Lecture 2 - Basic Plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.plot([1,2,3,4,5], [4,5,6,7,3])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = [1,2,3,4,5]\n",
    "y = [4,7,4,7,3]\n",
    "\n",
    "plt.plot(x, y)\n",
    "plt.xlabel('Plot Number')\n",
    "plt.ylabel('Random #')\n",
    "\n",
    "plt.title('Epic Graph tutorial for data viz in Python with Matplotlib.\\nTutorial showing labels and titles')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAElCAYAAADnZln1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzsnXd4FcX6xz9vegIJIRA6IYTQSSgiIh1sKNLtvftTuPar2CsC91rvFXsXFQtVESu9FwUSegu9BEIK6WV+f8zmGkLKSU5P5vM850nO2d2Z7+7Z8+7s7Mz3FaUUBoPBYKj5+LhbgMFgMBhcgwn4BoPBUEswAd9gMBhqCSbgGwwGQy3BBHyDwWCoJZiAbzAYDLUErw74IjJfRG52tw5bEJFPReQld+uoiKocTxFJEpELy1kWLCI/iEiaiHznWJX/q0OJSKwzyq6ijs0iMqiK21wvIr86SVJVdDwnItPcraMYEekvItsrWB5tfe9+rtRVVew5rqX3seRvUkRuEZFl9mhze8C3Ake2iJwu8XrLlm2VUpcqpT6rRp0iIuNFZJOIZInIURFZJCLXVH0PHE91TmxL/x321Fvd41kGVwCNgQZKqSsdUF61cXaQUEp1VkotquI2XyqlLq5OfVYwybd+J6kiskJEzrdhu0EicrA6dboKpdRSpVT74vcVNSpswWpkKREZUerzN6zPb7GxHLt02FO2A3+TgAcEfIvhSqm6JV7jnVzff4AHgIeBBkBz4ClgaFkrWxcITzlWDscJ+9cK2KGUKqiGFo9uvXkI3yil6gKRwDJgpoiImzV5KjuA/921WufXlcButylyIx4dxKxbmOUi8l+re2CbiFxQYvkZrVoRuVNEtopIhohsEZEeZZTZDrgXuEYp9ZtSKlspVaiUWqaUuqVU2RNFZDmQBcSIyK0lyt8jIneXWH+QiBwUkSdE5IR15b6+VPX1RWSetf1qEWlTzq4vsf6mWi2580vfJpZsuYrIRKA/8FbJOyQR6SMia61jt1ZE+lSyf/87niLSRkQWiMhJa3++FJHwir4va7vngWeAqy0tt4uIj4g8JSL7ROS4iHwuIvVK7cftIrIfWFBOuf8UkSMiclhEbiu1bJiI/CUi6SJyQESeq+RY2rxvIvKuiLxS6rM5IvKQ9f//WmhWi7v4LjXT2q/oMso849bcWu//RGSniJwSkam2BHClVD7wGdAEaCQiKSISV6LcRqLvnlsB84FmJfQ1s1YLsL6PDNHdUz1LbN/ROidSrWUjSiz71NJZ6fksIp+JyMPW/82t/b3Xeh9r6RYpcRciIl8AUcAPlt5HSxR5vYjst767Jys5TD8AfUWkvvV+KLAJOFpCX7nnQ1k6Spyzd1nn45Hi/Stn/0dYxy/VOp4dbdjH4m1L37mLlBMPbUIp5dYXkARcWM6yW4AC4EHAH7gaSAMirOWLgDus/68EDgHnAgLEAq3KKPP/gCQbdC0C9gOdAT+r/mFAG6v8gehA2cNaf5Cl9TUg0FqeCbS3ln8KpAC9rPK+BKaXU3c0oAC/Ep89B0wrb52Sx8J6HwGcAm606rvWet+ggv0reTxjgYusfYlEB843bPzeSmu9DdgFxAB1gZnAF6X243OgDhBcRnlDgWNAF2udr6xtYksc+zh0AybeWndUBceywn0rVfcA4AAg1vv6QDbQrKLjALxsletfznm9rMR7BfwIhKMDQDIwtLJja+n/N3DAev82MKXEuvcDP5Q4RgfLKCsHuAzwBSYBq6xl/tZ39gQQAAwBMqje+XxbCR3XoVvX35RYNqcsjaWPbYnv8gMgGOgK5AIdy6n3U+Al4H3gHuuzb9G/hWXALdU510vo+Bp9PsZZ39mFZXxH7dBx4CLrmD5qHdeASso+63dNJfHQlpentPBnW1e/4tedJZYdRx/8fKXUN8B2dOAtzR3Av5RSa5Vml1JqXxnrNaTE1R1AdMs8VURyrNZQMZ8qpTYrpQqs+ucppXZb5S8GfkW3rEvytFIq11o+D7iqxLKZSqk1Snd1fAl0s+HYVJdhwE6l1BeW/q+BbcDwEuucsX8lN7aO32/WviSjL2QDq6nleuA1pdQepdRp4HHgGjmz++Y5pVSmUiq7jO2vAj5RSiUqpTLRP6iSWhcppRKUUkVKqU3oH2K5Wqu4b0vRP8Di7/kKYKVS6nB55YvI1ejANrb0ca2AyUqpVKXUfmAhFZ8bV4lIKvpCdA4wyvr8M+A6+bt77kbgi0rqXaaU+kkpVWit29X6vDf64jxZKZWnlFqAvihdW2JbW8/nxUB/S9cA4F9AX2vZQGt5VXhe6TvzjcDGEprL43PgJtF3lQOB2SUX2nGuP2+dswnAJ5x5bIq5GphnlZ8PvIK+WPUpY11bsDUelomnBPxRSqnwEq8PSiw7pKzLm8U+oBln0xLb+uVOAk1LfqCUaoG+EASiW+/FHCi5nohcKiKrrFvQVHTLqGGJVU5ZAak8rSUvNFnoH5SzaGbVX5J96OcVxRygHKzugOkickhE0oFpnLmv9mjZh24VNrZFi7V9yeVn7JeInCciC0UkWUTS0Hdx5Wqtyr5Z5950/v4xX4cObuWV3R14CxhtBQ9bqcq58a31O2mklBqilFpvaV2Nbk0OFJEO6Jbr3CrWG2RdiJuh7xyKSiwvff7YpFkptRs4jb4g9EdfOA6LSHuqF/Cr9DtSSi1Dt9yfAn4s3aiw41wvfU6WFZfOOPet43mAM49jVbA1HpaJpwT8imheqj8zCiirdXUA3d1SGQuAFiX7KivgfwdWRAKBGegrdGOlVDjwE2deIOqLSB0btNpcbwkygZAS75tUss1h9MPTkkShu70qqqeYSdbyeKVUGHADZ+5rVSitJQp9a3rMRi1H0Bf0ktuX5Ct0YGuplKoHvFtCa1nlVnXfvgausO7+zkOfB2chIpHALGC8UuqvCspzJp+h9+dG4HulVI71eVVtcQ8DLeXMh/mlz5+qsBh9dxSglDpkvb8J3UW2oZxtHGnlOw09SOPzMpZVdj6Up6P0OVnWb/2Mc9+KZS35+zhWdR9tjYdl4g0BvxFwn4j4i8iVQEd0oC3Nh8AjInKO9QAotlT3DABKqe3Ae8B0EblI9JhxXyq/xQpA3wEkAwUicilQ1tC650UkQET6A5cD1RmHngwUofu8i9kADBCRKOvW9PFS2xwrtf5PQDsRuU70g92rgU7o1pUthKJbZaki0hz4ZzX2o5ivgQdFpLWI1EX3b3+jbB/F8y1wi4h0EpEQ4NkytKYopXJEpBe6FV5MWceySvtmBe9k9Dn2i1IqtfQ6Vqt4BvCldavtLr4ARqODVsngdgxoYJ07tlB8t/Co9dsbhO4OnF5NXYuB8fz9EH0R8A90l1JhOduUPqft4T/ofvQlZSyr7HwoT8fTIhIiIp2BW4GyvvdvgWEicoGI+KMvOrnAikrKLg9b42GZeErAL35KXfyaVWLZaqAtcAKYCFyhlDpZugCl1HfW8q/QD5dmox9clsU49AnwGvrB00HgRXR/2/6yNlBKZQD3ob/AU+igUvp2+ai17DD6tv//lFLbKt71MuvKsvZlufVsobdS6jf0CbUJWM/ZgftNdCv0lIj8xzpGl6NPsJPoh0WXK6VO2CjjeaAH+qHQPPSD1uryMToQLQH2oh8U/sPWjZVS84E30Hdnuzh7JM+9wAsikoEeIfRtiW3POpZUb9++Bi5En19l0QLdXfFAqXO59N2IU1FKHQT+RLccl5b4fBt6H/ZYx6HCbgClVB4wArgU/dt7G7ipOuezxWJ0YC0OuMvQd6xlBeBiJgFPWXofqWa9ACilUpRSf5TqDimmsvOhPB2L0efjH8ArSqmzJtNZDcwbgP+ij+Nw9DD0vErKLo9y46HoEWXvVrSxlL3/noHoiRF3KKX6uVtLZVgtoGnW8wCDwW2IyMfAYaXUU+7WUhMRPdR2L3oEVpXnmrgTM8nFYKhBWMFoDNDdvUoMnoindOkYDAY7EZEXgUTg30qpve7WY/A8PLpLx2AwGAyOw7TwDQaDoZZgAr6hXERkuzW8tLL1/KQc35hKtrtDRBZVU56tdXwoIk84odxYEbHp9lhELhSRpGrWU+1tHUVVNYj2xNlcwXKbj53BsZiA76GUGtpXJGdaSJc2ZStr+4NSRZ/20iil2iullla+pueilLpDKfWyu3XUVMq62FtWF51LrGP3uWhwDGaUjoeitP0toB0Z0cNTf3dF3SLi523DzQwGQ+WYFr6XIiLTpIQNcMnbbhH5Gu2vMd+6Iyi28h0lf9u0LhDtZVK8/UHRFsQJaH+SM1pmom2FV1nbHhGR/1gzB23RertoG+FiW+lrzlwsr1vl7hGRi0ssaCEiP4r2Ltopli2yNbsxRyzLW/k7KUgd6/1ksSyNSx6n4mMk2uI2WbS17U0l6osUbfebLiJrRORlW7ucrO6pYuvs3VJGMhoReUa0Be/eksdARIJE5DXR1s7HRORtEQkqp54nLN3pou1xB5Wz3ggR2WDp2S8iT5dYFmu1ym+yvuNkEZlQYnmIiHwhehLfZrRBW3kUT5zabJ1rY205F0tpDReRT6zz6qCIvCCWpYOItBORJaLtgE+ISHkT3ww2YAJ+DUQpdS16tu+lSieUeU20B/c09AzXSOB39AznkkH7GvTMyrKm3xeg7XYbop0OhwJ3l7HeGYhIGHpG80VKqVBr200lVukDJKAT0bwOfFRi2TfoCS7N0LOg/yUiA63Zs3+inRex/u7nb3uMAZRvyNUC7VbYDG2y9o6lEeAdIBVt6nYbJRJn2MAxtGthGHAn8F8RiS9Vb6hV7+3Ax/J3isZXgNZoa+e2aIvcs3zeRU/hvxttyR2G/q7KnBmOtgq4Af1dDgfuF5HLS63TB22wdgnaEqSt9fkLaL+XGLRBYEXHofg76Gyda2f4DJV1LpZRxjS05XQboCf6ON5qLZuInv1aH30Mp1agxVAJJuDXHq4B5iqlFlg2rZPRwem8Euu8qZQ6WJZFsdK206uVtlLeg/YYt9UuWQFdRCRIKXVEKbWlxLLdSqmPLT+Vz9DGdg1FpDXaa32CUipHKfUn2oL2Rmu7xWhXSH+0R9Bb1vsQ9DT58p495AAvWfayc9G+Ju2sckYBz1jWu4lUbi389w4q9YPS9s/KshL+gzOts4uAZy0L3gXAz8CVVkv2DuABpdQppVQ6erp9Wek2C4AgoLPobre91ndRlp4FSttJFyltIzyds7+v50oc2838bTN8lXWMTiltMW5TytHqINq75gLgQaVUllLqKNpGo3j/89EXwKaW1uXO0lIbMAG/9lCWTetBbLdL7mB1dxwVbSH7AjZYyFoB7Fq0f9FRq4umXYlVSlvdgra7bQacKMNuuljvYnTCjHOBv9ABdiC61bq1LIMzixOlzLqK7XUbo5OAlDwGFVk2n4GIXC4661OxdfbFnHl8Tlp3JiX3pRna9TQQ2Gh1a6WifZIala7D8mV5GH3sj4vI1yJS2jW1WM/5orMlFVtG31FKD1ZwLaakzXBTKrCjdjCt0Pt/rMT+T+Vv6+yH0ck+1olIglgJvQ3VwwR878Uuu2SrZdkC2+2S30PP4oy1uhOewUa7ZKXUfKXUhehAsssqqzIOAw3lbLvpYr3L0dm6RqCDfwK6S2AoVfdXB90lU4Q+JsW0LGfdMxCRYOB7dMu82Dr7V848Pg2s9YoptrU9BuShM0kV54OoZ9k8n4VSappSqi+6C6g4S1VZTEe7dxZbRn+Ijd8X+iJckR31GZJsKK+idQ6gLzYRJfY/TCkVD2DdEd6hlGqKbjS8b939GaqBCfjeywa07Wp9EWmKdvIsSWnb1W+BEaLHSPujLWAz0O57thCKdhPMtJ4HVNp/DyAiTUVkuNXVkoe+UJVnh/s/LGuAdcDLIhIoIt3Q/bpfWssz0NmO7gUWWy6Iq4G7qEbAt7q5ZqP7soOt/vIbbNw8EG2fnQwUWn3lpXON+gDPibbOHoTuf//eutv4EHjDemgsoh9Wn2W9LTrH7GDRuRmyrVd5x7KkZXRvyu4iKo9vgSesh6lRaFvjMrH0n6Rii99yLYCVUgfQ39crIhImOv9xrIgMABCRq6xuH9DPVxQ2nD+GsjEB33v5FNiKvt3+mbN9yl9GB69UEXlAKbUZ/fDtHaycqcAIZXsKvoet7TPQLXRbPd990ReXI+jA0IcKAkgprkY/xDyKbkE/oZRaWGL5Yqv8dSXe16X8/vvKuAf98PgY+nnB1+g+/gqxuo8eRCc/SUEn+ihtX30QfbE7gn5WcYdSaqe17GH097gGfVH9Fb3fpQlEpwc8gT4m9dFZnMrbl0miLaOfoIRltA08a+lMQic/LytpSOn1v7LOtTFlLD/jXCxj+Q3o3LBb0Pbi3/H3Het5wFoRyUTbFo9TOg2koRoYLx2DoRxE5FUgXCl1u7u1GAyOwLTwDQYL0Rm14qxuld7oLqRZlW1nMHgLZqatwfA3YehnBE3R3TqTlVK2poQ0GDwe06VjMBgMtQTTpWMwGAy1BI/q0mnYsKGKjo52twyDwWDwGtavX39CKRVpy7oeFfCjo6NZt25d5SsaDAaDAQARsXkmtOnSMRgMhlqCCfgGg8FQSzAB32AwGGoJJuAbDAZDLcEEfIPBYKglOC3gi0h70SnWil/p5RgnGQwGg8EFOG1YppWsoRuAiPiifcyNL4nBYDC4CVd16VyATmXnzMw5BhtZvCOZHccy3C3DUEPZcjid1XtOuluGoQxcFfCvQXuLn4WI3CUi60RkXXJysovk1F4SD6Vx26drufnjNWTk2GqFbzDYRkpmHjd8tJpbP13Lqcw8d8sxlMLpAV9EAtBp6L4ra7lS6n2lVE+lVM/ISJtmBxuqSUFhERNmbiI0yI+j6Tn8+5ft7pZkqGG89OMW0rPzycor5JMVSe6WYyiFK1r4lwJ/KqWOuaAuQwV8tGwviYfSmTQ6jlv6RPPFqn2sS0pxtyxDDWHR9uPM/OsQ9w5qw8WdGvPp8r3mLtLDcEXAv5ZyunMMriPpRCav/baDizs1ZmiXJjxycXua1QvmsRmbyC0wKUIN9pGZW8CTsxJpE1mHcUNiGT8klvScAqatMtkIPQmnBnwrcfVF6FyUBjehlOKJWQkE+PrwwsguiAh1Av2YOLoLu5Mzmbpwt7slGrycV3/dwaHUbKaMjSfQz5f4FuH0b9uQj5btISffNCg8BacGfKVUllKqgVIqzZn1GCrmu/UHWbH7JI9f1pEm9YL+9/mg9o0Y3b057yzaxfajZtSOoXr8tf8Un6zYy429W9EzOuJ/n/9jSFtOnM5j+hrTyvcUzEzbGs7xjBwmzttKr9YRXHNuy7OWP315J0KD/HlsxiYKi0z2M0PVyCso4vGZCTQODeLRoe3PWNardQS9oiN4b8ke8gqK3KTQUBIT8Gs4z8/dQnZ+IZPGxOHjI2ctj6gTwDOXd2LDgVQ+X5nkcn0G7+a9xbvZdjSDF0d1ITTI/6zl44bEciQth5l/HnSDOkNpTMCvwfy6+SjzEo5w/wVtaRNZt9z1RnZrxsB2kfz7l+0cPJXlQoUGb2bX8dP8d8EuhsU35aJOjctcZ0DbhsQ1r8c7i3dTUGha+e7GBPwaSnpOPk/PSaRDk1DuGhBT4boiwsTRXQB4anYiJrG9oTKKihSPz9xEcIAvzw3vXO56IsK4wbHsO5nFvIQjLlRoKAsT8Gso//p5G8kZuUwZG4+/b+Vfc4v6IfzzkvYs2p7M3I2HXaDQ4M18tWY/a5NO8dSwjkSGBla47sWdGtOucV2mLtxFkXlO5FZMwK+BrNmbwrRV+7mtb2u6tgy3ebubzo+mW8twnv9hCylmWryhHI6kZTN5/jb6xjbginNaVLq+j49u5e84dppft5j5l+7EBPwaRk5+IRNmbqJF/WAeurhdlbb19RGmjI0nPTufF3/c4iSFBm9GKcXTsxMpKCpi0uh4RM4eCFAWw+Ka0qpBCFMX7jJdhm7EBPwaxtSFu9iTnMnLo+MICai6+3X7JqHcO6gNs/46xKLtx52g0ODN/JRwlN+3Hufhi9oT1SDE5u38fH24Z2AbEg6lsWTnCScqNFSECfg1iG1H03ln0W7G9mjBgHbVN6IbNySWNpF1eHJWIpm5BQ5UaPBmUrPyeHZuInHN63Fr3+gqbz+mRwua1gti6oJdjhdnsAkT8GsIhUWKx2YkUC/Yn6eGdbSrrEA/X6aMjedQajav/GocNQ2aifO2ciorn8lj4/CzYSBAaQL8fLhrQAxrklJYs9eY9rkDE/BrCJ+uSGLjgVSeHdGZ+nUC7C6vZ3QEN/Zuxacrkvhr/ykHKDR4M8t2nuC79Qe5a0AMnZvVq3Y515wbRcO6Aby10LTy3YEJ+DWAAylZvPLLdoZ0aMTw+KYOK/fRoe1pEhbEhBkJZmp8LSY7r5AnZiXQumEd7r+grV1lBQf4cnu/GJbsSGbjgVQHKTTYign4Xo5SiidnJ+Ij8NKoLjaPmrCF0CB/XhrVhe3HMnhvsXHUrK288fsO9qdkMWlMHEH+vnaXd0PvKMKC/JhqWvkuxwR8L2fWX4dYsiOZxy7tQLPwYIeXf0HHxlwe35T/LtjFruPGUbO2kXAwjQ+W7uHaXi3pHdPAIWWGBvlzS9/W/LrlmHFpdTEm4HsxJ07n8sKPW+gRFc4N57VyWj3PDu9McIAvE2YkmJmStYj8wiIem7GJhnUDmXCpfQMBSnNrn2hCAnx5e5Fp5bsSE/C9mBd/3EJWbiFTxsaX6YTpKCJDA3lqWEfW7TvFl8bbvNbw4dK9bDmSzgsju1Av+GwnTHuoXyeAG3q34oeNh0k6kenQsg3lYwK+l7Jw23HmbDjMuMGxtG0c6vT6rjinBf1iGzJl/jaOpGU7vT6De9l7IpM3ft/B0M5NGNqliVPquKN/a/x8fXjXPB9yGSbgeyGncwt4clYC7RrX5Z5BbVxSp4jw8ug4CoqKeNo4atZolNJOmAF+Pjw/snwnTHtpFBrENee2ZMafBzmcahoRrsAEfC/klV+2cyQ9h0lj4gnwc91XGNUghIcvas/vW48bq9sazDdrD7BqTwpPXNaRxmFBlW9gB3cPbINS8P6SPU6tx6AxAd/LWL/vFJ+tTOLm86M5p1V9l9d/a99o4prX47m5m0nNMo6aNY3j6TlM/GkrvWPKTonpaJqHBzO6e3O+XrOf5Ixcp9dX2zEB34vIKyhiwoxNNA0L4pFL2le+gRPw8/Vhyth4TmXlM3HeVrdoMDiPZ+duJregiEljbHfCtJd7BrUhv7CIj5btdUl9tRkT8L2ItxftYufx00wcE0fdwKo7YTqKTs3CuHtADN+tP8gy43xYY/g58SjzE4/ywIVtad2wjsvqjYmsy2VxTZm2ah9pWfkuq7c2YgK+l7DzWAZTF+5iZLdmDG7fyN1yuO8CHRQen7WJ7LxCd8sx2Eladj7PzEmkY9Mw7uxfcUpMZzBucCyncwv4dEWSy+uuTZiA7wUUFSkem7GJuoF+PHN5J3fLASDI35dJY+I4kJLN67/vcLccg51Mnr+NE6dzmTI2zqaUmI6mY9MwLuzYmI+X7+W0seR2GibgewHTVu/jz/2pPH15JxrUrTh/qCvpHdOAa3tF8eHSPSQcTHO3HEM1WbXnJF+v2c8d/WOIb2F7SkxHM35ILGnZ+Xy5ap/bNNR0TMD3cA6nZjNl/jYGtItkdPfm7pZzFhMu7UDDuoE8OmMT+YXGUdPbyMkv5PGZCURFhPDghVVLielourUMp19sQz5YupecfNNN6AxMwPdglFI8NTuRIgUTHeyE6SjqBfvzwsgubD2SzgdLzVhqb+M/f+xk7wmdEjM4wH4nTHsZNziWE6dz+XbdAXdLqZGYgO/B/LDpCAu2HeeRS9rTMsL2/KGuZmiXJgzt3IQ3ftfBw+AdbDmczntL9mjbjLYN3S0HgN4xEfRsVZ/3Fu8xORicgAn4HsqpzDyen7uZri3DuaVPtLvlVMrzIzsT6OfDhBmbjKOmF1BQWMSEmZuoH2J/SkxHIiKMGxLLodRsZv91yN1yahwm4HsoL83bSlp2PlPGxuHrRCdMR9E4LIgnL+vI6r0pfGNuxz2eT1ckselgGs+N6Ex4iP0pMR3JoHaRdGkexjuLd1NoGg8OxQR8D2TJjmRm/HmQewa1oUOTMHfLsZmrz21J75gIXv5pK8fSc9wtx1AO+09m8cqv27mwYyOGxTkuJaajEBHGDYpl74lM49nkYJwa8EUkXES+F5FtIrJVRM53Zn01gay8Ap6YlUBMZB3GDY51t5wqISJMGhNPbkERz87Z7G45hjJQSvHErAT8fHx40UMHAgBc0rkJsY3q8vbCXaaL0IE4u4X/JvCzUqoD0BUw5iuV8NqvOzh4KpvJY+Idkj/U1bRuWIcHLmzLz5uP8nOiaZ15GjP+PMSyXSd47NIONK3n+JSYjsLHR7h3UBu2Hc3gj23H3S2nxuC0gC8iYcAA4CMApVSeUsqkqa+AjQdS+Xj5Xm7oHUWv1hHullNt7uwfQ6emYTwzZzNp2cYbxVNIzsjlxR+30LNVfa7vFeW8iuZPgOnXg505E0Z0bUbLiGDeWrjL5F9wEM5s4ccAycAnIvKXiHwoImc5MonIXSKyTkTWJScnO1GOZ1OcP7RRaBCPDu3gbjl24W85ap44ncvk+eamzlN44cctZOcVMnlsnPNSYqbshTXvw7YfYd9yu4ry8/XhnoGxbDyQyrJdxqTPETgz4PsBPYB3lFLdgUxgQumVlFLvK6V6KqV6RkZGOlGOZ/P+kj1sO5rBi6O6EBbk2Pyh7iCuRT3u6B/D12sOsHL3SXfLqfX8sfUYP2w8zPghscQ2cmJKzOVvgI8vhDSAJa/YXdzYc5rTJCyItxaYZOeOwJkB/yBwUCm12nr/PfoCYCjF7uTTvPnHTobFNeWiTo3dLcdhPHhhO6IiQnhiVoKZKu9GMnLyeWp2Iu0bh/J/A52YEjP9MGz4CrrfAH3ugz0L4dB6u4oM9PPlzgExrN6bwrqkFAcJrb04LeArpY4CB0SkOFPHBcAWZ9XnrRQVKR6fmUCwvy/PjXBe/lB3EBygHTX3nsjkzT92ultOreXfv2znaHoOk8fGOTcl5or/QlEh9L0fzr0dgsKocghTAAAgAElEQVRhyat2F3ttr5ZE1AngrYWmlW8vzh6l8w/gSxHZBHQDXnZyfV7H12v3s2ZvCk8O60hkqOc4YTqKvrENufKcFry/ZA+bDxtHTVezLimFL1bt45Y+0XSPcmJKzNPJsO4TiL8a6kdDYCj0vge2z4Nj9g3RDQnw4/Z+rVm0PZnEQ+YcsgenBnyl1Aarfz5eKTVKKXXKmfV5G0fTcpj80zb6tGnAlee0cLccp/HksI7UD/FnwowECoyjpsvILShkwswEmtUL5pGLnZwSc9XbUJAD/R/6+7Ned0FAXVhqfyv/xvNbERrkx1TTyrcLM9PWTSileHpOInmFRUwaE+exE2AcQXhIAM+N6EzCoTQ+WZ7kbjm1hqkLd7Pr+Gkmju5CHWemxMxOhbUfQqeR0LDt35+HROiunc2z4ORuu6oIC/Lnlj7RzE88ys5jGXYKrr2YgO8mfk48ym9bjvHQRe1o1cB1+UPdxbC4plzYsTGv/radfSeNo6az2X40g3cW7WJ09+YMcnZKzDUfQG469H/47GXnjwffAFj2mt3V3Nq3NcH+vry9yL6LR23GBHw3kJaVzzNzN9OleRi392vtbjkuQUR4cVRn/Hx8eGJWgplI40QKrZSYoUH+PO3slJi5p3V3TttLoGn82cvrNoIeN8HG6ZBqn6leRJ0Arj8virkbD7P/ZJZdZdVWTMB3Ay//tJWUzDwmj4nHzw35Q91F03rBPHZpB5bvOsn36w+6W06N5fOVSWw4kMozl3cioo6TnTDXfwLZKTDgkfLX6XMfILDiP3ZXd+eAGHxFeGexaeVXh9oTbTyEFbtO8M26A9zZP4Yuzeu5W47Lub5XFOdG1+eleVtJzsh1t5wax8FTWfz7l+0Mah/JyG7NnFtZfo4eitl6ALTsVf564S2h6zWw/jPIOGZXlY3DgriyZwtmrD/I0TTjyFpVTMB3ITn5hTw+K4HoBiE8cGHbyjeogfj4aEfN7LxCnvvBOGo6kuKUmAAvucIJc8M0OH0M+lfQui+m34NQlA8r37K72v8b2IZCpXh/iUmpWVVMwHchr/++g30ns3h5TJxXOmE6ithGdfnHkFjmbTrCb1vsa/EZ/mbuxsMs2p7MPy9pT4v6Tk6JWZgPy96EFufqFn5lNGgDncfAuo8hy74Zsy0jQhjVrTlfrdnHidPmLrEqmIDvIhIPpfHh0r1cc25L+rTxjPyh7uTugW1o3ziUp2cnkpFjHDXtJSUzj+d/2EK3luHcdH608ytM+A7S9uvWva13Ev0fhrzTsPo9u6u/d3AbcguK+HjZXrvLqk2YgO8CCiwnzIg6ATx+qefkD3UnAX4+TB4bx7GMHP7183Z3y/F6XvxxCxk5+UwZG+/8lJhFhbD0NWgcB+0usX27xp2g/TBY/S7kpNsloU1kXS7r0pQvVu4zFtxVwAR8F/DRsr1sPpzOCyM6Uy/E+50wHUX3qPrc0ieaL1btY60xxqo2i7YfZ9Zfh7hnUCztmzjRCbOYLXPg5E4Y8LDtrftiBjwMOamw7iO7Zdw7uA0ZuQV8viLJ7rJqCybgO5mkE5m89tsOLuncmEs9MH+ou3nk4vY0Dw9mwoxNxlGzGmTmFvDkrETaRNZh3GAnOmEWo5Ru3TdoCx1HVH375udAmyGwcirkZ9slpXOzelzQoREfL99LZm6BXWXVFkzAdyLF+UMDfH14YWQXd8vxSOoE+jFxdBd2J2fytvFJqTKv/LqdQ6nZTBkbT6CfCwYC7PgFjiVozxyfatbX/xHITIY/P7dbzrghsZzKyuer1fvtLqs2YAK+E/lu3UFW7D7J45d1pHFYkLvleCyD2jdidPfmvL1oN9uO2te3W5v4a/8pPl2RxI29W9Ez2gUpMZWCpa9AeBTEXVn9cqL7QtT5sPxNKMizS1KPqPr0adOA95fuMXeINmACvpM4npHDS/O20Kt1BNec29Ldcjyepy/vRFiwdtQsLDK2C5WRV1DEhBkJNAkL4tGhTnbCLGbvEji4Vvvd+9r5LKr/I5B+CDZNt1vW+MGxJGfk8p2ZvV0pJuA7iefnbiGnoIjJY5yYP7QGEVEngGeHd2LDgVQ+Mw/hKuW9xbvZfiyDl0Z1IdRVKTGX/BvqNoFuN9hfVuwF0LQbLHsdCu3rfz+/TQO6R4Xz7qLd5Bv77QoxAd8J/Lr5KPMSjnD/BW2Jiazrbjlew4iuzRjUPpJXft3OgRRjjlUeu46f5r8LdnF5fFMu6OiilJgH1kDSUujzD/B3QPekiPbfSdmj7ZPtKkoYPziWQ6nZzNlw2H5tNRgT8B1Mek4+T89JpEOTUO4aEONuOV6FiPDSKP1w+8nZicZRswx0SsxNBAf48uxwF6bEXPIKBEdAz1sdV2b7YRDZUSdIKbKvZT6kQyM6Ng3j7UW7TJdgBZiA72CmzN9GckYuU8bG41+LnDAdRYv6IfzzkvYs2ZFsWmtl8OWa/axNOsXTl3dyXUrMI5tg5y/Q+14IcGDuBh8fPdoneSts/8muoopb+XuSM5mfeMRBAmseJiI5kDV7U/hy9X5u69uari3D3S3Ha7np/Gi6R4Xz/A+bOWm8Uv7HkbRspszfRr/Yhozt0dx1FS99FQLDoNedji+78xidA3fpK3oUkB0M7dKEmMg6TF2429wdloMJ+A4iJ7+QCTM20TIimIcubuduOV6Nr48wZWw8p3MLePHHLe6W4xEopXh6diIFRUW8PNqFKTGTd+iZtefeAcFOaMT4+mknzcN/we4F9hXlI9w7KJatR9JZsO24gwTWLEzAdxBvLdjFnhOZvDw6jpAAJ+YPrSW0axzKPYNimb3hMAu3mx/vvIQj/L71OA9f1J6oBk52wizJstfALwjOH+e8OrpeC2HNHZLsfGS3ZrSoH8xbC3eZVn4ZmIDvALYeSefdxbsZ26MF/dtGultOjWHc4DbENqrLU7MSa/XU+dSsPJ6bu5m45vW4tW+06yo+lQSbvtUPaus40eHVL1Bnxdq3HPatsKsof18f7h7Yhr/2p7Jy90kHCaw5mIBvJ4VFigkzNlEv2J+nhhknTEcS6OfLlLFxHE7L5t+/1F5HzYnztnIqSzthujQl5vI3tX1Cn384v64eN0FIQz0ayE6uPKcFjUIDectYdZyFCfh28snyvWw8mMZzIzpT39n5Q2sh57SK4MberfhsZRJ/7j/lbjkuZ9nOE3y3/iB3D4ihU7Mw11WcfgT+mgbdroMwJ6dKBAgI0d1Gu/+AQ3/aVVSQvy93DYhhxe6TrN9X+86ZijAB3w4OpGTx6q87uKBDIy6PN06YzuKfl7SnSVgQE2ZsIq+g9sykzM4r5IlZCbRuWIf7LnBxSsyVb2nf+74PuK7Oc++AoHoO6cu/7rwo6of4M9W08s/ABPxqUuyE6SPwoivyh9ZiQoP8eWlUF3YcO827i3e7W47LeP33HexPyWKSq1NiZp7UqQjjroCI1q6rNygMet0N236E41vtKiokwI/b+rZmwbbjbD6c5iCB3o8J+NVk1l+HWLrzBI9d2oFm4cHullPjuaBjY4Z3bcZbC3ax63iGu+U4nYSDaXy4dA/X9oqid0wD11a+6m3tVd/vIdfWC9D7HvCv45BW/k19ogkN9OPthbWnkVAZJuBXgxOnc3nhxy2c06o+N5zXyt1yag3PDu9ESKAvj81IoKgGT5/Pt1JiNqwbyIRLO7i28pw0WPMBdBwOjVxcN0BIBJx7GyTOgJP2Bep6wf7c1KcVPyUeYdfx0w4S6N1UGvBFxGTcLsULP2whK7fQOGG6mIZ1A3lqWCfW7zvFl6v3uVuO0/hg6R62HEnnhZFdqBfs4pSYaz6A3DRtbOYuzh8PPv6w/A27i7qtb2uC/Hx5Z5Fp5UMFAV9Eipf9WuKz+52uyMNZsO0YczceZtzgWNo2dkH+UMMZjO3RnP5tGzLl5+0cTrUvRZ4nsvdEJm/8vpOhnZswtEsT11ael6m7c2IvgqZdXVt3SUKbQI8bYcPXkGafx32DuoFc2yuK2RsOGQdWKm7hLxaRn4EmIjJURJoBN1elcBFJEpEEEdkgIuvsUuoBnM4t4KlZibRrXJd7Brkgf6jhLESEl0fHUVikrQZq0mzKImtOR6CfDy+MdKETZjHrP4Osk+5t3RfT935AwYr/2l3UXQNi8BWpVQ/8y6PcgK+U6g9cA2QDvYD/AO1EZLqI3FOFOgYrpboppXraJ9X9vPLLdo6k5zB5bDwBfubxh7toGRHCwxe3449tx/lxU81xRvx23QFW703hycs60sjVKTELcmHFf6BVP4jq7dq6yyI8CuKv1heh0/ZZazSpF8TYc1rw3bqDHEvPcZBA76SiLp1fgQeBIuC/SqkrgJ3Ao4BnDZNY8wGccO542/X7TvHZyiRuPj+aHlH1nVqXoXJu6RNNfIt6PDd3M6cy7cuL6gkcT89h4k9b6R0TwdXuSIm54UvIOOIZrfti+j0EBTmwcqrdRd0zsA2FSvHBkj0OEOa9VNRMHQUsAeoCn4vIGqAVMBbYZmP5CvhVRNaLyF1lrSAid4nIOhFZl5ycXAXpFlkpsHgKfD5Ce384gdyCQh6bsYlm9YJ55BIX5Q81VIifrw+Tx8STmp3PxJ/sG7PtCTwzZzN5BUVMGhPv+jkdhQWw7A1ofg7EDHJt3RXRMBY6j4a1H0G2fTNmoxqEMLJrM75cvZ+UGtBAqC4VdelkKaX+AI4qpYYrpXoBh4ADwE02lt9XKdUDuBQYJyIDyqjnfaVUT6VUz8jIahiPhUTAjbP1A6fPRkDaoaqXUQnvLNrNruOneWl0F+oGGidMT6FTszDuHhDD9+sPsnRnNRoLHsLPiUf4efNRHriwHa0bOjDBiK0kfg+p+3RicU+bQNj/YcjLgNXv213UvYPbkFNQyCfL9zpAmHdiS0f02BL/L1NKfa+Uus+WwpVSh62/x4FZ6GcBjqdJF7hxlm4FfD7C7j6/kuw8lsHUhbsY1a0Zg9s3cli5Bsdw3wVtiWlYhydmJZCV532OmmnZ+TwzZzOdmoZxR38XzmotpqhIT3Jq1BnaDXV9/ZXRpAu0uxRWvwO59o2lj20UytDOTfh0RRLpOfkOEuhdVBrwlVJ7Svxv88NaEakjIqHF/wMXA4nVEWkTzXvA9d9p06fPR+rp4XZSWKR4bMYm6gb68fTlnRwg0uBogvx9eXlMHAdSsnn9tx3ullNlJs/fxonTbkyJuXUunNihUw36eOhAhAGP6Mbcuo/tLmrc4Fgycgr4YmXNncdREc78hhsDy0RkI7AGmKeU+tmJ9enRBdd+DSl7YNpoyE61q7hpq/bx5/5UnhneiQZ1XZQ/1FBlesc04NpeUXy0bC+bDtr3nbuSVXtO8vWa/dzRP4a4FvVcL0Ap3bqPaKP7yj2VFj2h9UBt6JZv39yLLs3rMah9JB8t2+uVd4T24rSAr5Tao5Tqar06K6UmOquuM4gZCFdPg2Nb4MsrILd6A4oOpWbzr5+3MaBdJKO6uTB/qKFaTLi0Aw3rBvLo95vIL/R8R82c/EIen5lAVEQID17oppSYO3+Do5us1r0Lzdmqw4B/wulj2rLZTsYPjiUlM4+v1xxwgDDvwkPv4eyk7UVw5SfaV/urayCvajPslFI8NSsBBUw0TpheQb1gf14c1YVtRzN43wuG3v3nj53sPZHJpDFxBAe4IdgqpROH12upx7t7OtH9oOV5OilLoX397z2jI+gdE8H7S3aTW1DoIIHegS1eOuEicp+IvCYi/yl+uUKcXXQcDmPe12nTvrleTyyxkbkbD7NwezKPXNyelhEuzB9qsItLOjfh0i5NePOPnexJ9lyzrC2H03lvyR6uPKcFfWPdZFWVtAwOrNYzWn1d7NdTHUT0KKK0A7DpG7uLGz+4LcfSc/l+vX3WDd6GLS38n4BoIAFYX+Ll+cRdASOnwu4F8N0tNrUMUjLzeP6HLXRtGc7NfaKdLtHgWJ4f0ZlAPx8en+mZjpoFlhNm/RB/nnRnSsylr0CdRtD9BvdpqCptL4Im8bD0NZ2cxQ76xjaga8tw3l28mwIv6AJ0FLYE/CCl1ENKqU+UUp8Vv5yuzFF0vx6GvQrbf4IZd+hJJhXw0rwtpGfnM2VsHL7GCdPraBQWxJOXdWT13hSmr/W8PtpPlieRcEinxAwPcVNKzIPrYM8i6DMe/L0ol4OIHpefshu2zLazKGH84FgOpGQzd+NhBwn0fGwJ+F+IyJ0i0lREIopfTlfmSM69Ay6eqE+SueP12OMyWLIjmZl/HuKeQW3o0MSF+UMNDuXqc1tyfkwDJv201aO8U/afzOLV37ZzYcfGDItzY0rMJa9AcH3oeZv7NFSXjiOgYXtY8mq5v2NbuaBDIzo0CeXtRbs98m7QGdgS8POAfwMr+bs7x/ucL/uMh8FPwcavYd5D+qFVCTJzC3hiVgJtIuswfkism0QaHIGI8PKYOPIKi3hmjvOmflSF4pSYfj4+vDiqs/sGAhxNhB3z4bx7INAL7b19fPSoouObYYd9o7x9fIR7B8ey6/hpftl81EECPRtbAv5DQKxSKlop1dp6xThbmFMY+E99S7j+E/j58TOC/mu/7eDgqWwmj40n0M/Dh6gZKqV1wzo8cGE7ftl8jJ8T3e+o+f36gyzbpVNiNq3nxm6Upa9CQCicV6a1lXfQ5QoIb6WfQ9hpjz0srimtG9bhrYW7apTVdnnYEvA3AzUnc8CQp6H3vXqq9oIXAdhwIJVPlu/lht5RnBvtXb1VhvK5o39rOjUN4+k5m0nLct9U+uSMXF6at5Vzo+tzfa8ot+ngxE7YPAvOvV136Xgrvn7Q7wE4tF4/i7CnKB/hnkFt2Hw4nUXbvdePyVZsCfiFwAYRec+rhmWWhwhc8jKccyssfZXCRf9iwoxNNAoN4rGhbsjhaXAa/r4+/OuKeFIy85g0332Oms//sJnsvEImjYl3b0rMZa+DXyCcP859GhxFt+shtKlDkp2P7t6c5uHBtaKVb0vAnw1MBFbgbcMyy0MEhr0GXa/Fd9FE+iVP58VRXQgN8oLxyIYq0aV5Pe7o15rpaw+wYvcJl9f/+5Zj/LjpCP8YEktso7our/9/pO7X49d73Ax1a4AJoF8g9PkHJC2F/avsKsrf14e7B8awft8pVu1JcZBAz8QW87TPgK/5O9B/5VXDMsvDx4dd50/mp6LePOX/JRednutuRQYn8cCF7YiKCOGJmQnk5LtuZmVGTj5Pz0mkfeNQ7h7o5pSYy98EBPraZHTrHZxzC4Q00KOO7OSqni1pWDeQqQudm0jJ3dgy03YQOtPVVOBtYEdZvvbeRlGR4onZW3na535y2wyFnx5xiE+HwfMIDvBl0pg4kk5m8cbvO11W779+3s7R9Bwmj41zb0rMjKPw5xfQ7Vqo18J9OhxNQB39PG7Xb3B4g11FBfn7cteA1izbdYINB7zHgK+q2HIWvgpcrJQaqJQaAFwCvO5cWc7n67X7WZOUwmOXxxF47efQZgjMGQ8J37tbmsEJ9I1tyFU9W/DB0j0kHkpzen3rklL4YtU+bu3Tmu7uTom58i0oyoe+D7hXhzPodScE1nNIX/7157UiPMSftxbU3Fa+LQHfXym1vfiNUmoH4NWd3UfTcpj80zb6xjbgynNa6P7Aq7+EVn1h5l2w9Qd3SzQ4gScu60j9kAAmzNzk1On0xSkxm4cH8/DFbnLCLCYrBdZ+DF3GQgM3dys5g6B6Ouhv/QGSt1e+fgXUCfTj1j6t+X3rMbYeSXeQQM/CloC/TkQ+EpFB1usDvPihrVKKp2Ynkl9UxMuj4/6eABMQAtdN13k9v7tVW8caahThIQE8P6IziYfS+diJae6mLtzN7uRMJo7uQh13p8Rc9Q7kZ+qE4DWV3vdqi4ilr9ld1C19oqkb6Fdj+/JtCfj3oMfi3wfcD2wB/s+ZopzJ/MSj/L71GA9d1I5WDUrlDw0M1VmzGneCb26APYvdI9LgNC6La8KFHRvz2m872Hcy0+Hlbz+awTuLdjG6e3MGuTslZk46rHkPOlyuz+maSp0Geph1wneQYt+FvF6IPzf0bsW8hCMe7bhaXWwZpZOrlHpNKTVGKTVaKfW6Usp2r2EPIi1L5w/t0jyM2/qWkz80OFwnRY+Iga+vsXvIl8GzEBFeHNUZPx/tqOnIcdfFKTFDg/w9IyXm2g8hJ02nCKzp9PmHTuKy/A27i7q9X2sCfH14Z9FuBwjzLMoN+CKSICKbynu5UqSjePmnrZzKymPK2Hj8KsofGhIBN82BsGYw7Qo9o89QY2haL5gJl3Zgxe6TfOdAP/TPVyax4UAqzw7vREQdNzlhFpOXBSunQpsLoFl392pxBWFNtdXzhq8g3T73y8jQQK7tFcWsvw5x8FTNMRmAilv4lwPDgZ+t1/XW6yfA64ayrNh1gm/WHeCuATF0bmZD/tC6jeCmuTr4fzFGm04ZagzX9Yri3Oj6TJy3leMZ9jtqHjyVxb9/2c6g9pGM6NrMAQrt5M/PIetE7WjdF9P3fu2Tv+K/dhd198AYRPCK7GlVodyAr5Tap5TaB/RVSj2qlEqwXhPQQzO9huy8Qh6flUB0gxDuv6Ct7RvWaw43/6DH+34+0u5RAAbPwcdHmDQmnuy8Qp7/YYtdZSmleHKWbhC85AkpMQty9USrqD7Qqo97tbiS+tEQfxWs+wQy7ZtV3bReMGN7tGD62gMc9yCLbXux5aFtHRHpV/xGRPoAdSpY3+N4448d7DuZxctj4gjyr6ITZv1WOuj7+MJnI+BkzevXq63ENqrLP4bEMm/TEX7bcqza5czZcJjFO5L55yXtaVHfA1JibvwaMg7DgIfdrcT19HsICnJg1dt2F/V/A9tQUFjEh8ucN6LL1dgS8G8HpopIkogkoWfbek3mhMRDaXy4dC/XnNuSPm2qmT+0QRvdp1+Yp1v6qfsdK9LgNu4e2IYOTUJ5anYC6TlVd9Q8eTqX53/YTPeocG46P9rxAqtKYYE2SWvWXfff1zYi20GnkbDmA8i2b8ZsdMM6DO/ajGmr9nEqM89BAt2LLaN01iulugLxQFelVDel1J/Ol2Y/xflDI+oE8PhlduYPbdQRbpoNuem6pZ/ufo91g/0E+PkweWw8xzNy+dfP26q8/UvztnI6t4ApY+M9IyXm5plwKkkn/HZ315K76P+w/p2u+cDuou4dFEtWXiGfrEiyX5cHYIuXTqCIXAeMB+4XkWdE5BnnS7OfD5ftZfPhdF4c2Zl6wQ6YHNy0K9wwEzKT4fMRcLrm+2fXBrq1DOfWPq2Ztmo/a5Nsd0tctP04s/46xD2DYmnX2AOyRxUVaYuByI7Q/jJ3q3EfTeOh7SW6WyfXvrH07ZuEcknnxny6fC8Z1bgD9DRs6dKZA4wECoDMEi+PJulEJq//toNLOjdmaBcH5g9t0ROu+xZSD8AXo/TUdYPX8/DF7WgeHsxjMzbZ5KiZmVvAk7MSiW1Ul3GDPcSyYPs8SN6mW7g+bjRr8wQGPALZKbD+U7uLGj+4Lek5BXyxap/9utyMLWdFC6XU1UqpfymlXi1+OV2ZHSileHxmAgF+PrwwsovjK4juC9d+pTMITRujJ7cYvJo6gX68PCaOPcmZNk2rf+XX7RxOy2bK2DjPSImpFCz5N9RvDZ1Hu1uN+2nZC6L76yGa+faNsolrUY8B7SL5aOlesvNcZ6/tDGwJ+CtEJM7pShzIt+sOsHLPSZ64rCONw4KcU0mbIXDV53A0Ab68CvI8/qbHUAkD20Uypntz3lm0m21HyzfP+mv/KT5dkcSNvVtxTisPSYm56w84shH6PahTABp0K//0Udjwpd1FjR8cy8nMPKav9e4BG7YE/H7AehHZbs2yTfDkmbbH03OYOG8r57WO4OqeLZ1bWfuhMPYjOLhG2zDkZzu3PoPTeeryToQF+/PYjAQKi862XcgrKGLCjASahAXxz0vau0FhOSx9BcKaQ9dr3a3Ec2g9EFqcC8vegEL7+t97tY6gV3QE7y/ZQ16B85xWnY0tAf9SoC1wMXrmbfEMXI/kuR82k1NQxKQxca7JH9p5FIx6F/YuhW9u1JNeDF5LRJ0Anh3eiY0HUvm0jJEZ7y7ezfZjGbzkSSkxk5bD/pV6pqmfmy0dPAkRPVopbb82VrOTcUNiOZKWw8w/HWfH4WpsGZZZPOM2G1AlXh7HL5uP8lPCUe6/oC0xkS7MH9r1ahj+hs688/1tdrcmDO5lRNdmDG4fySu/bOdAyt9eKruOZ/DWgl0M79qMCzo2dqPCUix9BepEQo+b3K3E82h3CTSO09bJRfb1vw9o25D4FvV4Z/Fup+ZTcCa2DMscISI7gb3AYiAJmO9kXVUmPSefZ+Yk0rFpGHcNiHG9gHNugaFTYNuPMOv/7D65DO5DRHhpdBwi8OTsRJRSFBUpJsxIICTQl2eHe4ATZjGH1sPuBXD+OO0JbzgTEej/EJzcCVvty1stIowbHMu+k1n8uMk75+HY0qXzItAb2KGUag1cACy3tQIR8RWRv0Tkx2pqtInJ87eRnJHLlLFx+FfkhOlMev8fXPgcJH4Pc+/T46INXknz8GAevaQ9S3YkM3vDIb5cs591+07x1LBONKwb6G55f7PkVZ31qeft7lbiuXQaCQ3a6mNlpx32RR0b065xXaYu3EVRGc94PB1bImO+Uuok4CMiPkqphUC3KtRxP7C1WupsZPWek3y1ej+392tNfItwZ1ZVOf0ehIETYMM0mP9Pu08wg/u48fxoukeF8/wPW5gyfxv92zZkbI/m7pb1N8c267H3590DQWHuVuO5+Pjq3+WxBNj5q31F+ehW/s7jp/nVDv8ld2FLwE8VkbrAEuBLEXkTPQmrUkSkBTAM+LD6EismJ7+Qx2cm0DIimAcvcnP+0GIGTYA+9+kEFL8+ZYK+l+LrI0wZG09mbgGFRerMlJiewNLXIKAunHe3u5V4PvFXQb0oPVfBzt/jsLimtGoQwm4g6PwAACAASURBVNSFuxyaQMcV2BLwRwJZwINoX/zd2D5K5w3gUaDcvg0RuUtE1onIuuTk6lkVXNCxEZNGxxMS4CHjj0Xgoheg112w8i1YNMndigzVpF3jUN6+/hzeu/EcWkZ4gBNmMSd3a9+cnrfpnA2GivH1h373w8G1sHeJXUX5+fpw76A2JBxKY8lO+2yYXY0to3QylVJFSqkCpdRnwFRgaGXbicjlwHGlVIXpopRS7yuleiqlekZGRtosvJggf1+eHNaJfm2r6YTpLET0Q9zuN8LiKQ5JsGxwDxd1asyAdlU/N53KstfBxx/OH+9uJd5DtxugbhM9qslORndvQbN6QUxd4F3JzitKcRgmIo+LyFsicrFoxgN7gKtsKLsvMMKyVJ4ODBGRaQ5R7S34+MDwNyHuSvjjeVj1jrsVGWoCqQe0532PmyDUg4aHejr+QdBnvG7hH1hrV1EBfj7cNSCGNUkprN5z0kECnU9FLfwvgPZAAnAH8CtwJTBSKTWysoKVUo8rpVoopaKBa4AFSqkb7JfsZfj46olZHUfAzxN0Nh6DwR5W/Ef/7Xu/e3V4I+fcCsH1HdLKv6ZXFA3rBvCWDd5LnkJFAT9GKXWLUuo94FqgJ3C5UmqDa6TVIHz9tAVD24vhxwdh43R3KzJ4K6eP63y1Xa+BcCdbh9REAutC73thx89wxD6HmCB/X27vF8PSnSfYeMC+ZCuuoqKA/7/pokqpQmCvUiqjOpUopRYppS6vzrY1Br8AuOoLaD0AZt8Dm2e5W5HBG1n5ls681u8hdyvxXnrdBYFhOneAndzQO4qwID+bHFY9gYoCflcRSbdeGUB88f8iUr6VoKF8/IPg2q+h5Xkw4w7Y9pO7FRm8iawUWPuRtj9u4CEe/N5IcDicewdsmQPJO+wqKjTIn1v7tubXLcfYfrRa7WGXUm7AV0r5KqXCrFeoUsqvxP9mlkd1CaijE6g0iYfvbta2tgaDLax+D/JO6wQnBvs4fxz4BenRTnZya99o6gT48vYiz2/l1/K0OG4iKAxumAEN28P06yFpmbsVGTyd3AxY/a5OXdi4s7vVeD91Gmr/q03fwCn7MlmFhwRwQ+9W/LDxMEknPDsvhgn47iIkQidFD4+Cr66GA2vcrcjgyaz9CHJStd2vwTH0+QeIDyx/0+6ibu/fGj9fH95ZtNsBwpyHCfjupE5DuHku1G0E066Aw2YAlKEM8rNh5VSIGQwtznG3mppDvebQ/Xr46wtIt8/9slFoENec25KZfx3kcKrnJkIyAd/dhDaBm+Zqx8MvRsOxLe5WZPA0/vwCMo/rlH0Gx9L3AW1lvvItu4u6e2AblIL3l+xxgDDnYAK+JxDeEm6eA36B8PlIOOH5D38MLqIgT3c5tOwNrfq6W03NI6I1xF0B6z6GTPtmzDYPD2ZMj+Z8vWY/yRmemfnOBHxPISJGt/RVEXw2HE4luVuRwRPYNB3SD+rWvSc5ddYk+j0E+Vmw2n7rk3sGxZJfWMSHyzyzlW8CvicR2Q5umgMF2Trop3lv7kyDAygs0MMGm3aF2Avdrabm0qgDdBwOq9+HnDS7imrdsA7D4psxbeU+UrPyHCTQcZiA72k06QI3zITsVPhsBGR4X5IFg4PYMhtS9uiROaZ171z6Pwy5aTqHhZ2MG9yGzLxCPl2RZL8uB2MCvifSvAdc/z1kHNV9+nb2LRq8kKIiPfU/sgN0qN2uJC6hWXeIvUiPhsqzbyx9hyZhXNixMZ8sT+J0rk25olyGCfieStR5cN10OLUXvhgF2afcrcjgSnbMh+NbdP+yj/mZuoQBj0DWSVj/md1FjR8SS1p2Pl+usm9Sl6MxZ5In03oAXP0lHN+qx+nner5Xh8EBKKVT8dWPhi5j3a2m9hDVG1r10/bTBfaNsunWMpz+bRvywdK95OQXOkig/ZiA7+m0vRCu/BQO/6Vn5OZluVuRwdnsXqC/774PaGttg+sY8DBkHIENX9ld1LjBsZw4ncs3aw84QJhjMAHfG+h4OYz9APavhOnXQX6OuxUZnMnSVyG0GXS7zt1Kah8xg6FZDz06qtC+/vfzWkfQs1V93lu8m7yCctN6uxQT8L2FLmNhxFuwZ6F22SzwvCFfBgewbyXsWw5979MT8QyuRUT35afug8Tv7SxKGDcklsNpOcz+65CDBNqHCfjeRPfrYdirOlvPzDvtboEYPJClr0BIQ+hxs7uV1F7aXcr/t3fn0VFV2eLHvzshECAMhjAoAQOoKIQQIAISgjTNA2dsxKmRsWkQEUFBn9qPfmg3/uzXPEQG5UFjtzZxaBBssJVGhJiIDAkQZhmUiEHFgBBmTOD8/jgFhpihkhpuVWV/1sqiUnVz716H1M6te8/Zm0ZtIWOanS3lgZ7XNSS+aV1e/eQLzl8wXgqw8jThB5sbR0DfF+wc7X+O8fgXUgWQbzbDvpVw0yNQvZbT0VRdYWGQ8gQc3g2fL/NoVyLCo7+4hv2HT/GvbZ4VaPMGTfjB6KYx0Ou/7LL798fbWR0q+KVPhRr17B915ay2v4LoVvb/xMP3V582Tbi2URSzV+3jgsNn+Zrwg1WPJ+3qwE2vw/KnNekHu+93wefvQ5eRtnKqclZYOHR/HL7baj91ebKrMOGRX7Ri96ETrNzl7Mp5TfjBrNck6DrGdkJaOVmTfjDLmAYRtaDLaKcjURcl3A91Y+2aCA/fW3cmXEXz6FrMXr0P4+D7VBN+MBOBvlMgaTismW5/MVXw+eFLOyMkaTjUbuB0NOqiatWh+3j4er3HbUirhYfx8M2t2JKbz6f7DnspwIrThB/sROC2/4X2v4bVU2DNDKcjUhX16XQIi7At91Rg6fAQ1G5kZ0956J5OTWlSN5JZq5zrd6EJPxSEhUG/WdC2P3w0CTbMczoi5a78XLuqs8NDtvuZCiwRNaHbo/BlGuRu9GhXNaqFM7JHS9bv/4GsnB+8E18FacIPFWHh0H8utL4dPpho2+KpwPfZTNv0Jnmc05Go0iQNh8j6XjnLf7BzcxrUrs6s1c6c5WvCDyXhEXDvX6HVL2HpWNi60OmIVFlO5tnKjAn3wxVXOx2NKk2NOtB1NOz+AA7t8GhXNauHM7x7C9J257Et17NmK5WhCT/UVKsB9y+AuO6wZBTsXOp0RKo062ZD4Vm7yEcFts4joXqUrXPkoUE3XU2dyGrMduAsXxN+KKpeCx58C5p2gkXDYc8KpyNSxZ05Chv+Am3vhphrnY5GladWtF0Qt30xHPYsUdeNjGBotziW7/iOvYf8W/JcE36oqlEHBi6Exm3gnYfsTScVODbMgx9P2MVzKjjcNMZ+gv70JY93NSy5BTUjwnkl7QsvBOY+TfihrGZ9GPQeNGgFbz1oKzEq5507CetegetugSbtnI5GuSuqkS1qt/VtOHbAo11F167OQ12bs3TLN3x1xLOWihXhs4QvIpEiskFEtojIDhF5zlfHUmWoFQ2D/wl1r4LUez2eWqa8IOs1e0knZaLTkaiKSn4MEK+sd/ltSkvCw4Q5n/jvLN+XZ/jngF7GmPZAInCLiHT14fFUaaIaweClNvkv+BV8u9XpiKqugrOwdpZtX9nsRqejURVVLxbaPwCb3oATntXFaVQ3kvuSYlm0MZdv8894KcCy+SzhG+uk69sI15cWe3FKvaYwZJmdafD3uzXpO2Xz3+HkIVv8TgWn7o/DhQJYO9PjXY3q0YoLBuamf+mFwMrn02v4IhIuItnA98BHxpj1JWwzUkSyRCQrLy/Pl+GoK662ST8sAubeDEtGw9Ecp6OqOs4XwJqXIbYzxKU4HY2qrAatbAe6zNfgtGcrZptF1+LuxKa8t/mgX5qd+zThG2POG2MSgVigs4jEl7DNXGNMkjEmqWHDhr4MR4H9ZR39GXR9BHYshpmd4P3H4fg3TkcW+ra+A/lf2xZ6Ik5HozzR/QkoOGUr1XroqVta89ETNxMZEe6FwMrml1k6xphjQBpwiz+Op8pRu4GtsvnYZjvrYNMbMKMD/Pt3cOqI09GFpgvnbQnkJu3g2j5OR6M81bgNXH+HTfhnj3u2q7qRxET5p3+xL2fpNBSR+q7HNYHewOe+Op6qhLpXwR3TYOxGW3ht3SvwcgKsmgJn/b/sO6TtfA9++MLOu9ez+9CQMsG+T7LmOx2J23x5hn8lsFpEtgKZ2Gv47/vweKqyroiDX70Kj6yDa3pD+v/A9AR7Rvqj/+YIhyxj7Fg2uBZuuMvpaJS3NO0IrXrB2tnw42mno3GLL2fpbDXGdDDGJBhj4o0xz/vqWMpLGraG+16HUenQrAt8/By8nAjr5kDhOaejC157lsOh7faMMMz312mVH6VMhFN59rJoENCVturnrmwPA/8Bw1fYPwLL/xNmdLSVHc8XOB1dcDHGNsKu3xzaDXA6GuVtccnQvBt8NgMKf3Q6mnJpwlela94Fhr5vV+rWaQLLHoPZnW3Z5QsXnI4uOHyZBgezIHm8LV+tQk+PCXD8IGx5y+lIyqUJX5WvZU8YsRIefNs22l48AuYkw673tXF6eTL+F6KaQOJApyNRvtLql3Bloi2qdr7Q6WjKpAlfuUcEWt8KozJgwGtw/kd4ZyDM6wX7PtbEX5ID6yEnw/aqjYh0OhrlKyJ2bcXR/bBjidPRlEkTvqqYsDC7yvCR9dBvNpw6DAv6w99u12qcxWVMhZrRkDTM6UiUr7W+HRreYD/RBfDlTk34qnLCq9nG22Oz4LapcGQf/PUWWHAPfLPZ6eic9+0W2LsCbnoEqtd2Ohrla2FhdhZW3i7Y/S+noymVmAD6KJ6UlGSysrIue66goIDc3FzOnj3rUFShKTIyktjYWCIivHQj8cfTkDnPXsc8cxRuuBN+8TtodIN39h9s3hlkb9iO32b7EqjQd74QZiVBZD0Ymea3BXYistEYk+TOttV8HYyncnNzqVOnDnFxcYiuUPQKYwxHjhwhNzeXFi1aeGen1WtB8jjoNMyu2P1slr2pm3Af9Hwaolt65zjBIG837Fpme9Vqsq86wqvZSprLHoMvPraLGANMwF/SOXv2LA0aNNBk70UiQoMGDXzzqSmyrk3w47faZhE7l8KsG2HZOMg/6P3jBaKMaRBR0xaoU1VL+wehblNI97zZuS8EfMIHNNn7gM/HtFY0/MfzMC4bkobD5lRboG35M3AyhMtg/7Afti2ETkOhdozT0Sh/q1Yduj0GBz6DnDVOR/MzQZHwVRCr0wRu+zM8tgkS7rXVBV9uDx8/b6/1h5o1L9vyCd3GOh2JckrHwVArxs7SCjCa8N0QFRVV7jYjRoxg586dALzwwguXvdatW7dKH6Ok5+fMmcMbbwRH7Y5L6je30zjHZELrW+z0tZfbQ/qfbVPvUHD8G8hOtYus6l7ldDTKKdVrQbdH4YtVcDCwekgH/CydXbt2ccMNzs70iIqK4uRJ95NSRbcv62cqsy93OTq2322zZZj3fGjPhlKegKTfBPcCpeXPwPr/s59mrohzOhrlpLPHYXq87Wz2QKpPDxVSs3SKem7ZDnZ+41mzgeLaXFWX/76zrVvbpqWlMXnyZGJiYti+fTudOnViwYIFiAg9e/Zk6tSpLFq0iDNnzpCYmEjbtm1JTU29lLRPnjxJv379OHr0KAUFBfzxj3+kX79+FY558uTJREVFMXHiRHr27EmXLl1YvXo1x44dY/78+aSkpHD+/Hmefvpp0tLSOHfuHGPGjGHUqFEVPpbPNGkHv34bcrNg1R/g38/amT03PwkdBgVf3ZlThyHrr9DuXk32yk5e6PIwfPInOLTTNkwJAHpJp4I2b97M9OnT2blzJ19++SVr1lx+Y+bFF1+kZs2aZGdnk5p6+V/2yMhIlixZwqZNm1i9ejUTJkzAG5+wCgsL2bBhA9OnT+e5554DYP78+dSrV4/MzEwyMzOZN28e+/fv9/hYXhebZIuzDVkG9WJtu8VZSbDlbdslKlisewUKz9pPKkqBTfgRteHTaU5HcklQneG7eybuS507dyY2NhaAxMREcnJy6N69u1s/a4zh2WefJT09nbCwMA4ePMihQ4do0qSJRzH1798fgE6dOpGTkwPAihUr2Lp1K4sWLQIgPz+fvXv3em/evbe16AG/WWFXp676AywZZRdx/eJZ2zQkkGdqnTkGG+bZxWYNWzsdjQoUtaLhxuG2QUrPZ2w/aYfpGX4F1ajxU+/J8PBwCgvdr46XmppKXl4eGzduJDs7m8aNG3tlLvzFmIrGY4xh5syZZGdnk52dzf79++nTJ8B7qYrAdX1hZDrc+zcwF+Afg2HuzbD3o8At0JY5D84dtwW0lCrqpkchLMKevAQATfg+EBERQUHBzxuF5Ofn06hRIyIiIli9ejVfffWVz2Lo27cvr7766qU49uzZw6lTQdKuMCwM2v7Ktly8e449g04dAH+9FXI+dTq6y507CWtfsY3Jr2zvdDQq0NRpYqdpbnkb8nOdjkYTvi+MHDmShIQEBg68vAb6wIEDycrKIikpidTUVK6//vpy93X69GliY2MvfU2b5t71wBEjRtCmTRs6duxIfHw8o0aNqtCnkYAQFg6JD8KjWXD7NDiaY6tyvnF34Ex32/g3OPODbXWnVEmSxwEG1sxwOhKdllmVBd3YFpyBzL/Yj8enj9iStL1+B40durdTcNauJYi51nYGU6o0742B7YtsMb2oRl7ddUWmZeoZvgoeETXtCtZxW2wlzpwMeDUZFv0Gjnzh/3iyU+Hkd7YsrlJl6f64bRq0drajYWjCV8GnRh24+Smb+LuPh90f2AJt/3wUjn3tnxjOF8Ca6dA0ybaAVKosMddAm7vtJ9TTPzgWhiZ8FbxqRUPvyfBYNnT+LWx9B2Z2hA+eghOHfHvsbYvg2AE7MyeQp4yqwJEyAX48CRvmOhaCJnwV/Oo0hlv/BGM3QfsH7FnUjERYOdk3Z1MXzttaQI3j4bpbvL9/FZqaxEPr22Ddq3DuhCMhaMJXoaN+M7hrJjyaCdffDp9OtzdV0/7k3TfYrqVwZK9dVatn96oiUibC2WOQ9Zojh9eEr0JPg1Zwz19g9Bq7gjftBZieYKfFFZzxbN/G2OYWDVzXZJWqiNhO9p7PZ7M8/12sBE34bhARJkz4aSbG1KlTmTx5stf2n5OTQ3x8/M+e//3vf8/KlSsrvd+ePXtSfJprldK4ra1U+NtVcFUifDQJXk60l3wKf6zcPveugEPb7KyLsHDvxquqhpSJcOp72LzA74fWhO+GGjVqsHjxYg4fPuzX4z7//PP07h14fTGDTtNOMGgJDP0AolvAvybArE6Q/aZtPO0uY2z9/nrNIOF+38WrQltcd2jWxV5yrOyJRyUFVfE0Pnza1lH3pibt4NYXy9ykWrVqjBw5kpdeeokpU6Zc9lpeXh4PP/wwBw4cAGD69OkkJyfTrl07MjIyqFevHjExMbz00ksMHjyYQYMGMWTIELcS+dChQ7njjjsYMGAAcXFxDBkyhGXLllFQUMDChQu5/vrrOXXqFGPHjmXbtm0UFhYyefLkSpVcrhLikmHYh7DvY1ug7b3RdhFXz2fs5Zmwcs5/9qdDbibcNjX4yjerwCECPZ605UK2vgMdB/nt0HqG76YxY8aQmppKfn7+Zc+PGzeOxx9/nMzMTN59911GjBgBQHJyMmvWrGHHjh20bNmSjIwMANatW0fXrl0rFUNMTAybNm1i9OjRTJ1q26dNmTKFXr16kZmZyerVq3nyySeDp2aOE0Tg2t4wMg3u+ztIGCwaBnN7wJ5/l12gLWMqRDW29fqV8sQ1vW3tpU9f8msZ8OA6wy/nTNyX6taty+DBg5kxYwY1a9a89PzKlSsvtTYEOH78OCdOnCAlJYX09HSuvvpqRo8ezdy5czl48CDR0dFutUwsSdEyyIsXLwZsGeSlS5de+gNw9uxZDhw4EFwlE5wgAm3usrN5ti2yN3bfvA9iO8MvJ9mbvUV9nWnP8P/jD8HdlUsFBhE7L/8fg2HHEmg3wC+H9VnCF5FmwBtAE+ACMNcY87KvjucP48ePp2PHjgwbNuzScxcuXGDt2rWX/REA6NGjB7Nnz+bAgQNMmTKFJUuWsGjRIlJSUip9/NLKIL/77ru0bv3zOuxpaWmVPlaVERYO7e+H+P72Jton/wOv3wktboZek6DZjXa7jKlQ8wpIGu5svCp0XH8nxLSGjGnQtn/5lxS9wJdHKAQmGGNuALoCY0QkMPp8VVJ0dDT33Xcf8+fPv/Rcnz59mDVr1qXvs7OzAWjWrBmHDx9m7969tGzZku7duzN16lSPEn5J+vbty8yZMy91ztq8ebNX919lhEdA0jB4bDP0/X9waAfM7w1v3g9bF8Ke5dBlNNSo3KczpX4mLMyu5fh+h/398schfbVjY8y3xphNrscngF1AU18dz18mTJhw2WydGTNmkJWVRUJCAm3atGHOnDmXXuvSpQvXXXcdACkpKRw8eLDU7li7d+++rAzywoUL3Ypn0qRJFBQUkJCQQHx8PJMmTbr02ogRIy673KTcEBEJNz1i6/T0mgQH1sLiEVC9DnQZ6XR0KtTED4D6V9vZX36oXOyX8sgiEgekA/HGmOPFXhsJjARo3rx5p+JNQYKuhG8Q0bF1w8X2hQ1aQvw9TkejQtHmVPhmE/SZUqn7QxUpj+zzm7YiEgW8C4wvnuwBjDFzgblg6+H7Oh6lKqRmfbj5SaejUKGsw0D75Qc+vUsgIhHYZJ9qjFnsy2MppZQqm88SvogIMB/YZYxxry9fKQKpK1eo0DFVqurx5Rl+MjAI6CUi2a6v2yq6k8jISI4cOaIJyouMMRw5coTISJ1PrlRV4rNr+MaYTwGPa8fGxsaSm5tLXl6eF6JSF0VGRhIbG+t0GEopPwr4lbYRERG0aNHC6TCUUiroaS0dpZSqIjThK6VUFaEJXymlqgi/rLR1l4jkAV+Vu2HJYgD/dihxj8ZVMRpXxWhcFROKcV1tjGnozoYBlfA9ISJZ7i4v9ieNq2I0rorRuCqmqsell3SUUqqK0ISvlFJVRCgl/LlOB1AKjatiNK6K0bgqpkrHFTLX8JVSSpUtlM7wlVJKlUETvlJKVRFBlfBF5DUR+V5EtpfyuojIDBHZJyJbRaRjgMTVU0Tyi1QN/b2f4momIqtFZJeI7BCRcSVs4/cxczMuv4+ZiESKyAYR2eKK67kStqkhIu+4xmu9q5tbIMQ1VETyiozXCF/HVeTY4SKyWUTeL+E1v4+Xm3E5Ml4ikiMi21zHzCrhdd++H40xQfMF9AA6AttLef024ENslc6uwPoAiasn8L4D43Ul0NH1uA6wB2jj9Ji5GZffx8w1BlGuxxHAeqBrsW0eAea4Hj8AvBMgcQ0FZvn7d8x17CeAN0v6/3JivNyMy5HxAnKAmDJe9+n7MajO8I0x6cAPZWzSD3jDWOuA+iJyZQDE5QjjXiN5v4+Zm3H5nWsMTrq+jXB9FZ/V0A943fV4EfBLV7Mfp+NyhIjEArcDfyllE7+Pl5txBSqfvh+DKuG7oSnwdZHvcwmAROJyk+sj+Yci0tbfB3d9lO6APTssytExKyMucGDMXJcBsoHvgY+MMaWOlzGmEMgHGgRAXAD3uC4DLBKRZr6OyWU68BRwoZTXHRkvN+ICZ8bLACtEZKOIjCzhdZ++H0Mt4Zd05hAIZ0KbsPUu2gMzgff8eXApu5G8Y2NWTlyOjJkx5rwxJhGIBTqLSHyxTRwZLzfiWgbEGWMSgJX8dFbtMyJyB/C9MWZjWZuV8JxPx8vNuPw+Xi7JxpiOwK3AGBHpUex1n45XqCX8XKDoX+pY4BuHYrnEGHP84kdyY8wHQISIxPjj2FJ+I3lHxqy8uJwcM9cxjwFpwC3FXro0XiJSDaiHHy/nlRaXMeaIMeac69t5QCc/hJMM3CUiOcDb2HamC4pt48R4lRuXQ+OFMeYb17/fA0uAzsU28en7MdQS/lJgsOtOd1cg3xjzrdNBiUiTi9ctRaQzdtyP+OG47jSS9/uYuROXE2MmIg1FpL7rcU2gN/B5sc2WAkNcjwcAq4zrbpuTcRW7znsX9r6ITxljnjHGxBpj4rA3ZFcZYx4qtpnfx8uduJwYLxGpLSJ1Lj4G+gDFZ/b59P0Y8C0OixKRt7CzN2JEJBf4b+wNLIwxc4APsHe59wGngWEBEtcAYLSIFAJngAd8/UvvcrGR/DbX9V+AZ4HmRWJzYszcicuJMbsSeF1EwrF/YP5hjHlfRJ4HsowxS7F/qP4uIvuwZ6oP+Dgmd+N6TETuAgpdcQ31Q1wlCoDxcicuJ8arMbDEdR5TDXjTGLNcRB4G/7wftbSCUkpVEaF2SUcppVQpNOErpVQVoQlfKaWqCE34SilVRWjCV0qpKkITvgoqInLeVWlwu4gsFJFarudPlvNzcSLy6zJeMyIytshzs0RkqJdiThORgGucraoeTfgq2JwxxiQaY+KBH4GH3fy5OKDEhO/yPTBORKp7GJ9XuVanKuUVmvBVMMsArin6hGuF4p9dnwC2icj9rpdeBFJcnw4eL2FfecDH/LQqtOg+L52hi0iMa8n+xZrq74nIMhHZLyKPisgTYmuwrxOR6CK7eUhEPnPF1dn187XF9lLIdP1MvyL7XSgiy4AVHo2QUkXo2YMKSq4z31uB5cVe6g8kAu2BGCBTRNKBp4GJxpg7ytjti8CHIvJaBUKJx1b7jMSujvxPY0wHEXkJGIyt2ghQ2xjTzVUs6zXXz/0Ou+x/uKt0wgYRWena/iYgwRgTcGW3VfDShK+CTc0i5RgysEv3i+oOvGWMOQ8cEpFPgBuB4tU4f8YYs19ENlD2pZ/iVrtq+p8QkXxsFUaAbUBCke3ech0jXUTquhJ8H2yRr4mubSJxlZfAlkDWZK+8ShO+CjZnXGWCS+Npc40XsI060os8V8hPlz8ji21/rsjjC0W+v8Dl76/iNUwMNtZ7jDG7i74gIl2AUxWOXKlySxV8uwAAALlJREFU6DV8FWrSgfvFNgxpiG0/uQE4gW2nWCZjzOfATqDopZ8cfiqfO6CScd0PICLdsRUQ84F/A2OLVAXtUMl9K+UWTfgq1CwBtgJbgFXAU8aY71zPFYrtoFXSTduipmDrkF80FVu58zPsfYHKOOr6+TnAb1zP/QFbVXWriGx3fa+Uz2i1TKWUqiL0DF8ppaoITfhKKVVFaMJXSqkqQhO+UkpVEZrwlVKqitCEr5RSVYQmfKWUqiL+PyIkK0ncLr/qAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = [1,2,3,4,5]\n",
    "y = [4,7,4,7,3]\n",
    "\n",
    "y2 = [5,3,2,6,2]\n",
    "\n",
    "plt.plot(x, y, label='Initial Line')\n",
    "plt.plot(x, y2, label='New Line!')\n",
    "\n",
    "plt.xlabel('Plot Number')\n",
    "plt.ylabel('Random #')\n",
    "plt.title('Epic Graph tutorial for data viz in Python with Matplotlib.\\nTutorial showing labels and titles')\n",
    "\n",
    "plt.legend()\n",
    "\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "x = [2,4,6,8,10]\n",
    "x2 = [1,3,5,7,9]\n",
    "y = [4,7,4,7,3]\n",
    "y2 = [5,3,2,6,2]\n",
    "\n",
    "plt.bar(x, y, label=\"One\", color='m')\n",
    "plt.bar(x2, y2, label=\"Two\", color='g')\n",
    "\n",
    "plt.xlabel('bar number')\n",
    "plt.ylabel('bar height')\n",
    "plt.title('Bar Chart Tutorial')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "test_scores = [55,45,88,75,43,56,89,98,55,54,65,77,88,81,82,89,92,98,65,76,76,73,72,84]\n",
    "\n",
    "##x = [x for x in range(len(test_scores))]\n",
    "##\n",
    "##plt.bar(x, test_scores)\n",
    "##\n",
    "##plt.show()\n",
    "\n",
    "bins = [10,20,30,40,50,60,70,80,90,100]\n",
    "plt.hist(test_scores, bins, histtype='bar', rwidth=0.8)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "test_scores = [55,45,88,75,43,56,89,98,55,54,65,77,88,81,82,89,92,98,65,76,76,73,72,84]\n",
    "\n",
    "##x = [x for x in range(len(test_scores))]\n",
    "##\n",
    "##plt.bar(x, test_scores)\n",
    "##\n",
    "##plt.show()\n",
    "\n",
    "bins = [10,20,30,40,50,60,70,80,90,100]\n",
    "plt.hist(test_scores, bins, histtype='bar', rwidth=0.8)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "test_scores = [55,45,88,75,43,56,89,98,55,54,65,77,88,81,82,89,92,98,65,76,76,73,72,84]\n",
    "time_spent  = [11,10,22,23,28,32,54,55,43,23,53,33,23,55,23,33,38,48,22,35,37,42,29,12]\n",
    "\n",
    "plt.scatter(time_spent, test_scores)\n",
    "\n",
    "plt.title('Test scores vs Time Spent')\n",
    "plt.xlabel('time spent on test')\n",
    "plt.ylabel('Test Score')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "x = [1,2,3,4,5]\n",
    "y1 = [2,3,2,4,2]\n",
    "y2 = [8,8,6,7,6]\n",
    "\n",
    "plt.scatter(x, y1, marker='o', color='c')\n",
    "plt.scatter(x, y2, marker='v', color='m')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEWCAYAAAB8LwAVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3Xd4VGX2wPHvyaRXOmiQpijSexdcQWyIDQURBRvWVVwV0PWnuMLaFbFTVBBUFAv2VSyAiJTQe5MSakJJ73l/f9wJBgxkJpmZOzM5n+eZJ8nMnXvfCWHOvO0cMcaglFJKnSjE7gYopZTyTxoglFJKlUkDhFJKqTJpgFBKKVUmDRBKKaXKpAFCKaVUmTRAKKWUKpMGCOVzIjJERJaJSKaI7BOR70Skp93tUkodTwOE8ikR+RcwAfgvUBdoALwBXGFnu5RSf6cBQvmMiCQA/wHuMcZ8ZozJMsYUGGO+MsY87DwmQkQmiMhe522CiEQ4HztfRJJFZJSIHHT2Pq4UkUtFZLOIHBaRR0tdb6yIzBaRWSKSISLLRaRNqcfHiMg252PrReSqUo8NF5HfROQFETkiIn+KyCXOx64VkaQTXtuDIvLFyV63iEx1tnePiIwTEYfzsTdFZHapY58VkZ/EUvJ6HxWRVBHZISI3lDo2wtm+XSJyQETeEpGoE35XD5b6Xd1c6rmXOl9zhrNND5V6rL+IrBSRoyLyu4i0LvXYaOfxGSKySUT6uP4XoAKOMUZvevPJDbgYKARCT3HMf4A/gDpAbeB34CnnY+c7n/84EAbcDqQAHwBxQAsgF2jiPH4sUAAMdB7/EPAnEOZ8/FrgdKwPSoOALOA052PDnc+9HXAAdwF7AQEigMPAuaXavQK45iSv6QvgbSDG+bqWAHc4H4sGNjuvdx6QCtQ/4fW+5Lxmb2cbz3E+PgH4EqjhfP1fAU+f8Nz/OF/7pUA2UN35+D7gPOf31YH2zu/bAweBLs7XPQzY4bz+OcBu4HTnsY2AM+3+u9KbF//P2t0AvVWdG3ADsL+cY7YBl5b6+SJgh/P784EcwOH8OQ4wQJdSxycBVzq/Hwv8UeqxkNJvjGVceyVwhfP74cDWUo9FO69Vz/nzm8B45/ctgCNARBnnrAvkAVGl7rse+KXUz52dAWcncH2p+0ve5GNK3fcx8H9YgSqr9Bs00A3484TfVWipxw8CXZ3f7wLuAOJPaO+bOANyqfs2YQWns5zn6IszyOotuG86xKR86RBQS0RCT3HM6VhvlCV2Ou87dg5jTJHz+xzn1wOlHs8BYkv9vLvkG2NMMZBccj4RuanUUMpRoCVQq9Rz95d6brbz25JzTwOGiIgANwIfG2Pyyng9DbE+we8rdZ23sXoSJedeAmzHetP/+ITnHzHGZJX6ueT3URsraCWVOu/3zvtLHDLGFJb6ObtU+6/B6lXsFJF5ItKtVHsfLDmn87xnYPUatgIjsQLvQRH5SERK/9uoIKMBQvnSIqwhoCtPccxerDepEg2c91XUGSXfiEgIUB/YKyINgcnAvUBNY0w1YC3Wm3S5jDF/APlYw0JDgPdPcuhurB5ELWNMNect3hjTolS77sEawtkLjDrh+dVFJKbUzyW/j1SsYNii1HkTjDGxuMAYs9QYcwVWoPqCvwLTbqyeUbVSt2hjzIfO531gjOmJ9W9kgGdduZ4KTBoglM8YY9Kw5g9ed04uR4tImIhcIiLPOQ/7EHhMRGqLSC3n8TMqcdkOInK1s9cyEuvN+g+s+QCDNYeBcwK3pZvnng68BhQaY34r6wBjzD7gB+BFEYkXkRAROVNEejuvezYwDhiK1RMZJSJtTzjNkyISLiLnAf2BT5y9ocnAyyJSx3muRBG5qLxGO891g4gkGGMKgHSgpFc2GbhTRLo4J8pjROQyEYkTkXNE5AKxFg3kYgWoopNcRgUBDRDKp4wxLwH/Ah7DenPejfUpvmQF0DhgGbAaWAMsd95XUXOwJqCPYL0BX22slVPrgRexejUHgFbAQjfP/T5WUDlZ76HETUA4sN7ZjtnAac6gNQN41hizyhizBXgUeN/5JgzWMNcRrF7DTOBOY8xG52Ojga3AHyKSDszFmkh2xY3ADufz7sQKUBhjlmFNzL/mvO5WrPkYsHo5z2D1XvZj9T4eRQUtMUYLBqngJCJjgbOMMUO9dP4orEnb9s43d0+f/3xghjGmvqfPrZQrtAehVMXdBSz1RnBQyh+cajWJUuokRGQH1oT2qSbclQpoOsSklFKqTDrEpJRSqkxeG2ISkXewluQdNMa0dN73PHA51vrxbcDNxpijzsceAW7FWjZ3nzHmf+Vdo1atWqZRo0beeQFKKRWkkpKSUo0xtcs7zmtDTCLSC8gEppcKEP2An40xhSLyLIAxZrSINMda/94Za5foXODsUjtmy9SxY0ezbNkyr7RfKaWClYgkGWM6lnec14aYjDHzsfLLlL7vh1Jb///A2tUKVqrnj4wxecaYP7HWXnf2VtuUUkqVz845iFuA75zfJ1IqZw5WvpxEn7dIKaXUMbYECBH5N1aWypkld5VxWJljXyIyQqxqZMtSUlK81USllKryfL4PQkSGYU1e9zF/TYAkUyqpGs6EamU93xgzCZgE1hyEF5uqlCpDQUEBycnJ5Obm2t0UVY7IyEjq169PWFhYhZ7v0wAhIhdj5Y/pXSp9MlhFTz4QkZewJqmbYhVVUUr5meTkZOLi4mjUqBFWtnPlj4wxHDp0iOTkZBo3blyhc3htiElEPsRKhHaOs/ThrVgJwOKAH515+N8CMMasw0o3vB4rp/095a1gUkrZIzc3l5o1a2pw8HMiQs2aNSvV0/NaD8IYc30Zd089xfHjgfHeao9SynM0OASGyv476U5qpZRSZdIAoZQKKEePHuWNN96w5drFxVCV0tdpgFBKBRQ7A8ShQ3DwoC2XtoUGCKVUQBkzZgzbtm2jbdu2PPDAA/Tp04f27dvTqlUr5syZA8DSpUtp3bo1ubm5ZGVl0aJFC9auXQvA888/T6dOnWjdujVPPPEEAFlZWVx22WW0adOGli1bMmvWrL9d1xg4cAD27IH8fN+9XjtpPQilVIVtGbmFzJWZHj1nbNtYmk5oetLHn3nmGdauXcvKlSspLCwkOzub+Ph4UlNT6dq1KwMGDKBTp04MGDCAxx57jJycHIYOHUrLli354Ycf2LJlC0uWLMEYw4ABA5g/fz4pKSmcfvrpfPPNNwCkpaX97bppaVCyIGj3bjjzTI++bL+kAUIpFbCMMTz66KPMnz+fkJAQ9uzZw4EDB6hXrx6PP/44nTp1IjIykokTJwLwww8/8MMPP9CuXTsAMjMz2bJlC+eddx4PPfQQo0ePpn///px33nl/u9aBA399f+SIFTASEnzyMm2jAUIpVWGn+qTvCzNnziQlJYWkpCTCwsJo1KjRsXX/hw8fJjMzk4KCAnJzc4mJicEYwyOPPMIdd9zxt3MlJSXx7bff8sgjj9CvXz8ef/zxY49lZUFGxvHH79oFLVpASBAP1AfxS1NKBaO4uDgynO/WaWlp1KlTh7CwMH755Rd27tx57LgRI0bw1FNPccMNNzB69GgALrroIt555x0yM61hsT179nDw4EH27t1LdHQ0Q4cO5aGHHmL58uXHXbN076FEXh7s3++lF+kntAehlAooNWvWpEePHrRs2ZJOnTqxceNGOnbsSNu2bWnWrBkA06dPJzQ0lCFDhlBUVET37t35+eef6devHxs2bKBbt24AxMbGMmPGDLZu3crDDz9MSEgIYWFhvPnmm8eul59vDSmVZd8+qFEDIiO9/rJtEdA1qbVgkFK+t2HDBs4991y7m+Ezu3eX3YMoER8PZ5/tu/a4q6x/L9sLBimlVKArKoLU1FMfk54Ohw+f+phApQFCKaVOIiXFChLl2b3bteMCjQYIpZQqgzGu75ouKIC9ZVawCWwaIJRSqgyHD7u3Y/rgQcjOLv+4QKIBQimlynCqiemyGGPtjQjgdT9/owFCKaVOkJ5esd5AZmb5k9qBRAOEUko5xcbGAu73HkrbswcKC4+/7/zzzycQl+RrgFBKVXnGGIqLiwHIybHyLFVUYSEkJ3uoYTbTAKGUCkgvvfQSLVu2pGXLlkyYMIHRo0cfVydi7NixvPjii0DZKb537NjBueeey91330379u3ZvXs3AA899G+GDGnDzTd35dAhqytx5EgKo0Zdw003deKmmzqxatVCANatW8Itt3Tnhhvaccst3dmxYxMAyck5DBw4mNatWzNo0CBycnJ89nvxJE21oZSqsJFbtrAy07PpvtvGxjKh6amTACYlJfHuu++yePFijDF06dKFGTNmMHLkSO6++24APv74Y77//vuTpvhu0KABmzZt4t133z0WWLKysjjrrK7cfPN4Jk4cxRdfTObWWx/jxRfvZ8iQB2jbtif79+/in/+8iE8+2UDDhs2YNGk+oaGhLF48lzfeeJTnnvuUTz99k6KiaFatWs2aNatp3769R39HvqIBQikVcH777TeuuuoqYmJiALj66qtZsGDBscR7KSkpVK9enQYNGjBx4sQyU3w3aNCAhg0b0rVr12PnDQ8Pp2fP/gA0a9aBJUt+BGDJkrls377+2HFZWelkZWWQmZnGk08OY9euLYgIhYUFAKxYMZ9Bg+7j4EFo3bo1rVu39snvxdM0QCilKqy8T/recrIccgMHDmT27Nns37+fwYMHHzu2rBTfO3bsOBZgwKo37XCEISIAOBwOCp2zzcXFxbzzziIiI6OOO8fzz/+TDh3+wfPPf87evTu4887zjz0mIuzZA9WrV/rl2kbnIJRSAadXr1588cUXZGdnk5WVxeeff855553H4MGD+eijj5g9ezYDBw4ETp7i+0SnWp7atWs/PvnktWM/b9q0EoCsrDTq1EkE4Ouv3zv2eLt2vfj++5kUF8NPP61l9erVlX3JttAAoZQKOO3bt2f48OF07tyZLl26cNttt9GuXTtatGhBRkYGiYmJnHbaaQD069ePIUOG0K1bN1q1asXAgQOP1ZMoUVJv+mQeemgi69cv4/rrW3Pddc357LO3ALjxxlG8/voj3HprD4pKJWO65pq7yM7O5PrrW/Paa8/RoUNnz/8SfEDTfSul3BKM6b6PHIFt27x3/ogI+6rPabpvpZSqhMpsjHNFoFaf0wChlKrSMjOtm7ft2wfOctkBw2sBQkTeEZGDIrK21H01RORHEdni/Frdeb+IyEQR2Soiq0UkMBcNK6UCjrd7DyVKkvkFEm/2IN4DLj7hvjHAT8aYpsBPzp8BLgGaOm8jgDdRSikvy8s7eb1pbwi06nNeCxDGmPnAib+KK4Bpzu+nAVeWun+6sfwBVBOR07zVNqWUAt/1HkoLpOpzvp6DqGuM2Qfg/FrHeX8isLvUccnO+/5GREaIyDIRWZaSkuLVxiqlgldhoT2puQOp+py/TFJLGfeVuf7WGDPJGNPRGNOxdu3aXm6WUioYfPHFF6xfv/64+1JSrN3Tp5KU9CurVv1e7vnnzfuS9957xuX2eLL63NGjR49LUuhJvg4QB0qGjpxfS7YzJgNnlDquPhAgMVYp5e9ODBDFxeXXmy4sLCQp6VdWry4/QPTuPYDhw8eUe1wJT1af82aA8HUupi+BYcAzzq9zSt1/r4h8BHQB0kqGopRSqiwzZsxg4sSJ5Ofn06VLF9544w0SEhK4//77+frrr4mKimLOnDls27aNL7/8knnz5jFu3Dg+/fRTDh+G++67h6NHU4iMjObf/55Mo0bNGDt2OAkJNdi0aQXx8TVYtWohDoeD776bwcMPv0pGxlHeeWccBQX5JCTU5KmnZlKzZl2++uo9NmxYxqhRrzF27HBiY+NZv34Zhw7t5777nqNPn4EkJf3K228/Qc2addm8eSXnn381Xbu24t13XyEnJ4cvvviCM888k5SUFO688052OZc8TZgwgR49ejB27Fh27drF9u3b2bVrFyNHjuS+++5jzJgxbNu2jbZt23LhhRfy/PPPe+x37LUAISIfAucDtUQkGXgCKzB8LCK3AruAa52HfwtcCmwFsoGbvdUupZTnjBwJK1d69pxt28KECac+ZsOGDcyaNYuFCxcSFhbG3XffzcyZM8nKyqJr166MHz+eUaNGMXnyZB577DEGDBhA//79j+VnuuGGPowa9RYNGjRl7drFPPvs3bz55s8A7Nq1mddfn4vD4WDSpLFERcVy440PAZCefoR33/0DEeGLL6YwffpzPPDAi39rX2rqPqZM+Y0dOzby4IMD6NPHuu6WLav47383EB9fgyuvbEJk5G38/vsSXn/9FV599VUmTJjA/fffzwMPPEDPnj3ZtWsXF110ERs2bABg48aN/PLLL2RkZHDOOedw11138cwzz7B27VpWevofAi8GCGPM9Sd5qE8ZxxrgHm+1RSkVXH766SeSkpLo1KkTADk5OdSpU4fw8HD697fSdXfo0IEff/zxb8/dsyeTlSt/Z8yYa4/dV1CQd+z7Pn2uxeFwlHndgweTefTRQaSm7qOgIJ/TT29c5nG9e19JSEgITZo05/Dhv5ZKNW/eiVq1rAWa9eufSefO/UhOhlatWvHLL78AMHfu3OOGw9LT04/ljrrsssuIiIggIiKCOnXqcMDLy7A03bdSqsLK+6TvLcYYhg0bxtNPP33c/S+88EKZ6bpLO3CgmNjYanzwQdmfuKOiYsq8H6z03kOG/IvevQeQlPQrkyaNLfO48PCI49pa1v0iIYSFRZCaCnl5IcelFl+0aBFRUcenFgeIiPjr+Sd7fZ7kL6uYlFLKZX369GH27NnH0nYfPnyYnTt3nvT4uLg4MjIyyM6G4uJ4Tj+9MXPnfgJYb+CbN68q83nR0XFkZ/+V+TUzs3R672llPqciSudp6tevH6+99ldq8fKGjkpemzdogFBKBZzmzZszbtw4+vXrR+vWrbnwwgvZt+/k61oGDx7srEvdjuTkbTz11EzmzJnKkCFtGDSoBfPmzSnzeeeddzm//vo5Q4a0ZcWKBYwYMZYxY67l9tvPo1q1Wh57Pfn51q5ugIkTJ7Js2TJat25N8+bNeeutt0753Jo1a9KjRw9atmzJww8/7LE2gab7Vkq5KVDTfefnw5o1nlla6g0hIdCyJYSHe/a8mu5bKaXKcfCg/wYHsPZm7N5d/nG+pAFCKRX0ioqsndP+7sgRSEuzuxV/0QChlHJboA1Np6YGToK8XbvKTwHiqsr+O2mAUEq5JTIykkOHDgVMkCiv3rS/8VT1OWMMhw4dIjIyssLn0H0QSim31K9fn+TkZAIlm3JWlj1ZWyvj0CGrzWFhlTtPZGQk9evXr/DzNUAopdwSFhZG48Zl7yD2R126wJIldrfCfRdfDN99Z28bdIhJKRW0FiwIzOAA8P33MHu2vW3QAKGUClov/j2PXkAZORIyM+27vgYIpVRQ2rwZvvrK7lZUzp498MQT9l1fA4RSKii9/LLnlovaaeJEawe4HTRAKKWCTmoqTPNcLj1bFRbCXXfZswu8ygYILyU/VEr5gTfegJwcz583KsoQHu77d+qFC+Hdd31+2aobIB5/HKZOtbsVSilPy82F11/3zrk733mUTmM9sIutAkaNsvZH+FKVDRD5+XDbbfDww8ExTqmUsrz/vpWYz9MaNC5m0SVrWNhtE71v9/0QxKFDMGaMb69ZZQNEiRdegKuvtnZbKqUCmzHw0kveOXfdkbvID7M+TS4YlETHPvneudApTJ0Kixb57npuBQgRCRGReG81xi5z5sB551lLypRSgeubb2DjRs+ft2PffJa23nHs52IHbH5wGY3P9u3wgzHWhLWvEg+WGyBE5AMRiReRGGA9sElEPFu2yA+sWAGdO0NSkt0tUUpVlDc2xoWHG1JGrP/b/elR+Zhxa0io5ttJ61WrrKWvvuBKD6K5MSYduBL4FmgA3OjVVtlk717o1Qs+/dTullQ9X39t9eK6doXHHoNffrHmiZRyVVIS/Pqr58/b7dZ0dtY+WuZjO2of4cynt+Nw+DZIfPyxb67jSoAIE5EwrAAxxxhTAARGnt8KyM6Ga6+Fp5+2uyXBr6gIPvoI2raFyy+H336DxYth/Hi44AKoXh0uugieew6WL9fFBOrUvNF7qJdoWHrFqXepLW+2mx5jfJsu1ld7IlwJEG8DO4AYYL6INATSvdkouxkDjz4Kw4frp1hvyM+HyZOhWTO4/nqry1yW7Gz44QcYPRo6dIA6dazg/fbbsHWrb9us/NuuXfDJJ54/b+ORe8iOKCz3uPl919Hz+mzPN8Bm5QYIY8xEY0yiMeZSY9kJ/MMHbbPdtGnQt6/v1x4Hq6wsa4VJkyYwYoT7b/KHDlnZLe+8E5o2hUaN4NZb4cMPvbOsUQWOV16xdhx7UpsehSzq6Pof6eJbltG6q4cbYbOT1oMQkX+V81wvLSbzLwsWWPnkv/7a+sSr3HfkiDWp9uqrng22O3fCO+9YNxFo2RL69LGCeu/eEBvruWsp/5WWZvVIPSk01JB9j3vLoQpCi9n77+Uk3t2JPbvFsw2yyal6EHHOW0fgLiDRebsTaO79pvmPbdugWzeYO9fulgSWffusjYgNGsDYsd7tiRljJTSbMAH694caNaBnT+u6CxZAQYH3rq3sNXmy51PndL8pky2nuT+vkBqbTczT64iJCY5p2pMGCGPMk8aYJ4FaQHtjzIPGmAeBDkDFa9gBIvKAiKwTkbUi8qGIRIpIYxFZLCJbRGSWiIRX5hqedvQoXHIJvPWW3S3xf3/+aQ0DNW5sbUS0I599QYGVv+bJJ62VaTVqwKWXWkNcq1fbk/hMeV5BgTW85Em16hhWDqx4+tTNiam0HLcbkcD/I3NlkroBUHqqNh9oVNELikgicB/Q0RjTEnAAg4FngZeNMU2BI8CtFb2Gt5RkVRw5UlfUlGXtWrjhBmt+4O23reLr/iIz0yrf+OCD0KYN1KtnTZBPmQI7dtjdOlVRH38MycmePWez+/aTHlW51SmL226n1/1lL40NJK4EiPeBJSIyVkSeABYD0yt53VAgSkRCgWhgH3ABUFJgbxrWslq/9MorMGCAZoQtsXgxXHEFtG4NH3zgu12elXHwoLXE9vbbrZ7OmWfCHXdYbzi6KCFweHppa4sORfzWfZNHzjVvwCq6Dsj1yLns4soqpvHALVif6o8CNxtj/lvRCxpj9gAvALuwAkMakAQcNcaULAFIxprv+BsRGSEiy0RkWUpKSkWbUWnffAM9eljL66qquXOt/Qpdu8KXXwb2sM327TBpEgwaBO3baw8xEPz8s5UBwVNEDMX3bQZPzS8LrLpnGc3aBMAnppNwNRfTSuAT4HPgkIg0qOgFRaQ6cAXQGDgda3/FJWUcWubbjTFmkjGmozGmY+3atSvaDI9Ys8ZKz7F4sa3N8Clj4PPPrdd94YXWjudgs2uXVTBeWZKT/TP4e7r30GNwNhsaHPDoOXPCC0kbu5Ladf3wF+gCV3Ix/RM4APwIfA184/xaUX2BP40xKc5d2Z8B3YFqziEnsCbB91biGj5z4ACcfz7MmmV3S7yrsBCmT7eWkl59NSxdaneLvMvTyyYDVU4OtGplbVIcNMjqZW3fbnerYP16a07JUxKqGTYMWeu5E5ayr1oGdZ/ebEuhocpypQdxP3COMaaFMaa1MaaVMaZ1Ja65C+gqItEiIkAfrCSAvwADnccMA+ZU4ho+lZtrTXj+5z92t8TzcnOt6lxNm8KwYdZ/zKrg669hvz11YfzKxx9bK/hSU63v77jDmq9p0sSav5k1C+wY6X3pJc/2alrfm8KhWC+UoHNa23ifbYWGKsOVALEba57AI4wxi7Emo5cDa5xtmASMBv4lIluBmkBA1XszBp54wlrF40+rdyoqIwOefdbarXzPPVVvpU9hoT0lHv3N22+Xff+ff1orwAYPhrp1rXxaDz5ofar3dm2VAwdgxgzPne/slkUsPN/7n3zsKjRUGSfdSV3KduBXEfkGOPbWZ4yp8E5qY8wTwBNlXKdzRc/pLz74wHoz/fxzq1seaFJTrc1mr79ufXKsyqZMsSp4SXBsinXbmjWuFacxxsqntWqV9ck+LMxauNC3r7WzvUsXCHXlncZFr73m2Q9hkfdvo9jhufOdyoJBSXTc3p1lP/nVNq+TcqUHsQtr/iGcv3ZXx3mzUYHu99+t/xTr1tndEtclJ1v7Oxo2tLKpVvXgANZY+88/290K+1R0U2hBgbV7/YknrN3sNWpY2XonTLD2ylRGdja8+WblzlFat6tyWH2W76Y77So0VFHlxnXnbmrlph07oHt3a4z24ovtbs3f7dgBS5b8dfvjD01HUZbJk61PwVVNVpbnhnEyMqw5na+dS1vq1bOWR/fta93OOMP1c733nuf2qcTGGrYP887E9KmkR+VTY9waEka0Ju2of3dPyw0QIlIbGAW0ACJL7jfGXODFdgWF9HQrL9DLL8M//2lfOw4fPj4YLF2q2U9d9fnn1rBbrVp2t8S3PvrI+vv1hv37raHYDz6wfm7a9K/hqJI6IGUpLrb+L3lKh7sOMy/BnmL0O2ofof3T21l1bxOKivw3SLgyMjgTmAX0x0rUNwywb4dagCkqgvvug02brB3YDi+PdebmWsV1SgeEbdu8e81glp9vLe/9V3m5jYPMySanvWHLFuv25psQEgLt2v3Vu+jZEyKdH0vnzPFcHZBGTYv5vZ+9Y8DLm+2m15h45o+3dz/XqbgSIGoaY6aKyP3GmHnAPBGZ5+2GBZvXX7f+uGfNgoQEz5yzuNhadlo6GKxdq0NFnjZ5ctUKECtW2LfPpbjYKh2alGStoouMtIZq+/SxenOeUvOBHewItX8eYH7fdfTc3pnfPoy2uyllciVAlLzd7BORy7A2sFUqm2tV9b//WX/sX39t5f9x1+7dxweDpCTNB+ULGzda5VB79rS7Jb7hTxmLc3OthQKeXCzQ+ZI8lpzrPzlyFt+yjNZ/dmf1Hx5c6uUhrrRonIgkAA8CrwLxwANebVUQW7/eWuH0+edWLqeTOXrU+hRXet5g3z7ftVMdb/LkqhEgMjL+mhsIRpGRhr23+dduT38uNOTKKqaStBppVJFSo94f4mxoAAAgAElEQVSWkmJ1madMgaFDrTXdK1ce3zvYssU/899UVZ98Ys0hVatmd0u864MP7Knf4StdRqQxr4bH9v16TGpsNmc/vY6YO1qQleU/QcKVXEzPiUi8iISJyE8ikioiQ33RuGCWlwc33milyI6PtzYW3XeftbRw8+aqGRw6X5JHj2tz/LLQSk4OzJxpdyu8z5eT076W2MCwuL/vl7W6yh8LDbmyUa6fMSYdaxVTMnA28LBXW1WFrFljrZSp6s5pXcSakUtZePdimr+7kRYd/C9FcrAn8Fu61LPps/1N4gO7yQ0rLP9AG/lboSFXAkSY8+ulwIfGmMNebI+qgmrVMWSMXUlOuPWfd13DA6x7fgE9/ruXOvX859PUqlXBncU2mHsP7c8vYElbP0hD6wJ/KjTkSoD4SkQ2Ah2Bn5wb5/yj9SrghYcb6j2zmb3VT1iOJbCw22ay31tE77vS/CZVcrD2ItLSrM1xwSgszHDkrg12N8N1flRoyJWKcmOAblg1pAuALKyCP0pVWucn9rO28cmXZ2VG5DPvuhXUm7mKzhfbnyb3ww+DcxJ3xgzvZ2G1S/ebM/izTmANfPhLoSFXJqlvAi4HbnB+PxDo5+2GqeDX+7YMl+v/7qp1lCWjF9H+jW00Oce+DU6ZmcH5STtYh5fqnmZIutp/J6ZPxR8KDbkyxNSp1O08YCwwwIttUlVAhwvyWTA4ye3nLT93NztfX0Cvf6eQUM2e/zjBNsy0aJG1WCIYnXn/XjIjAncViN2FhlwZYvpnqdvtQDus1N9KVUijpsVseSipwjn4ixyG+X3X4ZixhPOGZhES4ttAsWQJrF7t00t6VbD2Hlp3LeT3Llvsbkal2VloyJUexImygaaeboiqGhKqGRi/hvSoys8nHI7JYcGtSzlr+nradPft8sVg6UUcOWKVEg02Doch996NdjfDYxYMSqJjH9/3hFyZg/hKRL503r4BNhFA9aKV/3A4DGf+dzs7ah/x6Hk3J6awavxvdHthN4ln+KY3MWOGtXku0E2fHhyv40Q9hmaxOTHV7mZ4jF2FhlzpQbwAvOi8/Rfo5VzZpJRbeoxOZfm5u712/kUdtnFo6kJ633+UqCjvBoqjR2H2bK9ewieCcXipZi3DqkHBN6mSHpWPGbfGp3NvrsxBzAM2YpUZrQ4E7oyPsk3PwdnMv9D7+fdzwwqZd+VKqs9cTjcvbzYK9GGmBQtgQwBtD3BV838eIM0DQ5j+aEftI5z59HYcob4JEq4MMV0HLAGuBa4DFovIQG83TAWPVl0LWXzrMp9ec2/1DBY98AetJ2/mnNbe2XC0YIGVCjxQBWPv4dx2RfzWM4D/UVywvNluGt7rmzrargwx/RvoZIwZZoy5CegM/J93m6WCReIZhn3/Xk6BTcVZVp+1l80vL+C8sfupWcvzn7qmTPH4KX3i0KHgGCIrTcQQcv8WTEWW3gSY7U19s/TVlV9liDGmdAXjQy4+T1VxMTGGmKfXkxqbbWs7TAgs6L2Rgul/0OvWDEI92D2fNi0wky2+956VUTiYdL82h3UN7dszEIxceaP/XkT+JyLDRWQ48A3wrXebpQKdiKHVU7vZnOg/5cvTo/KYPzSJhu+vof35nqnLmpoKX3zhkVP51KRJdrfAs+LjDZuGBuaOaX/myiT1w8AkoDXQBphkjBnt7YapwNbrvqP80c4/s2duq3eY5U8spPMrO2jQpPJDX4E2Wf3LL1bNkWDS9t5UUuPs7akGI5eKoBpjPgU+9XJbVJDoenku865YZXczyrWk9Q7C3t5F7x9akPRmDTIzK1bJ66efYPt2aNLEww30kmCbnD7r3GIWXuBfZUSDhSurmK4WkS0ikiYi6SKSISLpvmicCjzN2hSx6t5l4D9VE0+pILSYeZeuIXrmsgpXszMGpk71QuO8ICXFqoceTGJHbqfI4R/p4IONK3MQzwEDjDEJxph4Y0ycMSa+MhcVkWoiMltENorIBhHpJiI1RORHZzD6UUSqV+Yayvdq1TGklSr8E0gOxmcdq2bXvL37y2LffRcKA+Blv/NOYE6qn0zXAbmsPDvZ7mYELVcCxAFjjKe307wCfG+MaYY1r7EBGAP8ZIxpCvzk/FkFiJLCP/uq2ZNUzFPWNTzAvv8sJTravU+k+/bBN994qVEeYkzgzZecSnS0YefN3t98WZWdNEA4h5auBpaJyCwRub7kPuf9FSIi8UAvYCqAMSbfGHMUqwjRNOdh04ArK3oN5XvlFf4JJEdicuk4yP2qQP7+5jt3LmzbZncrPKfTnUcC/gOJvztVD+Jy5y0eK4Nrv1L39a/ENZsAKcC7IrJCRKaISAxQ1xizD8D5tU5ZTxaRESKyTESWpaT4zxLKqsydwj+BYlv/zW7vl/j+e0j249GOYJqcbtCkmEUX67JWbztpgDDG3GyMuRmYUvJ9qfsqMyUXCrQH3jTGtMMqYerycJIxZpIxpqMxpmPt2rUr0QzlCR37VKzwj7/bUyODTpe7l8upqMga4/dH+/fDnCDKwVxn5E7yw+yrLFhVuDIH8aqL97kqGUg2xix2/jwbK2AcEJHTAJxfD57k+cpPND67mM0PLqtw4R9/d+ga9/dxTJ0KxX74vjV1amBMorui04X5LGu10+5mVAkn3QchIt2A7kBtEflXqYfigQq/JRhj9ovIbhE5xxizCegDrHfehgHPOL8G0eed4JNQzWDGrSE9KoiWxJxgc2IKHf5RQNIvYS4/Z9cu+OEHuPhiLzbMTcXF/j8/4qqICMOBEbrnwVdO1YMIB2KxgkhcqVs6UNlsrv8EZorIaqAtVp2JZ4ALRWQLcKHzZ+WHvFX4xx8VDXL/k6q/pbH43/9gZ5B84O56Wzq7ah21uxlVxkl7EM46EPNE5D1jjEf/vIwxK4GOZTzUx5PXUd7RY3Qq871Y+MefrDwnmXPbNWbDCtc7zV99ZY3516vnxYa5oTKT0+HhhsT315AdkUdUbjhReeFE5IQRnhtGaE4YoTkOJDsMsh0UZzkoznZQkBlCQXYIeRkh5GYKWZlCdgZkZoIxFd9BeXp9w5IBwVcIyJ+Vm2rD08FBBTZfFf7xJ9Vu2AsrznD5+MJCK1vqGD/YybNnD3z9dcWf3/X6LObXOWz9kJBVucYYiM0PJyY3nOi8cCJzwojMDSMsN4ywnDBCskMJyQmFLAcm20FhloNCZ7DJzQgh/qY97A3ATZiBzKVcTEqBPYV//MHittto0CSRXdtdz3I/ZQqMHg1ic8qRKVOs1VUVERlp2HSVB/fICmRG5JMZEbzzVsFG6zool9hd+MdOxQ5oONS9PTfbtllZU+1UVFS5gkZdhmZyoLK9BhXQyu1BiEht4HagUenjjTG3eK9Zyp9YhX/Wscfmwj92WtpzC7Vq1yE1xfUuweTJcMEFXmxUOb79tuIb92JiDOuuCMKC1cotrvQg5gAJwFysYkElN1UFiBhajtvN5sRUu5tiq9ywQloMdW/1zOefW6U97VKZyemON6XbXglQ2c+VABFtjBltjPnYGPNpyc3rLVN+odd9R1nc1j8L//jaqr6biIlxPf1GXh5Mn+7FBp3Crl3w3XcVe25cnGH1Zdp7UK4FiK9F5FKvt0T5nUAp/OMrR6Nz6eBmEj+7NqhNmVLxHd3th6dxJMa9NCMqOLkSIO7HChI5WjCo6gi0wj++su0y95L4bdgACxd6sUFlKCyseAGjatUNKy7RncrK4kpN6jhjTIgxJspTBYOUf6tdN3AL/3jbnhoZdB7g3qdrX/civvoK9u6t2HPb3HwkqNOnKPecqh5EM+fX9mXdfNdE5Uvh4Ya6Twd+4R9vSrnGvaIKn3wCaWleakwZKjo5XbOWYVk/nXtQfznVMtd/ASOAF8t4zAA2LuBT3tL5if38FiSFf7xly+mpdLggn6Sfw106PjsbZs6Eu+/2csOAP/+0kgVWRMtbDzMvosCzDVIB7VS5mEY4v/7Dd81Rdup9Wwbzgqzwj7cUDd4FP5/l8vGTJ/smQEyebJUWdVftuoYlF2jvQR1Pd1IrIHgL/3jLyqbJNG/veg6LlSthmZezlBQUVLxg0bm3peqck/obDRBVXGSkodewzKAu/OMt8Te4NxPs7cnqL76AAwfcf169RMMfvbX3oP5OA0QVFRdn6H1nOrEfL2X+8GW6cqUCrCR+rm82+PBDyPJiaqOKTk43ve2glu9UZXI7QIjIaSIS4Y3GKO+rWcvQ+19HkFl/MG/QclLjNJ1CRZkQaHiT60n8MjLgo4+805atW+Hnn91/XmIDwx89dd5Jla0iPYj3gY0i8oKnG+NLDkcFZvIC2GmJhl7/TiF75kLmXb6K9Kg8u5sUFJZ030ytOq7/LXlrmGnSpIpNTje+fX+VzNCrXON2PQhjTF8REaC5F9rjO3dtpePZoYT9eBrL/xdBXl5wbhludFYx9YcdYHHXLezTNwKPywsrousNR5j3cg2Xjl+8GNasgVatPNeG/Hx49133n9egSTGLum32XENU0Cm3ByEi75dx93RjTECXFStyGJa13MmiB/4g4vM/6Dl2P626BM8qjnNaF9H1hd3sfHs+v/XcpJ8SvWjlhZuIjbWvF/Hpp5BagWS7Z4zYR1EV60kr97jSg2hR+gcRCQU6eKc59kiPyuO33huhNzRIrUbj+Y3YOieBPbsCr1fRumshYTfuJqm5Vor1lbSoPHoNymT+1DiXjp8xA557DiIjPXP9ikxONzmnmN87bfFMA1TQOmmAEJFHgEeBqFLJ+QTIByb5oG222FXrKLuuXglXQZtticTNTWTVt1FkZPh3sOjYN5+863ewukkFk/CoStnSfzOh09pTWFj+38mRIzB7NgwdWvnrbtwI8+a5/7y6t+/BjQqqqoo61U7qp4GnReRpY8wjPmyTfxBYddYeOGsPUbeE0n1lI3K/q8vK+aEUF/tHsAgJMXTpn8eh67axLNG9kpjKs/ZVy6D7Fbn8/mmUS8dPnuyZADGpAh/Vzm5ZxKL27uWTUlWTK0NMX4tIjDEmS0SGAu2BV4wxVWYMIye8kN87b4XOW6mXFss5CxuT/FV1tm205yNYWJihyzU5JF+9hUW1j9jShkAQAsSGOIgVB3GEEFscQmxRCDGFQmy+EJ0rxORCVBZEZ0F0hiEqzZAbK4y5IB13R+dTrtkGn7Z06dj582HTJjjnHLdf1jG5uTBtmvvPq3ZbsqZxVy5xJUC8CbQRkTbAKGAqMB3o7c2G+av9CZnsv3QNXArn7q5L7Z/PYN3XMRxK9f7/uOhoQ8fBmWwesJnfEoIz26pgvanHSQixOIg1IcQVhRBd4HxTzxNiciA623pTj3K+qUceLSbqiCHiUBGRqcVEphQRnlqMmCLA9ZQYJa7oFs8XUe6VPdlyWiod++azbK5rSfymTIHnn3e7acd88gkcPuzec85tV8SSNn9W/KKqSnElQBQaY4yIXIHVc5gqIsO83bBAsOGMA2wYdoDQoSF0XtsQ/lePFXPDKSjwbLBIqGZoOzSNNRdvYn5MjkfPbQcBEh3hNC0Ip/EhBw12wulrC6n3Rz6xmwtKvanbl1n0hqfy+PppodDNzQUF1+2EuU1dOnbaNBg/HsJdiyd/U5HJ6Zhbd7l1fFRICC9Pj2L29cJch3vV9FTgcyVAZDgnrG8EzhMRBxDm3WYFlkJHsfWprM2fVL8nkpaLm3Dom5qsX1655EZ16hma3XSY5RdsYl5E4KXCCBPhzJAIzswOo/HBEOpvM5y+ooA6v+cRkZqPtd7BP9ValMegIwnMrOZeIYdVTffQokMT1iWV/2+fkgJz5sC117rfvnXr3K9U17JTIctauDcyPDw5jnOmpvHvqXDFP2N55doCthbpJsuqwpUAMQgYAtxijNkvIg2ASnSMLc5AswzYY4zpLyKNgY+AGsBy4EZjjP++g5zEkZhcFlywHi6AJgdqcMavDdn0VTz797jeq6jfsJjGw1JY0nMz88PcHx7xtfgQB2ebCJpkhNJwj1B/YzGnLcunxpI8HPm5QGDWN772/7L59LUQco17e0hib9gDSQ1cOnby5IoFiIr0HsJudS841HCEcvnDf/UaWr6ayZtT4acXEnijRSbpxf7/t6kqp9wA4QwKM4FOItIfWGKMme6Ba98PbABKypc+C7xsjPlIRN4CbsWa/whY2+seZvugw8i10G7zGUTPPZ0V30WSnV12sDizWTF1h+9jccetJPvhBqbE0HDOzA+nyRFrWChxXSF1F+WTsKEACL6cTglrC7hpXwKT6rnXi1jSZjuNzqrPjq3lL2KYO9cq8tO4sevnz8mB98vavnoKbboXsuKc3W49Z8SaGKL2Hv/aQ7PhorvT6H52KDNfiOfjOPcn81XgKDdAiMh1WD2GX7GGj18VkYeNMbMrelERqQ9cBowH/uVM3XEBVk8FYBowlgAPECVMCKxothua7Sbm9jB6LG9C1re1WLUwFGOEFh2KiLkxmSWt/2SbzatLQkVoEhLBmTnWsNAZ2w2nryyk7sJcIg7697CQNwwYk8lH0x1ufVo2IVB/6EF2jK1X/rEGpk6FceNcb9NHH8HRo64fD2Bu3u7W8WeEhnPB6JMHxrjNhdw5IJ3LrozmtZHCEuPFNLXKNq4MMf0b6GSMOQggIrWBuUCFAwQwAWtFVMnW05rAUWNMSa6LZCCxrCeKyAisUqg0aOBaN96fZEUUsLDbJui2icTDcdQ8EsfqM+3d3NYoNIL7vwzntKUF1PojF0du4A4LeVrMziJu3pbAK43d60Us7b6F2nXrknKg/Ij/7rvw5JPgcHHKyt3hpfa9C1h+lnt/Y3f/HElYZvkfBs74Iptn5sCSx+OZ2CeHvUVasjSYuLKQP6QkODgdcvF5ZXIOUx00xpQuX1bW/6Iye67GmEnGmI7GmI61a9euaDP8wp4aGbYHh2oOB888LrR9PoO6v+bi0LjwN5eMyaCWw728lnlhRTQf6toelb174ZtvXDvvqlVWwj+32nKze5viWjqi6Pwf15f4ioEuT6bzzpWF3JOcQIToJotg4cob/fci8j8RGS4iw4FvgO8qcc0ewAAR2YE1KX0BVo+imjPPE0B9QHNGeFmYCM++F0ndXzQqnErEwWJGrIpx+3kr+riexM/VBH7u9h469s1nXcP9bj3nro8chFRg/jnisGHgjWnMHBXGJfmu5aUKFA6gT1Esz8+N57GVCZwRWsG1yQGm3ABhjHkYeBtoDbQBJhljRlX0gsaYR4wx9Y0xjYDBwM/GmBuAX4CBzsOGAXMqeg3lmicXxHH2Ozp27IrzH0mjvptvCulRebQf7Nrege++gz17Tn1MVhbMnOlWE8gcttWt488zsTR/o3L7HWouyWfURRm8NSOGcx2upR7xVy0cUYxen8Bnd4fxWN9MOo5Pp88Dabx7YT7jF8ZztsNDGRf91EkDhIicJSI9AIwxnxlj/mWMeQA4JCJneqEto7EmrLdizUlM9cI1lNO9uxLo9n/u7RSuysIyYcRv7r8ZbO6/mbCw8nsRRUXwzjunPubDDyHdjX+yLpfmsbH+wfIPdBLg9omeSwt/ztQsXu2Tw/+tTKC6m0N0dqrjCOOWlARmvBjFa71yuPieNOI3HD+34siF7o+l8+Y/cnnp+3jahkTb1FrvOlUPYgJQVj6HbOdjlWaM+dUY09/5/XZjTGdjzFnGmGuNMbobx0uuzo7nmmHuTboq6P54Ok3d/MS4PyGDzle6NoQ3dSoUn+L9+a23XL+uiOHwUPfSeV+eG88ZX3h2ubKjAC54II33bzTcdCSBym0d9Z4IES7Pi2Pi53F80LeAG69LI/Hr8rMWhBRBu2fTebl3Nm/MiqU77g9F+rNTBYhGxpjVJ95pjFkGNPJai5RXdSWGOwdpz6EiHAVwx3fuJxE4cPU2RMrvRezcCT/+WPZjSUnWzVVdB+Sx5TTXqwiFiXDjf7z3mSxmZxE3X53G9Gej6OlHb6KdJJqxyxL4fGgI/7o4g1YTM3BUcCX3uW9lMv4fWUydFM2FhcExB3OqAHGqj0qBPbBYRZ3liOCx4bmEaUqdCmv/TAZtQtz7899aL5WOfV1b/nmyyWp3JqcdDsP+Ie6VEh2SGk+tRd7vtJ/+fQ5P/SOLl76Pp4FNE71nhIZz7+4EPv6/CJ47P5veD6cRley5XeFNPszm0QszmPFcJFfmxPttr8kVpwoQS0Xk9hPvFJFbATc+yyh/UNMRyn/HWJ/kVMWJgRGz3P8vn3fdDpeO+/JLOHjCtEFGhjX/4KquV+XyZx3X07zGhTgYOMa3ixXaPZvOlEsLeGB7AtEh3k+bHxvi4LrMeCZNj2Far3yuuSmN2r95NyAmfpfL/Zem89GjEQxJiyc8AJf/nupfZiRws4j8KiIvOm/zgNuw0mSoABEhwnNvRVD7d53W8YTmb2TSzc1hktVn7aVlp/JrnhcUWBvnSps5EzJd7PWFhhp2D9roVttu2RZL7Fbf12MPyzAMuDWND+4N5aqc+PKf4KYQoFdxLM/Mi2f2VcXcdXk6Td/NwoXRPo+qtSiP269M5+N7Q7ntQAIxPgiInnLSlhpjDhhjugNPAjuctyeNMd2MMe4trFa2EeCpuXE0+UCXs3rSbS7uWygteohrW3umTLFScJRwZ3ip67U57Krl+gKEuo4wLhllb22RhDX53HdpOlMnx3hkNdDZjkge2pLApyPDebJPJl3GphNx2P6MUQlrC7hhcBqzbhLu2xkYK7tc2QfxizHmVeftZ180SnnOA9sS6DROJ6U9rckHWfQtcm8icmnr7TRqWv4y0q1b4ddfre8XL4aVK107f3i44c+BG9xq0x1LoolI9dzS1spo8kEWL16QzVN/JFDbzTfPGo5Qhh1O4L1Xo3m7Vy6XjUij2ir/zBsWs7OIq4an8eHAYkZvSKCew3+rJwROX0e57bqMeC6/TZezesvwlwrdqtxpQqD+ja7tSyiZrHan99BlcBZ7arjeGzjLEUGvR/3r7yOkCHo+ksa0QcXcdjCBsFOM24eJcHFBHC9/G8esiwsZfk0aDT8LnKzCEQeLufjuNKZfWsDYpfE0Co2wu0l/owEiSJ1nYhlxnfYcvCnx2xwGuDl2vqTrZurUK3+447PPYPt2mDXLtfNGRhq2XO3e3MNd30RUeEmnt0XtK+aGQWnMeCKCPkWxxz3WLiSax1Yl8NktDkb3y6Dt8xmEBk5c+JuwTOg9Kp0pF+Tx7M/xNPej3ecaIILQOY5IHhmao4n3fOCG8XmEurE6JT+smHNvLH+FUV4eXHUVZLv4xtd5SCb7E1xfv9whJJr2z/r/B4g683J5rG8mEz+L5a49CXw4LpKXemfTZ2Qasdt9P7HuTY4C6PxUOq/1zuGVOXF0FPt3Z2uACDJ1HGH898FiovbqclZfqL0wj0FH3etFrPjHJuLiyu9FrP7bNtWyRUcb1l/p3tzDnVMDa8llq1czuW5oGvV+Cv5PPWKg9YQMnj8/m7enx9C7OLb8J3mJBoggEhUSwnMTw6ix1E/HDYLUtY9lEymu/1dKj8qn3WDPrRzqdFMGqXGuj7H0LYrjrOm6qi0QnP1uFmP7ZDJtYjSX5Me5NeflCRoggoQA47+JoeHsAB6MDVAJawu4cb97K5o2X+ZaEr/yxMUZVvdf7/LxIcAtzwXX0ExV0ODzbEZdlMEHT0UyMCv+lJP3nqQBIkiM2pBAu+fsXc9elV3xSBZxIa7vsN6fkEmXq8pPBlee9sPSOBLj+rDLwMx4Tvuh8tdV9qj3cy739E/n6Sd989atASIIDD2awMV3+9dyxaom5s9Cbtnm3ljxvqu2upTE72QSqhlWXOr63EOkhHD9Y8E/hl8VRB3wzRyjBogAd0FxLMMHaXDwB+6WJt1W7zAdL6x4Dee2Nx8lPcr19Ck37Y3z281jyj9pgAhgLRxRPDwk22/Xslc1EQeLuX21ezmacgftqNC1atQ0JF3keu+huiOUK0dpGl/lHg0QAeo0Rxjj/llE5AH/SJOgLP94JJ1EN9JYr2myl1Zd3J80bnXLYTIjXP9kcPu6GI+mtFZVgwaIABQTEsJzz4fqcIEfCssw3PGbeztho64vpxj1CWrVMSzt43rvoX5oOH1H+f+mOOV/NEAEmBDg6c9iqP+VrkTxV92fSOMsh+t5dZa0/pPGZ7veE2xxWyrZEa73Ou7+NZKwDPuzmarAowEiwDy6KoFWr+hyVn/myIc7vnejWppA4o0HXDq03umGP853PedSc0cUXcZq70FVjAaIAHJzagJ9RuqKpUDQ4Wn3SpMu7rqFuqeV/yn/7NsOkhfm+lzCXZ84CNGpB1VBGiACxEWFcQwdrMEhUIiB2z92feNcQWgxzYaeOolf4hmGRedtcvmcPYih5au6cklVnAaIANA2JJoHBmXqJ8EA0+L1TLq6UZp0xT82ER9/8l5E4xEHKAh1fa7i9td13kFVjgYIP1c/NJwn7yzwi5KJyn23u1GaND0qn3bXlz2/1KBJMYu6ud576J8Xp3m5VKVpgPBjcSEOnh3vIH5DxXfbKntZpUldT8Gx8ZJNhIf//cPAGbfvp8jh2oeEUBFuGqdLoFXlaYDwU6EiPPthFKd/r8tZA93wl4pcTtN8ICGLTick8Wt8djGLOm12+XrXH46n9m+up+BQ6mQ0QPipx5bEce5bOsEYDBK/zWFArutFhfZefXwSv3q376XYxfnumJAQrn1Eh5aUZ/g8QIjIGSLyi4hsEJF1InK/8/4aIvKjiGxxfq3u67b5ixH7EuitO1+Dyg3jXC9N+medw3S6yBoiOqt5EYs6bHX5Orf+GUfcJh2SVJ5hRw+iEHjQGHMu0BW4R0SaA2OAn4wxTYGfnD9XOf3z4hl8gy5nDTa1F+Zx3VHXiwplX7sDgJq378HV8ak6jjAuHaWbKJXn+DxAGGP2GWOWO7/PADYAicAVwDTnYdOAK33dNrt1lGjuG5RBJUoEKD923f/lulyadFLYshAAAAjRSURBVG2TffQansniNttdPv8dSdFEHNTkjcpzbJ2DEJFGQDtgMVDXGLMPrCAC1DnJc0aIyDIRWZaSkuKrpnpdw9AInrgtn7A0jQ7BKmFNvlulSefftMzl3kOT0Ah6P6I9T+VZtgUIEYkFPgVGGmNcHnA3xkwyxnQ0xnSsXbu29xroQ9UcDp59XIjdqrWCg51bpUndKDt813fhOLRYnPIwWwKEiIRhBYeZxpjPnHcfEJHTnI+fBhy0o22+FibCs+9FUvcX/d9dFcT8Wcgt290rTVqediHRdHha5x6U59mxikmAqcAGY8xLpR76Ehjm/H4YMMfXbfOmSAmhjiOMJo4I2oRE0Z0Y+hXGMX5uHGe/k2V385QPXTLavdKk5blzmui8lfIKz/2Vuq4HcCOwRkRWOu97FHgG+FhEbgV2Adfa0LbjRIgQF+IgThzEFocQWxxCTGEIsQVCTJ4QnQsxORCdCVGZhqh0Q3SaIeJIMVGHDRGHiohMKSLiYBGO3GJAJxCVVZr0ttVxPNOi8nMGfYpiOfsd3S+jvMPnAcIY8xsnH13t46t29N0QTr0NCURlFBOVZoh0vqlHphYRkWLdQrMN1qpcnRtQnnXBI+m8/204ewornhIjBLjlBc3gqLzHjh6EX2jxQz7V39BVH8oeYRmGOxZG8XiXigeIq7PiOf173VCpvEdTbShlk+6Pu1eatLQIEa5/XBc2KO/SAKGUTRz5cMf/KhYgbtofT43lmrFVeZcGCKVs1OG/6bR2uF6aFCDB4eDKUToxrbxPA4RSNhIDI2a5XpoUYMSGWKJ36eS08j4NEErZzJ3SpImh4VyomX6Vj2iAUMoP3DbVtePuXBCp+bqUz2iAUMoPnDmj/NKkzRyRdHtCew/KdzRAKOUnhk84dWnSuz4Nw6G1gJQPaYBQyk8kfp3D5ScpTdqVGFq/ogn5lG9pgFDKjwwdX3Zp0jve1HkH5XsaIJTyI7V/y+PaE0qTXpofR6OPs21qkarKNEAo5WeueyKXCGcvwgEMG687ppU9NEAo5WeqrcrnxgPWXMTgownUmZ9nc4tUVaUBQik/dOWYLOo5wrjuUR1aUvbRAKGUH4r5s5BXR4cQv0HXtSr7aIBQyk/VWqRDS8peGiCUUkqVSQOEUkqpMmmAUEopVSYNEEoppcqkAUIppVSZNEAopZQqkwYIpZRSZdIAoZRSqkwaIJRSSpVJA4RSSqky+V2AEJGLRWSTiGwVkTF2t0cppaoqvwoQIuIAXgcuAZoD14tIc3tbpZRSVVOo3Q04QWdgqzFmO4CIfARcAaz39IUiG0QS2z7W06dVSimvi24W7ZPr+FuASAR2l/o5GehS+gARGQGMcP6YKSKbfNQ2b6kFpNrdCD+iv4/j6e/jL/q7KLEcmFap30dDVw7ytwDx92rtcFy1dmPMJGCSb5rjfSKyzBjT0e52+Av9fRxPfx9/0d/F8Xzx+/CrOQisHsMZpX6uD+y1qS1KKVWl+VuAWAo0FZHGIhIODAa+tLlNSilVJfnVEJMxplBE7gX+BziAd4wx62xulrcFzXCZh+jv43j6+/iL/i6O5/Xfhxhjyj9KKaVUleNvQ0xKKaX8hAYIpZRSZdIAYRMROUNEfhGRDSKyTkTut7tNdhMRh4isEJGv7W6L3USkmojMFpGNzr+Rbna3yU4i8oDz/8laEflQRCLtbpMvicg7InJQRNaWuq+GiPwoIlucX6t7+roaIOxTCDxojDkX6Arco2lFuB/YYHcj/MQrwPfGmGZAG6rw70VEEoH7gI7GmJZYC1gG29sqn3sPuPiE+8YAPxljmgI/OX/2KA0QNjHG7DPGLHd+n4H1BpBob6vsIyL1gcuAKXa3xW4iEg/0AqYCGGPyjTFH7W2V7UKBKBEJBaKpYvujjDHzgcMn3H0F8P/t3U+olFUcxvHvU7rpCi4Kzf6ABVG26mb2TwjRaBX9WbgzNINok7QpyE1URC0i2kVghZAoYZYuooRSItBLaGFBRFFiN0xFyrCIyp4W5wizeBeNzPW8t3k+MMzLmYHzm8XwvOe88Dub6/Vm4L5Rz5uA6AFJi4FJYKptJU29DDwB/NO6kB64GjgBvFG33DZJmmhdVCu2fwReBI4AR4FTtne3raoXFto+CuWGE1gw6gkSEI1Jmge8DTxm+9fW9bQg6W7guO0DrWvpiTnAjcArtieB35iB7YPZou6t3wtcBVwGTEha07aq8ZCAaEjSXEo4bLG9o3U9DS0H7pF0GNgGrJT0ZtuSmpoGpm2fXVFupwTGuLoT+N72Cdt/ATuA2xvX1AfHJC0CqO/HRz1BAqIRSaLsMX9l+6XW9bRk+0nbV9heTHn4+JHtsb1DtP0T8IOka+vQKmag5f0scgS4VdJF9X+zijF+aD9gF7C2Xq8Fdo56gl612hgzy4EHgC8kfV7HNtp+r2FN0R+PAltqT7LvgAcb19OM7SlJ2ylNrv8GPmPM2m5I2gqsAC6RNA08BbwAvCXpIUqIrh75vGm1ERERXbLFFBERnRIQERHRKQERERGdEhAREdEpAREREZ0SEBER0SkBEdGYpAtb1xDRJQERMQRJzw6e3SHpOUkbJD0u6VNJhyQ9PfD5u5IO1LMMHh4YPy3pGUlTwFif9RD9lYCIGM5r1PYGki6gtAY5BlwD3AzcACyVdEf9/nrbS4GbgA2SLq7jE8CXtm+x/cn5/AER/1VabUQMwfZhSSclTQILKW0flgF31WuAeZTA+JgSCvfX8Svr+EngDKVRY0RvJSAihrcJWAdcCrxOaR73vO1XB78kaQWlE+lttn+XtBc4e1TmH7bPnK+CI85FtpgihvcO5fjHZcAH9bW+nu2BpMslLQDmAz/XcLiOcrRsxKyRFUTEkGz/KWkP8EtdBeyWtATYV7pRcxpYA7wPPCLpEPA1sL9VzRHnIt1cI4ZUH04fBFbb/qZ1PREzJVtMEUOQdD3wLfBhwiH+77KCiIiITllBREREpwRERER0SkBERESnBERERHRKQERERKd/Aaifp4svNe+uAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "year = [1,2,3,4,5,6,7,8,9,10]\n",
    "\n",
    "# are in the thousands\n",
    "taxes = [17, 18, 40, 43, 44, 8, 43, 32, 39, 30]\n",
    "overhead = [30, 22, 9, 29, 17, 12, 14, 24, 49, 35]\n",
    "entertainment = [41, 32, 27, 13, 19, 12, 22, 18, 28, 20]\n",
    "\n",
    "plt.plot([],[], color='m', label = 'taxes')\n",
    "plt.plot([],[], color='c', label = 'overhead')\n",
    "plt.plot([],[], color='b', label = 'entertainment')\n",
    "\n",
    "plt.stackplot(year, taxes, overhead, entertainment, colors = ['m','c','b'])\n",
    "plt.legend()\n",
    "plt.title('Company expenses')\n",
    "plt.xlabel('year')\n",
    "plt.ylabel('Cost, in thousands')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "labels = 'Taxes', 'Overhead', 'Entertainment'\n",
    "\n",
    "sizes = [25,32,12]\n",
    "colors = ['c','m','b']\n",
    "\n",
    "plt.pie(sizes, labels=labels, colors=colors, startangle=90,shadow = True, explode = (0.09, 0.09, 0.09), autopct = '%1.1f%%')\n",
    "plt.axis('equal')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "## loading data from csv.py\n",
    "import matplotlib.pyplot as plt\n",
    "import csv\n",
    "\n",
    "x = []\n",
    "y = []\n",
    "\n",
    "with open('-.txt','r') as csvfile:\n",
    "    plots = csv.reader(csvfile, delimiter=',')\n",
    "    for row in plots:\n",
    "        x.append(int(row[0]))\n",
    "        y.append(int(row[1]))\n",
    "\n",
    "plt.plot(x, y, label='Loaded from File')\n",
    "plt.xlabel('Plot Number')\n",
    "plt.ylabel('Randomly Chosen Tutorial #')\n",
    "plt.legend()\n",
    "plt.title('Awesome Graph')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#loading data with numpy.py\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "x, y = np.loadtxt('example.txt', delimiter = ',', unpack = True)\n",
    "\n",
    "plt.plot(x, y, label='Loaded from File')\n",
    "plt.xlabel('Plot Number')\n",
    "plt.ylabel('Randomly Chosen Tutorial #')\n",
    "plt.legend()\n",
    "plt.title('Awesome Graph')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}