGeUso/DSxxdtbo3n6XD8jP5uKJ/eJajxJKqBzL4m3RB5aDtQ1+R1J26s0VFSzxk47DdY3MXd225dr+mgY+2bAn8hMqpULSwBJn/fOzGe8nJ3DeuD5JFVTAmlsmWA/8sn1H2HWwNqpzRFJx7+v3b65t1Ueludnwq1dWcSRAk+T/xmAgTaXUUTELLCLyiIjsEpFVXst+IyLlIrLMfpzrte5nIrJRRNaLyFmxSlcyOG9c2w6OX/GzLNGy0lPp0yN4nZC/3EI4Iqm497Vo637m2LkTYwx3vrGGl/wUg3ksLtUKfKViKZY5ltnA2X6W32eMmWA/3gIQkVHApcBoe58HRST8Dh/thG/P+SEFXRnVJznqVXwNKsgOun5JgB7yToXbhyWQe95ZR0NTM/e/t4HZn5UG3fbLXdUR1+sopUKLWWAxxnwE7HO4+SzgGWNMnTFmC7ARCDxHbjtXnJfNsQNyW14nYzGYx4D84FMcR1uB7ztkfqS27DnM1Y8u5K/vbgi5rTFWPxylVGwkoo7lFhFZYReV5dnL+gFlXttst5e1ISI3iMgiEVm0e7f7sxnGy3leuZavjOubwJQEN7Bn8BzLyu0HqGt0NryKP24UhXl8stF5pfziUqf3PEqpcMU7sPwDGApMACqAv4R7AGPMQ8aYycaYyYWFsR8zK1Y89SwlRd0Y0Ts+w7REYlCIwFLf1Myq8sjH4KpyofI+lNQUadPM240WbUop/+IaWIwxO40xTcaYZuBfHC3uKgf6e21abC/rsPr06MLkgXlJnVuB0EVhEF1HSTdzLIGcfkwRZ4zq1WrZsm3uDUmjlGotroFFRLxrrb8KeFqMvQZcKiKZIjIYKAEWxDNtiXDeuD58ZXzytQbzNiBEjgWiaxnmL8cypl93RzNkOnXp1AFMHpTfatnh+ibWVbozJI1SqrWYTU0sIk8DM4ECEdkO/BqYKSITAAOUAt8BMMasFpHngDVAI3CzMSbygvt24htT+pOdkdyzQ3fLTKOgWyZ7DtUF3GbR1v0YYyJqgOCdYxnYM5sfnTmC88b2ISVFWLBlH398e21ULc/65XbhpJJCv63AlmzbH3IUZ6VU+GL2q2aMuczP4oeDbH83cHes0pOMkj2oeAzsmR00sOyuruPEez6gZ7cM8rIzyO/q+ZtOXtcM8rMzrL9dMxha2K3VqMmeDpLji3vw/I3Htxpwc+rgfF686XjeXFnBr15ZFVFnyq9P7k9qipDfNYNhRd3YuOtQy7pFpfu58rhBYR9TKRVc+/hlUwk1MD87ZLPi8qojlFcdCXmsx66ZysnDjza68PRjKc7P9juKs4jwlXF9mToonx+/sIJ5XzpvCZgi8PUpxS2vpwzKaxVY3BjrTCnVVsg6FhEpEpGvisjNInKNiEwVER0KphMZ2DN0Bb5Tb6+saPXaUxSWn50RdL+i7lnMvnoKv5s1mqx0Zx+/U0YUtRo5YPLA1vUs5VVHqDwQ3ZA0Sqm2An5DReQUEZkDvAmcA/QBRgG/BFaKyG9FJDm7iytXherLEo45qytbRheubWiitsF6ntc1eGABK/dyxXGDeOPWGYwLMfIyWHPaeJviU4EPmmtRKhaC3fqdC1xvjJlijLnBGPNLY8yPjDEXAOOBpcAZcUmlSig3A8v+mgbmb95rPz9acZ+fne74GMOKuvHiTcdz66nDAg6SOahnNjNHtO7n1D+/C0U5ree40cCilPsCBhZjzI+NMdsCrGs0xrxijHkxdklTycLNojCAt1ZWAq2Hc8kPc1Kz9NQUfnjmCJ6/8fg2gW9GSQEvffcE0lJbf7xFpE2uZUHp3lYjIyulohe0sNq3LkVELheRG0XEvVtYlfTystPJyXSvncec1ZU0NjW3GoAyVB1LIJMG5vHWbTO4dEp/ROB7p5Uw++qp5AcoWps8KK/V61XlB3niC7/3T0qpCIWqBX1TRI4BEJFfAFdiFYM9E+uEqeQhIgwMMcpxOPYdrueLLftaNR/O6+q8KMxX18w0/njxOD75yal8/4zhrZoz+/JXz/Lb11azUMcOU8o1wSrvT8bqAV9oP78C+CdWUBkpIieJyIBA+6uOZaCDoV3C8ebKitZ1LA4q70Pplxt87hiAkb1z6JrRekaGxmbDTU8s0RZi7cz2/TWJToIKwEm7zSygN9AEeIaP9XRYSM6x3pXrfId2Gd6rW1THm7Oqkr2HjgaWvAiLwsKVlprCxIF5bZbvOVTHjU8sjmqkZhU/dY1N3Pb0UpqjmddaxUywyvt5wFPAfcDvgHvtOVZWAXuMMR8ZY7bGJ5kq0bxHOc5IS+Hv35xINFPI7D1cz9w1ViV+dkYqWenxm9fNX3EYWHO03PHKaq3MbwdW7zjIkm1VvL5iR6KTovwImmMxxtwBXAKca4x51Guf62OdMJVcvEc5vnzaAEp65TCiV3TD/a/eYQ23H6/ciscJwwoCrnt2URlPamV+0ltqjx9379z11DfqKNXJJlgdiwAYY9YaYzZ6lhtjdhtjNntvozo+T5PeLumpfHfmMMBqkeUGN+pXwjG+uAc5WYFbuf329dUs0sr8pLbUHlG7bN8RnvxCC06STbAcywcicqtvBb2IZIjIqSLyGHBVbJOnkkXv7llkpKVw9QmDKLQ7GbbXwJKWmsLxQ3sGXN/QZLhRK/OT2lKvEa8feH8j1bVHWxgeqW/SupcEC9Y54WzgGuBpe46UKqyK/FRgLvBXY8zSmKdQJYWUFGFM3+5856ShLcvaa2ABmFFSyJzVOwOu91TmP/ud6WSmxa/+R4W262BtqwFP9x2u5+cvryK3SzpLtu1nXWU1JUXd+N5pJZw1ujcpQZqfe9TUNzJndSVfPbY45LYqtICBxRhTCzwIPCgi6UABcMQYUxWntKkk89sLxtDDa+iVAfnZFHTLYM+h6GaBjHcdC8BJJaGntfZU5v/x4rFB55ppaGomPVXHZY2XpWVVbZa9vrx1Jf66ympuenIJI3vncPvpJZw5KniA+d0ba3l+URlDCroxvn+uyynufBx9G4wxDcaYCg0qndtYn4EfRYSJA6LPteRH0TkyUgN6ZjMgP3Snz1CV+esrqzn1Lx+2jH+mYm9pGBO/raus5sYnlnDu/37MO6sq/BaRvbOqkqcXbKOx2XD7s8s4XNfoYmo7J73NUlFxozjMycjGsTCjJHDrMG+BKvNXlR/g0oc+p2zfEa6ZvVAr/ONkaQRTYXsCzHkPfMI7qypbAkzFgSP89KUVLdtt2XOY372xxrW0dlYaWFRU3AgskY4TFi2ngcWqzF/MX+au54N1u6iqqWfptv1c9q/5LcPS1NQ38e1HF7Ikgh895VxjUzMrth+IeP+1FQe58YnFdoCp4AfPLqfKZ2bSZxaW8c6qigBHUE44GllQRAYCJcaYd0WkC5BmjKmObdJUezCmXw/SU4WGpshb4SQqx3Lc0AJSBJw0INpzqJ4H3m9pdU9aitDos+OhukaufnQhi355uta5xMi6ymqONEQ/OoIVYJYEXP/SknLOHtMn6vN0Vk5mkLweeAFrnDCAYuCVGKZJtSNZ6amM6Rd60q1geiYosPTokh5xRa1vUPE4cKSBVeWR31Gr4PxV3MeC9zh2KnxObqtuBk4ADgIYYzYARbFMlGpfJkVZgZ+oHAtYzY7dtqhUi8NiJZL6lUjsO6yBJRpOAkudMablXRaRNEB7H6kW0daz5HaJf6swj5OHO6tnCccCrcSPmWVhtAiLxn6fehcVHieBZZ6I/BzoIiJnAM8Dr8c2Wao98TdasFM9uqS3mekxniYOyAvaCz8Si0r36UCWMbDrYC2b9xyOy7mqaupp0t77EXPyjf4psBtYCXwHeAv4ZSwTpdqXXt2zmDggN6J9E9Hr3puIcOesMaSnujfs3f6aBjbtPuTa8ZJZQ1Mzy8qqYh5IaxuauPGJxTE9h7dmAwePaK4lUk4CSxfgEWPM14wxlwCP2MuUanHDSUMi2i8vO3HFYB7Dirpx/YzI0h/Iwk5Sz3L3m2u58O+fcs79H/PYZ6UciMGPcVOz4fZnlrEkTsVgHvu0Aj9iTgLLe7QOJF2Ad2OTHNVenTGqd6s5W5xKdI7F49ZTSxzNQOnUwi0dv57lxcXbmf1ZKWA1A/71a6v58fPLXT/P799ayzurK4Nu42A4sLDt1wr8iDmaQdIY05Kvt5+7NwG66hBSU4TrIrjrT8Q4Yf50yUjlNxeMdu14C7d27MCyYnsVP3t5ZZvl763bxa6D7o0K/e+PN/PwJ1uCbjO8Vzfe++FMThjmbl2ZtgyLnJPAclhEJnpeiMgkjk5NrFSLSyYVh50Dye+WHIEF4IxRvThtpDst6cv2Hemww+7vrq7jO/9Z7HeCraZmwwtLtrtyntmfbuGuN9cG3WZ8cQ+eveE4Bhd05eGrpnDmqF6unBto0yNfOecksNwOPC8iH4vIJ8CzwC0xTZVql7LSU7nyuIFh7ZOo4VwC+c0Fo8lMc6eV2sIO2Oy4oamZm59aQkWQoPnswrKo50OZ/ekWfvN68DG7pg/J58nrp7f0g8pKT+XByydy0cR+UZ3bQ+tYIhfyG2SMWQiMBG4CbgSOMcbEr3mGaleuPG4QWenOf5gT2TnSn/752dxyyjBXjtURA8tdb6xhQYj6o617a6Ia7fmxz0pDBpUeXdL55xWT6ZbZelSqtNQU/nzJeEb2jm7abNA6lmgEm5r4VPvvRcD5wHD7cb69TKk28rtm8LVJ/Z1vn2Q5FoAbTh7C4IKuUR+no7UMe25RGY997mwa4GcWlkV0jsc/L+XXr60Oud0NJw2hR4COtakpwo/PGhHR+b1pHUvkgt1anmz/Pd/P4ysxTpdqx66bMZgg82K1kmw5FoDMtFTunBV9Rf66yoMxaX6bCMvKqvjly6scb//Oqsqw7/gf/7yUO14NHVTyu2bw7eMHBd3m1JFFTI5yRAgdLyxyAQOLMebXIpICvG2MudrncU0c06jamYE9u3L26N6Otk2W5sa+ZpQUct646Ea3NQY+3rDbpRQlzq7qWm78z2Lqm9pW1gdS39TMy0vLHW/vNKgA3HTyULpmBh+YXUT4yTkjHZ/fH82xRC5oYbgxphn4nzilRXUgTjtMJmNRmMevzhtF14y2893nZafz6s0n8NT107j/0gl8d+bQgDm0+9/dQGMYP8jJpr6xmZufXEJlBE2In1m4zVGP/P+EEVSKcjL51nRnDUSmDMqPqpWfjhcWOSe1rO+KyI9EpL+I5HseMU+ZateOHZDH1EHBPyapKUL3Lo6mBEqI3j2y+P4Zw9ssv+P8UYzvn8vxQwuYNaEf/3P2SO65eJzf4LJh1yFedKn5bSLc+cbqiOuKvtx5KGRv+f/M38qvHAYVgFtOHUYXP8E+kB+dNcJxsawvzbFEzklg+QbW0PkfAYvtx6JYJkp1DKFyLXnZGUik3/o4uer4Qa1aGJ00vJALJ7Rtzvr1yf358yXj/f6I3fffDRypj35yqnh7duE2npi/LepjBPKf+Vv51SvO622KcjL5xhTnDUMAjunT3e/1cuLAkYZ2ndtMJCfNjQf7ebg7sJLqkE4dWcTQwsCtq/K7Jn6csFDSU1P43YVjAMjOSOXuC8cEDIaXTCrmTxePa7O88mAtj34WvPd4sllVfoBfveI8JxHI68srqK5tW6T0/KKysIIKwPnj+5KZ5jy34vH904dHPMhoR2l8EW9OZpDMEpEfiMhLIvKiiNwuIlkO9ntERHaJSJtPj4j8UESMiBTYr0VE/ldENorICu+e/qr9SkmRoIM7JstwLqFMGZTPJZOK+dGZI+ifH3w0o0smFVPQLbPN8n98uKnd9Iuorm3g5qeWOKqsH1LQNWifkSMNTby+vPX88RUHjvAbB02KfV0wvm/Y+wAM6JnNN6cOiGhfbRkWGSdFYY8Do4EHgL/Zz//jYL/ZwNm+C0WkP3Am4J1HPgcosR83AP9wcHzVDlx4bD+/P7SQvC3C/PnVeaO4KkQTV7BaI00d3LaZa3VtI3//YGMMUuYuYww/e2klW/fWONr+DxeNZfKg4M16n/EpDvvta2s4HGbR4MCe2YwrjnwK7FtOLSE7jLoZj32HNccSCSeBZYwx5lpjzAf243qs4BKUMeYjwF8X3fuwWpp5NxeZBTxuLPOBXBGJrq2nSgpZ6alcfcIgv+uSsQ9LID2y00l1OITulACNFh7/fCtl+5z9YCfKMwvLeGNFRegNgW9OG8C0IT0Z2y/4D/6K7QdYveMAAO+t3RlypGJ/LhjfN6r6uMKcTK47cXDY+2kFfmScBJYlIjLd80JEphFh5b2IzALKjTG+Y2v3A7y76m63l6kO4PJpA/zeLSZzU+NoBAos9U3N3PffL+OcGue27DnsuIiqKCeTn9r9RMb2yw25/bMLy6ipb3TcrNhXpMVg3q47aUjY8/9oUVhknASWScBnIlIqIqXA58AUEVkpIiucnkhEsoGfA3dElNKjx7lBRBaJyKLdu9t/57POIDc7g69Pbtuap6i7/yKy9u6YPt3bjGHl8fKyctbsOBjnFDnz3tqd1PkZsdif3104hu5Z1o90Sa9uZIQYuPPlpeXc8/Y6yqvCHxh9ZO8cSnpFP/ZX96x0bg4yDlyfHm2rjjXHEhkngeVsYDDWEC8n28/PxhrW5fwwzjXU3ne5HaCKsXJDvYFywPuXp9he1oYx5iFjzGRjzOTCwsIwTq8S6doTB7cqSjp7dG8unRJZhWqyS00RJgYYTsQYuOeddXFOkTNLtjnrr3L26N6c5TWyQnpqCqP6dA+6T3Vto+NxxnxdMCH63IrHt6YP9BtAZpQUcIqfzpTtpcFFsnHS3HhrsIfTExljVhpjiowxg4wxg7CKuyYaYyqB14Ar7dZh04EDxhhnBb2qXeifn825Y61qs/PG9eGBbx4b8i63PZsSZJyqeV/u5rONe+KYmtCMMSzeGjqw5GSl8Vs/46iFqmeJxvnj3AssWempfP/0tp1ef3DGcHrl+MmxaFFYRGL2zRaRp7GKzUaIyHYRuTbI5m8Bm4GNwL+A78YqXSpxbpgxhFkT+nL/NyaQntpxgwrAlMHBRx34w9vrop6zxE3lVUfYebAu5HY/P/cYenVv+wM8NooWW8FMHJAbsol3uC6a2I9hRd1aXp82sohjB+T5LZrVHEtkYvbtNsZcZozpY4xJN8YUG2Me9lk/yBizx35ujDE3G2OGGmPGGmO0Z38HNLa4B/d9fQJpHTyoAEzonxu0U97K8gO8uTJ5MuVOcivTBufzDT91ZRCbHEtGago/OjP64e99pfkc1zNsT1GOn8Ci44VFpON/w1VSSXHYZLe9y0pPZVxxbtBt7p273u/0vomwJERgyUhL4Q8XjQ14/UqKurk28yZAisD9l07g+GEFrh3T21mjezG+fy7njOnNGDso+suJaauwyGhgUSpGQnUc3Lq3hqcXRDcWl1sWh6i4/95pJQwp7BZwfVpqCqP7Bq/AD8fvvzqWc8bGriubiPDTs0e2GmTUX45FW4VFRgOLUjESanRngP99bwOH6hrjkJrADtc1sraiOuD6kb1zHE2D4FZx2E/OHsmlEQ7BEo7jhvZkuFcz5p7dMvHNkFXXNtKgA1GGTQOLUjEyeWB+yCHb9x6u56GPNscnQQEs315FU4CGBCkCf7x4nKPGFmNDFP058Z2ThnDTzKFRHycSqSnid/ghLQ4LnwYWpWKkR3Y6Ixx07Pv3x5vZVR3+RFpuCVa/cvUJg5nQP9fRcaLNsXxjcv+W3vyJ4r9lmFbgh0sDi1Ix5K/Tna+a+ibmrN4Zh9T4tyhAYCnO68IPz2zb5yOQoYVd6ZIe/kCPYFWm3/3VwFMSxEuRv74sWs8SNg0sSsXQeQ4roFdtPxDjlPjX3GwC5ljuunAM2RnOZ/hMS01hVAQV+McP7cn9lx6bFM3Qe/nLsWhRWNgSfyWV6sBG9+3OAAcd/FaU+w8sdY1NMa3c37T7EAdr2x5/fHEPTh4e/pBJ48OsZxlX3IOHrpxMVoQ5HbcVao7FFRpYlIohEWkZyiaYL3dWU9vQdo6SldsP8K8oK/c/+nI3G3cd8rsuUMfIq44fFFGx1EUTnQ9KPqSwK7OvnhpwwM5E8NtJUgNL2DSwKBVjTorDmpoNayvajnr8xZZ9/OvjzeyuDj3cij8LtuzjuscWceZ98/jJCyuoOHAEYwxl+2p4YfF2nvyibT+agm4ZnDcusj4kY/r1cFTZ37dHFk9cOy3pJnvT3vfuSJ5bBaU6qDH9ulOc14Xt+4MPGb+y/ADHDmjdqXJh6T5q6pt44P0N3DlrTFjn3bT7ENc/vqhliuFnF5Xx8rJyCrpmsONA4FZol00dENHc8h5XHjeQZWVVQbe55dQS+uZ2ifgcsaK9792hORalYkxEHOVaVvhU4Dc1GxaXWkVVT32xjdI9hx2fc8+hOr796AIOHGl9t13f2Bw0qKSlCJdPG+j4PP6cO7ZPyJzItCGhO48mgr/mxlrHEj4NLErFgZN6lpU+gWVd5UGq7Yr7xmbDvXPXOzrXkfomrntsEWX7wp9U66wxventZ76ScGSlp/qd2M2joFsmQwq6RnWOWCnoltmmU6vmWMKngUWpOBhX3IPivOBFPxt2VXOk/mgF/sIt+1qtf2NFBSu2VwU9RlOz4fZnl4Ysigrk6uMHRbSfr8unDQg46sC0wfkJ768SSHpqCj19clvxzLF8unFPwIYW7YkGFqXiwEnrsGYDayqO5loWlO5rs80f316HMYHncbn7zbURd7Yc0SuHSUEmKAtH//xsThnhv3Po1BBz1SSab5PjeLUK27T7EN/5z2LO/utH3P3mGqpr22+jAQ0sSsWJk+IwTz2LMYYFW9o2Bf5s014+3uB/9slHP93CI59uiTh9UwbnuZqTuOI4/3U1yR5YfFuGHa5v4r7/fhk0oEfrcF0jN/5nMYfqGmlsNvzr4y2ccu88Xli8PakmhHNKA4tScTK+uAf9QrSE8tSzlO6tYc8h/02M/+hn9sk5qyu58401UaVvdF93J+s6uaSQ/vmt/98eXZyNn5ZI/nrf3//eBn7z2uqY/MgbY/jJiyvY4FMEtudQHT96fjkX/99nIYtAk40GFqXixCoO6x10m5V2D3zf+hVvayoO8vqKHS2vl5VV8b1nlhLtDbWb86mANanbt3xamE0ZlJ/0k735Gy8M4LHPt/L955a5Poz+w59s4Y0VgWcTXbqtill//5SfvLAi4M1GstHAolQchZq8auPuQxyua+SLIIEF4M9z1lPX2MS2vTVcO3shtQ3R/dilpkiruUnc8vXJ/cnwmllyWpIXg4H/Jscery7bwT8+3OTauV5YvJ273lwbcjtjrH5Ip9z7IY9+uoXGJJ8jRgOLUnF0bP9c+gZpzmsMrN5xkIV+Ku69bd9/hAc/2MS3Zy9grwuVy8MKu8VkvK68rhmcP65vy+tkr1+BwDkWjyfmb3Ul1/La8h38zwvLw9qnuraR376+hhufWBL1+WNJA4tScSQiIXMt767dybZ9NSGPdf97G9i823mnyWDcLgbzdqVdiZ+dkRrT87glWI4FYFd1HXNWV0Z1jndWVfL9Z5cRaZVNsheJaWBRKs5CtQ57ekHr8bvSU2NfJxHJcPdOje+fy7jiHkwamJcUQ+OH4m+8MF+Pf7Y14uNX1dRz29NLA87a2REk/1VWqoM5tn8ufYIUh1V7DWPfs2sGXwvSi90tsQwsAN+aPpDpQ3rG9BxuKXQQWBaU7mPNjraDhjrx3zU7W8Zv66g0sCgVZykpwjljnI0eXNQ9i5tPGUaGS3f6mWkpZGe0rUsZ3cfdpsa+Lhjfl9OOCT2bZjLITEslLzs95Hb/mV8a0fGjLUZrDzSwKJUA540L3uzYoygnk365XfjGFHdyLXd/dSwXHtt6zpTivC70cPBDGo2s9FRG9k7++hWPUBX4AC8vLedAmEPqH6pr5KMAHVw7Eg0sSiXAsf3z6O1niHZfns563z1laNS5lsunDeCSScVc6hOk2kOFeryFqsAHqG1o5vnFZWEd94N1u6hv7NjFYKCBRamESEkRzh4TOtfiuXPu06MLl02NPNcyvn8ud5w/CoCx/XowsvfRPitu97jvCJzkWAAe/3xrWL3x31nV8YvBQAOLUgnjZJZG7+FFvnvKsFadDZ3K75rBg5dPbJm8S0Ra5VpG9dEciy8nORaAbftqmPflbkfb1jY08cH6XdEkq93QwKJUgkwakOd3XCpv3iPt9uqexTenDgjrHNMG5/P6rSe2GaPswmP7tQSp0f00sPjq5aBlmMdjn5c62u6jL3dT4zUtQkemgUWpBHHSOsw38Hx35lAyHeRa0lOFn50zkqeun+534Mvc7AzOGdOb/K4Zjup6OpthRc6Ht/lw/W5Hs3u+0wlag3loYFEqgUJ1lizy+dEv6p4Vcurg4b268crNJ/Cdk4eSGmTAx29M6c/ovt2TdtKtRJoyOM9vs+xAnpgfvMNkfWMz764JPU9OYU4mST5GpyMaWJRKoMkD84L29C7s1nbdjTOHkJXu/6t7zQmDee2WEx1VyE8f3NNxf5rOJjMtlROGFTje/rlFZdTUNwZcP3/zXg7WBl7vcdVxA/nTJeMdnzdZaWBRKoGs4jD/rcPyu2b4rawvyslqMxx9r+6ZPHHtNO44f5TjwSRTUsS1/jEdUaAZMP05WNvIq8t2BFz/tsPWYDNHFHHJpGLu/uoYx+dORhpYlEqwQINSBsvJfOfkoS25lvPG9mHO7SdxYonzO2yPYEVlnd3MEYVhbf/YZ6V+Z5lsajb8d03owFKYk9nSQu/yaQO54yujwjp/MklLdAKU6uymDMqnoFtmmxFrfetXvBXmZPLdmcMozuvCV4/tp/UkMdA3twsje+ewrrLa0fbrKqtZWLq/zdQAi0r3sedQ6KkNTh5e2GoStGtOHExdYzP3vLMuvIQnAc2xKJVgqSnCicPaDtAYqsnrbaeVcNHEYg0qMXTKyPDGN/PX9NhpazB/OaSbZg7l9tNLwkpDMtDAolQSKPEze6PTTnoqdsKpZwGYs6qSygO1La+NMcxxUL+SmiLMGOa/6O17p5Vw08yhYaUj0TSwKJUE/E0L3Ev7lyTcxAG5dM9yXmPQ2Gx4yms+nRXbD7DDK9AEO0+ggUBFhP85awRXnzDIcToSLWaBRUQeEZFdIrLKa9nvRGSFiCwTkbki0tdeLiLyvyKy0V4/MVbpUioZlRR1a7PMyYRTKrbSUlM4aXh4lfhPfbGtZaBJ58VgwXNGIsIdXxnF5dPCG3khUWKZY5kNnO2z7M/GmHHGmAnAG8Ad9vJzgBL7cQPwjximS6mk0z8/u02P+mCV9yp+wi0O23OojrdXVWCMcTzopJMWaCLC72aN4ZJJxWGlJxFiFliMMR8B+3yWeU+51hXwtM2bBTxuLPOBXBHRnluq00hNEYYWts61aI4lOZwcZrNjsEY9/nLnIbY4GOqlyKuZcSgpKcI9F4/jgvF9w05TPMW9jkVE7haRMuByjuZY+gHeExtst5f52/8GEVkkIot273Y2qqhS7cHwXq0Di5MpclXsFXTLJDfMidAWb93PvXPXO9r25OGFYbXsS00RrjlxcFjpibe4BxZjzC+MMf2BJ4FbItj/IWPMZGPM5MLC8O8klEpW3i3D8rLTW4a5V4nXp0fbgTxD+a+DscGAsIaOaS8S2SrsSeBi+3k54D22RLG9TKlOw7sCX1uEJZc+PWJ3PcZ0wGkL4hpYRMS7p88swNOl9DXgSrt12HTggDGmIp5pUyrRvJscazFYcukdo8DSJT2VwQVtWwS2dzEb0kVEngZmAgUish34NXCuiIwAmoGtwI325m8B5wIbgRrg6lilS6lk5WkZVtfYrDmWJNMnRtdjZJ+cDjleW8wCizHmMj+LHw6wrQFujlValGoPPC3D1lQc1BZhSSZWOZbRfTteMRhoz3ulkoqnZZjmWJJLXz+zcLrBybw57ZEGFqWSiKdlmOZYkovmWMKjgUWpJOJpGaa97pNL7xhcj9QU8TtGXEeggUWpJDJccyxJqWtmWliDUTpRUtTN8Wyf7Y0GFqWSSP/8bLLSU3TI/CQUSSfJYEZ10GIw0MCiVFJJTREmDczTXvdJqE+uu8VhYzpoxT1oYFEq6XTEIT46Ard733fUinvQwKJU0gk0k6BKrN7dtSjMKQ0sSiWZjvyD0565mWMZ2DObnKzwRkxuTzSwKJVkOuIQHx2Bm31ZOnIxGGhgUUopR/q6WHnfUXvce2hgUUopB3q72Ny4oxd3amBRSikHumWmkZMZfSdJkY7d1Bg0sCillGNu1LNcML5vh59vRwOLUko5FG1gSRG47bSS0Bu2cxpYlFLKob5R1rNcOKEfQws73oyRvjSwKKWUQ9HkWFJThFs7QW4FNLAopZRj0XSS/Oqx/Rhc0NXF1CQvDSxKKeVQpDmW1BTh1lOHuZya5KWBRSmlHIp06PyLJ/ZjYM/OkVsBDSxKKeVYJEPnp6UIt57aOepWPDSwKKWUQzmZaXTNCG+unK9NLqZ/fnaMUpScNLAopZRDIhJWPUt6qnDzKZ2nbsVDA4tSSoUhnHqWr03uT3Fe58qtAEQ/8I1SSnUi931jAqt2HGBtxUHWVlSztuIgm3cfotm03i4jNaVT5lZAA4tSSoWlMCeTU0YUccqIopZltQ1NrK+stoONFXAmDMilX667s062FxpYlFIqSlnpqYzvn8v4/rmJTkpS0DoWpZRSrtLAopRSylUaWJRSSrlKA4tSSilXaWBRSinlKg0sSimlXKWBRSmllKs0sCillHKVBhallFKuEmNM6K2SlIjsBrZGuHsBsMfF5Ch36fVJLno9klu412egMaYwVolp14ElGiKyyBgzOdHpUP7p9Ukuej2SW7JdHy0KU0op5SoNLEoppVzVmQPLQ4lOgApKr09y0euR3JLq+nTaOhallFKx0ZlzLEoppWJAA4tSSilXJU1gEZH+IvKBiKwRkdUi8j17eb6I/FdENth/8+zlI0XkcxGpE5Ef+Rzr+/YxVonI0yKSFeCc74hIlYi84bN8sIh8ISIbReRZEckIsP8kEVlpb/e/IiL28q/Z528WkaRpAhiNJLs+t9jvuRGRgiBp9nsdReQkEVkiIo0ickm0700iJNn1eFJE1tv7PyIi6QH277DXw5fL1+d79nu7WkRuD3LOs+3rsFFEfuq1PP7fF2NMUjyAPsBE+3kO8CUwCvgT8FN7+U+Be+znRcAU4G7gR17H6QdsAbrYr58Dvh3gnKcB5wNv+Cx/DrjUfv5/wE0B9l8ATAcEeBs4x15+DDAC+BCYnOj3tgNen2OBQUApUBAkzX6vo73vOOBx4JJEv7cd4Hqca38HBHg6yPelw16PGF6fMcAqIBtrKvl3gWF+zpcKbAKGABnAcmCUvS7u35ekybEYYyqMMUvs59XAWqwP/SzgMXuzx4AL7W12GWMWAg1+DpcGdBGRNKwLsiPAOd8Dqr2X2bmOU4EXfM/ps10foLsxZr6x3v3HvdK21hiz3sn/3V4ky/Wxly81xpQGS2+w62iMKTXGrACagx0jmSXZ9XjL2LButop9t+no18OXi9fnGOALY0yNMaYRmAdc5OeUU4GNxpjNxph64Bn7XAn5viRNYPEmIoOwouwXQC9jTIW9qhLoFWxfY0w5cC+wDagADhhj5oZx+p5AlX0RAbZjfSB89bPXEWK7DifB18cpp9ex3UuW62EXgV0BvONndae5Hr6iuT5YuZUZItJTRLKxcof9/WzXDyjzeh3u++vq9Um6wCIi3YAXgduNMQe919l3REHbR9tllrOAwUBfoKuIfCtGye109PoklyS7Hg8CHxljPo5w/w4n2utjjFkL3APMxQrYy4CmmCTWRUkVWOw7nheBJ40xL9mLd9rFTp7ip10hDnM6sMUYs9sY0wC8BBwvItNEZJn9uCDI/nuBXLtYAKxsfbmIpHrtfydQTussf7G9rMNKkusTLH1z7P3/TYDrGMlxk1UyXQ8R+TVQCPzAa1mnuh6+XLo+GGMeNsZMMsacBOwHvrQbB3iuz41Y76V3Tibk+xvL65MWepP4sMv4HgbWGmP+n9eq14CrgD/af18NcahtwHQ723gEq8JxkTHmC2BCqHQYY4yIfABcglVOeRXwqjGmyXd/ETkoItOxsrhXAg+EOn57lSzXJxhjzFk+aW5zHaM5fjJJpushItcBZwGnGWNayuE70/Xw5eL1QUSKjDG7RGQAVv3KdGNMFV7Xxw4IJSIyGCsgXAp8M9hxY3p9nNTwx+MBnIiVLVyBld1bhlWe2BN4D9iA1SIi396+N1Y54EGgyn7e3V73W2AdVvnkf4DMAOf8GNiN9YXaDpxlLx+CVQm5EXg+yP6T7XNsAv7G0ZEMvmofrw7YCcxJ9Pvbwa7PbfbrRqyK5n8H2N/vdcRqfbMdOIx1p7Y60e9vO78ejfZ3wJOOOzrb9Yjx9fkYWIPV0uu0IOc8F6v12SbgF17L4/590SFdlFJKuSqp6liUUkq1fxpYlFJKuUoDi1JKKVdpYFFKKeUqDSxKKaVcpYFFqSiIyG98R6P1WX+hiIyKZ5qUSjQNLErF1oVYo9oq1WloPxalwiQiv8DqmbwLa+C/xcAB4AasIcs3Yg3GOAF4w153ALjYPsTfsYY/qQGuN8asi2PylYo5DSxKhUFEJgGzgWlYQyItwZq74lFjzF57m7uAncaYB0RkNtb8JS/Y694DbjTGbBCRacAfjDGnxv8/USp2kmasMKXaiRnAy8aYGgARec1ePsYOKLlAN2CO7472SLfHA89bQ0kBkBnrBCsVbxpYlHLHbOBCY8xyEfk2MNPPNilYc15MiF+ylIo/rbxXKjwfAReKSBcRycGaqhes6Wcr7KHSL/favtpeh7Hm49giIl8DawRcERkfv6QrFR8aWJQKg7Gmm30Wa6TZt4GF9qpfYU2f8CnWSMEezwA/FpGlIjIUK+hcKyLLgdXY08cq1ZFo5b1SSilXaY5FKaWUqzSwKKWUcpUGFqWUUq7SwKKUUspVGliUUkq5SgOLUkopV2lgUUop5ar/DyNsSzLcv58mAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fb_q4 = fb.loc['2018-Q4']\n",
    "plt.fill_between(fb_q4.index, fb_q4.high, fb_q4.low)\n",
    "plt.xticks(['2018-10-01', '2018-11-01', '2018-12-01', '2019-01-01'])\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('price ($)')\n",
    "plt.title('FB differential between high and low price Q4 2018')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can specify a specific range to fill with the `where` argument:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'FB differential between high and low price Q4 2018')"
      ]
     },
     "execution_count": 9,
     "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": [
    "fb_q4 = fb.loc['2018-Q4']\n",
    "plt.fill_between(\n",
    "    fb_q4.index, fb_q4.high, fb_q4.low, \n",
    "    where=fb_q4.index.month == 12, \n",
    "    color='khaki', label='December differential'\n",
    ")\n",
    "plt.plot(fb_q4.index, fb_q4.high, '--', label='daily high')\n",
    "plt.plot(fb_q4.index, fb_q4.low, '--', label='daily low')\n",
    "plt.xticks(['2018-10-01', '2018-11-01', '2018-12-01', '2019-01-01'])\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('price ($)')\n",
    "plt.legend()\n",
    "plt.title('FB differential between high and low price Q4 2018')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Annotations\n",
    "The `plt.annotate()` function can be used to add annotation to plots. Some important arguments:\n",
    "- `xy`: a tuple of the coordinates to annotate\n",
    "- `xytext`: a tuple of coordinates of where to place the annotation text\n",
    "- `arrowprops`: a dictionary of how to draw the arrow from the text of the annotation to the point being annotated\n",
    "- `ha`/`va`: specify the horizontal/vertical alignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = fb.close.plot(title='FB Closing Price 2018', figsize=(15, 3))\n",
    "ax.set_ylabel('price ($)')\n",
    "\n",
    "ax.axhspan(support, resistance, alpha=0.2)\n",
    "\n",
    "plt.annotate(\n",
    "    f'support\\n(${support:,.2f})',\n",
    "    xy=('2018-12-31', support),\n",
    "    xytext=('2019-01-21', support),\n",
    "    arrowprops={'arrowstyle': '->'}\n",
    ")\n",
    "plt.annotate(\n",
    "    f'resistance\\n(${resistance:,.2f})',\n",
    "    xy=('2018-12-23', resistance)\n",
    ")\n",
    "\n",
    "for spine in ['top', 'right']:\n",
    "    ax.spines[spine].set_visible(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have many options for the arrow:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'price ($)')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "close_price = fb.loc['2018-07-25', 'close']\n",
    "open_price = fb.loc['2018-07-26', 'open']\n",
    "pct_drop = (open_price - close_price) / close_price\n",
    "fb.close.plot(title='FB Closing Price 2018', alpha=0.5)\n",
    "plt.annotate(\n",
    "    f'{pct_drop:.2%}', va='center',\n",
    "    xy=('2018-07-27', (open_price + close_price) / 2),\n",
    "    xytext=('2018-08-20', (open_price + close_price) / 2),\n",
    "    arrowprops=dict(arrowstyle='-[,widthB=4.0,lengthB=0.2')\n",
    ")\n",
    "plt.ylabel('price ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also pass additional parameters down to the [`matplotlib.text.Text` class](https://matplotlib.org/api/text_api.html#matplotlib.text.Text), such as `color`, `fontfamily`, `fontsize`, and `fontweight`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'price ($)')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "close_price = fb.loc['2018-07-25', 'close']\n",
    "open_price = fb.loc['2018-07-26', 'open']\n",
    "pct_drop = (open_price - close_price) / close_price\n",
    "\n",
    "fb.close.plot(title='FB Closing Price 2018', alpha=0.5)\n",
    "\n",
    "plt.annotate(\n",
    "    f'{pct_drop:.2%}', va='center',\n",
    "    xy=('2018-07-27', (open_price + close_price) / 2),\n",
    "    xytext=('2018-08-20', (open_price + close_price) / 2),\n",
    "    arrowprops=dict(arrowstyle='-[,widthB=3.0,lengthB=0.2'),\n",
    "    color='red',\n",
    "    fontsize=14,\n",
    "    fontweight='medium'\n",
    ")\n",
    "plt.ylabel('price ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Colors\n",
    "We can pass colors to the `color` argument of the `plot()` method. This can be a color name, a hex code, or RGB values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'price ($)')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fb.plot(\n",
    "    y='open',\n",
    "    figsize=(5, 3),\n",
    "    color='#8000FF',\n",
    "    legend=False,\n",
    "    title='Evolution of FB Opening Price in 2018'\n",
    ")\n",
    "plt.ylabel('price ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "RGB values must be given as decimals:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'price ($)')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fb.plot(\n",
    "    y='open',\n",
    "    figsize=(5, 3),\n",
    "    color=(128 / 255, 0, 1),\n",
    "    legend=False,\n",
    "    title='Evolution of FB Opening Price in 2018'\n",
    ")\n",
    "plt.ylabel('price ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Colormaps\n",
    "| Class | Purpose |\n",
    "| --- | --- |\n",
    "| Qualitative | No ordering or relationship between colors; just used to distinguish between groups |\n",
    "| Sequential | For information with ordering, such as temperature |\n",
    "| Diverging | There is a middle value between two extremes that has meaning; for example, correlation coefficients are bounded in the range `[-1, 1]`, and `0` has meaning (no correlation) |\n",
    "\n",
    "#### Finding available colormaps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['Blues', 'BrBG', 'BuGn', 'BuPu', 'CMRmap', 'GnBu', 'Greens', 'Greys', 'OrRd', 'Oranges', 'PRGn', 'PiYG', 'PuBu', 'PuBuGn', 'PuOr', 'PuRd', 'Purples', 'RdBu', 'RdGy', 'RdPu', 'RdYlBu', 'RdYlGn', 'Reds', 'Spectral', 'Wistia', 'YlGn', 'YlGnBu', 'YlOrBr', 'YlOrRd', 'afmhot', 'autumn', 'binary', 'bone', 'brg', 'bwr', 'cool', 'coolwarm', 'copper', 'cubehelix', 'flag', 'gist_earth', 'gist_gray', 'gist_heat', 'gist_ncar', 'gist_rainbow', 'gist_stern', 'gist_yarg', 'gnuplot', 'gnuplot2', 'gray', 'hot', 'hsv', 'jet', 'nipy_spectral', 'ocean', 'pink', 'prism', 'rainbow', 'seismic', 'spring', 'summer', 'terrain', 'winter', 'Accent', 'Dark2', 'Paired', 'Pastel1', 'Pastel2', 'Set1', 'Set2', 'Set3', 'tab10', 'tab20', 'tab20b', 'tab20c'])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from matplotlib import cm\n",
    "cm.datad.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can pass a colormap to the `colormap` argument:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'price ($)')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = fb.assign(\n",
    "    rolling_min=lambda x: x.low.rolling(20).min(),\n",
    "    rolling_max=lambda x: x.high.rolling(20).max()\n",
    ").plot(\n",
    "    y=['rolling_max', 'rolling_min'], \n",
    "    colormap='coolwarm_r', \n",
    "    label=['20D rolling max', '20D rolling min'],\n",
    "    style=[':', '--'],\n",
    "    figsize=(12, 3),\n",
    "    title='FB closing price in 2018 oscillating between '\n",
    "          '20-day rolling minimum and maximum price'\n",
    ")\n",
    "ax.plot(fb.close, 'purple', alpha=0.25, label='closing price')\n",
    "plt.legend()\n",
    "plt.ylabel('price ($)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also grab colors out of a colormap, which is a callable. This gives us an RGBA color, which we already know can be used as the `color` for the plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 0.2529411764705882, 0.5019607843137255, 1.0)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cm.get_cmap('ocean')(.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Making colormaps\n",
    "In order to make colormaps, we need some utility functions which can be found in the `color_utils.py` module. We will need to be able to convert hex colors to RGBA decimals, blend colors to build a colormap, and draw the colormap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import color_utils"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Blended colormaps\n",
    "Use `blended_cmap()` to blend any number of colors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7bef145e1518>"
      ]
     },
     "execution_count": 19,
     "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": [
    "my_colors = ['#800080', '#FFA500', '#FFFF00']\n",
    "rgbs = color_utils.hex_to_rgb_color_list(my_colors)\n",
    "my_cmap = color_utils.blended_cmap(rgbs)\n",
    "color_utils.draw_cmap(my_cmap, orientation='horizontal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note: The `draw_cmap()` function also makes it easy to add a colorbar with our own colormap to the plot of our choice. Check out the [`covid19_cases_map.ipynb`](./covid19_cases_map.ipynb) notebook to see this in action.*\n",
    "\n",
    "#### Seaborn Color Palettes\n",
    "Seaborn also provides additional color palettes, along with utility functions for picking colormaps and making custom ones interactively in Jupyter. See [this tutorial](https://seaborn.pydata.org/tutorial/color_palettes.html) for more information.\n",
    "\n",
    "##### Showing a color palette"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "sns.palplot(sns.color_palette(\"BuGn_r\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Building a color palette interactively for use with matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4a4e1e59b4054b46a345a8b0105f1e08",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(IntSlider(value=220, description='h_neg', max=359), IntSlider(value=10, description='h_p…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "diverging_cmap = sns.choose_diverging_palette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7bef143eb748>"
      ]
     },
     "execution_count": 22,
     "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": [
    "from matplotlib.colors import ListedColormap\n",
    "color_utils.draw_cmap(ListedColormap(diverging_cmap), orientation='horizontal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cycling through colors\n",
    "We can use itertools to cycle through colors:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<itertools.cycle at 0x7bef143fe948>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import itertools\n",
    "\n",
    "colors = itertools.cycle(['#ffffff', '#f0f0f0', '#000000'])\n",
    "colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'#ffffff'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "next(colors)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or we can work with a `ListedColormap` object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1.0, 0.0, 0.0, 1.0), (0.0, 0.0, 0.0, 1.0), (1.0, 0.0, 0.0, 1.0)]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from matplotlib.colors import ListedColormap\n",
    "red_black = ListedColormap(['red', 'black'], N=2000)\n",
    "[red_black(i) for i in range(3)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We may also consider using a generator:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<generator object color_generator at 0x7bef148dfed0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def color_generator():\n",
    "    for year in range(1992, 200019): # integers in [1992, 200019)\n",
    "        if year % 100 == 0 and year % 400 != 0:\n",
    "            # special case (divisible by 100 but not 400)\n",
    "            color = '#f0f0f0'\n",
    "        elif year % 4 == 0:\n",
    "            # leap year (divisible by 4)\n",
    "            color = '#000000'\n",
    "        else:\n",
    "            color = '#ffffff'\n",
    "        yield color\n",
    "    \n",
    "year_colors = color_generator()\n",
    "year_colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'#000000'"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "next(year_colors)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also make a generator with a generator expression:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<generator object <genexpr> at 0x7bef14415138>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_colors = (\n",
    "    '#ffffff'\n",
    "    if (not year % 100 and year % 400) or year % 4\n",
    "    else '#000000' for year in range(1992, 200019)\n",
    ")\n",
    "year_colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'#000000'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "next(year_colors)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Textures\n",
    "We can add textures to our plots via the `hatch` parameter in `matplotlib`. Current options are: {'/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 0, 'week number'), Text(0, 0.5, 'volume traded')]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wBo7jtBJF3z/9DMLJlbRBEHEZOI4zkvj+mY6PYnJypbu7OzbTZvbs2bEZOMuXL29mcZ2C4ftnk7KYJF0g6RlJsXecSPq8pDvCa7GkVZI2DcselVQOy/yI38YkZdokZeA4zkji+2c6eV5iupDoWdOxmNk3zWxXM9sVOAW4wcyer1pln7A8tmVz2oOkTJukDBzHGUl8/0wntwbCzG4Enh9yxYgjgDl5lcVpHkmZNkkZOI4zkvj+mU7TO6klrUd0pnF51WwDfiPpNknHDvH5YyUtlLRw6dKleRbVGQZpmTaVDJyenh56enro7PRBdc7I4vtnOq3wjf8VuHnQ5aW9zGxA0huBayXdG85I1sLMzgXOhaiTOv/iOllI+6OKy8BxnJHE9890ch3FJGki8CszSwwwkXQFMM/Mfpaw/HTgZTP7n6G256OYWo/+/v7YTBszi83AGY1ZN07r4vtnCz9RTtLGwLuAX1bNW1/ShpX3wL6AZ++2KaVSKfYB8EkZOI4zkvj+mU5ul5gkzQH2BjaXtAQ4DSgBmNk5YbV/A35jZn+v+ug44Irwn9YJ/MzMindu5ziO02RyayDM7Iga1rmQaDhs9byHgV3yKZXTTCp5NjNmzGhySRxnbXz/XJumj2JyikEl02bWrFmp8QaO0wx8/4zHGwgnd+IybfyP0GkVfP9MxrOYnFyZNGlSbKZNR0dHbAbOGWec0cziOgXD988WHsXkjH6SMm2SMnAcZyTx/TMdbyCcXEnKtEnKwHGckcT3z3S8gXByJSnTJikDx3FGEt8/02mFqA1nlFPJtBk3bhwATz/9dGoGjuOMJL5/JuMNhJM7cZk2c+fObXaxHAfw/TMNH8Xk5Eq5XI7NtFmxYkVsBs5ozLpxWhffP9NHMfkZhJMrSZk2nnPjtAK+f6bjndSO4zhOLN5AOE1n5syZq3NwHKfVKPL+6ZeYnKZSycABOO6445pcGsdZk6Lvn34G4eRK2iCIuAwcxxlJfP9Mx0cxObnS3d0dm2kze/bs2Ayc5cuXN7O4TsHw/dOzmJwmkpRpk5SB4zgjie+f6eTWQEi6QNIzkmJvSZS0t6S/SbojvPqqlu0v6T5JD0o6Oa8yOvmTlGmTlIHjOCOJ75/p5HkGcSGw/xDr3GRmu4bXmQCSOoAfAAcAbwWOkPTWHMvp5EhSpk1SBo7jjCS+f6aT5yNHb5Q0cRgf3R14MDx6FElzgUOAuxtYPGeESMu0icvAcZyRxPfPdJo9zHVPSXcCTwKfM7O7gB7giap1lgB7NKNwTv10dibvYnEZOI4zkvj+mU6uo5jCGcSvzGytABNJGwGvmdnLkg4EzjazbSUdBuxvZkeH9Y4E9jCz4xO2cSxwLMCECROmPPbYYzl9G2c49Pf3x2bamFlsBs5ozLpxWhffP1t0FJOZvWhmL4f3VwIlSZsDA8BWVauOD/OSPOea2VQzmzp27Nhcy+xkp1QqrfXHB8kZOI4zkvj+mU7TGghJb1L4n5G0eyjLc8ACYFtJ20haFzgcmN+scjqO4xSV3PogJM0B9gY2l7QEOA0oAZjZOcBhwHGSVgLLgMMtut61UtLxwDVAB3BB6Jtw2pxKns2MGTOaXBLHWRvfP9fG76R2cqUySsTM2HnnnQFYtGhR7Gk9jM5rvE7r4vtni/ZBOMUhLtNmNP0wcdob3z+T8TMIJ1cmTZoUm2nT0dERm4FzxhlnNLO4TsHw/dPPIJwmkpRpk5SB4zgjie+f6SQ2EJI2TXuNZCGd9iUp0yYpA8dxRhLfP9NJO4O4DVgY/l0K3A88EN7fln/RnNFAUqZNUgaO44wkvn+mkzjM1cy2AZB0HnBFuJkNSQcAh45I6ZxRQVymTVoGjuOMJL5/JlPLfRBvN7NjKhNmdpWkb+RYJmeUEZdpM3fu3GYXy3EA3z/TGHIUk6RrgJuAn4ZZ04F3mtl+OZctMz6KqfUol8uxmTYrVqyIzcAZjePMndbF98/0UUy1nEEcQXQX9BWAATeGeW1D1tPF0bgTNIukTBvPuXFaAd8/0xmygTCz54FPS1rfzP4+AmVyHMdxWoAh74OQ9M+S7gbuCdO7SJqZe8lGkJkzZ67OYXFGHq9/p5Up8v5ZyyWm7wD7ERJVzexOSe/MtVQjiJkxa9YsAI477rjEDJYkhrp8NTjjZaeddhpeQUcpg+vfcVqJou+fNd1JbWZPDJo1Kh7O2ogMlrT14/xFw+vHaWV8/0ynllFMlwHfBr5P9OjPTwNTzezw/IuXjaRRTJMmTVorU2X27NmJGSzLli2reZvd3d2xmS1J/uXLl9f7NdsKrx+nlfH9s/4spk8AnyR6VvQAsGuYbhviMlXSMliykJTZkuQvGl4/Tivj+2c6QzYQZvasmU03s3Fm9kYz+5CZPTcShWsUcZkqaRksWUjKbEnyFw2vH6eV8f0zncROaknfI7rvIRYzOyGXEuVAXKZKJYPljjvuWD2vksGShaTMliR/0fD6cVoZ3z/TSTuDqAT1dQG7EQX1PUB0iWndocSSLpD0jKTYYT6SpktaJKks6Y+Sdqla9miYf4ek3G6NrmSw9PT00NPTQ2dnZ+ab6tLWj/MXDa8fp5Xx/TOdtLC+nwBIOg7Yy8xWhulziKI3huJCoo7tixKWPwK8y8z+GgIAzyXqBK+wj5k9W8N2hk0jMljSdpo4f9Hw+nFaGd8/06llFNN9wJ7hjmokbQLcambbDSmXJgK/MrPU7IrgXGxmPWH6UaKRUpkaiKRRTOVyea37G8wsMYNl8uTJNW+zv78/NrMlyV+0GA+vH6eV8f2z/iymrwH9kn4PCHgncHrjigfAx4CrqqYN+I0kA35oZucmfVDSscCxABMmTEhaJ3ZeIzJYktZP8hcNr5/m4jlk6fj+mU4tWUw/lnQVr1/+OcnM/tKoAkjah6iB2Ktq9l5mNiDpjcC1ku41sxsTyncu0eUppk6dOnoesO0UAj+AO61Mrb0urwJPEXVYv0XSW5IO2FmQtDNwPnBA9dBZMxsI/z4j6Qpgd6IU2bqo5KnMmDGjXlVT/O1OO9ZP9QG8lvLXcwD3/bO5eP2szZANhKSjie6eHg/cAbwduAV4dz0bljQB+DlwpJndXzV/fWAdM3spvN8XOLOebUH9mUvN9rc77V4/7b7/tHv9543XTzy13En9aeCfgMfMbB9gMvDCUB+SNIeoIdlO0hJJH5P0CUmfCKv0AZsBMwcNZx0H/EHSncCfgV+bWV3DBxqRudRMf7vT7vXT7vtPu9d/3nj9pGBmqS9gQfj3DmBMeH/XUJ9rxmvKlCkWR1dXl5VKJSPq/LZSqWRdXV3W29trfX19Vi6XrVwuW19fn/X29sY6kujt7c3kLxrtXj95l7/d/e2O148ZsNASjqm1nEEskfQG4BdEHca/BB5rSOs0QlhC5lJSBksW0jKd4vxFo93rJ+/yt7u/3fH6SaeWLKZ/M7MXzOx04EvAj4BDcy5XQ0nKXErKYMlCWqZTnL9otHv95F3+dve3O14/6aQ2EJI6JN1bmTazG8xsvpm1Vebtdtttt0aOSiVzKSmDJQuVzJZa/UWj3esn7/K3u7/d8fpJJ3UUk5mtknSfpAlm9vhIFarRVDJVxo0bB8DTTz+defx5M/15snjxYg4//HDuu+++Ncq//fbbM2fOnLXWH84wznauH2j//afd6z9v8qyfLH9frXiPSy33QWwC3CXpz8DfKzPN7ODcStVgGpG51Ex/3nj9pNPu9dPu9Z83Xv/J1JLF9K64+WZ2Qy4lqoOkLKb+/v7YzKWkDJYsz40ul8uJmU5x/lb7lZB3+b1+Rre/3Wml+m9W3debxXSgmZ00SPh1oOUaiCSyZC5lvUGmUZlOzSLv8nv9jG5/u+P1n04tw1zfFzPvgEYXxHEcx2kt0p4odxwwA3izpEVVizYEbs67YCOJZ+Ck4/WTTrvXT7vXf96MVP1X/m0lEvsgJG1M1EH9VeDkqkUvWXg2RKuR1AeRNiLBzNh5550BWLRoEZIyXQscarTDYH+W/o2RIO/ye/2Mbn/etHv9ZPEP1R+cF2l9EImXmMzsb2b2qJkdYWaPVb1asnEYDtaADJa09eP8rUbe5ff6Gd3+vGn3+snib0WGHMXUTiSdQUyaNInp06czbdo0AObNm8fs2bMZGBhg1apVq2+zL5VKdHR0sGzZspq32d3dTU9PT83+5ctb6x7DvMvv9TO6/XnT7vWTxd9WZxCjiaTMpaQMliykZTrF+VuNvMvv9TO6/XnT7vWTxd+K1NRASNpa0nvD+25J2RLtmkxS5lJSBksW0jKd4vytRt7l9/oZ3f68aff6yeJvRYZsICQdA1wG/DDMGk+U7No2JGUuJWWwZCEt0ynO32rkXX6vn9Htz5t2r58s/laklhvlPkn0yM8/AZjZA+FZ0W1PIzJY0taP87caeZff62d0+3faaafYzC4gNoMo6yWVdq+fLP5WpJYG4lUzW165w1hSJ9GDNYZE0gXAQcAzZrbW2FFF0rOBA4FXgKPM7Paw7CPAqWHVs8zsJ7VsMwuNyEjp7Eyuwjh/q5F3+b1+3O/+2vytSC1ZTN8gesToh4FPEd08d7eZfXFIufRO4GXgooQG4sDgPBDYAzjbzPaQtCmwEJhK1BjdBkwxs7+mbS9pFFO5XI7NXErKSJk8efJQX201/f39iZlOcf5Wy7rJu/xeP+53f23+VsxiqqWT+mRgKVAGPg5cyeu/7FMxsxuBtPsmDiFqPMzMbgXeIGkLYD/gWjN7PjQK1wL717LNOOLylRqVkVIqlTL5W428y+/14373t+/+P+QlJjN7DTgvvBpND/BE1fSSMC9p/lpIOhY4FmDChAk5FNFxHKeY1DKK6SBJ/ZKel/SipJckvTgShasFMzvXzKaa2dSxY8emrjtz5sxc807y9ueN10867V4/7h/d/jyo5RLTd4GPAJuZ2UZmtqGZbdSg7Q8AW1VNjw/zkuYPGzNj1qxZzJo1K5cOobz9eeP1k06714/7R7c/L2ppIJ4AFls+32o+8GFFvB34m5k9BVwD7CtpE0mbAPuGecOiEZlLzfTnjddPOu1eP+4f3f5cMbPUF/BPwNXAKcBnK6+hPhc+Owd4ClhB1I/wMeATwCfCcgE/AB4i6gSfWvXZjwIPhtd/1rK9KVOmWBxdXV1WKpWMaESUlUol6+rqst7eXuvr67NyuWzlctn6+vqst7c31pFEb29vJn+rkXf53e9+99fmbxbAQks4ptZyH8SXiYaqdgHrZmh7MLMjhlhuRDfixS27ALggy/ZStrNWpso666wTm5Eyf/78TO6kzJYkf6uRd/nd73731+ZvRWq5xLSlmb3fzE4zszMqr9xL1kCSMpeSMlKykJbpFOdvNfIuv/vd7/7a/K1ILQ3ElZL2zb0kOZKUuZSUkZKFtEynrK44Fi9ezOGHH46kNV5HHHEEixcvXuuVlbzL7373uz8/f97UconpOOBzkl4l6ksQ0dWhRo1kyp1GZC653/3ud38r+vOklhvl2iraO45GZC653/3ud38r+vOkliymd8bNtyhGo6VIymLq7++PzVxKykjJ8tzZcrmcmOkU58+at+J+97u/GP5WzGKq5RLT56vedxFFf98GvLsBZRsRsmQuxeWmpNGoTCf3u9/97m81arnE9K/V05K2Irq72nEcxxnFDOeZ1EuAbM/lbHHaPYPF/e53v/vzoJY+iO/x+gOC1gF2BR41sw/lW7TsJPVBpI0YMDN23nlnABYtWoSkTNcChxqNMNifpX/D/e53f3H8Qx2L86Le50EsJOpzuA24BTipFRuH4WANyEhJWz/OP5wyut/97h/9/lZkyDOIdiLpDGLSpElMnz6dadOmATBv3jxmz57NwMAAq1atWn0bfKlUoqOjg2XLltW8ze7ubnp6emr2L1++PNN3cr/73V8Mf1udQUgqS1oU8ypLWpRfcRtPXKZKUkbKcM4gsviz4n73u78Y/lYk7RLTQcC/xrwq89uGpMylpIyULKRlOsX5s+J+97u/GP5WJLGBMLPHKi/gH8BO4bUszGsbkjKXkjJSspCW6RTnz4r73e/+YvhbkSHvg5D078A3geuJcpi+J+nzZnZZzmXLnUZkpKStH+cfThnd7373j35/K1LLndRfBP7JzJ4BkDQW+C3Q9g1EIzJSOjuTqzDOP5wyut/97h/9/laklvsgyma2U9X0OsCd1fNSPrs/cDbQAZxvZl8btPw7wD5hcj3gjWb2hrBsFdFT5gAeN7ODh9pe0iimcrkcm7mUlJEyefLkoTa1mv7+/sRMpzh/1rwV97vf/cXwt2sW09WSriF6fCjAfwBX1rDRDqLHib6P6O7rBZLmm9ndlXXM7DNV638KqD4yLzOzXWso35DE5Ss1KiMlLdOpEXkr7ne/+93fLGrJYvq8pPcDe4VZ55rZFTW4dwceNLOHASTNBQ4B7k5Y/wjgtBq8juM4zghQSyf1Z4FLzOznGd09wBNV00uAPRK2sTWwDVB9q2KXpIXASuBrZvaLjNtfi0reyYwZM+pVud/97nd/S/nzoJY+iNOAfweeBy4B5pnZkN35kg4D9jezo8P0kcAeZnZ8zLonAePN7FNV83rMbEDSm4kajveY2UMxnz0WOBZgwoQJUx57bO0RuIsXL47NXEpiOFlMtfqzXmd0v/vdXwx/K/ZBDJnFZGZnmNmOwCeBLYAbJP22hu0OAFtVTY8P8+I4nNf7OCrbHQj/Pkw0xDa259jMzjWzqWY2dezYsUnfoe7MpTTc7373u79Z/lwxs5pewJuATwE3A4tqWL8TeJjo0tG6wJ3AjjHrbQ88SjibCfM2AcaE95sDDwBvHWqbU6ZMsTi6urqsVCoZUSqtlUol6+rqst7eXuvr67NyuWzlctn6+vqst7c31pFEb29vJn9W3O9+9xfD3yyAhZZwTB3yDELSDEnXA78DNgOOMbOda2h4VgLHA9cA9wCXmtldks6UVD1k9XBgbihohR2AhZLuBH5P1AeR1Lk9JBaTqWIpGSlZSMt0ivNnxf3ud38x/K1ILXHfWwEnmtmOZnZ6lgO1mV1pZm8xs14z+3KY12dm86vWOd3MTh70uT+a2U5mtkv490e1bjOOpMylpIyULKRlOsX5s+J+97u/GP5WpJY+iFPM7I4RKEtuJGUuJWWkZCEt0ymry/3ud7/7W4labpRrexqRueR+97vf/a3oz5NCNBCNyFxyv/vd7/5W9OdJIZ4o19/fH5u5lJSRkuW5s+VyOTHTKc6fdayz+93v/mL4W/E+iEKcQWTJXEq7gS5p/UZkOrnf/e53f6tRyygmx3Ecp4B4A0GUkVLJSXG/+93v/tHkr4dC9EGkjRiwmIyU4WQx1erP0r/hfve7vzj+Zh2L68piGs1YAzJS0taP8w+njO53v/tHv78VKcQZxKRJk5g+fTrTpk0DYN68ecyePZuBgQFWrVq1+jb4UqlER0cHy5Ytq3mb3d3d9PT01Oxfvnx5pu/kfve7vxh+P4NoEkmZS0kZKVlIy3SK82fF/e53fzH8rUghGoikzKWkjJQspGU6xfmz4n73u78Y/lakEA1EUuZSUkZKFtIyneL8WXG/+91fDH8rUogb5ZJoREZK2vpx/uGU0f3ud//o97cihW4gGpGR0tmZXIVx/uGU0f3ud//o97cihRjFVC6XYzOXkjJSJk+OfbppLP39/YmZTnH+rHkr7ne/+4vh9yymJhGXr9SojJS0TKdG5K243/3ud3+zyLWTWtL+ku6T9KCkk2OWHyVpqaQ7wuvoqmUfkfRAeH0kz3I6juM4a5PbGYSkDuAHwPuAJcACSfNt7UeWXmJmxw/67KbAacBUogd93xY++9d6ylTJO5kxY0Y9Gve73/3ubzl/HuTWByFpT+B0M9svTJ8CYGZfrVrnKGBqTANxBLC3mX08TP8QuN7M5qRtMy2LKS5zKYnhZDHV6s96ndH97nd/Mfyt2AeR5yWmHuCJquklYd5gPiBpkaTLJG2V8bNIOlbSQkkLly5dGluQRmQupeF+97vf/c3y54qZ5fICDgPOr5o+Evj+oHU2A8aE9x8HrgvvPwecWrXel4DPDbXNKVOmWBxdXV1WKpWM6HKVlUol6+rqst7eXuvr67NyuWzlctn6+vqst7c31pFEb29vJn9W3O9+9xfD3yyAhZZwTM3zDGIA2KpqenyYtxoze87MXg2T5wNTav1sFiwmU8VSMlKykJbpFOfPivvd7/5i+FuRPBuIBcC2kraRtC5wODC/egVJW1RNHgzcE95fA+wraRNJmwD7hnnDIilzKSkjJQtpmU5x/qy43/3uL4a/FcmtgTCzlcDxRAf2e4BLzewuSWdKOjisdoKkuyTdCZwAHBU++zzw30SNzALgzDBvWCRlLiVlpGQhLdMpq8v97ne/+1uJXG+UM7MrgSsHzeuren8KcErCZy8ALmhEORqRueR+97vf/a3oz5NC3EndiMwl97vf/e5vRX+eFCKLqb+/PzZzKSkjJctzZ8vlcmKmU5w/61hn97vf/cXwt+J9EIU4g8iSuZR2A13S+o3IdHK/+93v/lajEA8MchzHcbLjDQRRRkolJ8X97ne/+0eTvx4K0QeRNmLAYjJShpPFVKs/S/+G+93v/uL4m3UsblYWU8tjDchISVs/zj+cMrrf/e4f/f5WpBBnEJMmTWL69OlMmzYNgHnz5jF79mwGBgZYtWrV6tvgS6USHR0dLFu2rOZtdnd309PTU7N/+fLlmb6T+93v/mL4/QyiSSRlLiVlpGQhLdMpzp8V97vf/cXwtyKFaCCSMpeSMlKykJbpFOfPivvd7/5i+FuRQjQQSZlLSRkpWUjLdIrzZ8X97nd/MfytSCFulEuiERkpaevH+YdTRve73/2j39+KFLqBaERGSmdnchXG+YdTRve73/2j39+KFGIUU7lcjs1cSspImTx5cs3b7O/vT8x0ivNnzVtxv/vdXwy/ZzE1ibh8pUZlpKRlOjUib8X97ne/+5tFITqpHcdxnOzk2kBI2l/SfZIelHRyzPLPSrpb0iJJv5O0ddWyVZLuCK/5gz87HNo9U8X97ne/+0eS3PogJHUA9wPvA5YQPTr0CDO7u2qdfYA/mdkrko4D9jaz/wjLXjazDbJsMy2LKS5zKYnhZDHV6s96ndH97nd/Mfyt2AeR5xnE7sCDZvawmS0H5gKHVK9gZr83s1fC5K3A+DwK0ojMJfe73/3ub0V/rphZLi/gMOD8qukjge+nrP994NSq6ZXAQqKG49BatjllyhSLo6ury0qlkgEGWKlUsq6uLuvt7bW+vj4rl8tWLpetr6/Pent7Yx1J9Pb2ZvJnxf3ud38x/M0CWGgJx9SW6KSW9CFgKvDNqtlbW3Ta80Hgu5J6Ez57rKSFkhYuXbo01m8xmSqWkpGShbRMpzh/VtzvfvcXw5+VBQsWMHnyZLq6upC0xqurq4vddtuNBQsWsHjx4sw3AFfIs4EYALaqmh4f5q2BpPcCXwQONrNXK/PNbCD8+zBwPRB7c4KZnWtmU81s6tixY2MLkpS5lJSRkoW0TKc4f1bc7373F8OflaEy5er1Q74NxAJgW0nbSFoXOBxYYzSSpMnAD4kah2eq5m8iaUx4vznwDuBuhklS5lJSRkoW0jKdsrrc7373u7+V/LndKGdmKyUdD1wDdAAXmNldks4kuuY1n+iS0gbAvNCr/7iZHQzsAPxQ0mtEjdjXrGr0U1Yakbnkfve73/1F8+d6J7WZXQlcOWheX9X79yZ87o9Atmf7pdCIzCX3u9/97i+avxBZTP39/bGZS0kZKVmeO1sulxMzneL8Wcc6u9/97i+Gfzj3WJglZ8rV6i98FlOWzKW0G+iS1m9EppP73e9+97eavyWGuTqO4zithzcQtH8Gi/vd73735+EvRB9EWo++xWSkDCeLqVZ/lv4N97vf/cXxZz0Wxz3nZjj+ZmUxtTzWgIyUtPXj/MMpo/vd7/7R78/KUMerev1QkDOISZMmMX36dKZNmwbAvHnzmD17NgMDA6xatWr1bfClUomOjg6WLVtW8za7u7vp6emp2b98+fJM38n97nd/MfxZj8XrrrsuHR0ddfsLfwaRlLmUlJGShbRMpzh/VtzvfvcXw5+VoTLl6vVDQRqIpMylpAyTLKRlOsX5s+J+97u/GP6sDJUpV68fCtJAJGUuJWWYZCEt0ynOnxX3u9/9xfBnZahMuXr9UJAb5ZJoRIZJ2vpx/uGU0f3ud//o92els7MzVz8UvIFoRIZJZ2dyFcb5h1NG97vf/aPfn5Wzzjor9XhVrx8KMoopbrxwWobJ5Mmxj56Ipb+/PzHTKc6fNW/F/e53fzH8w8liSsuUq9Vf+CymuJtJGpVhkpbp1Ig8FPe73/3ub5a/EJ3UjuM4TnYK1UC0cuaJ+93vfve3mr8QfRCV3PTBmUtJDCeLqVb/cK4zut/97h/9/uG66/U37U5qSftLuk/Sg5JOjlk+RtIlYfmfJE2sWnZKmH+fpP3qKUcjMpfc7373u79wfjPL5UX0HOqHgDcD6wJ3Am8dtM4M4Jzw/nDgkvD+rWH9McA2wdMx1DanTJlicXR1dVmpVDLAACuVStbV1WW9vb3W19dn5XLZyuWy9fX1WW9vb6wjid7e3kz+rLjf/e4vhj8rleNVvX5goSUcU/M8g9gdeNDMHjaz5cBc4JBB6xwC/CS8vwx4j6Jzo0OAuWb2qpk9AjwYfMPCYjJVLCXDJAtpmU5x/qy43/3uL4Y/K0NlytXrhxz7ICQdBuxvZkeH6SOBPczs+Kp1Fod1loTph4A9gNOBW83sp2H+j4CrzOyymO0cCxwbJrcD7stQzM2BZzN+tVZwu9/97nd/o9xbm9nYuAVtfx+EmZ0LnDucz0paaAmdM/WSp9v97ne/+0fCneclpgFgq6rp8WFe7DqSOoGNgedq/KzjOI6TI3k2EAuAbSVtI2ldok7o+YPWmQ98JLw/DLgudJrMBw4Po5y2AbYF/pxjWR3HcZxB5HaJycxWSjoeuIZoRNMFZnaXpDOJes3nAz8CLpb0IPA8USNCWO9S4G5gJfBJM6svtzaeYV2aagG3+93vfvfn7h5VN8o5juM4jaNQURuO4zhO7XgD4TiO48TiDYTjOI4TSyEaCEmdkj4u6WpJi8LrKkmfkFR/aHryduvuLJLUEcr+35LeMWjZqQ3wryfpvyR9XlKXpKMkzZf0DUkb1OtP2Ob9DXTtXPW+JOnUUP6vSFqvAf7jJW0e3k+SdKOkF0J22E4N8P9c0odyrOs3S7pA0lmSNpB0nqTFkuZVZ5/V4V9H0kcl/VrSnZJulzRX0t51Fz7ybyzpa5LulfS8pOck3RPmvaER20jZ9lUNcGwk6auSLpb0wUHL6opeHYnjWiE6qSXNAV4givVYEmaPJxpiu6mZ/Ucd7k2TFgF3mtn44bqD/3xgPaJhvkcCN5jZZ8Oy281stzr9lwJPAN1Ed6LfA1wCHAy8ycyOrNP/ElFGDER1AtH3eQUwM9uoTv/qOpD0LWAz4MfAocBmZvbhOv13mdmO4f2vgfPN7IpwAPyymb0j7fM1+AeAW4B3A78F5gC/DvE0dSPpxuDcGPgQUd1cCuwLTDezd9fp/zHwGFHZDwNeBG4CTgJ+aWbfq9N/DXAd8BMz+0uY9yaiv933mNm+dfqT/n4E/MrMtqjTfznwAHAr8FFgBfBBM3u13r/fPI9rq0kKaRpNL+D+4Syr0b0KeBh4pOpVmV7egLIvqnrfSTSE7edEQYb9DfDfEf4V8Bde/9Gg6m3X4f9f4CJgXNW8Rxr4f9tf9f4OoNTg8t9X9X5B0v9NveUHNiL6AXAlsJToQL5vg+vn8aRldfgXDZq+Nfw7BrinkfWfZVkG/yqiBuj3Ma9lDfDfMWj6i8DNRD9kbq/TndtxrfJq+6iNGnle0jTgcjN7DaJTY2Aa8Nc63Q8T/ZJ5fPACSU/U6YYoCReI7i0BjpXUR7RTN+yyhJmZpCst7F1huu7TSzM7QdIUYI6kXwDf5/UzikawsaR/I7pcOsbMVoTtNqT8wGWSLgTOBK6QdCJwBdEv/rX+z4dBpb5fBC4mui9oM6J982TgN3X6X5P0FqIziPUkTTWzhZImEd2fVC8rJPWa2UPh1/hyAIt+ITei/h+T9F9EZxBPA0gaBxxFdOZbL/cAHzezBwYvaNDf7xhJ61SOO2b25XDWeCP1//3meVyLaEQr0+ovYCLRZZOlwP3htTTM26ZO9yeBXRKWfaoBZf8pUaDh4PlHAysa4D8f2CBmfi/whwb+H6wDnEB0+eHJBnp/POg1Lsx/E/C7Bm3jKOBPRAFoLxHdwPkVYOMGuG9sVF0k+N9DFGB5D7AXcDlROvIzwCEN8FcaygeIzpr3CPPHAt9ogH8T4OvAvUQ30z4fvsvXiS6j1Os/DNguYdmhDfB/A3hvzPz9gQfqdA8+rj3QqONa5VWIPohqwq8zzOy5Zpel1ZEka/AOImkLYLKZXdlIr1M7odP9r9agdAJJIurvyTP91Ekhr+NaIUYxVWNmz5nZc5IuymsbebpH0t/oxiE4nyJEquTFaKn/HPl2oxoHiPaT6sYh57+tvSR9VlJdndOjxS9pe0knAacBp0k6SdL2jXDDKIj7rgVJg0MCBexTGSZnZge3otv97ne//mxmu4f3xxBd0r2C6GC4m5l9raj+0DAcQfQwtkqY6XhgrqS59ZYdCtJAEFXa3UTX241oJ54KfKvF3e53f9H91eP5jwXeZ2ZLJf0P0dDReg+C7ez/GLCjhYEZFSR9G7irTndEIzoyWv1FdCntM8C1wK5h3sOt7na/+93PnUQd1Zsx6NnJNGaYbtv6iTrut46ZvzUNGAJsVrBOaknjge8ATwMHm9mEdnC73/1F9Ut6FHiN6MzEgHeY2VOK7jz/g5ntWlS/pP2Jho0/wOtDficAk4DjzezqOooOFOcSEwAWPft6mqT/Q3THZ1u43e/+ovrNbGLCoteAfyuy38yuDve47A70hNkDRDd0NmaEWpHOIBzHcZzaKdwwV8dxHKc2vIFwHMdxYilEAyHpREm7S2p4n0uebve73/3ub4a7QlE6qccD3wW2l1QmSlP8I/BHM3u+hd3ud7/73d8MN1CwTmpJ6xLdxPPPwJ7h9YKZvbWV3e53v/vd3wx3Uc4gKnQT5e5vHF5PAuU2cLvf/e53/4i7C3EGoejRnzsSRTX/iegW91vNrO7M9Dzd7ne/+93fDHeFQnRSE91dOIboiWkDRI/ne6EN3O53v/vd3ww3UJAzCFidWb8j0XW6fwbeRvTwkVvM7LRWdbvf/e53fzPcUKAGooKizJh3EFXmQUQPOnlDq7vd7373u3+k3YVoICSdwOst7ArCULDwKlt4nmurud3vfve7v1llh+KMYpoIzAM+Y9ETzdrF7X73u9/9zXADBTmDcBzHcbJTlFFMjuM4Tka8gXAcx3Fi8QbCcTIi6XpJU5u07dMlfa4Z23aKhzcQjlMQFOF/807N+M7ijGokfT4MB0TSdyRdF96/W9Ls8H5fSbdIul3SPEXPC0bSFEk3SLpN0jWSthjkXkfShZLOitnuo5LOCM6ypO3D/DXOACQtljQxvO4NvvslzZb0Xkk3S3pA0u5V+l1CeR+QdMyg77pA0iJJZ4R5EyXdJ+kiYDGwVYOq1ikA3kA4o52bgH8J76cCG0gqhXk3StocOBV4r5ntBiwEPhvW+R5wmJlNAS4Avlzl7QRmAw+Y2akJ2342OGcBtVwWmgR8C9g+vD4I7BU++4Wq9XYG3k2U2tknaUtJ+wLbEj2feFdgiqR3hvW3BWaa2Y5m9lgN5XAcoDj3QTjF5Taig+VGwKvA7UQNxb8AJwBvB94K3BylFrAucAuwHVFswbVhfgdQPdb8h8ClZlbdaAzm51VleH8NZX3EzMoAku4Cfmdmpijrf2LVer80s2XAMkm/J2oU9gL2BfrDOhsQNQyPA4+Z2a01bN9x1sAbCGdUY2YrJD0CHEV0h+kiYB+iX+v3AL3AtWZ2RPXnJO0E3GVmeyao/wjsI+lbZvaPhHVeDf+u4vW/tZWseebeFbM+wGtV06+x5t/q4JuXDBDwVTP74aDvMRH4e0L5HCcVv8TkFIGbiC7T3BjefwLot+gu0VuBd0iaBCBpfUlvAe4DxkraM8wvSdqxyvkj4ErgUmV75OOjwG7BuRuwzTC+zyGSuiRtBuwNLACuAT5a1X/SI+mNw3A7zmq8gXCKwE3AFkQJl08D/wjzMLOlRGcXcyQtIrq8tL2ZLQcOA74u6U7gDqLMm9WY2beJLulcnGF00OXApuES0vHA/cP4PouA3xM1bv9tZk+a2W+AnwG3hEtSlwEbDsPtOKvxqA3HcRwnFj+DcBzHcWLxBsJxHMeJxRsIx3EcJxZvIBzHcZxYvIFwHMdxYvEGwnEcx4nFGwjHcRwnFm8gHMdxnFj+P5jFI/V3l3DTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "weekly_volume_traded = fb.loc['2018-Q4'].groupby(pd.Grouper(freq='W')).volume.sum()\n",
    "weekly_volume_traded.index = weekly_volume_traded.index.strftime('W %W')\n",
    "ax = weekly_volume_traded.plot(\n",
    "    kind='bar', hatch='*', color='lightgray',\n",
    "    title='Volume traded per week in Q4 2018'\n",
    ")\n",
    "ax.set(xlabel='week number', ylabel='volume traded')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can combine textures to create new ones and repeat them to intensify the effect:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7bef143208d0>"
      ]
     },
     "execution_count": 31,
     "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": [
    "import calendar\n",
    "\n",
    "fb_q4 = fb.loc['2018-Q4']\n",
    "\n",
    "for texture, month in zip(['oo', '/\\\\/\\\\', '...'], [10, 11, 12]):\n",
    "    plt.fill_between(\n",
    "        fb_q4.index, fb_q4.high, fb_q4.low, hatch=texture, \n",
    "        where=fb_q4.index.month == month, facecolor='white',\n",
    "        label=f'{calendar.month_name[month]} differential'\n",
    "    )\n",
    "\n",
    "plt.plot(fb_q4.index, fb_q4.high, '--', label='daily high')\n",
    "plt.plot(fb_q4.index, fb_q4.low, '--', label='daily low')\n",
    "plt.xticks(['2018-10-01', '2018-11-01', '2018-12-01', '2019-01-01'])\n",
    "plt.xlabel('date')\n",
    "plt.ylabel('price ($)')\n",
    "plt.title('FB differential between high and low price Q4 2018')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<div style=\"overflow: hidden; margin-bottom: 10px;\">\n",
    "    <div style=\"float: left;\">\n",
    "         <a href=\"./2-formatting_plots.ipynb\">\n",
    "        <button>&#8592; Previous Notebook</button>\n",
    "    </a>\n",
    "    </div>\n",
    "    <div style=\"float: right;\">\n",
    "        <a href=\"../../solutions/ch_06/solutions.ipynb\">\n",
    "            <button>Solutions</button>\n",
    "        </a>\n",
    "        <a href=\"../ch_07/financial_analysis.ipynb\">\n",
    "            <button>Chapter 7 &#8594;</button>\n",
    "        </a>\n",
    "    </div>\n",
    "</div>\n",
    "<hr>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}