data visualization with matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x112bcada0>]"
      ]
     },
     "execution_count": 5,
     "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": [
    "plt.plot([1,2,3], [5,7,4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.show() # this one was to show the above plot when running the .py files in terminal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# titles and legends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'y')"
      ]
     },
     "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": [
    "x = [1, 2, 3]\n",
    "y1 = [5, 7, 4]\n",
    "y2 = [10, 14, 8]\n",
    "\n",
    "plt.plot(x, y1, label = 'line 1')\n",
    "plt.plot(x, y2, label = 'line 2')\n",
    "plt.title(\"Graph\\nsubtitle\")\n",
    "plt.legend()\n",
    "\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# bar charts and histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2, 4, 6, 8, 10]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = list(range(2,11, 2))\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 3, 5, 7, 9, 11]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = [1, 4, 5, 4, 3]\n",
    "x2 = list(range(1,12, 2))\n",
    "x2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "y2 = [3, 6, 7, 4, 4, 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x115c69828>"
      ]
     },
     "execution_count": 21,
     "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": [
    "plt.bar(x, y, label = \"bar chart 1\")\n",
    "plt.bar(x2, y2, label = \"bar chart 2\")\n",
    "\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.title(\"bar charts\\ncheck it out\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x115ce7cf8>"
      ]
     },
     "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": [
    "plt.bar(x, y, label = \"bar chart 1\", color = \"r\")\n",
    "plt.bar(x2, y2, label = \"bar chart 2\", color = \"c\")\n",
    "\n",
    "plt.xlabel(\"x\")\n",
    "plt.ylabel(\"y\")\n",
    "plt.title(\"bar charts\\ncheck it out\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "ages = range(20, 50)\n",
    "population_ages = np.random.choice(ages, 40)\n",
    "ids = [i for i in range(len(population_ages))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'bar charts for ages\\nwho is the oldest?')"
      ]
     },
     "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": [
    "plt.bar(population_ages, ids)\n",
    "\n",
    "plt.xlabel(\"ids\")\n",
    "plt.ylabel(\"ages\")\n",
    "plt.title(\"bar charts for ages\\nwho is the oldest?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that bar chart doesn't make sense. Histogram is better."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[20, 25, 30, 35, 40, 45, 50]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bins = list(range(20, 51, 5))\n",
    "bins"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([10.,  5.,  7.,  7.,  3.,  8.]),\n",
       " array([20, 25, 30, 35, 40, 45, 50]),\n",
       " <a list of 6 Patch objects>)"
      ]
     },
     "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": [
    "plt.hist(population_ages, bins, histtype = \"bar\", rwidth = 0.8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1178f4320>"
      ]
     },
     "execution_count": 13,
     "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": [
    "x = list(range(1,9))\n",
    "y = list(range(4, 12))\n",
    "\n",
    "plt.scatter(x, y, label = 'skitscat', color = 'k', marker = '*')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# stack plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "days = list(range(1,6))\n",
    "days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "sleeping = [7,8,6,11,7]\n",
    "eating = [2,3,4,3,2]\n",
    "working = [8,8,7,6,5]\n",
    "playing = [1,2,2,1,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.collections.PolyCollection at 0x117a20dd8>,\n",
       " <matplotlib.collections.PolyCollection at 0x117a2b0b8>,\n",
       " <matplotlib.collections.PolyCollection at 0x117a2b320>,\n",
       " <matplotlib.collections.PolyCollection at 0x117a2b588>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAD8CAYAAABw1c+bAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzt3Xd4VGXax/HvPZNJSCehJZQkoLSglBCqSAmuBV11saKroGBsa2/IrmtD17Kua11EQLCArm3XdbEtQbGAAgEEQQGlBUILmAIhpDzvHzPhjXFCQqacKffnunKRmTlznpsD+eXMOfd5jhhjUEopFT5sVheglFLKvzT4lVIqzGjwK6VUmNHgV0qpMKPBr5RSYUaDXymlwowGv1JKhRkNfqWUCjMa/EopFWYirC7AndatW5uMjAyry1BKqaCxfPnyvcaYNk1ZNiCDPyMjg2XLllldhlJKBQ0R2dLUZfVQj1JKhRkNfqWUCjMa/EopFWY0+JVSKsxo8CulVJjR4FdKqTCjwa+UUmFGg18ppcKMBn8Y+2n/T2z+ebPVZagQtXHfRnaW7bS6DOVGQF65q3ynvLKct9e9zYz8GSzasgiDoXPLzuR0zmF059HkdM6hXVw7q8tUQWhH6Q4W/LSAvM155G3KY2vxVqIjorl+wPVMHjaZVjGtrC5RuYgxxuoafiU7O9volA3etaJwBTPyZzB3zVx+PvTzUZfNbJN55JfAyIyRtGzR0k9VqmCyr3wfCzctZMGmBeRtyuOHoh8aXDY+Mp5bBt/CbUNvIyEqwY9Vhg8RWW6MyW7Sshr8oevnQz/z2revMXPFTFbsXNGsddjERlZqFjkZOYzuMpphacOIccR4uVIVDMoOl7FoyyLyNuWxYNMCVu1cheHY8iM5Opk7ht7BjYNu1P9HXqbBH8aMMXy25TNm5M/gnXXvUF5V7tX1R9ojGdRh0JFPBIM7DsZhd3h1DBUYKqoq+GrbV+RtyiNvcx7fbP+Gqpoqr6y7XWw77h52N9dkX0NURJRX1hnuNPjDUGFpIbNXzmbWylls3LfRb+PGOmIZljaMnM455HTOISs1C5toz0Awqq6pZtmOZUf26L/a9pXXdxzq65TQiXuG38MV/a4gwqanHD2hwR8mqmqqmL9hPjPyZzB/w3yqTbXVJZHUIokRGSOOfCLIbJNpdUmqAcYYVu9e7dyj35THZ1s+o6SixJJajk8+nvtG3Me4E8fpjkMzeTX4RaQT8DLQDjDAdGPMUyKSDLwBZACbgQuNMfvdvH888CfXw6nGmDmNFaXBf3Qb921kZv5M5qyaQ2FZodXlHFVKXIrz04DrHEFGywyrSwprG/dtPNJ58+nmT9l9YLfVJf1Crza9eGDUA4ztOdbqUoKOt4M/FUg1xuSLSDywHDgXmADsM8Y8IiKTgSRjzF313psMLAOycf7SWA70d/cLoi4N/l8rryznrbVvMXPFTD7b8pnV5TRbbeto7VdKXIrVJYW02hbLBZsWsHDzQrYWb7W6pCbpn9qfB0c9yBldz7C6lKDh00M9IvJv4FnX10hjTKHrl8Onxpju9ZYd51rmatfjF1zLzTvaGBr8/y+/MN/Zhrl6LsUVxVaX43WZbTKPfBrQ1lHPFR0sYuHmhUcO3xytxTIYDEsbxtRRUxmRMcLqUgKez4JfRDKARcAJwFZjTEvX8wLsr31cZ/nbgRbGmKmux/cA5caYvx5tnHAPfm+0YQajuq2jOZ1zODn9ZG35a0Rti2Xt4ZvmtFj6yoDETPbXHGBjaZPvCNigU7qcwkM5DzGww0AvVBaafBL8IhIHfAY8ZIx5R0R+rhv0IrLfGJNU7z1NDn4RyQVyAdLS0vpv2eL5f5ZgUrcN8+11b3Oo6pDVJVmutnW09qpibR39ZYvlgk0LWLpjqddaLL0huUUSl5oTmfTfQnp/sYGS1vGMn5LJv0q+9sr6z+5+Ng+OepDe7Xp7ZX2hxOvBLyIO4H3gI2PM31zP/YAe6vGYVW2YwSjGEcOwtGFHOobCoXW0uqaapTuWHjl08+W2LwNup0AQchL7MnFtC8a+tpyog4d/8boReGzKCP4Y+YVXOs8E4cJeF/LAqAfo1qqbx+sLFd4+uSvAHJwncm+u8/zjQFGdk7vJxpg76703GecJ3SzXU/k4T+7uO9qYoR78VTVV/Hf9f5m5YmbAtGEGo5YtWjIyY+SRQ0O92vayuiSP1bZY1h66WbRlkWUtlo3pEJPCFeXdufKtH+m8uqDR5fPG9mXcoAJ2l+/1yvh2sXN5n8u5d8S9pLdM98o6g5m3g38Y8DmwGqhxPT0F+Br4J5AGbMHZzrlPRLKBa4wxk1zvv9K1PDgPE73UWFGhGvwbijYwc4WzDVNnLfS+lLgURmWMOnJoqHNSZ6tLapINRRuOXB27cNNC9hzcY3VJDXLYHJwVl8WkpdWc9mY+9qqaxt9Ux/auKVxwXWsWF6/xWk2R9kgm9ZvEn4b/idT4VK+tN9joBVwBpLYNc8YK52yYyn8yWmYc6RgKpNbR7SXbj0xsFiwtlt3jOzNxbyfGz11L2y2e7bFXRkVw6/1DefaQd38eoiOiuW7AdUweNpnWMa29uu5goMEfAJbvWM7MFTNDtg0zGPVs3fMXs44mRSc1/iYvqNtiuWDTAtYXrffLuJ6KccRwQWQ/Jn1awrD/rvb6+udePZSr0lZysPKgV9cbHxnPzYNv5rYht5HYItGr6w5kGvwW+fnQz7z67avMXDGTlTtXWl2OOgqb2OiX0u/IYSFvto6WVpQemcUy0Fosm2JAYiYTtyQz7tVVJOwt9elYa4Yez9jzqthQutnr6w63mUA1+P3IGMOnmz9lxgrnbJiB1nGhmibSHsnADgN/MetopD2ySe+tbbGsPXwTaC2WTZHcIonfmxOZ6GrD9Cdvt3zWFy4zgWrw+8GO0h3ONswVs/hx/49Wl6O8rLZ1tPYcQd3W0botlrWzWAbjL/zaNsxJa1vwOzdtmP5kBB67ewR/jPJOy6c7nRI68afhf+LKfleG5EygGvw+UtuGOWPFDD7Y8EHQtmHaxEZWQndGHWhLiaOGBfatbCwLrwvmjlVt62hVTVVAt1g2RcfYVCYc6MaVbzetDdOfFv6uLxcP9l7LpzvHJR3HfSPv45ITLwmp60A0+L0sFNoweyUcT05Fe3LWHWLkR9/Tctcvg2tbj1TyRndhQWdDXs1PbD8YnH9P5d6RNsxvqpxtmNWB93Nfyxctn+5ktsnkgZHOmUCdlysFNw1+LyivLOfNtW8yc8XMoGzD7BzXidE1GeRsqCLnkw2023xse1Dr+2ewYHgn8jpVsvDweooOHfWaOxWgvNmG6U++avl0Jys1i6mjpgb9TKAa/B5YvmM5M/JnMG/NvKBqw0yNacco23HkbLExeuEmMtZs99q6jcCqk7uRNzSVBe0O8Hn5D5Qe9m23h2q+GEcMF0ZmMfHTYp+0YfqTr1o+3Tmp00lMzZnKyIyRPh/LFzT4j9H+8v28tvq1oGrDTIpqycio7uRsjyTni+1kfv2T38aucthZOronCwa0Ii+5mK/K1lFRXeG38ZV7AxIzmbSlFRe/utLnbZj+5MuWT3dO6XIKU0dNZVDHQX4Zz1s0+JvAGMPCzQuZuWJmULRhxjpiGRbTg9F74shZvIt+n/2ArSYw/u0OxUbx5Wk9yeuTSF5CEUtL1gXtie9gk9wiid/XOGfDPPFL/7Zh+lNJ63gmTMnkXR+1fLrz226/5cFRD9InpY/fxvSEBv9R7CjdwUsrXuKllS8FdBtmpD2SwXE9ydnfktHL9zHof+twVARHb3hJ63gWndqdvBNiWdCikNUlG4LqAqZAF0htmP722JQRTPFhy2d9gnBBrwt4YOQDdG/dvfE3WEiDv56qmireX/8+M/Jn8OHGDwNyb9QmNvon9CCnrA0535Yy7KN1xJSUW12WV+zp1IqFp3Ylr5uDvIhtfvvIHmoCuQ3Tn/zR8lmfXexc1ucy7h1xb8DeN1qD32V90Xpm5s/k5W9fDsg2zNoWy9HrDjHCTYtlqNrWI5W8nC7kdYEFNT9q6+hROGwOfhuXxcQgaMP0J3+1fNbnsDmYlOWcCbR9fHu/jt2YsA7+g5UHnbNh5s/g862fe7kyz3SJSyOnJo2cDdXNarEMVeuz0skbkcaCjpV8WrmBvYeKrC7Jcj3iuzBxbycun/tdULVh+lNlVAS33TeUZyr8324diDOBhm3w/7D3BwbNGBQwbZipMe3IsR1HzmYh59PNXm2xDFVHWkeHpJCXUs6i8u/DpnU01hHLBZF9mbSwhJPmB3cbpj/NvXoouWmrOFB5wO9jx0fGc9Ogm7h96O2WzwQatsG/dPtSBs6w7mbMtS2Wo7dHkfP5Nnp+s8myWkKFs3W0B3kDWrMguZjFB74P+A6sYzUgMZNJm5MZ98pK4veVWV1OUPJ3y2d9SS2SjswEGhsZa0kN3r4D1yzgLGC3MeYE13NvALWnuFsCPxtj+rp572agFKgGqppaVLAEf6wjlpNjepKzO4acJbsDqsUyVB2KjeKr03qyoE8ieQl7WVb6Q9DNhAnh04bpT1a0fNbXNrYtdw+7m2uzr/X7TKDeDv7hQBnwcm3w13v9CaDYGPOAm9c2A9nGmGM6SBmowV/bYjl6f0tygqzFMlQdaR3tFUNe9E6+DeDWUUEYndiPiWujwq4N058emzKcKVFfWtq91zGhI/cMv8evM4F6/VCPiGQA79cPfteN2LcCOcaYX+22BHvw28VOVkL3kGyxDFV7Oyaz8NRu5HV3sCBAWkc7xqZyxYFuXBHmbZj+ZEXLpzvHJR3HvSPu5dLel/p8JlB/Bv9w4G8NDSYim4D9gAFeMMZMP8oYuUAuQFpaWv8tW459mmBvBH+vhOMZXdGenLXljPj4h7BpsQxVBd1SyDvlOBZ0hjx+ouBAoV/GrW3DnPRNNaf9c7keArSAVS2f7mS2yeT+kfdzXs/zfDYTqD+D/x/ARmPMEw28r4MxZruItAU+AW4wxjTae+XPPf4ucZ3IqUln9IZqRmmLZcjbkJXOghFprllHvd862iO+CxP3dOTyecE1G2aosrLl052s1CweHPUgY7qO8fq6/RL8IhIBbAf6G2Ma/fwqIvcBZcaYvza2rC+Dv26L5ei8zaSv1RbLcGUEvh3Wlbyh7VmQcoBFzZx1VNswA5+VLZ/uDO00lKmjpjKq8yivrfNYgt+Tsw6nAN83FPoiEgvYjDGlru9PBX51AtjXkqJaMqp2FsvPC1wtlrv8XYYKQGKgz+cb6PP5Bm7B2Tq6LKcXCwa0Jq9VCV8dWHfU1tGBib2YuDnJ1Yb5pf8KV8fskhe+ovfQ4znvvCrWB8B5n6+2fUXOyzmM7jyah3Ie8vtMoE3p6pkHjARa40zMe40xM0VkNrDEGDOtzrLtgRnGmDEi0gV41/VSBDDXGPNQU4ryZI9/1JxRnBzTg5zdsYxespu+2mKpmulQbBRfndqTvL6uWUdLvycxMoHf15zARG3DDEolreO5Ykom71jY8unOWd3OYuqoqR7NBBq2F3BVrFyObfBgbbFUPlGaHEfkocPahhkCHp8ygrv9OMtnUwjChhs2cFzycc17/zEEf+jcaRiIqqzR0Fc+E7+vTEM/RNzx8Gd8svJE2kYHxjw7AAZDZU2lX8YKqeBXSqmmGvXuSla8aGdo4olWl+J3GvxKqbDVfuMuPp28jhujhltdil9p8Culwpqjooqn7l7E3B1DiHVYM8Gav2nwK6UUMG76Yr5+P4Vu8RlWl+JzGvxKKeXSa/GPLP1LEWMT/NtX728a/EopVUfC3lLevvVrHjs8ArvYrS7HJzT4lVLKjTse/oz/rTiBdtFtrC7F6zT4lVKqASP/tYr8F20h1/Kpwa+UUkcRii2fGvxKKdWIUGv51OBXSqkmqm357B7f2epSPKLBr5RSx6DX4h9Z+tCeoG751OBXSqljFL+vzNnyWTE8KFs+NfiVUqqZ7vjLoqBs+Ww0+EVklojsFpE1dZ67T0S2i8hK15fbG0iKyOki8oOIbBSRyd4sXCmlAkEwtnw2ZY9/NnC6m+efNMb0dX3Nr/+iiNiB54AzgExgnIhkelKsUkoFoiMtn5HB0fLZaPAbYxYB+5qx7oHARmPMT8aYw8DrwDnNWI9SSgU8R0UVT01ZxLztgd/y6ckx/j+IyLeuQ0FJbl7vAGyr87jA9ZxSSoWsi18M/JbP5gb/P4DjgL5AIfCEp4WISK6ILBORZXv27PF0dUopZZlAb/lsVvAbY3YZY6qNMTXAizgP69S3HehU53FH13MNrXO6MSbbGJPdpk1wnSFXSqn6als+H68IvFk+mxX8IpJa5+HvgDVuFlsKdBWRziISCVwMvNec8ZRSKljd/pfPWJAfWC2fTWnnnAcsBrqLSIGITAQeE5HVIvItMAq4xbVsexGZD2CMqQL+AHwErAP+aYz5zkd/D6WUClgj/u1s+TwpQFo+IxpbwBgzzs3TMxtYdgcwps7j+cCvWj2VUirctN+4i4WTi7j93uE8fXiRpbXolbtKKeUngdLyqcGvlFJ+dvGLi/nmP9a1fGrwK6WUBTKXOFs+z0sY7PexNfiVUsoi8fvKeOvWJX5v+dTgV0r5hImLoybJ3UX9qr7als/4Sv9Esga/UsqrTIsWLLvqKjLnzaP3nDkUnHWW1SUFhRH/XkWH4hq/jNVoO6dSSjWFcTj4btw4Lh87lhWJiUee73TbbTw6ejS3Pfoo9p07LaxQ1dI9fqWUR4zdzsYLL2TE669z4hVX/CL0a93Vty9dZs1i/UUXWVChqk+DXynVLEaErWefzZlz59L12mv5PDn5qMtvjY6m+zXXcOe0aVRmZPinSOWWBr9S6pjtPO00LnrlFdJvuYUP2rY9pvc+3r07qS+8QP7EiRibRpAVdKsrpZqsaPhwJs2eTerkybzZofm31yiKjKT/73/PpFmzONSzpxcrVE2hwa+UalTJoEHc/OKLtL7/fmamp3ttvbPS02n99NN8etNNGIfDa+tVR6ddPUqpBh3s04dHr7qKB3r18tkYByIiGHXuuZw7eDCv/PWvxC1f7rOxlJMGv1LqVw716MGzV13Fnf36YUT8Mua/UlJo+dhjvP2//3H2U08hBw/6ZdxwpMGvlDqisnNnZl59NX8YMIBqC068VttsnHvqqYzo3593nn6a5EXWTl8cqjT4lVJUdejA67m5TDrpJCrs1t8m8LNWrWh1//3M/vxzLn/iCaS42OqSQkpT7sA1S0R2i8iaOs89LiLfi8i3IvKuiLRs4L2bXXfqWikiy7xZuFLKczVt2/LulCkkv/QSlw0fHhChX9eEk0+m/5w5FJ5xhtWlhJSmfJabDZxe77lPgBOMMb2B9cDdR3n/KGNMX2NMdvNKVEp5W01SEh/dfjspL7/M2N/8htIA7qhZkZhI+zvv5Mm//pWaY7xmQLnXaPAbYxYB++o997HrnroAS4COPqhNKeVlJi6ORTfcQMZrr3H6mWeyJyrK6pKa7Nb+/en60kv8eMEFVpcS9Lxx9uZK4IMGXjPAxyKyXERyvTCWUqoZTIsWLMvNpcfrrzNi7Fi2RUdbXVKz/BQTw/HXXccfn3+eqrQ0q8sJWh4Fv4j8EagCXmtgkWHGmCzgDOB6ERl+lHXlisgyEVm2Z88eT8pSSrkYh4PV48fT//XXGTBuHOtjrbvPqzc93LMnHadPZ9WECX5rNw0lzQ5+EZkAnAVcaowx7pYxxmx3/bkbeBcY2ND6jDHTjTHZxpjsNm3aNLcspRTOGTM3XHghJ7/xBr0nTHA7Y2aw2xUVRd/x47luxgwqunWzupyg0qzgF5HTgTuBs40xbq+yEJFYEYmv/R44FVjjblmllHcYEbaecw5j5s6l27XX8mUY3AFrWpcutHn2Wb68/npMhHaoN0VT2jnnAYuB7iJSICITgWeBeOATV6vmNNey7UVkvuut7YAvRGQV8A3wX2PMhz75Wyil/n/GzJtv5sMw634pdTgYdv75XDR7Ngf79rW6nIAnDRylsVR2drZZtqwZbf9Ll8LABo8mKRWSikaM4M4rrmCWFydPC2aO6mr+9dFHnPHMM8ihQ1aXc2zWrYMePZr1VhFZ3tS2ef1cpFSQKhk0iD9PmsRTxx9vdSkBpdJu58wxYzhlwADe/PvfafnVV1aXFHA0+JUKMgf79uWRq67iwcxMq0sJaP9r04bkqVN5ddEixv3tb0hJidUlBQwNfqWCxKEePXgmN5e7+vbVFsYmMiJcOmIET/bty/vPPUe7Tz6xuqSAoMGvVICr7NKFGbm53GDRjJmhYFliIilTpvDMKadw3eOPY9u71+qSLKX/i5QKUFUdOvDyAw8QP3061w0apKHvBTcMHEjP2bPZ/LvfWV2KpfR/klIBpqZtW9754x9Jfuklxp98csDNmBns1sfG0vnGG3ngmWeo8uC+wcFMg1+pAFGTlMSHd9xByssvc94ppwT0jJmh4N4TTiBjxgy++/3vw+6ciQa/UhYz8fFHZsw8Y8yYoJoxM9htb9GCEyZO5Kbp0zkcRm2xGvxKWcRER7M0N5ce8+YF9YyZoeCZ44+n7fPPs+SaazBhcGhNu3rCUE1SEjsHD+ar/v2piIjg+J07ab9jB8nbthG9dSu2oiKrSwxpJjKS1ePGcfnYsaxKSLC6HJ85vTKejvttvNqulEOmxupyGlXscDDkoou4dOhQXnz8caJXr7a6JJ/R4A8DJiaGosGD+To7m9d79WJex45H7RDpcOgQQ4qKyNq7l567d9O5sJCU7dtJ3LaNqC1bkINu5+VTjTB2OxvOP58rLryQr5KTrS7HZ9raHdzxQQuy/1IKwFmZDt6ZGs+85BIqA3CKmPpe69SJt558kv/Mn88pzz2HVFRYXZLX6Vw9IchERlLSvz/5Awfy1oknMic9nQNenLWwV2kpg/fto8/u3XTftYu0wkLaFhQQv3UrEQUFSFVV4ysJI0aErWefzTWXXBLyk6eddyCBK64/QOyW6l+9tm9AJG/8uQVvx5Xw61cD0xm7d/P6k0+SsGSJfwb001w9GvwhwNhsHOzTh9WDBvFe795MP+44iiIjLanFUV3NwJISBu7dy4m7dtF11y467thBq4ICYrZuxb5zpyV1WaXw9NO54bLLeLt9e6tL8alOEZFMnhdJ5vNljS67e0QLXpscyX9alBB46fNrYgyvL1zIBU8+iZQ1/vfziAa/Bv/RHOrRgx+GDGF+nz5M69aNrUFyYjCpspKTiorov3cvvXbvpvPOnbTfvp2WBQVEb94cMvOpFI0cye0TJjA7xGfMFODyfYmMu7aUqN3Hdhx/+xkteOVWBx9FlPqmOC8bvH8/7z33HG0WLPDdIBr8Gvx1VWZk8NOQIXzcrx8v9OjBd/HxVpfkE10OHmRIURH99u6lx65dpBcW0q6ggMRt23Bs3Rrwx1tLBg/mnokTeToMWgO72Vtw1zQ7XeYe8Gg9Wy6IYdY1NhbZfLw37SXTlizhqscfx7Zvn/dXrsEf3sFfnZLC1qFD+bRfP2ZlZvJFCJ8MbCoxhqySEgYWFdF7zx66FxbSqbCQ1gUFxG3din3HDqTGmu6RA/368ZerruKhnj0tGd+fIkTI3ZbAudcW4/BiVm8cH8uMK+Br49kvEn/ILCvjwxdfpNN773l3xYEU/CIyC+f9dXcbY05wPZcMvAFkAJuBC40x+928dzzwJ9fDqcaYOY2NF47BX5OUxM4hQ/iif39eyczk/ZQUq0sKOrFVVQz6+WcG7tnDCbt3c9yuXbTfvp3kggJitmzxSZvqoZ49eTo3l7v69IEwuPqzjy2aOx6FDvPLfTbGd9fH8eKF1ayq8d0Y3vLwqlXc+eij2AsLvbPCAAv+4UAZ8HKd4H8M2GeMeUREJgNJxpi76r0vGVgGZAMGWA70d/cLoq5wCH4TG8veQYP4JjubeSecwOsdOugkXD6WWlHB0No21V276LxzJykFBbRsRptqZZcuvHj11dyYnR0W/24txMYN38dz2o3F2A/7fjwjsOKOeF48q5LvqwP7Llpp5eV8/MordJ83z/OVBVLwu1aaAbxfJ/h/AEYaYwpFJBX41BjTvd57xrmWudr1+AXXckfdQqEY/CYykuLsbFYMGMBbJ57ISxkZlIfBFYLBJLOsjMFFRfTZs4fuO3eSXlhI2+3bnW2q27YhVVVUdezI3NxccocODZvJ04YSy833VNHmC/+fX6mxw9J7EnhhdAWbqgL7/M6t69fzyCOP4Ni0qfkrCYJbL7YzxtR+vtmJ8+bq9XUAttV5XOB67ldEJBfIBUhLS/OgrMBwpMVy8GD+feKJvGhhi6VqmrVxcayNiwM3nTiO6moGFBezOj4+bCZPi7fZufWbOEbcWYxYdCrQVg2D7ish+2H48sFEpg8tZ3uVHz5yNMPfunVjzrRpfPjWW/SfOdOy801N4ZWreowxRsSz/xrGmOnAdHDu8XujLn871LMn3w8ezPy+fXmha9egabFUjau020P6atv6TqmO5/qbK2i5qtjqUgCwH4bhdxUzJA4+fTiRGX0Psru60uqyfqUoMpIBl1zChJNO4h+PPUaLtWutLsktT4J/l4ik1jnUs9vNMtuBkXUedwQ+9WDMgFKZkcGPQ4fySd++Id1iqcJHa3sEd3wSw8AHA/N6CkcZ/ObGYoYnC/97JJGZPQ6wvzrwrhSfnZ7OG08/zX//8x9G/uMfyOHA+pTiSfC/B4wHHnH9+W83y3wEPCwiSa7HpwJ3ezCmpapTU9k6ZAifZmUxMzOTL5OSGn+TUkHi3PIEJv7hIHE/BWbo1xW1z3BmbjE5qTY+eCSR2RlllNYE1kQQ5XY7Oeeey9mDB/PaE08Q15zzlj7SpOAXkXk499xbi0gBcC/OwP+niEwEtgAXupbNBq4xxkwyxuwTkQeBpa5VPWCM8cFVD76hLZYqHHSIiOSut6I48anAD/z6ogtrGDu+mNM6R/DvhxN5tX0p5QF2bP29lBRaPvooby1YwDl//3tATHKoF3DVcaTFcsAA5vbqxRvaYqlCmACX7k/g0mvLaLErsMKyuYozHbz7YAxzWwXmTKAn79vHv55+muTPPnO/QBB09QS9ui2Wb/buzez0dG3Yda5YAAARUUlEQVSxVGHhuIgoJr8YwfEvB99e/tEkrq1kwnnFnNM/ktfvbcHb8YE1E+jnycm0uu8+Zn3xBeOfeALbzz9bUkdYBb+x2TjQty+rBw7kvd69tcVShR07MKkwkfOuLcFRHNh98Z5IWn6Ya88+zHnDo5h7dxTvBdhMoFcOG8ZTvXsz/4UXaD9/vt/HD/ngP9SzJ98PGcJ/+/RhurZYqjB2gj2aO/8Knd4LjBZNf2i7qIKbF1Vw4enRvHJrBB86Amcm0FUJCXS44w4eHz2aWx57DPuuXX4bO7SCX4TKzp35ccgQbbFUyiVKhOs2JnDmH4qxB/bsBz7T/sNy7voQLj4/hpeutfFZAM0EekdWFv+YNYuP5szheD/N9xRSJ3eXl5SQnZ/vg4qUCk6DJJZb7q+m3cIwTfwGbLw8lplXwpIAmwn0+4ED6R4T06z3HsvJ3ZBqWQmNvgSlPBdrs/GnVYk8PPqAhr4bx798gL+MPMBzb8bRz9a8oPUFf+2Ih1TwK6UgpyaOl2+JYPTNxdgCqaUlAGU+X8YTIw7y5Px4etrD5/yfBr9SISLZHsHDnydwz+gykvMDa4qAQCZA38dLeXZUOY8uTKBLRJTVJfmcBr9SIeC3FfHMngRD/hxaffn+ZKuGgQ+UMH10BQ98nUjHiNBt9Q6trh6lwkyq3cFd/2pBn78FTptisLMfhpMnFzM4Dj57KJEZ/Q6yKwBnAvWEBr9SQWpccQKXXXeA6B0a+r7gKINTbirm5GRhwV8SmdEzMGcCbQ491KNUkOkcEcW0V2PJPbeE6B169tbXovYZxlxdzGsX1XDjlkTibcE/rYsGv1JBwgZM2pXItLMP031mYPWfh4Powhp+N6GYeROE3MJEooN4AsfgrVx5LMZmwz/XCSpP9bRHM+u5GC69uJjI/YF30WU4id1UxbhLinn9GjvjixKJ9NPVtt6kx/hDWIQIneyRpFU66FBio/1uod0WQ5sfqmi18jBxG6s4kG7nh4tiWDXIxpI2Fayv1ot9AkmkCNdsSuC31xcTYf007qqOhHWVTDi/mLOzInnz3mjeTCgOqJlAj6bZwS8i3YE36jzVBfizMebvdZYZifPOXLW3nX/HGPNAc8dUvyRAit1BWk0kHQ/YSd0rpBQY2q2vJnl1JYmrD2OvrAAanoUxdks1WY+VkgVcARSf4OD786PJz4Kvkg5REKA3tg4H/W0x3D7VkPJJ+EyqFoyS8w9z9TmHGTssirlTovh3dGDNBOpOs4PfGPMD0BdAROw476/7rptFPzfGnNXcccJdot1Ouomk06EIOuyzkVIIbX+spvXaKpLzK3AUVwLeazVLXFPJoDWVDAKuBfYOieK7c6PI7w2LYw+yJ0S6GgJZjM3GTd/Gc4peeRtU2nxRwU1jKrjw1GheuT2CDwJoJtD6vHWoZzTwozFmi5fWFzaiREi3RdHpcAQdi+2k7oK2m2tos66KVisOE11QDZRbVl/rxRWMWFzBCOBmgcJTo/nuzEiW96xhceRBSgLsPqfBboSJ44Y7DtPqG93LD1apH5dz58dw0dgYZl9v49MAmgm0lreC/2JgXgOvDRGRVcAO4HZjzHdeGjMo2HDe0zStykGHUjvt9wopW13H2VdVkrCuEjHBcVxdDLT/qJz2H5XzG6DaAQVnx7DmNAffHFfN0oiDAXe/02DR0m7nti9iGTZFr7wNFenvHOTed+DSy1wzgRI4nVgeT8ssIpE4Q72XMWZXvdcSgBpjTJmIjAGeMsZ0bWA9uUAuQFpaWv8tW479w8PSkhIGWjAtc2t7BOkmko4HI2hfJKRsh7Ybq2m15jDJKw6HzRzolXGw5bxYVuVEsDS9iuUcpCoAp/0ONGMOx3P1zYdIWBdaV4eqX1p7TRwzxtWwoqbhs/TrBgygR2xss9Z/LNMyeyP4zwGuN8ac2oRlNwPZxpi9R1uuufPx+yr4Y2020iWKToci6Piz6zj7phrauI6zR+3VvVx3Klrb2HhRDN8Os7Ok/WFW15QH/Ekvf2pnd3Dn+y3IeixwjwUr71t1WzwvnFPFuupfH8L1V/B741DPOBo4zCMiKcAuY4wRkYE4j3wUeWFMr3K42h47HXbQsdR5nL3dlhrafF/tbHv8qQorj7MHq6i9NfR6roxezzn/kxxIt7P+ohhWDrKxuE0FG8K4dfTCsgTGX3+AmK0a+uGmzxOlPPt3WDYlgemnVvBjlf/vfexR8ItILPAb4Oo6z10DYIyZBpwPXCsitcl5sbHgll+1bY/pNZF0KLM7D8dsM7TdUE3yt5Ukrmm87VF5LnZLNf0eK6Ufv24dXZx0iG1h0DqaFhHJ5Fcj6fmCHssPZ7ZqGPhgCf0fhcX3J/LCsHK/tk6H1K0X1+wpYXL+Bjrst5GyA9r9WE3r76pIyq/AURp4f0/1S3uGRLLunGjy+xi+CrHWURswfm8iF11bqocG1a9UxsGiBxOZOL47GUm+v/ViSAV/ydIS8gfqPXdDgRHY+Zto1pwVyfIeNSxpcZDi6uBsHe1ub8Fdz9vo/LpeequObsC6AcT2CI5j/Ep5nRhnP3Tqx/VaR091sPT4ar4JgtZRhwi5WxI45/piHIHXyq3CmAa/Cgr2Skh/+yDpb8OZOD8abz4vltU5EXwTgK2j/Wwx3PZIDR0+0AuxVODR4FdByVEGXeccoOscGIuzdfTHC2NZebKdb1yto1Z8Hoi22bjxu3h+c1Mxdm3LVwFKg1+FhKi9NWQ+X0bm83AJcDDNNevoYGfrqD9mHT2JWG6eXEXrxbqXrwKbBr8KSTFbq+n3uLN1dAJQnOng+wuiye/v/dbRBJudW5fEMnxyCRI4R5uUapAGvwoLiWsrGXR/nVlHB0ey9txo8nsbFseVs7uZN9M+tSqe6245ROIa7ctXwUODX4Wl1ksOM3zJYYYDNwnsPCWa785yzTrahNbRNvYI7vgohgEPaeCr4KPBr8KeGEj9pJzUT8o5BVfr6G9j+O40B9+4aR0dezCBK/9wkNhNGvoqOGnwK1WPvdI5pW76OzCGX7aOdltWzQnPaOCr4KbBr1Qj6raOKhUKbFYXoJRSyr80+JVSKsxo8CulVJjR4FdKqTCjwa+UUmHG4+AXkc0islpEVorIrybRF6enRWSjiHwrIlmejqmUUqr5vNXOOeooN1A/A+jq+hoE/MP1p1JKKQv441DPOcDLxmkJ0FJEUv0wrlJKKTe8EfwG+FhElotIrpvXOwDb6jwucD33CyKSKyLLRGTZnj17vFCWUkopd7wR/MOMMVk4D+lcLyLDm7MSY8x0Y0y2MSa7TZs2XihLKaWUOx4HvzFmu+vP3cC7wMB6i2wHOtV53NH1nFJKKQt4FPwiEisi8bXfA6cCa+ot9h5wuau7ZzBQbIwp9GRcpZRSzedpV0874F0RqV3XXGPMhyJyDYAxZhowH+ckhxuBg8AVHo6plFLKAx4FvzHmJ6CPm+en1fneANd7Mo5SSinv0St3lVIqzGjwK6VUmNHgV0qpMKPBr5RSYUaDXymlwowGv1JKhRkNfqWUCjMa/EopFWY0+JVSKsxo8CulVJjR4FdKqTCjwa+UUmFGg18ppcKMBr9SSoUZDX6llAozzQ5+EekkIgtFZK2IfCciN7lZZqSIFIvIStfXnz0rVymllKc8uRFLFXCbMSbfdfvF5SLyiTFmbb3lPjfGnOXBOEoppbyo2Xv8xphCY0y+6/tSYB3QwVuFKaWU8g2vHOMXkQygH/C1m5eHiMgqEflARHp5YzyllFLN5+nN1hGROOBt4GZjTEm9l/OBdGNMmYiMAf4FdG1gPblALkBaWpqnZSmllGqAR3v8IuLAGfqvGWPeqf+6MabEGFPm+n4+4BCR1u7WZYyZbozJNsZkt2nTxpOylFJKHYUnXT0CzATWGWP+1sAyKa7lEJGBrvGKmjumUkopz3lyqOck4DJgtYisdD03BUgDMMZMA84HrhWRKqAcuNgYYzwYUymllIeaHfzGmC8AaWSZZ4FnmzuGUkop79Mrd5VSKsxo8CulVJjR4FdKqTCjwa+UUmFGg18ppcKMBr9SSoUZDX6llAozGvxKKRVmNPiVUirMaPArpVSY0eBXSqkwo8GvlFJhRoNfKaXCjAa/UkqFGQ1+pZQKMxr8SikVZjy95+7pIvKDiGwUkcluXo8SkTdcr38tIhmejKeUUspzntxz1w48B5wBZALjRCSz3mITgf3GmOOBJ4FHmzueUkop7/Bkj38gsNEY85Mx5jDwOnBOvWXOAea4vn8LGF1783WllFLW8ORm6x2AbXUeFwCDGlrGGFMlIsVAK2CvB+M2yB5rJy4rzherVkopn7O18M9pV0+C36tEJBfIdT0sE5Efmrmq1vjoF4uHtK5jo3UdG63r2ARmXZ09qiu9qQt6EvzbgU51Hnd0PedumQIRiQASgSJ3KzPGTAeme1APACKyzBiT7el6vE3rOjZa17HRuo5NuNflyeeKpUBXEeksIpHAxcB79ZZ5Dxjv+v58IM8YYzwYUymllIeavcfvOmb/B+AjwA7MMsZ8JyIPAMuMMe8BM4FXRGQjsA/nLwellFIW8ugYvzFmPjC/3nN/rvP9IeACT8ZoBo8PF/mI1nVstK5jo3Udm7CuS/TIi1JKhRedskEppcJMUAa/iMwSkd0isqaB10VEnnZNFfGtiGQFSF0jRaRYRFa6vv7sbjkf1NVJRBaKyFoR+U5EbnKzjN+3WRPr8vs2E5EWIvKNiKxy1XW/m2X8Ph1JE+uaICJ76myvSb6uq87YdhFZISLvu3nNsulbGqnLku0lIptFZLVrzGVuXvftz6MxJui+gOFAFrCmgdfHAB8AAgwGvg6QukYC71uwvVKBLNf38cB6INPqbdbEuvy+zVzbIM71vQP4Ghhcb5nrgGmu7y8G3giQuiYAz/r7/5hr7FuBue7+vazYXk2sy5LtBWwGWh/ldZ/+PAblHr8xZhHOLqGGnAO8bJyWAC1FJDUA6rKEMabQGJPv+r4UWIfzquq6/L7NmliX37m2QZnrocP1Vf9kmN+nI2liXZYQkY7AmcCMBhaxZPqWJtQVqHz68xiUwd8E7qaTsDxQXIa4Pqp/ICK9/D246yN2P5x7i3VZus2OUhdYsM1chwdWAruBT4wxDW4vY0wVUDsdidV1AZznOjzwloh0cvO6L/wduBOoaeB1S7ZXE+oCa7aXAT4WkeXinLWgPp/+PIZq8AeqfCDdGNMHeAb4lz8HF5E44G3gZmNMiT/HPppG6rJkmxljqo0xfXFekT5QRE7wx7iNaUJd/wEyjDG9gU/4/71snxGRs4Ddxpjlvh7rWDSxLr9vL5dhxpgsnLMbXy8iw/00LhC6wd+U6ST8zhhTUvtR3TivgXCISGt/jC0iDpzh+pox5h03i1iyzRqry8pt5hrzZ2AhcHq9l45sL2lkOhJ/1mWMKTLGVLgezgD6+6Gck4CzRWQzzll6c0Tk1XrLWLG9Gq3Lou2FMWa768/dwLs4Zzuuy6c/j6Ea/O8Bl7vOjA8Gio0xhVYXJSIptcc1RWQgzu3v87BwjTkTWGeM+VsDi/l9mzWlLiu2mYi0EZGWru+jgd8A39dbzO/TkTSlrnrHgc/Ged7Ep4wxdxtjOhpjMnCeuM0zxvy+3mJ+315NqcuK7SUisSISX/s9cCpQvxPQpz+PATM757EQkXk4uz1ai0gBcC/OE10YY6bhvJp4DLAROAhcESB1nQ9cKyJVQDlwsa//87ucBFwGrHYdHwaYAqTVqc2KbdaUuqzYZqnAHHHebMgG/NMY875YPx1JU+q6UUTOBqpcdU3wQ11uBcD2akpdVmyvdsC7rv2ZCGCuMeZDEbkG/PPzqFfuKqVUmAnVQz1KKaUaoMGvlFJhRoNfKaXCjAa/UkqFGQ1+pZQKMxr8SikVZjT4lVIqzGjwK6VUmPk/Awq26VJgAOUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.stackplot(days, sleeping, eating, working, playing, colors = ['m','c','r','g'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x117d15780>"
      ]
     },
     "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": [
    "plt.stackplot(days, sleeping, eating, working, playing, colors = ['m','c','r','g'])\n",
    "\n",
    "plt.plot([], [], color = 'm', label = 'sleeping')\n",
    "plt.plot([], [], color = 'c', label = 'eating')\n",
    "plt.plot([], [], color = 'r', label = 'working')\n",
    "plt.plot([], [], color = 'g', label = 'playing')\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# pie chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.patches.Wedge at 0x117d94f98>,\n",
       "  <matplotlib.patches.Wedge at 0x117d9e550>,\n",
       "  <matplotlib.patches.Wedge at 0x117d9ea20>,\n",
       "  <matplotlib.patches.Wedge at 0x117d9eef0>],\n",
       " [Text(0.6696375991452628, 0.8726886534216935, 'sleep'),\n",
       "  Text(-0.5499999479716445, 0.9526279742014657, 'eat'),\n",
       "  Text(-0.95262792270675, 0.5500000371631103, 'work'),\n",
       "  Text(-0.14357877740594213, -1.0905893519921306, 'play')])"
      ]
     },
     "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": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "slices = [7,2,2,13]\n",
    "activities = ['sleep', 'eat', 'work', 'play']\n",
    "cols = ['m','c','g','r']\n",
    "\n",
    "plt.pie(slices, labels = activities, colors = cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.patches.Wedge at 0x117f68ac8>,\n",
       "  <matplotlib.patches.Wedge at 0x117f71550>,\n",
       "  <matplotlib.patches.Wedge at 0x117f71ef0>,\n",
       "  <matplotlib.patches.Wedge at 0x117f7b8d0>],\n",
       " [Text(0.6696375991452628, 0.8726886534216935, 'sleep'),\n",
       "  Text(-0.5999999432417941, 1.03923051731069, 'eat'),\n",
       "  Text(-0.95262792270675, 0.5500000371631103, 'work'),\n",
       "  Text(-0.14357877740594213, -1.0905893519921306, 'play')],\n",
       " [Text(0.36525687226105236, 0.47601199277546913, '29.2%'),\n",
       "  Text(-0.3499999668910465, 0.606217801764569, '8.3%'),\n",
       "  Text(-0.5196152305673181, 0.30000002027078737, '8.3%'),\n",
       "  Text(-0.07831569676687751, -0.5948669192684347, '54.2%')])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(slices, \n",
    "        labels = activities, \n",
    "        colors = cols, \n",
    "        shadow = True, \n",
    "        explode = (0, 0.1, 0, 0),\n",
    "        autopct = '%1.1f%%')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# load data from files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}