BoE_interest_analysis.ipynb

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  "metadata": {
    "colab": {
      "name": "BoE interest analysis",
      "provenance": [],
      "authorship_tag": "ABX9TyP0pIyRuZP4Z6pfaS2DHsvL",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
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      "cell_type": "markdown",
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        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/DataMinati/Super-Notebooks-1K/blob/main/BoE_interest_analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "w_E2Ny_D0MaF"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline\n",
        "import seaborn as sns\n",
        "sns.set(style='darkgrid', font_scale=1.4)\n",
        "from datetime import datetime"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Read in data\n",
        "interest_df=pd.read_csv('https://raw.githubusercontent.com/MainakRepositor/Datasets-/master/Bank%20Rate%20history%20and%20data%20%20Bank%20of%20England%20Database.csv')\n",
        "\n",
        "# Shape and preview data\n",
        "print(interest_df.shape)\n",
        "interest_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 223
        },
        "id": "2_PJBptx1AoG",
        "outputId": "7bc84b05-9c5f-4ebf-94cc-9105364f7523"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(239, 2)\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date Changed</th>\n",
              "      <th>Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>16 Dec 21</td>\n",
              "      <td>0.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>19 Mar 20</td>\n",
              "      <td>0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>11 Mar 20</td>\n",
              "      <td>0.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>02 Aug 18</td>\n",
              "      <td>0.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>02 Nov 17</td>\n",
              "      <td>0.50</td>\n",
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            "text/plain": [
              "  Date Changed  Rate\n",
              "0    16 Dec 21  0.25\n",
              "1    19 Mar 20  0.10\n",
              "2    11 Mar 20  0.25\n",
              "3    02 Aug 18  0.75\n",
              "4    02 Nov 17  0.50"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Figure size\n",
        "plt.figure(figsize=(14,6))\n",
        "\n",
        "# Time frame = 30 years\n",
        "xx=np.arange(0,30.1,0.1)\n",
        "\n",
        "# Compound interest\n",
        "yy1=1000*(1.001)**xx\n",
        "yy2=1000*(1.01)**xx\n",
        "yy3=1000*(1.05)**xx\n",
        "yy4=1000*(1.10)**xx\n",
        "\n",
        "# Aesthetics\n",
        "plt.plot(xx,yy1,xx,yy2,xx,yy3,xx,yy4)\n",
        "plt.legend(['0.1%','1%','5%','10%'])\n",
        "plt.title('£1000 investment over 30 years at different interest rates')\n",
        "plt.ylim([0,18000])\n",
        "plt.xlabel('Time (years)')\n",
        "plt.ylabel('Savings (£)')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "L2ssdDzc0mce",
        "outputId": "74316a67-eab2-4768-dabc-11dd79112e71"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Savings (£)')"
            ]
          },
          "metadata": {},
          "execution_count": 2
        },
        {
          "output_type": "display_data",
          "data": {
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rwvc8nrxzKf2M69oS2gp3Aq7rWPBXySW4P3jH4btvzEsAj+YAAxKE0TvA/V53rtB7pmDfr8abi5L0eqOBDQeGGze63c+4C4MvvCL5dSMNh2Ccq8N4IVDcWFcBnY0xCSGta8H7ulb6luXeM+jd33Qe8ErI+bIc17VuXgHdb8tCddxFbTLuwqvU56jXkvgmcJMx5m5cq927Nu+0E8txF6vf2QNPtH0GbnTTy0Putyr2fG9FOFfz0xPXxTjPIA/GmHq4z05QSc6do/L5zihswJOSCMd5tRw3ymc4fggLKq9z/ED7Cn6P7CjFsUXrd2ZxPjuFvT9F+p61bmTVpcAzxg0y9CPuvrabihO4SHFUlF/NRCT8PsfNV/SPkOX/wCVgH/uWvYf7o9gzuMDr198TN0DBbgBvsJPPcPfz1PatfzWuS9i7lL23cT9EXQVcRN57psC1iqThfu2tGrqy2Tf6Vw3jRojLZa1dg5twua5v8U7KpuvTdNwv6o+Y/UezC77/xRWcL6mo8X6MGw67r2+/8bgWjD34kmDfPYPn4wbPSCJviya4RLoJ+59zGGOSjDHJRYxrP8aY0G5qePfNXA78Za3d5MUZrnN0Ei4BHIt7PyeHvP4O7m/sfpM3G2MSvGQI9rWa+Idrj8d1tyqSYpyr+dlLSAuNMaYP+49wV9xzZzauroPdT4MjRN5YxPWLIxzn1TvA8caY7vlsI9l3L2lxBEefLYvvh3z3xf718yOuxWlgfu+D2X9U2fxE63dmcT47BdVFkb5njTG1jTGhDRy/4X4AKuwzJlIqalkTqQCMMVfhkiWAo73nfh/YfcPSt8ZdeIIbohrgLmNMOm4+myngbvY3xjwMjDbGTMcNwHEqLsl51LuJPeg93FDJE4wbpnkzbujiRFw3F78Hcd2pvjTGjMV1SbkHlxzOKul7UFTW2iXGmKW4Eb5qEpIwWGu3G2NuxQ37/5Mx5i1cl7ZWuNagpbjuPu2Bz42b/HspLjnpDnQg771Ji4HbjDGP4u7HSbfW+rvDlfQ4/jRu5LsXgNbGmA9xF0xtcV2M3sENn10cy3Hd7/7hnQ87gCXWjaaZn/G4Uf0mGGM647qCXQKchZuHK/RejeA9g08DK62134W8/gbu4n20ccOJBwcCMLh7wHpy4FagA1lgjPkv7uJ0M+5+uutxF/G9Q8qW+hy11v7i7a8XbsjvBSGvf2WMGQ3c6/0C/ynuHDoE9x48guuqtQDXXXKSMWYkbkTJy3GJY1EV9VzNz0e4uRK341odj8a9X6Hd/kpy7tzhHdexuO5zV5H/wC6lFY7z6gXcjzszjDGTcOdRddxoqD1xUz6sLGZcwfsnR3mtzdn4phAJs59wScc/jRuVcTewyLvX6gbcsPv/53XjW4NLxk/HvU+hA7DkEcXfmcX57BRUF0X9nj0Td369hxvcJQ73OUn2yoiUGbWsiVQMU9g3X01v77n/n//X0ba4ROVJ9v0Rvt97foN/o9bal3HdNzri5o45BXex/WRIub24P7pv4eYwGoL7I3mmtfa3kLL/wY0SuNOL+VbcAA+XlmPXt7dxf0RD75kKxvgO7r1ZjTvel3CtR7+xb06lv3AXJ6fi5oh6AXdRf4O19kXf5p7A3as0ENetbmS4DsIb/voS3AhrD+Hm7LoUd+FZ7FZK6+ZEuxrXcjoaV5+XH6B8Bu59moSbvPtF3H1dN1tr9xsW3hvc4w8KuIDxusP9HTc/WEfce/o4bs68l3FzxJXUONwF6CDcaHbB0SC7hgy1Hc5zdJL3+EZ+61lr78B95urjzqFncfe6TMMlhlhrt+JGzfwL9148gBuFrl8x4ijquZqfAbjBJ3rj3ovDcRfgeQaEKMG5swuX1M/FJW0P4xLk+wpap6TCcV55vQO6As/hfuQajquLDrjvww0lCO19bztn4Vpe3yLvd3XYWGs34s75erhE+S1cMoY3kuSJuB/cbsMNw389rmfFc0XcftR9Zxbzs1NgXRTxe/a/uB80u+P+/j2JS9guCf1+EQm3uECgPLtU52XcbPD34L5EOuHm9ugUUqYK7ovhOtyvOBuBD3G//G/3lUvEfQFcg2uS/gEYEDo8rzGmKW6OnPNwfZg/Bu7yDbccLPc33Af2WNwX2qvAE/mMiiYiIpWQMeZ23IWvsdaWxSiHIiJSyUW6Ze1w3K8if+BGcsrPI7hJByd7ZV/AJW6TQsoNw41E9iiu6ToTmGeMye137yV+c3DdGfrh+s6fDHzk76tsjGmHu6dhK25ks6dxv9j9q+SHKiIiMeZG3CTRStRERKRMRPqetZnW2hkAxpiJuNG5QvUFplprn/aezzfG1MKNxFPTWrvTGNMC143lTmvteG973+HuI7iLfd0uLsPNo9LJG9EHY8w6XL/n83E3RINLzNJwM9XvwSV9dXA3oD7vNb2LiEglY9yEuD1wXcyO5gBdAUVEREoroi1r+UyWmZ9E9k0iG5SG6yscbA07B0jAd4+EtXYHroujf2Sn7sCvwUTNK/ctbojh0HIfhgzDPBU3utmZRYhZRERiUyPc34PewPPW2ukRjkdERGJYpFvWiuJV3JCzH+Fujj0Md5/bRN/cNR2AjfmMTLYUNzxzcJ6XDuTf3XKpt93gr6atQstZa1caY3axb34hERGpZKy1Kym/icZFRKSSi/pkzVr7pHev2Vz2/YF8FzecdFA9XGtbqFRcy1wtYHsh5Tp6/w/Ol1FQufpFDD0JOB5Yz765QERERERERPwScKMt/0DIFCdRn6wZY+7ADS08EPgPblCSJ3HDxt4WwdAKczzwdaSDEBERERGRCuFU3FyRuaI6WTPGNMDNZ3GftfYlb/FX3uSdbxhjhnujcKWS/wzy9XCTJAa7Sx6oXHDQkGCLWmHlCrMeIDV1Jzk5kZsewa9Bg1qkpKQXXlAqFNVr7FLdxibVa2xSvcYu1W1siqZ6jY+Po169muDlD35RnawBB+O6E/4csvwn3+u/4yZlbGyMqR8yUmNH4HffQCa/4UbvCtURmAXgjS65Gnd/Wy5jTGugBrCsiLHvBcjJCURNsgZEVSwSPqrX2KW6jU2q19ikeo1dqtvYFIX1ut+tU5GeZ60wq7zHY0OWB5+v9B7nAjlAr2ABb3j/i9g3HD/e/48wxnTwlTsRaJNPuUuMMVV9y/rg+pDOK8FxiIiIiIiIFEtEW9aMMTXYN2R+a6C2MSY4Z80P1tpVxpjpwBPGmATgR9w9a48Dn1lrfwOw1q41xrwCPGeMycYleffgBiQZ7tvldOAX4D1jzD9xx/8CsBD4xFfuBeBKYJoxZiRggIeB4dba1LC+CSIiIiIiIvmIdDfIxriRHf2Cz68DJnqPDwG3AC1xfTnfBB4NWe9u3L1pTwF1cKOpnG2tXRcsYK3NNsacB4wA3gACuLnYBlhrA75yfxpjzgaG4bpHbgVexCWJIiIiIiIiZS4uEIi6vpqxog2wIiUlPWr6wzZqlMzmzTsiHYaEmeo1dqluY5PqNTapXmOX6jY2RVO9xsfH0aBBLYC27LvNy70WiYBERERERETkwCLdDbLS2717J+npaezdm13m+9q0KZ6cnJzCC8awhIQq1KpVl+rVa0Y6FBERERGRA1KyFkG7d+9kx45U6tZtRGJiVeLi4sp0f1WqxJOdXXmTtUAgQFZWJmlpmwGUsImIiIhUQrvsMjb+soP4I4+PdCiFUjfICEpPT6Nu3UZUrZpU5omaQFxcHFWrJlG3biPS09MKX0FEREREYsqetWtY+9Iwti76PtKhFImStQjauzebxMSqhReUsEpMrFou3U5FREREJHrs3bWTdaNHEl+tGu1uuTnS4RSJkrUIU4ta+dN7LiIiIlK5BHJy2DB+LFkpW2h+6+0kNagf6ZCKRMmaiIiIiIjEtJSZM9j56y807t2H6oe2j3Q4RaZkTcLir79WM3Bgf7p1O5ULLzybYcOeJyMjo9D15s2by4MP3sull3bnlFOOY+rUKfuV2bt3LyNHDuWCC86iZ88ezJ37yX5lnnzyYSZMGBuWYxERERGR2JH+809snTmD2id3oc4ZZ0U6nGJRsialtmPHDu6881Z2797Jk08+x+2338Vnn33KM888Xui68+fPY926tZx88ikFlpk9eyazZn3EwIGD6dHjUv71r8dYvXpV7uu//vpffv75J6688pqwHI+IiIiIxIbMDevZMGEcSa1a0/iqayrc7TAaul9KbcaM6ezYsZ3XX59K3bp1ATef2RNPPMQ119xIu3YHF7juE088Q3x8vLed9/Mts2jRQrp1O5+zzuoGwJw5s1i8+HtatWpNTk4Ow4cP4R//6E+1atXCfGQiIiIiUlHt3bWLtaNGEJdQhea39ye+asUb2E8ta1Jq3333Lccee3xuogbQteuZVK1ale+++/aA6wYTtQPJysokKSkp93lSUjWysjIBmDXrI5KSkjj77HNLGL2IiIiIxJpATg7rx71C1ubNNLvtDhIbNIx0SCWiZE1KbeXKFbRp0y7PsqpVq9K8eUtWr15Z6u136HA4X345n/Xr17F48ff88cfvdOzYifT0dF59dQx33XVPqfchIiIiIrFjy/vvsWvJLzTucyU12ptIh1Ni6gYppbZjx3Zq1Ureb3lycjLbt28v9fZ79ryCRYsW0rNnDwB69erDEUccxUsvvcjJJ59G+/aHlXofIiIiIhIbtn/3LalzZlPn9DOo2/XMSIdTKkrWosyCX9fzzS/ry2TbcXEQCBy4zClHNqPLEc3KZP8lVbNmLcaMmcC6dWupXr0G9erVY+XKFcyd+wlTprzLli2befbZJ1my5FfatTuYwYMfolWrNpEOW0RERETKWcbKFWyc9DrVD21P4z5XRjqcUlM3SCm15OTapKfv2G/5jh07qF27dtj207x5C+rVqwfAiBFD6NfveurVq8ewYc9TvXoNPvhgNsZ04IknHgnbPkVERESkYshOS2Pd6JdISK5Ns3/cQVyVit8uVfGPIMZ0OaLsWraqVIknOzsn7Ntt06Ytq1atyLMsMzOTdevW0L37RWHf31dffcGmTRv5+997AfCf//zIww8/QfXq1bnooot599232LVrJzVq1Az7vkVEREQk+uRkZbFuzCj27tzJQYMfpEoYGwwiSS1rUmonnngyP/74A9u2peUu++qr+WRmZnLSSV3Cuq/MzExGjRrGnXcOoorv15LgBNzBx0Bh/T1FREREJCYEAgE2vTGZjOV/0PT6G6nWqnWkQwobtaxJqV188WVMnz6NwYMHce21N5KaupVRo4Zx1lndaNt23yiRzzzzBHPmzOLLLxflLlux4k9Wrvwz9/mff/7B/PmfAXDGGWfvt6+pUyfTtm07TjjhpNxlnTsfy9Spk6lVqxZvv/0mxnSgZs1aZXGoIiIiIhJl0ub9m+0Lvqb+hReRfNzfIh1OWClZk1JLTk5mxIgxDB8+hAcfvJekpCTOOuscbrttQJ5yOTk57N27N8+yzz//N6+/Pj73+Zw5s5gzZxYA33yzOE/ZTZs28s47Uxk/flKe5XfddQ9PP/04Dz54H23btuPhh58I5+GJiIiISJTa+X9L2TztbWoe3ZkGPS6NdDhhF6fuYmWmDbAiJSWdnJz83+MNG1bRtGn5NdOW1T1rFVF5v/dlqVGjZDZv3n+AF6n4VLexSfUam1SvsUt1G70yN21i9VOPU6VuXVo98BDx1aoXed1oqtf4+DgaNKgF0BZYmee1SAQkIiIiIiJSUnt37WLdqOEQB83vGFCsRK0iUbImIiIiIiIVRmDvXtaPfZnMjRtpfuvtVG3cONIhlRklayIiIiIiUiEEAgE2vfUmu5YuocmV/ajRoWOkQypTER1gxBhzCHAPcCLQCVhmre2UT7lqwGDgaqAlsAWYba29KaTcPcDtQFNgKXC/tXZeSJlk4AXgcqAaMB/ob61dGVLuUGAkcAqwG3jb296u0h21iIiIiIiURNq8z9j2xefUO/c86px2eqTDKXORblk7HLgA+AP4v/wKGGPigQ+BfsDTwDnAfUB6SLl7vNdHe9v8HzDLGHNUyCbfAnoA/YHeQHNgnjGmhm9bdXFJXDIuqRsE9AFeK/mhioiIiIhISaX/8jOb35lKzc7H0PCyXpEOp1xEeuj+mdbaGQDGmCr8wfwAACAASURBVInAcfmUuQ44CehorV3rW/5m8D/GmCTgIWC4tXaIt+xL4FfgQaCXt+wEXCJ3gbV2trfsV2A5cC3wsrfJW4B6wNHW2i1euWzgTWPMk9bapaU+chERERERKZI9f/3F+rGvkHRQK5rdeAtx8ZFucyofET1Ka21RxpG/CXg3JFELdTJQB9dVMbjtvcA04HxjTJy3uDuwDZjjK7caWOC9hq/cvGCi5pkO7AHOL0LMIiIiIiISBtnb0lg7chjx1avRvP9dxCclRTqkchPVKakxJhE4BlhpjJlkjEk3xuw0xnxojGnlK9rBe/wtZBNLgVpAC1+5ZfkkiUuBw0K2l6dbprV2D64Fzl9ORERERETKSE5mJutGvcTe9HRa9L+LxHr1Ih1SuYrqZA1oACQC9+MGDbkMuAE4CphtjAl246wH7LHW7g5ZP9V7rO8rl5bPflJ9ZYpTTkREREREykAgJ4cNr40nY+UKmt10K9Vat4l0SOUu0vesFSaYTKYDlwSTMWPMH8APwKXAuxGKrUi82cjztWlTPFWqlG++XN77i1bx8fE0apQc6TDCJpaORfJS3cYm1WtsUr3GLtVtZKx6Yyrpi3+gzbX9aHFO+Ed+rAj1Gu3JWhoQABb4W82stYuNMdtxw/2/i2vxSjLGVLPWZvjWD7aTbvUeUwF/90l/ua2+56lA3QLKLSvOAaSkpJOTE8j3tZycHLKzi3LbXnhUqRJfZvtbs+Yv3nprCkuXLmHFiuW0atWaKVOm5SmzaNFCRowYwtatKZx22hkMHHg/1apVy3198eLvGTLkWaZMeYfExMQyiTMoJyeHzZt3lOk+ykujRskxcyySl+o2NqleY5PqNXapbiNj+7cL2PDudGqfehqJXc4Iex1EU73Gx8cV2MAT1c0s3pxmKwt4OYCbJw323avWIaRMR2AHsNZXzvgGHPGX8ydhv4Vuyxtx8mCKmaxVFitWLGfhwgW0bNmSNm3a7vf69u3beOSRwZx0UhcefvhJFi/+njfemJj7enZ2NiNGDKF//7vLPFETERERkei163fLhkmvUf2wDjS5sh9xcaGX7pVHVCdrno+BU4wx1YMLjDF/w43++KO36FvcKI+9fWUScEP2z7HWBpu2ZuNazM71lTsIN/H1bN8+ZwNnGWMa+JZdCiSFlBNPly6n8f77s3jqqedp337/MViWLPmVQABuu20AXbqcyt//3pNFi77Nff2DD96jUaMmdOlyanmGLSIiIiJRZM+6tawbNYKqjZvQ/B93EFcl2jsClq2IHr03EXVwyPzWQG1jzOXe8x+stauAF4CrgJnGmGG4ZOtpYAnwAbiRGo0xTwFPG2M2A/8BbsS1hPUN7s9au8gYMwuYYIwZBGwHngBWAxN9oY3FTZo9wxjzJNAYGAq8Y63Nd/Luyi6+kLkusrIySUysQkJCAgDVqlUjMzMLgLS0NCZPfo1Ro8aVeZwiIiIiEp2y01JZO3wocYmJtLhrIAk1a0Y6pIiLdMtaY9w9Z+8CXYGDfM/PALDW/uX9P85bPgr4GjjbWpsV3JA3GfYDwJ3AJ7gh9i+w1v43ZJ99cK11L3vb2+Bta5dvW2nAmbiBTd4HhgHvANeH7cgrmfbtDyM9PZ25cz8hJWULc+bMpmPHTgCMHTuac845j9aVcIQfEREREYGcjN2sHTGMvTt30mLAQBIbNIx0SFEhoi1r1tqVuCSssHL/Bc4qQrkhwJBCyuwAbvH+Hajc78B5he0z3LJ+X0CW/apMth0XF0cgkP9gJ0GJ5jQS23cJ+76bNWvOLbfczlNPPUpOTg7t2h3M9dffxO+/L+Pbb7/izTenh32fIiIiIhL9AtnZrBszmj1r19Dizrup1qp1pEOKGpW7E6iUq759+3HRRZeSlpZKixYtiY+P55FH/skNN9xKrVq1mDBhLB999AGJiYn063c9PXpcGumQRURERKQMBQIBNk6ZxK6lS2hy7fXU7HREpEOKKkrWokxi+y5l0rIFZTt0f1ElJyeTnOzmtJg79xP27Mngwgsv5ptvvmL69GmMGzeRtLQ07rjjJg4//AgOPviQiMYrIiIiImUn5aMP2b7ga+pfdDF1Tjkt0uFEnUjfsyaV1O7duxkzZiQDBtxLfHw8P/20mGOOOY6WLQ+iU6cjOPjgQ/npp8WRDlNEREREysi2b75i68wZ1O5yKg16XBLpcKKSkjWJiMmTX+PII4/mqKOOzl22Z09Gnv8XcnudiIiIiFRQO5f8wsbJE6lxeCeaXH1NpZ5L7UDUDVLCIiMjg4ULvwFgw4b17Ny5k/nzPwOgQ4fDadq0WW7ZtWvX8OGH05k4cWruss6dj+X999/lk08+Ztu2NFavXkXnzseW70GIiIiISJnLWL2KdWNeJqlFS5r/4/ZKP5fageidkbBITd3Kww8PzrMs+PyBBx6le/eLcpePHDmUXr360KRJ09xlp5xyOn36XM3o0SNITExk4MD7OOSQQ8sneBEREREpF1kpW1g7YigJNWvSYsDdxFerHumQopqSNQmLZs2a8803RbvH7Nlnh+a7/Oabb+Pmm28LZ1giIiIiEiX27tjB2mEvEsjKouWg+6hSt16kQ4p6umdNRERERETKVE5GBmtfGkZWyhaa3zGApOYtIh1ShaBkTUREREREyoyb9HoUGatW0uyW26jR3kQ6pApDyZqIiIiIiJSJQE4OGyaMc5NeX3MdtY7uHOmQKhQlayIiIiIiEnaBQIDNb7/Jjh++p+HlvajT5dRIh1ThKFkTEREREZGw2/rxR6R9Po96555H/fO6RzqcCknJmoiIiIiIhFXa/M9JmfEBtU/uQsPLe0c6nApLyZqIiIiIiITNjsXfs2nqFGoeeRRNrrmeuLi4SIdUYSlZExERERGRsNj5f0tZP34s1Q85lGa33EZcQkKkQ6rQlKyJiIiIiEipZaxcwbrRI6natBnN7xhAfFJSpEOq8JSsSVjMnj2TU045br9/Q4c+l1tm0aKF9O17Geed15Wnn36cjIyMPNtYvPh7rrji72RlZZV3+CIiIiJSCpnr17F2+FASkmvR8u5BJNSsGemQYkKVSAcgseXFF0dSs2at3OcNGjQAYPv2bTzyyGAuvPBijjnmeF588VneeGMiN954KwDZ2dmMGDGE/v3vJjExMSKxi4iIiEjxZW3ezJqhL0B8HC3vvocqdetFOqSYoWRNwsqYDtStW3e/5UuW/EogALfdNoCEhARWrFjOl19+npusffDBezRq1IQumn9DREREpMLISk1lzYvPk5OZyUH3DqZqk6aRDimmKFmTcpGVlUliYhUSvJtMq1WrRmam6+6YlpbG5MmvMWrUuEiGKCIiIiLFkL1jO2tffJ696TtoOeg+kloeFOmQYo7uWZOw6tevN6ed9jd69uzBa6+NIzs7G4D27Q8jPT2duXM/ISVlC3PmzKZjx04AjB07mnPOOY/WrdtEMHIRERERKaq9u3aydugQsram0PzOu6nWtl2kQ4pJalmTsGjQoCE33HALHTocTkJCPN999y2TJk1g/fp1PPjgYzRr1pxbbrmdp556lJycHNq1O5jrr7+J339fxrfffsWbb06P9CGIiIiISBHkZGSwdvhQ9qxbS4v+d1GjvYl0SDFLyVqUWbT+Rxau/6FMth0XB4HAgcuc1Ox4Tmh2bLG3fcIJJ3HCCSflPj/++BOpWbMWr702jmuvvZEWLVrSt28/LrroUtLSUmnRoiXx8fE88sg/ueGGW6lVqxYTJozlo48+IDExkX79rqdHj0uLHYeIiIiIlJ2czEzWjhpBxsoVNLv1dmp2OiLSIcU0dYOUMnPmmd0AsHZZ7rLk5GQOOqgV8fHxzJ37CXv2ZHDhhRfzzTdfMX36NEaPHs9jjz3N0KHPsXz5H5EKXURERERCBLKzWf/KaHbbZTS97kaSjyn+D/xSPBFtWTPGHALcA5wIdAKWWWs7HaD8scD3wG5rba2Q1xKBJ4BrgLrAD8AAa+3PIeWaAiOA84AA8DFwl7V2S0i5vwFDgWOBrcCrwBPW2r0lPuAiOKHZsSVq2SqKKlXiyc7OKZNtF9fu3bsZM2Ykjz32NPHx8fz002KOOeY4WrY8iJYtD+Lggw/lp58Wc/DBh0Q6VBEREZFKL5CTw/pXx7Hzl//S+OprqH3SyZEOqVKIdMva4cAFwB/A/x2ooDEmHhgDbC6gyDDgduBR4GIgE5hnjGnu20YVYA5wBNAPuBE4GfjIGBPnK9cO+AyXpF0IPA3cC/yr2EdYic2bN5e4uDiMOWy/1yZPfo0jjzyao446OnfZnj0Zef5fWJdNERERESl7gZwcNk58jfTF39OwZ2/qnn5GpEOqNCJ9z9pMa+0MAGPMROC4A5S9CagDvAbc6X/BGNMCuBW401o73lv2HbACuAu4zyt6GXAU0Mlau9Qrtw5YAJwPzPbK3QukAT2ttXtwSV8d4BFjzPPW2q2lOehYNHDgHRxzzHG0a3cIcXFxLFr0LR988B4XXngxLVq0zFN27do1fPjhdCZOnJq7rHPnY3n//Xf55JOP2bYtjdWrV9G5s5rWRURERCIpEAiw6a032f7tN9S/6GLqn3t+pEOqVCKarFlri9QnzxjTENe6dSWuy2Soc4AE4B3ftncYYz4GurMvWesO/BpM1Lxy3xpjVnmvzfaV+9BL1IKm4lrWzgTeK0rclUnr1m2ZNesjNm/exN69e2nZ8iBuvbU/vXr12a/syJFD6dWrD018kyaecsrp9OlzNaNHjyAxMZGBA+/jkEMOLc9DEBERERGfQCDA5nemsm3+POqdcx4NelwS6ZAqnUi3rBXVc8A31to5xpj8krUOwEZrbUrI8qVAX2NMvJcYdiD/7pZLgcMAjDE1gVah5ay1K40xu4LlJK8BAwYxYMCgIpV99tmh+S6/+ebbuPnm28IZloiIiIiUQCAQYMu0t0n77N/UPbsbDXv2Ji4urvAVJayiPlkzxpwE9MENQFKQerhui6FSgUSgFrC9kHIdvf/X9R4LKle/8KhFRERERCqmQCDAlvemkfrvT6l75tk06t1XiVqERHWyZoxJAF4Ghlpr/4x0PCXRoEGtAl/btCmeKlXKd4yX8t5ftIqPj6dRo+RIhxE2sXQskpfqNjapXmOT6jV2Vaa6DQQCrJryJqmffkLT88+l3S03xWyiVhHqNaqTNdygIs2Al40xwRavagDe8z3W2t24Fq+6+axfD8gC0r3nByoXHDQk2KJWWLkiSUlJJycn/2ENc3JyynUo/Wgauj/ScnJy2Lx5R6TDCItGjZJj5lgkL9VtbFK9xibVa+yqTHUbCARI+fB9ts6aSZ3TupJ8aW+2bEkvfMUKKJrqNT4+rsAGnmhvZjkMaAKsxSVaqcD9QE3v/8945X4DGhtjQrsodgR+9w1k8hvuvrVQHYFlANbancDq0HLGmNZAjWA5EREREZFYkvLRh2ydNZPap55G46v6ERcf7alC7Iv2GhgFnBHybxKQ4f1/lFduLpAD9AquaIypBVzEvhEe8f5/hDGmg6/ciUCbfMpdYoyp6lvWB9gDzAvDcYmIiIiIRI2UmTPYOnMGtbucSpOrr1WiFiUi2g3SGFMDN0w+QGugtjHmcu/5D9baP3ATZvvX6QrstdZ+EVxmrV1rjHkFeM4Ykw2sAu4B4oDhvtWnA78A7xlj/ok7/heAhcAnvnIv4KYJmGaMGQkY4GFguLU2tbTHLSIiIiISLVJmzSRlxgfUPqkLTa65TolaFIl0TTQG3vX+dQUO8j0v7tTodwNjgKeAj4DqwNnW2nXBAtbabOA8YAnwBvA68B3Qw1ob8JX7EzgbaATMAh4CXgQeLO4BioiIiIhEq62fzCLlg+kkn3gSTa67QYlalIkLBPIf/EJKrQ2w4kADjGzYsIqmTVuXW0AaYGSf8n7vy1I03SAr4aW6jU2q19ikeo1dsVy3W2d/zJb33yP5byfS9MabK1WiFk316htgpC2w0v9atI8GKSIiIiIiYRQIBNg6cwYpH31I8gkn0vT6mypVolaRKFkTEREREakkAoEAKR9MZ+vsj6l98ik0ufZ6JWpRTMmahMWaNX/x1ltTWLp0CStWLKdVq9ZMmTJtv3ILFy5g/PiXWblyBQ0bNqJXrz5cfvkVecpMmTKR9957C4ijd+++9O3bL8/r48ePYePGDTz00ONleUgiIiIiMSUQCLDl3XdInTuHOqd11fD8FYCSNQmLFSuWs3DhAjp2PJxAIIecnP3vjVuy5BcGDx7IeeddwB133M0vv/zMSy8NpUqVKlxyiRsE9IcfFjFhwivcc89gAgEYMuQZjOnAscceD8C6dWuZMeN9Jk58q1yPT0RERKQiCwQCbH7rTdI+/4y6Z55Foz5XERcXF+mwpBBK1iQsunQ5jVNP7QrAv/71GMuW/d9+ZV5//VXatz+Mf/7zEQCOOeY4Nm7cyOuvj6dHj78THx/P999/x/HHn8CFF14CwBdffM6iRd/mJmujRg2nd+8radiwYfkcmIiIiEgFF8jJYdObk9n25RfU63YuDXtdoUStglC7p4RFfCFN6JmZmfznPz9w1lnd8izv1u1cUlJS+P33ZQBkZWWSlJSU+3q1aklkZmYBrtVt+fL/0bt33zBHLyIiIhKbAjk5bJz0Otu+/IL63S9UolbBKFmTcrF27RqysrJo06ZdnuVt2x4MwKpVKwHo0OFwFi/+nuXL/+B///udxYu/p2PHTmRnZzNixIv07383VatWLe/wRURERCqcwN69bJgwnu0Lvqb+RRfT4NLLlKhVMOoGKeVix47tANSqlZxneXKye759u3v97LPP5YsvPueaa9ygI127nsnZZ5/De++9Q+PGjTnllNPLMWoRERGRiimQnc36V8eRvvh7Glx6GQ0uuCjSIUkJKFmLMtu/XcC2b74qk23HxcVR2CTodU45jdondymT/RdFQkICzzwzhE2bNhIXF0ejRo1JTU1l8uQJjBw5jp0703nhhWf4/vvvaNKkCYMGDaZTpyMjFq+IiIhItMnJymT92DHs/PknGvbsTf1zz490SFJC6gYp5SI5uTYA6el5Z4rfscM9r127dp7ljRs3oVGjxgCMGzeabt3Op23bdrz22ng2btzAtGkzOOec7jz88GCysrLK4QhEREREol9ORgZrRwxj588/0ajvVUrUKji1rEWZ2id3KbOWrSpV4snO3n9I/fLQokVLEhMTWbVqBSeeeHLu8pUr/wSgdes2+a5n7TK++eYrpk6dDsBPPy3mggsuplatWlx88d8ZPXo4q1ev4uCDDynzYxARERGJZnvT01n70lAyVq6k6fU3RbS3lISHWtakXFStWpVjjjmezz//LM/yzz77lAYNGtC+/WH5rjd8+PPccMMtufe2AezZk5HnsbCunSIiIiKxLntbGn+98Cx7Vq+m+T9uV6IWI9SyJmGRkZHBwoXfALBhw3p27tzJ/PkuMevQ4XCaNm3GddfdyO2338Rzzz1Ft27n8euv/2XmzA8ZOPC+fIf+//TT2WRkZNCjx6W5yzp3PpYPPphO27btmDfv3zRs2IhWrVqXz0GKiIiIRKGslC2sefEFsrel0fzOu6nZ8fBIhyRhomRNwiI1dSsPPzw4z7Lg8wceeJTu3S+iU6cjefbZFxk79mXmzJlFw4aN6N9/IJdccvl+29u1axevvDKKRx99Kk8id+21N7Fx40YeffRBmjZtyhNPPKOh/EVERKTSyly/jjVDh5CzJ4OWA++lum4NiSlx6kJWZtoAK1JS0snJyf893rBhFU2bll+rUCTvWYs25f3el6VGjZLZvHlH4QWlwlHdxibVa2xSvcauaK7bjFUrWTvsRYiPo+Xd95J00EGRDqnCiKZ6jY+Po0GDWgBtgZX+19SyJiIiIiJSwez+3++sfWkY8dVr0HLQvVRt0jTSIUkZULImIiIiIlKB7FzyC+teHkWV+vVpOfBeEus3iHRIUkaUrImIiIiIVBDbF33HhtfGk9SiJS3uHkSV5NqFryQVlpI1EREREZEKIPXfn7L5nbeo3t7Q/I4BJNSoEemQpIwpWRMRERERiWKBQIAt098ldc5sah17HE1vvJn4RI2GXRkoWYuwQCBAXFxcpMOoVDQCqoiIiFQUgexsNk56ne0LF1Cn65k07nsVcfnMTyuxSclaBCUkVCErK5OqVZMiHUqlkpWVSUKCTn0RERGJbjl79rBuzGh2LfmFBhdfSv0Le+hH/kpGV6wRVKtWXdLSNlO3biMSE6vqw1fGAoEAWVmZpKVtJjm5XqTDERERESnQ3h07WDtyGBkrVtC437XUPa1rpEOSCIhosmaMOQS4BzgR6AQss9Z28r2eAAwCLgA64uL9FXjcWjsvn+3dA9wONAWWAveHljPGJAMvAJcD1YD5QH9r7cqQcocCI4FTgN3A2972dpX6wD3Vq9cEYNu2Lezdmx2uzRYoPj6enJzKPSl2QkIVkpPr5b73IiIiItEmK2ULa4YNITslhea33UGtzsdGOiSJkEi3rB2OS8QWAfHeP7/qwAPAJFyClQVcC/zbGNPDWvtxsKCXqD3tlf8PcBMwyxhzgrX2v75tvgUcA/QHtgNPAPOMMUcEEzFjTF1cErcKl9Q1BoYCjYArwnXw4BK28kocommmdhERERHZ3541f7Fm+IsEMjNpOfBeqh/aPtIhSQRFOlmbaa2dAWCMmQgcF/L6bqCttTY1uMAYMxdoj2tx+9hblgQ8BAy31g7xln2Ja4V7EOjlLTsBlxxeYK2d7S37FViOSwJf9nZzC1APONpau8Urlw28aYx50lq7NHxvgYiIiIgI7LLLWDdqBPHVqtHy/gdIatEy0iFJhEV0KBlr7QH75Flr9/oTNW9ZAPgZaO5bfDJQB9dVMXddYBpwvjEmeDNYd2AbMMdXbjWwwHsNX7l5wUTNMx3YA5xfpIMTERERESmi7YsWsnbYEKrUqctBgx9SoiZAhJO1kjDGxOOSs998izt4j7+FFF8K1AJa+MotyydJXAocFrK9//MXsNbuwbXA+cuJiIiIiJRYIBAgZdZMNowfS7V2B3PQPx8isUGDSIclUSLS3SBLoj9ggJt9y+oBe6y1u0PKBlvl6gNrvHJp+Wwz1Svj315RyomIiIiIlEggO5uNb05m+9dfkXzCSTS59nriExMjHZZEkQqVrBljTgeeB4ZYa7+OdDxF0aBBrUiHkEejRsmRDkHKgOo1dqluY5PqNTapXmNXWdRt9q5d2OeHs/2nn2nZ63Ja9b1C0ziVs4rwma0wyZox5khgBvAhcH/Iy6lAkjGmmrU2w7c8OJnWVl+5Vvlsvp6vTLBc3QLKLStO3Ckp6eTkBIqzSpnRaJCxSfUau1S3sUn1GptUr7GrLOo2a+tW1r40jMx1a2lyzXXUOPV0tmxJD+s+5MCi6TMbHx9XYANPhbhnzRhzMPApbkj+q71BRvyC96p1CFneEdgBrPWVM74BR/zl/EnYb6Hb8kacPJhiJmsiIiIiIkF7/lrNX888SfaWzbQYMJA6p54e6ZAkikV9smaMaQrMBTYAl1hrM/Mp9i1ulMfevvUScEP2z/Eld7NxLWbn+sodhJv4erZve7OBs4wx/rs7LwWSQsqJiIiIiBTJziW/8tdzTwNw0P0PUvPwThGOSKJdRLtBGmNqsG/I/NZAbWPM5d7zH4BNuGH2GwMDgY7GmNz1rbXfeY97jDFPAU8bYzbjWuBuxLWE9fWVX2SMmQVMMMYMYt+k2KuBib7QxuIGMplhjHmSfZNiv2OtzTNKpIiIiIhIYbZ9/SUbp0wiqUULmt85kMR69QpfSSq9SN+z1hh4N2RZ8Pl1wBfAUd7zD/NZP7c7o7V2iJfI3Qk0wQ3Hf4G19r8h6/QBhuAmwE4C5gM9rbW7fNtKM8acCbwEvI+bnPtt4L7iHZ6IiIiIVGaBnBy2TJ9G6qdzqHF4J5rdejsJ1atHOiypIOICgegY/CIGtQFWaIARKWuq19iluo1NqtfYpHqNXaWp25yM3awfP5ad//2ZOmecReMr+hKXkBDmCKUkoukz6xtgpC2w0v9apFvWRERERERiTlbKFta+NJzM9eto3Pcq6p55dqRDkgpIyZqIiIiISBjt/uN/rBs9kkB2Fi0GDNRAIlJiRUrWvKHzLwG64Ia5bwgEgC24Ye4XAB9Za/9XRnGKiIiIiES97QsXsHHS61Sp34AW/QdTtVnzSIckFdgBkzVjzIXAvbih7QGWA38CP+EG96gHdAIuBp43xnwLPG+tnVlmEYuIiIiIRJlATg4pH77P1tkfU90cRvN/3EFCrfwnOhYpqgKTNWPMd7iRGD8CegKfWWu3F1C2NtDNKzfNGPOztfakMohXRERERCSq5OzZw4ZXx5H+04/UOe10Gve9mrgquttISu9AZ9FXuEmoNxS2ES+Jmw5MN8Y0A+4OU3wiIiIiIlEra2sK60aOYM+av2jUuw91zz6HuLi4wlcUKYICkzVrbYnmFLPWrkfzkYmIiIhIjNv1u2X9mNEEsjJp3v8uah15VOEriRSD2mdFRERERIohEAiw7Yv5bHr7TRIbNqT57YNJaq6BRCT8ChtgpDnQzFr7Y2EbMsa0BU611k4OV3AiIiIiItEkJyuLzW+9wbavvqTmEUfS9KZbSKhRM9JhSYwqrGXtZSARuKAI2zoZeB1QsiYiIiIiMSc7LY11Y0aRsfwP6l9wEQ0uvpS4+PhIhyUxrLBk7UTgGf8CY0wDYBPQzVr7eVkFJiIiIiISLXb/uZx1o0eSs3sXzW69neTjjo90SFIJFJas1QWy8lmuIW5EREREpFLY9s3XbHpjElXq1qPlXQ+TdNBBkQ5JKonC2m2XA72MMfkldYEyiEdEREREJCoEsrP5c9yrbJw4geqHGlo99KgSNSlXhbWsvQSMAdYbY5YAu3H3sAE8a4xJ8ZVtVgbxiYiIiIiUu+xtaawfO4bdv1vqnXMeDS/rWFLccwAAIABJREFUSVxCQqTDkkrmgMmatXasMWYrcA1wMFAN1xoXAFoBjX3FNQyOiIiIiFR4u//3P9a9Mpqc3bs49O4BxB3eOdIhSSVV6Dxr1tp3gXeDz40xDXEDjFzpH2DEGHMVMKksghQRERERKWuBQIC0z+ay+b1pJDZoSMu7BtH4mI5s3rwj0qFJJVWSSbF3Ao8Df4Ys3wB8VeqIRERERETKWU7GbjZMfJ30xd9Ts/MxNL3uRhJq1Ih0WFLJFTtZs9buxiVrocs/Az4LR1AiIiIiIuVlz7p1rB8ziswN62l4WS/qnXc+cXEa/FwiryQtayIiIiIiMWHHD9+zYeJrxFetSstB91HjsA6RDkkkV4FD9xtjJhljDivuBo0xhxljdO+aiIiIiEStQHY2m96eyvqxL5PUsiWtHnlciZpEnQO1rNUHlhhjvgbeAT6z1v6RX0FjzCFAN6AXcAowO9yBioiIiIiEQ3ZaqhuW/3+/U/fsbjS6vDdxVdThTKJPgWeltfYiY8zJwL24+dYSjDHbgRVAKhAH1APaALWBbGAmcKq19rsyjltEREREpNh2LvmVDa+OIycrk6Y330rtv50Y6ZBEClTYPGvfApcaYxoBFwInAYcBTb0iW3CtbguAT6y1W8owVhERERGREgns3cuWD98n9ZNZVG3RkoNuvY2qzZpHOiyRAypSe6+1djPwuvcvbLzuk/cAJwKdgGXW2k75lDsf+BfQEVgLDLfWjsyn3D3A7bhkcilwv7V2XkiZZOAF4HLcJN/z4f/Zu/MwyaoCzf/f2JeMzMg9a6E2CjhVRRWyuQACggubCqKCoKJOt9M9bbuN2j0urbbtONOj09rtOGO3P1vttl1QtFsBUcBiUUCBYrOqOAUF1EpV7ktk7BH398e9kRkZlbUkZFZkRr6f54nnxr333BsnOE9R8dY59xzeb619rqbcycBXcYd1ZoAfePdLv4ivLCIiIiLHWWFwkAPf+DqZp3aQvOBCut72dvzhcL2rJXJUh51g5Dg5FbgCeBrYNl0BY8w5wM+AR4DLcAPjV4wxf1pT7qPAF4Cvefd8CrjFGPOSmlt+H3gj8H7gWmAZcKcxJl51r1bcENeMG+o+AlwH/POL+K4iIiIicpylHn+MXZ/7NNndu1ny3j+l54b3KKjJglHvJyl/bq39DwBjzLeBs6cp82lgi7X2j7z9zcaYlcBnjDH/ZK0tG2MiwKdwe9y+5N3vbuAJ4JO4E59gjHk5bpC7wlp7q3fsCWAn8G7g/3qf8Se4z+OdXhnaaYwpAv9mjPkba+3WWfxvICIiIiKzzCkW6f/pTQz98hdEVqxg6Z+8j/CSJUe/UGQeqWvPmrW2fKTzXgi7GPe5uGrfwx3qeKa3fy6QxB2qWLl3CbgRuMwYU1nV8HJgBLitqtxu3GfuLq+6/+XAnTXP4N0E5HB790RERERknioMDLDni/+ToV/+guSrLmbFJ/5KQU0WpHoPgzyatUCYQ4dIVnq2KuvAVRbF2D5NuQSwvKrck9OExK1V96qUm/KZ1tocbg/cjNeeExEREZHjI/XoI+z660+T37eXpX/yZ/S84wb8IQ17lIWp3sMgj6bN2w7XHB/ytu1V5XLW2swRyu31ytXeq1KuvWr/WMuJiIiIyDxQzufp+9EPGdl8J5GVq1j6J39GuKen3tUSeVHme1hb8Do6EvWuwhRdXc31roLMAbVr41LbNia1a2NSu9bP+HO72PG/v0x69x6WXfkGVr3z7fhDoVm7v9q2MS2Edn1RYc17puxqoBW42Vq7Z1ZqNanSM9Zac7zS4zZYVS5ijIlaa7NHKbdyms9pqypTKVf7mZVyTx5DvScMDKQol52ZXDJnurqa6esbq3c1ZJapXRuX2rYxqV0bk9q1PhzHYXjznfTf+AP88TjLP/QRmjZuYmA4C2SPev2xUNs2pvnUrn6/77AdPMf8zJox5qvGmIer9gPAvcB3cafL32qM2fQi61prJ5Bn8pm0ig3ethKcKs+qTVduDHdttko5UzXhSHW56hC2vfZeXjBdywzDmoiIiIjMvuLYKPu/+hX6vvdd4us3sOqzn6dp42z/FBWpr5lMMHIZ8Muq/Wtwp9p/H3AO0Af81exVbWJSj197n1XtOuAAsMXbvw93lsdrKwW8MHkNcJu1ttK1dStuj9klVeVW4C58fWvV/W8FXm2M6ag69iYgUlNORERERI6z8a1/YNdn/4r0tq10Xfd2ln3gwwRbWupdLZFZN5NhkEtxe7oqrgIes9Z+HcAY83XggzP5cG8h6sqU+auAFmPMW7z9B621u4DPAfcYY74B/BtwHvBe4H2VWR2ttTljzOeBLxhj+nBD3B/j9oRdX/k8a+3vjDG3AN80xnwEGPXuvxv4dlXV/hF30ez/MMb8DdAN/B3wQ2vttIt3i4iIiMjcKhcKDPzkxwzd/kvCy5Zxwoc+SmTFinpXS2TOzCSs5YA4gDeM8GLgm1Xnh4COaa47km7gRzXHKvvvAb5trb3fGHMl8AXgBmA/8OFKSKyw1n7JGAPwAaAHdzr+K6y1j9Xc/zrgS7gLYEeAzcBbrbXpqnsNG2MuBv4B+AmQwV3D7S9m+P1EREREZBbk9u/nwP/3j+R27yJ50avpeuu1+MOakl8a20zC2hPAO4wx38WdVKSdqUMCV+MOhTxm1trngNrnx6YrdyvHMPzQWvsl3CB2pDJjwJ94ryOV2wFcerTPFBEREZG545TLDP/6Dvpv+hG+SIRlf/5BEqefUe9qiRwXMwlrnwNuBvq9/d9Ya++pOn8F8PvZqpiIiIiILG6FwQEOfuubpLdvo+m0l9DzrvcQTE43YbdIYzrmsGatvdMYcybwWtzJPH5YOWeMaQfuAv59tisoIiIiIouL4ziMPXA/vd/7V5xyme4b3k3y/Avx+Y46IEukocxonTVr7XYmp8mvPj4IfHi2KiUiIiIii1MpleLgd79D6qEHia49iSV/9J8Jd3fXu1oidfGiFsUWEREREZkt4088zoFv/zOl1BidV7+Ftksvx+efyUpTIo3lmMOaMaYMOEcplgX24s6w+EVr7c6jlBcRERGRRa6cy9F34w8YuXsz4WXLWf7BDxNduare1RKpu5lOMHIVsAH4BfC0d/xk3FkT/wDcCZyEO+3+dcaYC6aZOl9EREREBID0DsvBb/8zhb5e2l53KR1vuhp/SFPyi8DMwtp+3HXU1llrn6k+YYw5CXeCkW3W2o8ZY04G7sddG+2KWaqriIiIiDSIci5H/09/zPCddxDq6OSEj/4lcbOu3tUSmVdmMgj4Y8DXaoMagLX2aeBrwMe9/aeArwPnzkYlRURERKRxpHdYdn32rxi+43ZaL7qYVZ/9GwU1kWnMpGftBKB0hPMlYEXV/nNA5AXUSUREREQaUDmXo/8nP2b413cQ6uzkhI/9N4U0kSOYSVjbCvwXY8x3rbXPV58wxiwD/otXpuJE4MCLr6KIiIiILHTpHZaD3/omhb5eWi9+NZ1vvgZ/RP+uL3IkMwlrH8WbWMQY8zMmJxg5CXgjEMCdWARjTBR4t1deRERERBYp9aaJvHDHHNastXcZY84F/ho3nMW8U1ngDuCz1totXtkssGyW6yoiIiIiC0j6ye0c/M63vN6019D55reqN01kBma0KLa19hHgjcYYP1BZSr7XWlue9ZqJiIiIyIJUGh+n78c/ZPTeewh1das3TeQFmlFYq/DCmZ5HExEREZEJjuOQ2vIQvd/7LqWxMdouvZyON1yp3jSRF2hGYc0Y0wZchzt5SBvgqyniWGv/aJbqJiIiIiILRGFoiN7v/Svjj2whsnIVyz/wYaKrVte7WiIL2jGHNWPMJcCPgSZgFBiappgzS/USERERkQXAKZcZuecu+m/6EU6xSOdbrqHttZfgCwTqXTWRBW8mPWv/G3fo49XW2ifmqD4iIiIiskDkDzzPwe98i8xTO4itW0/PO99NuKen3tUSaRgzCWsnAR9TUBMRERFZ3MqFAkO//AWDN/8MXzhMz7v/Ey3nnY/PV/uEjIi8GDMJa08BzXNVERERERGZ/9JPbufgd79D4cABEme/lO7r3k4w2Vrvaok0pJmEtU8B/8cY831r7bNzVSERERERmX+Ko6P0/egHjN1/H6HOLpZ/8L/StOm0eldLpKHNJKxdAgwA240xvwb2AKWaMo619n2zVTkRERERqS+nXGbk3nvov+lGyrkc7Ve8gfbLX6/p+EWOg5mEtT+ten/pYco4gMKaiIiISAPI7dnNwX/9DtlndhI7xdD9jncRWbas3tUSWTSOOaxZa/1zWRERERERmR/K2SwDP/t3hu74FYF4E0v+03tpPudcTSAicpzNaFHsejHGXAV8AlgPjAO/Bf6btfapmnI3eOVWAzuBz1lrf1hTJgR8DngX0Ao8CHzQWvtoTbklwN/j9iI6wM3Ah6y1/bP9/URERETmA8dxSD38EH03fp/i4CDJCy6k8+q3Ekgk6l01kUVp3veWGWNeDfwEeBK4Gng/sA64wxjTUlXuLcB3gJ8ClwF3AN83xlxWc8sv4w7V/AxwJZAH7jTGLKu6VxC4DdgE3AD8MXAu8DNjjP5JSURERBpObv9+9v3dF3n+61/DH29ixX/7JD03vEdBTaSODtuzZox5FigD66y1BW/fOcr9HGvt2tmsIHAdsAt4l7XW8eq2C/gdcB7wC6/c3wA/stZ+3NvfbIxZD/x1pYwxZjnus3cfsNZ+wzv2APAs8CHgL7xr3wy8BNhord3qlduP26N3GXDrLH9HERERkbooZTIM/vw/GLrzdvyRCF3Xv4PWCy/CFwjUu2oii96RhkHejRvOyjX7x1sIGKsENc+wt/UBGGPW4Pa2fbLm2u8B3zLGdFlr+4DXAQFgYmiktXbMGHMzcDmTYe1y4IlKUPPK3eeFxMtRWBMREZEFznEcxn53P30/upHS6Agt551P59VvIdjScvSLReS4OGxYs9a++0j7x9G3geuNMe8H/hX3ObMvAduBO70y673ttpprK2HLAH1euYPW2oFpyl1vjPFba8teudp7Vcqte+FfRURERKT+cnt20/u975J5ageR1WtY9r4PEDvxxHpXS0RqHPMEI8aYldba3XNZmelYazcbY64G/g34B+/wH4DXWmtz3n6btx2uuXzI27ZXlastUykXAhLA6FHKbZjpdxARERGZD0rj4wz8x08Y3vxrAk0Jet71HlrOOx+ff95PYyCyKM1kNsjnjDH3Az/AfTbswBzVaQpjzLnAvwDfBH4GdAB/hTvZxyuttZnjUY8XqqNjfj2U29XVXO8qyBxQuzYutW1jUrs2pvncrk6pxIFf3s7u7/2A4vg4Sy+/lJXXv42gJg85JvO5beWFWwjtOpOw9mngGtzp7P/OGHMv8H3gJmvt4FxUzvMPwGZr7YcrB7xJQXYD7wT+icketFagOkRWetwq9RvyytRqAwpA6hjKzei7DgykKJfr8ajfobq6munrG6t3NWSWqV0bl9q2MaldG9N8btfxrX+g74ffJ79/HzGzjuVvu57IipUMZRzIzM86zyfzuW3lhZtP7er3+w7bwXPMfd7W2s9ba08DTgW+ACwF/hF43hhzqzHmBmPMXMTTDcCUNdCstXuBfqAy8+R2b7ueqSpDFm1VuW5jTPs05XZ4z6tVytXeq1LuyRnVXkRERKQO8gcOsO8fvsy+L38Jp5Bn6Z+9nxM++pdEVqysd9VE5BjNeICytXa7tfYz1tr1wJnA3wGnAN9iaq/WbNkFnFV9wBizCugEnvPq9CxuiLq25trrgAe9mSABfoU7u+U1VfdKAG9g6gyPtwKbvKn/K+VegbvYtmaCFBERkXmrlB6n94ff57nPfJLMDkvnm69h1ee+QPOZZ+HzablYkYVkJsMgD2GtfdQYU8QNQH+OO0HHbPsa8FVjzFeB/8B9Zu1TQC9wY1W5TwM/NMbsBG7HXfD6dcAVVfXdZ4z5OvC3Xr13AR/FXQLgK1X3ugl4HPixMebjuP+dvgjcz+S6biIiIiLzhlMqMXLP3fT/x08oj4/T8srz6bzqzQSTyXpXTUReoBcU1owxpwBvw+3JWgcUcXutfjB7VZvwNSAP/BnwHmAMeAC4pnoKfmvtj4wxceATuAFsJ3C9tbY2XH0Y99m0zwNJ4EHgNdba/VX3KhpjLsV9Pu+7uOvL3Qx8sGa9NxEREZG6chyH9NYn6PvRjeT37SV2iqHrbdcTXbmq3lUTkRfJ5zjHlj28haev9V6n4fam3YUb0G6y1k431f1ithp4VhOMyFxTuzYutW1jUrs2pnq1a3bXc/T/+EbS27cR6uqi8y3XktBwx1mlP7ONaT61a9UEI2vwHvOqmEnP2k7cHqb7gA/gTt/fO0t1FBEREZFjVOjvo/+nP2Hsd/fjTyToetvbaX3VRfiCL+oJFxGZZ2byJ/pjwA+9mRhFRERE5DgrjY8zeOvPGb7zDvD5aL/89bRdejmBeLzeVROROXDMYc1a+7/nsiIiIiIiMr1yIc/wr+9k8JabKWfStJxzHh1XXU2ovXY1IhFpJDPuKzfGLMedsj/JNFP/W2v/ZRbqJSIiIrLoOeUyY79/gP6f3kRxYID4xk10vfkaIitW1LtqInIcHHNYM8ZEcNdSuwY3pDm4U97jva9QWBMRERF5kdLbt9H3ox+S272LyMpV9LzrP9G04dR6V0tEjqOZ9Kz9DfBW4K+A3+LOBPku4HngI0A3cMMs109ERERkUck8s5OBn95Eevs2gu0dLPnj/0zzy16Bz3/IgCYRaXAzCWvXAP9irf0fxpgO79g+a+2vjTF3AncDfwq8f7YrKSIiItLocnv30P/vP2H80UcINDfTde11JF91Ef5QuN5VE5E6mUlYW4K7GDVAwdvGAKy1jjHmx8DHUVgTEREROWb5gwcZ+NlPGfv97/BHo3RcdTVtr3kd/mi03lUTkTqbSVjrw51UBGAMyABrq86HgMQs1UtERESkoRUGBxi8+WeM/OZefMEgbZdeTvsllxFI6OeUiLhmEtYeAV4GEz1pdwMfMsZswZ1w5P1eGRERERE5jOLYKIO33sLI5jtxHIfWV11M+xWvJ5hsrXfVRGSemUlY+wbwHmNM1FqbxV0k+y7cZ9V8wADuRCMiIiIiUqOUHmfoV7cxdPvtOPkcLee9ko43XEmoo7PeVROReWomi2L/HPh51f5WY8xa4GKgCPzWWjs0+1UUERERWbhK6XGG77yDodt/STmdJnH2y+i88irCS5fVu2oiMs/NeFHsatbaUeDfZ6kuIiIiIg2jlB5n+I7b3ZCWydB0+hl0vPEqoitX1btqIrJAvOCwZox5FfAOYBmwHfh7a+3uWaqXiIiIyIJUSo8zdPuvGL7jV25IO+NMOt5wpUKaiMzYEcOaMeYzwF8Cq6y1fVXH3w18E/dZNYBLgXcYY15mrd01R3UVERERmbdK4+MM3TEZ0hJnnEX7G96okCYiL9jRetYuAn5ZE9QiwFeAEeDNwO+BK4BvA58A/mROaioiIiIyD5VSKXb96mb2//wWN6SdeRYdb7iSyIqV9a6aiCxwRwtrJwP/r+bYq4EW4JPW2s3esRuNMa8BXjPL9RMRERGZl0qpFEN3/JLhO26nnM2SOOtsOl5/JZEVK+pdNRFpEEcLa+3A/ppjFwEOcHPN8YeBd85SvURERETmpeLwEEO/+iXDd2/GyeVInHU2J91wHemmjnpXTUQazNHC2vPA8ppj5wNpYFvN8TKQm6V6iYiIiMwr+d5ehm67ldH7foNTKtH8spfTftkVRE5YQVNXM+m+sXpXUUQazNHC2u+BdxljvmqtHTbGnAacDfzcWluqKbse2DsXlRQRERGpl9yePQz+4hbGHvwdvkCAlvNeSdsllxPu7q531USkwR0trP01sAV4yhizDTgDdwjk31YXMsb4gDcBv5qLSoqIiIgcb5mdTzN4y88Zf/wxfJEoba+7hLbXXkKwta3eVRORReKIYc1au90YczHwKeBE4LfA/7LWPlBT9FVACrhpLiopIiIicjw4jkN621YGb/k5mR0Wf1MTHVe+idaLXk0gkah39URkkTnqotjW2vtxp+Y/UpnNwKbZqpSIiIjI8eSUSqQeeZjBX9xKbtdzBFpb6brmOpIXXIg/Gq139URkkTpqWBMRERFpVOVslpHf3svw7b+i0N9HqLuHnhveQ/M55+IPhepdPRFZ5BZMWDPGvBP4ELABdzbKLcB11tp+7/xlwH/3zu8DvmKt/eo09/ko8D5gCbAV+Etr7Z01ZZqBLwJvAaLAZuD91trn5uTLiYiIyHFVHB5m+Nd3MHzXZsrpcaJrT6LzmreROP0MfH5/vasnIgIskLBmjPkk8HHgfwAfAVpxn5OLeOfPAX4G/It3/jzgK8aYgrX261X3+SjwBeATuGHvvcAtxpiXW2sfq/rI7wNnAu8HRoHPAXcaYzZZa9Nz+FVFRERkDuX27WPoV7cx9rv7cUolEmecSdvrLiV20sn1rpqIyCHmfVgzxhjgs8CbrLXVC3H/e9X7TwNbrLV/5O1vNsasBD5jjPkna23ZGBPBnSjlK9baL3n3vht4AvgkcI137OW4z+hdYa291Tv2BLATeDfwf+fki4qIiMiccByHzJPbGfzlbaT/8Di+cJiW8y+g7TWXEO7pqXf1REQOa96HNeA9wK6aoDbBC2EX4/a8Vfsebs/ZmcBDwLlAEvhBpYC1tmSMuRH4iDHGZ611gMuBEeC2qnK7jTG/9c4prImIiCwATrHI2MMPMvTL28jt3kWguYWOq66m9cKLCDQ317t6IiJHtRDC2iuAx40xnwL+HOgAHgE+Zq29G1gLhIFtNddt9bbrcMPaem9/+zTlEsBy3EW91wNPWmvL05S75EV/GxEREZlTxbFRRu6+i+G7fk1peJjwkqXepCHn4A+F6109EZFjthDC2hLgLOAlwAdwnyH7KHCbMWY9UFmZcrjmuiFv2+5t24CctTZzhHJ7vXK196qUa5/muIiIiMwD2d27GL7zDvd5tGKR+Kkbab3h3TRtPE2ThojIgrQQwpoft+frfGvtowDGmHuAZ4GP4Q53nLc6OubXAppdXRr20YjUro1LbduY1K6zxymVGPjd73n+5lsZ3boNfyRCz2tfzdLLLyO+csVxrYvatXGpbRvTQmjXhRDWhoCBSlADsNamjTEPABuZ7Blrrbmu0uM2WHWfiDEmaq3NHqXcymnq0VZV5pgNDKQol52ZXjYnurqa6esbq3c1ZJapXRuX2rYxqV1nRymVYuTeexjefCfFwQGCnZ10vvVakq+8gEBTE+PA+HH876x2bVxq28Y0n9rV7/cdtoNnIYS1rbjPpU0nijtLYx73WbPbqs5t8LZPetvKs2rrcZ95qy43hrs2W6Xca6smHKku9yQiIiJSN7l9+xi+83ZGH7gPJ58nZtbRfd31NL1E66OJSONZCGHtZuA9xpgzrbVbAIwxTcA5wI+ttTljzK9xp97/ctV11wEHcNdTA7gPd5bHa/HCmjEm4F13W1UwuxV3KYBL8MKfMWYF8Ergg3P1JUVERGR6TrFI6pEtDG++k8wOiy8Uovnl59D26tcSWXF8hzqKiBxPCyGs/Tvwe+DH3uLYY7gLX8eBv/PKfA64xxjzDeDfcBfFfi/wvsqsjl6o+zzwBWNMH26I+2PcXrvrKx9mrf2dMeYW4JvGmI8wuSj2buDbc/xdRURExFMYGGDknrsYufduSqOj7lDHq99C8vwLNfW+iCwK8z6seQtaXwF8CXeNsyjwAPAqa+3TXpn7jTFXAl8AbgD2Ax+21n695l5fctfY5gNAD+4QyyustY/VfOx1VZ8XATYDb7XWpufmW4qIiAiAUy6T3vYHhu/azPhj7uPqTZtOI/mqi2nauElDHUVkUfE5zvyY/KIBrQae1QQjMtfUro1LbduY1K7TK42NMfLbexm5+y4Kfb0EmptJnn8hyQsuJNTZVe/qHZXatXGpbRvTfGrXqglG1gDPVZ+b9z1rIiIi0pgcxyH7zE6G7/o1qQd/j1MsEjv5FDquuprEmWfhD4XqXUURkbpSWBMREZHjqpRKMXr/bxm59x7y+/fhj0ZpOf9CWl91EZHlJ9S7eiIi84bCmoiIiMw5p1wmY59k5N67SW15GKdYJLrmRLrf+W5aXv5y/NFYvasoIjLvKKyJiIjInCkODzN6328YufceCn29+ONxkhe8iuT5F2rafRGRo1BYExERkVnllEqM/+EJRu69m/HHH4NymZhZR8eVV5E482z84XC9qygisiAorImIiMisyB88yOh9v2H0vt9QHBoi0NJC2+suJXn+BYR7ltS7eiIiC47CmoiIiLxgpXSa1EMPMnLfb8g+/RT4fMRP3UTXde8gcdpL8AX1U0NE5IXS/0FFRERkRpxymfT2bYze9xtSj2zByecJL1lK55vfSvMrziXU1lbvKoqINASFNRERETkm+QMH3GGO999HcWgQfzxOy7mvpOXcVxJdswafz1fvKoqINBSFNRERETmsUnqcsQcfZPS+35Dd+TT4fDRt3ETXtW+j6SWn4w9pshARkbmisCYiIiJTlAsFxp94nLHf3c/4Y4/iFIuEly2j863X0vLycwi2tta7iiIii4LCmoiIiLiLVj+1g9EH7iP18EOU02kCzS0kL7yIllecQ2S1hjmKiBxvCmsiIiKLWG7vHkYfuJ+x3z9AcXAQXyRC4syzaHn5OcTXb8AXCNS7iiIii5bCmoiIyCJTGBxg7HcPMPrA/eT37QW/n6aNm+h88zUkTj8DfyRS7yqKiAgKayIiIotCcWSYsYcfIvXg78k8tQOA6NqT6L7+HSRe+jKCzS11rqGIiNRSWBMREWlQxbFRUg8/xNhDD5KxT4LjEF62nI4r30Tzy88h3N1d7yqKiMgRKKyJiIg0kFIqRWrLw4w99HvST26HcpnQkiW0v/6NNJ/9MiLLl9fGukUyAAAgAElEQVS7iiIicowU1kRERBa4Unqc1CNbGHvwQdLbt0KpRKirm/ZLL6f5pS8jfMIKzeQoIrIAKayJiIgsQKVMhvFHH3F70Lb+AadYJNjRQdtrL3F70FatUkATEVngFNZEREQWiNLYGKnHHiG15WHS27a6Aa2tndaLXk3ipS8juuZEBTQRkQaisCYiIjKPFQYHSD2yhdSWh8nssOA4BDs7SV70aprPPJvo2rX4/P56V1NEROaAwpqIiMg8kz9wgNQjD5Pa8jDZZ58BILxsGe1XvJ7EmWcTWbFSPWgiIouAwpqIiEidOY5Dbs9uUlvcgJbfvw+AyOo1dF79FhJnnkV4ydI611JEZGHKlfIcTPdyYLyXg+O9HEj3sn7JWl7ZdV69q3ZUCy6sGWMSwJPAcuCl1tqHqs7dAHwCWA3sBD5nrf1hzfUh4HPAu4BW4EHgg9baR2vKLQH+HrgUcICbgQ9Za/vn5puJiMhi4pRKZJ7awfhjj5J6ZAuF/j7w+YidfApdb3s7iTPOJNTRUe9qiogsCI7jkCqMczDdx4Hxg97WDWaD2aGJcn6fn85YO+tZW8faHrsFF9aAzzJNvY0xbwG+A/xP4FfAVcD3jTGj1tpfVBX9MnAD8BHgOeAvgDuNMZustfu9ewWB24CwVzYE/C/gZ8aY86y1ztx8NRERaWSl9Dh99zzG87+5n/EnHqecTuMLBomt20D7Fa+n6fQzCDa31LuaIiLzVrFcpD8zwMF0n/sa97bpXtLFzES5kD9ET7yLE5OrOHfpS+lp6mZJvJuueCchf5Curmb6+sbq+E2OzYIKa8aYjcCfAv8V+Mea038D/Mha+3Fvf7MxZj3w18AvvOuXe9d/wFr7De/YA8CzwIdwgxvAm4GXAButtVu9cvuB3wKXAbfOyRcUEZGGk+/tZfyxR0g99iiZp3ZAqUQg0Uzi9DNoeskZNJ16Kv5orN7VFBGZV1L5cQ6ke+lN901sD4730Z8dpOyUJ8q1hJvpiXdxZvdp9MS76I53saSph/ZoK37fwp98aUGFNeBrwP8BdlQfNMasAdYBn6wp/z3gW8aYLmttH/A6IABMDI201o4ZY24GLmcyrF0OPFEJal65+4wxu7xzCmsiIjItp1wmu3MnqcceYfzxR8nv3w+4E4S0vfYSTnjVeWTbl2oGRxFZ9ErlEn0TvWS9Ez1lvek+xovpiXJBX4DueBfLEks5wwtlPU1d9MS7iAUb+x+7FkxYM8a8EzgJuAI4u+b0em+7reZ4JWwZoM8rd9BaOzBNueuNMX5rbdkrV3uvSrl1L+wbiIhIoyplMqS3/YHxxx5l/PHHKaXGIBBwnz87/0KaXnIG4e5uAFq6msktgKE3IiKzofIsWW+6f2ooS/fSn5m+l+z07k0smegl66Y92tYQvWQvxIIIa8aYJPBF4CPW2pQxprZIm7cdrjleeZqwvapcbZlKuRCQAEaPUm7DjCovIiINx3Ec8nv3MP7E44z/4QkyO5+GUgl/vImmTZtIvOQM4hs3Eog31buqIiLHRbqQpjfTT2/affVVvc+WshPlgr4AXfFOljUt4YyuyV6y7lgX8VBj95K9EAsirAGfB56y1v5bvSsyUx0diXpXYYquruZ6V0HmgNq1calt54/i+DjDjz7O0JYtDG95lPzgIABNa1az/Ko30nbWGbSsW4cvEDjqvdSujUnt2rjUtq5sIcvzqT6eH+vlQKqX/WMHOTDWx/OpXsZyqYlyPnx0NrWzNNHN+p61LG3uZkmim2UtPXTHO/DPk2HgC6Fd531YM8acijspyGuNMa3e4UoCShhjmpnsQWsFDlRdXulxG/S2Q16ZWm1AAUgdQ7nBaY4f1sBAinJ5fkweuVBmvZGZUbs2LrVtfVXWPkv/4QnGn3jc7T0rl/HHYsQ3nErbG6+iaeMmgq3uXzV5oH8wfeSbonZtVGrXxrXY2rZQKtCXGaA300+f1zPWm+mjL93PSH7qf4fWSJKuWAendWygO95FV6yT7ngnndF2QoHQoTfPwEBm/Dh9kyObT+3q9/sO28Ez78MacDJuPTdPc24z8BjwJm9/Pe4abBWVIYvW224Huo0x7dbawZpyO7zn1SrlTp/m8zYAt8z4G4iIyIJQGh8nvX0r4088wfgfnqA04o6Ij6xYSfullxPfuInYiWvxBRfCX58iItMrlosMZIe8MNZHb2aAPu+ZsuHcCA6THQ3NoQRd8U7Wtxu64510xTvpjrnbSCBcx2+xOCyEv21+A1xUc+x03PXS/hR42Fr7rDHmSeBa4KdV5a4DHvRmggR3/bUycA3wdZhYZPsNwD9XXXcr8E5jzHpr7Xav3CtwF9vWTJAiIg3CKRbJPP0U6e3bSG/bSva5Z8Fx8MfjxDecStPG07zes+kGW4iIzF/ZYo7+zAD9mQH6vFdlfzA7PCWQxYIxuuOdnNS6hq54Jz1eGOuOdzb8bIvz3bwPa9bafuCu6mNVE4w8bK19yHv/aeCHxpidwO3AlbhT9V9Rda99xpivA39rjCkCu4CPAj7gK1UfcRPwOPBjY8zHcf87fRG4H2/NNhERWXgcxyG/fx/prVsZ37aVzI4ncfJ58PuJrjmR9te/kaYNG4meeOIxPXsmIlIvlVkW+6oCWX9mgL60ux0rpKaUbwrF6Yp1sia5ipctOZPOWAfd8S66Y500heL4fL46fRM5knkf1o6VtfZHxpg48AncALYTuN5aWxuuPoz7bNrngSTwIPAaa+3+qnsVjTGXAn8PfBdwgJuBD1pr58cDaCIickyKw8Pu0MZtW0lv2zYxtDHUs4SW886nacOpxMw6AvF4nWsqIjJV2SkzlB2u6hUbnNJDli3lJsr68NEaSdIZa2dT53q6Yp10xjvojLXTFetQD9kC5XMcZY85shp4VhOMyFxTuzYute0LU85mSO/YMTG0Mb9vLwCBRDPx9euJbziV+IaNhDo66lI/tWtjUrs2rrlu23wpz0B2aGrvmLcdyAxRckoTZQO+AJ2xdjpjHXTGOuiKVcJYJx3Rtukn9ZBpzac/s1UTjKwBnqs+1zA9ayIisjiVczn3ubMnt5Ox28k+9xyUy/iCQWInn0LLK95KfMOpRFasxDdPposWkcWjVC4xnBuhPzPIQHaQgcwg/dlBBjJDDGQHGa2ZYTEaiNAZ62BZ01Je0rnRC2Tuqy2aXLSLQy9WCmsiIrKglPN5sjufJm23k37ySbLPPgOlEgQC7nNnl19B3KwnuvYk/GHNVCYic8txHMYKKQYy1UFskP7sEAOZQYZyw5Sd8kR5v89PWyRJR7SdUzvW0RFtpyPWNhHKEqEmPT8mExTWRERkXisXCmSffYbMk9tJP7md7DM7cYpFd1KQVatpe92lxNetJ3bSyfgjkXpXV0QaUKaYdcPYlCA2QH92iMHMIPlyYUr55nCCzmg7a5IrOTt6Oh2xNjqi7XTG2mmLtBLwawIjOTYKayIiMq+Uczmyz+wk89QO97XzaXfGRp+PyIqVtF78GmLr1hE72RCI6YF5EXnxssUcg9kh7zXMYHZooodsMDdEKj91IedoIEJHrJ2eWCcb2k+Z6B1zt+1af0xmjcKaiIjUVSmVIvP0U144s2R37XKHNfp8RE5YQfKCC4mb9cROMQSamupdXRFZYBzHIV3MTISxgZpQNpgZYryYnnJN0BegPdpGR6ydU7rXkKCZjlg7Hd6xpqCmupfjQ2FNRESOq8Lg4GSv2VM7JmZr9AWD7jNnl1xG7ORTiK49SdPpi8hROY7DaD7lBbDByRDmBbKB7CC5Un7KNWF/iPZYO+3RVla1rKAj0kZ7tHXiWEu4eWIij/k0a6AsPgprIiIyZxzHoXDwAJkdk+Gs0N8HgD8aJbr2JJpf+jJipxiia9bgD2nokIhMVSqXGMmPusErUxvGhhjMDVMsF6dcEw/GaI+20Rnr4JS2tW4vWbSNdu+lRaBloVBYExGRWVPO58k+9yzZnTvJPPM02aefpjQ2CkCguZnYyafQ+urXEDvZEFmxAl9AD9mLLGaO45ApZhjKjTCUHWYwO8xQbpih7AhDObdnbDg3MmU2RXAn8GiPtrG8eRmbujbQEXV7xCphLBaM1ukbicwuhTUREXlBHMehODhAZufTbjjb+TS5Pbvd582AUHcP8Y0biZ18CvFTDKGeJfqXbJFFJl/KM5QdnghjbhCb3B/MDZOvGaLo9/lpjSRpiyRZm1w9pUesPdpKW7SNsBZ/lkVCYU1ERI5JuZAnt2uXG86eccNZaXgYAF84THT1GtovuYzoiWuJrl1LsLmlzjUWkbnkLvY8WhXAKj1ik/vjhfQh17WEm2mLtLKkqZv1HafQFmmlLdpKWyRJW83zYiKLncKaiIgcwnEcikNDZJ95mszOnWR3Pk1u9y53fTMg1NlF3KwjtvYkomtPInKChjSKNJKyU2Y0P8ZIbnSiJ2wwO8RQboRhb38kN4qDM+W6WDA2EbpWJ1e6QSyS9HrEWklGkoT8+vkpcqz0p0VERCiNj7vPmj37jLd9ltKI12sWChFdvYbWV7+W6NqTiK1dSzDZWucai8gLVSgVGMmPMpwbZTg7zHB+lOHsCMM59zWUG2E0P3bIc2Ihf3CiF2xd28m0RZNej9hkz1hUz4qJzCqFNRGRRaacz5PbvWtKOCscPDhxPrRkCfENG4iuXkN0zVqiK1fiC+qvC5H5znEcsqWsF8Imw9fka5Th3Aipwvgh10YCYVojrbRGWjBtJ9EaSXqvFlqjSdojmkFRpB70t6+ISANzSiXy+/eTfe4Zss+64Sy3f9/EJCDBtjaiq08ked75RNecSGTVKgJxLTwtMt+UnTKpwrgburKTwav2VbueGEAi1DQRvla3rJgIZa3R5MRxzZ4oMj8prImINAinVCJ/4AC53c+R3bWL3K7nyO56Difv/njzx+PuJCCXXu71mq0h2NpW51qLLG6O4zBeTDOac58PG86PMpIbZdTbjuTc4Yqj+TFKTmnKtX6fn2S4hdZIkmVNS9jQYap6xNxXMtKiZ8REFjD96RURWYCcYpHc/n3ucMZdz5HbtYvc3j0TwcwXDhNZsZLkBRd6wexEQt09GsIkcpxU1g8bzo0ykh89fBjLjx2yoDO4izonIy0kwy2c0raWZKRlcliiF8SawwnNmijS4BTWRETmuXI+T27vXnK7n/PC2S7y+/ZOzMzoj0aJrFxF8sKLiK5cRWTVKsJLluLz60ecyGxzQ1iWkaqer5H8KPk9WQ6MDEwcG82PUpgmhMWCUZLhFpKRFta2rpl4XwlmyUgzLeEWrSMmIoDCmojIvFIaHye3dw+5PXsY7t3PsH2K/PP7oezOyuZvaiK6cjWtr3ndRDALdXUrmIm8SJVnwkZyY4zm3deY936kqhdsJDdKoVw45PpYKEpLqIVkuJkTk6uqAlgzyUhyIoiFA+E6fDsRWagU1kRE6sAplyn09pLbu5vcnj0TAa04ODBRJpRMElqxisQZZxBZuZroqlUE2zs0lFHkGFVmRxytCmCj+ZS7nXJsjLF86pA1wwCigQgt4WaSkRZWt6yo6Qlzj7eEW1ixtJO+vrE6fEsRaWQKayIic6yUyZDfu4fcnt3ucMa97rbyfBl+P+ElS4iddDKRFRcTWbGCyAkrWXLSCfT3p+pbeZF5qFAqTIaumtdYTQibbihiwBegJdxMS7iZtmiSVS0nTOy3hJtpibjb5nAzEfWEiUgdKayJiMwSp1Si0NdLbt9eL5TtIb9nD4X+voky/ngTkRUrSF5wIZETVhJZsYLwsmX4Q4f+IFQPmiwmhVKBsUKKsfzU12ihuhfMDWiZYmbaeyRCTROB68RkJy2RxJQQ5vaCNRMPxvTnS0QWBIU1EZEZcsplCgP95PftI79/H7l9+8jv30v++ecnJv3A5yPU00Nk9Rpazr/A6y1bQbCtXT8SZVGozIY4lk8xmk8xVkiRqno/GcjGGMuPky1lp71PJBCeCFvLmnpY137S1F4wryesOZQg4A8c528pIjK3FNZERA7DcRyKQ0Pk9+91A9m+feT2uwFtYggjEGxvJ7zsBFo3bCS8bDmR5ScQXroUfyRSx9qLzL5SuXRo79cR9mvXBQPw4aMpFCcRTtASSrCy+QSawwn3FUpMvg83kwg1EQ3qz5GILF7zPqwZY94KvB04C2gHdgL/D/hHa225qtxlwH8HNgD7gK9Ya786zf0+CrwPWAJsBf7SWntnTZlm4IvAW4AosBl4v7X2udn+fiJSf47jUBodIb9/v9dLto/cvr3k9++jnJkcbhVIJoksO8EdwrjsBMLLlxNeuoxAPF7H2ou8cGWnTLqYIZUfJ1UYJ5VPMeZta3vDUvkU48X0tPcJ+gI0h5tpDrvDDpcnltYEL/d4IpQgEYqrB0xE5BjN+7AGfATYBXwMOAhcBPwDcKJ3DGPMOcDPgH/xyp8HfMUYU7DWfr1yIy+ofQH4BLAFeC9wizHm5dbax6o+8/vAmcD7gVHgc8CdxphN1trp/6YSkXnPfaasj/yB58k/v5/8889PvK8OZf6mJiLLT6D5FecQWbac8PITiCxbTiCRqGPtRY6uWC56ocsLXxPvKyFsnPHC+EQgGy+kp50BESAWjNESTpAIJVjW1ENz21q3N2yiB6yZ5nATzeEE0UBUw3tFRObAQghrb7DW9lXtbzbGJIA/N8Z8ylqbAz4NbLHW/lFVmZXAZ4wx/2StLRtjIsCncHvcvgRgjLkbeAL4JHCNd+zlwBXAFdbaW71jT+D26L0b+L9z/H1F5EUqZ7PkDxwgf2BqIMsfPAilyWFZgWQr4aVLaX7FOYSXLCW8dBmR5csJtCT1w1PqznEccqU8qYIXsPKpmgDmhrBU3g1f44VxMsXpn/uqDD1sCjWRCDWxJN5FIrmaRKiJRDjhbd1ziZAbwIL+hfATQUSksc37/xPXBLWKR3CHJ7YbYwaBi4GP15T5Hm7P2ZnAQ8C5QBL4QdW9S8aYG4GPGGN81loHuBwYAW6rKrfbGPNb75zCmsg84DgOpZERN4gdeH5KKCsODk4W9PsJdXUTXrqUptNOJ7x0GeGlSwkvWUIg3lS/LyCLTqlcYryYJjeSYs9w38Sww1QhPRG6ao9NN+08uMMOE+EETaE4zaEEHbH2iaDlhq6pAawpFMfv08LpIiILzbwPa4dxPjAI9AIGCAPbasps9bbrcMPaem9/+zTlEsByYK9X7snq5+Gqyl0yG5UXkWNXSqXIHzxA4eBB8gcPkD94kMLBA+R7e3Fyk70IvkiU8NKlxE4xbiBbstQNZd09+IIL9X91Ml/lS3nGC2mv1yvN+MS2+lh64lyqkD7sbIfgLrycCDXRFG4iGWlheWLZlJ6u2gAWDUTU+ysisggsuF8wxpizgfcAf+31jLV5p4Zrig5523Zv2wbkrLW1i7NUl9vrlau9V6Vc+zTHReRFKmUybhjrnQxlhd6D5A8cpJwenyzo9xPq7CLU3UPSGMLdPYR6lhBeuoxgW5t+vMqMlZ0y2WKWVFWwqt6milNDV2V7uB4vgGggSsIbctgUitMd73RnP/T2l3Z0UMr4J44lQk2EAqHj+K1FRGShWFBhzRizBLgJ+D3wt3WuzjHp6JhfExJ0dTXXuwoyBxZCuxbHx8kePEj2+YNkDxwgs38/2f3Pk9n/PIXhqf8+EunqJLp0Ka0XvpLo0qXEli8jtnQpkZ5u/Iusl2whtO184DgOuWKOVD7tDifMj3vvJ/dHcylSuXHG8uPeNkUqn6bs1A6kcPl8vokJNBKRJpbGukhEmmiJJEiEm9xzkQTNkckyiXATQc10uGjpz2vjUts2poXQrgvmV48xJgn8AkgDb7TWFrxTlZ6x1ppLKj1ug1XlIsaYqLU2e5RyK6epQltVmWM2MJCiXJ5+pq3jraurmb6+sXpXQ2bZfGlXp1ymODxEoa+PQl/vxDbf20uhv49yKjWlfKClhXDPEmIbN5HsWUKou4fwkiWEurrxh8NTypaAFJAaqu0Yb2zzpW2Pp1K5RKaYZbyYJl1Iky5mGC+kSRcypIvuduq5DOlCmvHi4UMXQNAfnOjZagrG6Y52saZlNYlgfGLijeptIhQnGowe+3NeeSjkYYijTxi8GNt1MVC7Ni61bWOaT+3q9/sO28GzIMKaMSaKOzV/N3CutXag6vROII/7rNltVcc3eNsnvW3lWbX1uBOUVJcbw12brVLutVUTjlSXexKRRaycz1eFsd6JUJbv66XY349TrBoa5vcT6ugg1NVN9KyzCXV1E+rq8rbdBGKx+n0RmVOO41AoF9yQVayEqUxN+HKPZarC13ghc8TnusAdYtgUihEPxYkHYyxLJGkKTu43heJT33vnwv6QhsmKiMiCM+/DmjEmCNwInAZcaK3dVX3eWpszxvwad+r9L1edug44gLueGsB9uLM8XosX1owxAe+626qC2a24SwFcghf+jDErgFcCH5zt7ycynzilEsWhQQr9/RQGBigO9LvhrL+PfG8vpZGpwxX9sRihrm4iy08gcfqZVWGsi1B7B76AhoMtVI7jkC3lyBQzpAsZd1vMels3ZGWKWTeMVQWyjLctHuGZLr/PT1MwTjwUIx6Mkww3s7SpZyJYTZ6bDF9NwTixYFSLKYuIyKIy78Ma8DXgDcBfAHFjzCuqzm2z1lYWrb7HGPMN4N9wF8V+L/C+yqyOXqj7PPAFY0wfboj7Y2AtcH3lhtba3xljbgG+aYz5CJOLYu8Gvj2n31RkjjnFIoWhQYr9/RQG+in091McGJh8PzwE5aqhZD4fwdY2Ql1dNG3c5Iaw7m5Cnd2Eu7vxNzWpt2KeqvRupYteqJoIXJWw5QavyWPefiEzcc3hFkuuiAaixEMxYsEoTcE4S+LdVQEr5gYsbxsPxd0esWCMiGYyFBEROSYLIaxVpsv/X9Ocuwi4y1p7vzHmSuALwA3AfuDD1tqvVxe21n7JGAPwAaAHdzr+K6y1j9Xc9zrgS7hrqkWAzcBbrbVHfxhBpI7KhQLFwYFDQ1jl2PAQOFU/wH0+gm3thDo6iBlDqKOTUGcnoY5Ogh2dhNrbNe19HRVLRcbyKS881fRwTYSqqT1cGS+IpYsZSk7piPcP+0PEgjEvcMVIhpvdwOXtx4JR4sE48WDU3Q9N7s/oeS4RERF5QXyOMz8mv2hAq4FnNcGIzBanXKY0OkJhcJDi4KAbwAYHCYyPMn6gl8Lg4CHDFPH7Cba3uyGso8MNYF4YC3V0utPdK4zNiUK5SLbSW1XMkilmvf0smdLk/sQx73j1fqFcOOJnBHwB4lUhyg1XMWJeD1bMC1lx7xULTe7HglGCfrV9Pej/xY1J7dq41LaNaT61a9UEI2uA56rP6W9qkXnAcRzKqZQ7RHFgwN1WQtnQIIXBAYrDw1Ca2lPii0SIdnXib2mladOmyRBW6R1rbdVzYzNUGT6YqQpN2WmC1KHBa2ooKx6lVwsgHAgTC0S9UOUGrY5oGzGv56or2Uo55584V9vjFfIHNZxQRESkgSmsicwxp1ymNDZKcXiY4tAQxZFhil4YK3hhrDg0hJPPT7nOFwwSbGsj2NZO7ORTCLV3EGxrd3vK2jsItrfjj8fp7m6ZN/8yVE+O41AsF71JMbLkSjm356qUI1vMkS1l3W1VwDqkd8s7fqQp4CuigQjR4GTQSoQTdMU6J3qzqs/FglGigeiUY9FA5KiTZcynf/UTERGR409hTeRFKGUyFIeGKI14QWy48hp2t0PDFEdHDukRq0zcEWxvJ7JiFYnTzyDY1uEFsXaCbe0Empvx+Rv/maBKwMoWc+S8oJWdCFs579w0oavqeK6YI1M6tpDlw3dIaEpGWuhp6p7otYrVBqua4BUJRPS8loiIiMw5hTWRaTjFotsDVukNmwhflZ4x95iTO3RNKH88TrC1lWBrG/H1y9z3bW0Tx4JtbQSaWxb08MRSueSGqcMEqkqvVqaUJTdd4Kq8L+WOOMV7NXfIYIRIMDLRS9UZ6yA6sR+Z6O1ytxEigchEIKtcFw6EFLRERERkQVBYk0XDcRzK4+MUR0YojY64oavyfrhybITi6AjlVOqQ633BIAEvcEVWrKBp02lTQ1ir+94fidTh2x1e2SmTL+XJlfJuL1QpR66Yd7el3OTxaY9N7lfCWa6UP+aAFfIHDwlSrZEk0abuyVB1mKBVG7oUsEREZLFwHMedvdkpe6+p751pjlVvnZr96rLOEa479N6Hlj36+cN99nTXz6TuR/985wjfq/bevnUvhTOuqXdTH5XCmix45XyekheyiiMj7vuR4cnwNTIZxA4Zjgj4QiGCyVYCySThniXETjEEk0mCyak9Yv5EYs4nc3AntyhOCU25id6qybCVL06+9z3rMDye8kLYocEqX8of/YM9QV+AiBeOIoGw2yMViNASaSESCBMJRLxjYfdV1cs1EbKqQpcWMBYRmd8mQgFlb51NZ8rWqdmf2B41NBzph39tMDj8j/cjXf/CQsXMQ8nzIT/5XOEY6n64e8/8vwtHWedywfH5weebduubcuzQ974jXDvlvD+Azxea5tz094/0rOHQ8VHzj8KazDtOuUw5nXYn5RgbozQ66r4fHaU0NkZpzN0WR91gVs5kDr2Jz0eguZlgMkkg2Upk2XICyaQbwlqSE+8DyVb80eiMQ9hkb1WBfClPvpyfCFeVXqxDtuW823tVdo9VjlfCVeX6Y3nuCirPXkWIhaKEfOGJANUWTU6ErYgXttzeqcn9ieAVnAxl4UBYU7mLyAs27Y/+Kb0DtT9ua36YTvlx7UxTzrtHdWg45MfwYX4EM109pvsMt/5O2fseh9Sl5l/oq+rSHw2STecOLTNdXarqf9gf7VPOH6G+L7inpKo+jcTnA/zgr2z9gA/8fnze9qg/+mt+3JdLQZySMyUUHFIen/ec+fSfMWuB5IjXHykQHfq9qt8fev5Yzh0tbFV99jzU3NVMdgFM4qVfZjLnHKsBnUAAABTHSURBVMfByeUojo16wcsLYKkxL4CNUhodc897Qcz9i6yGz4e/qYlgcwuB5mYiJ6wgeOomN3S1JAm2ettkkkCiGfx+CuXCRCDKl/KkvGDkhqUD5IZ2ky8VpgSt6hCVL7nhqvbc0da/qhX0BQgHwoQDk6EqHAiTCDfREWiv6q1ye6bCwam9WNFg5JAAVpm2XTMGSqOY+PF7mB+kU350TvnBW1vmCD9Kj/jDteoehwSOqWWmDRVM/cHsTHvv8v/f3r1HSVKWdxz/Vk93z+xF2QtL4GCC3HxYRETlRA3iDTUsuQgKHkWNYEADMd6IaCIqino0F0QQFTWKRBQEg64RROVyiGIIXtAssI+6sJgEE24L7s7OvSt/vNUzNdXVMz07l66u/X3OmdPbb71V9XTXvDvvU+9bVTyyrMbIzhHiGRKO1m10EEtuEjN7YjI5epL7naeSoJbvPL29Eo4E5MkmAlE02SGd6KsQx9H0jmqz4067DnPU2rFNr1OptBkpSLY95473PDvuldb4sq9Rm0SJbMLU8hrWm2kkZNakhmhREgP9nZVuUrImcxY3GjQGB5nYsZ2JHc3X1L+T0a/x1ChY9rb0TdHAAJXHrSRauZJ41eOI990LVgwwvnyA8RX9jC2rM7q8yvBAjeH+CqOMMzYxloxkNZOo+xmd2MrI4Cgjvx1l9L6QYI1NjIXORYcqUSUkUZU6/dU6/ZWQUC2vLmN1fxitCglXbXJZM4HKS8Qmt9VX13TABTLVmU91KvPO3rfptE7vUDc7wtkz6NPPfsezbGOqI9t+G61JQv42mnE049q2vMbI4HCbDno86+eb3BYzdNbTZ+VbvstsZz+dEHSYIKXWiXMSq5Z6pRcxOtl5b+2wT+uIt9RrdlbzOvpTdaP0smnTgjId2rad3nRCUMnE0W56UWtiMtXpb01IJrfR8j1ktpneRkss7ZKPdLKU7eDPMHLREn/OdzIDdehFZDEoWdvNTSZegzuY2L4jjHbt2M7Y9t8ytv0xxreH940dO2gMDhIP7oShIaI2fapGX4XxZXVGl9cYHqgyvGeV4SesZudAhcE67OiH7fWY7fUG2+sxE9XmGbCdyU/GaPKTqEZ91Prq1Cs16n21kBRVQtL0+PrKUF6p01+pJslSLfmp0p/8u79SpV6pUo/6Qr2oRj2q0leJ8jvbeYlAuoM50YDxGOIRYGh6EhA3aBDTyD0D3+aM94yd7dbYHlkWOvRzTQTafb62iUBOYhC37Kcx9/3lJTLps/6725n7lJZTHNM6xunOZ+qMfEtntTUpmN4RT28rp06ljyiqtmwvf8pNusM+Qwc6b4SgTSe5JanIJDHtz7KnO+H5IyGtIwn5CcdUHG2SivSIQZuEo1lPo+Ei7YW/PZmy3Ip5RTnrdvgnI7/eVOHo2ARj4xO59YoQ30yxdL6P+Xz3ne14oeNrXzenLGfve6xa3vE2u0nJ2m7i+1ddwtjmTVRHxqmNTlAbbVBPftpNGBivwFB/heH+CsP9EUPLKgytqjDcv3yyfKg/Sl4rjNUqRBWoElGLodYgvMaN8NOIqcewdxzzu6NQG4kny2pxTL0R3tfimHrcSN43qMcx9UaDWhxTjWMipn4WQgyMLMiWllZIXSKGCJ3AmIg4mvp2SH9TUfM9rcujqfeN7HoAUfp93nqkllen182s29z/9H2kthUx7TOkY2/EyXpR6/amtklmf9n66X2n1w3/bvn8UUQcQ4PK9PWi7LYiGnHqs0U5cTR/4nRcM9WDar3K2OhE6rvM/z1o88sxbWHuKHOHf3Q77Si0qzufzsz8Ymy9odB8Oh+ddhZm+w6qfRHjE3FuxTJ3/Npts+idv05/p6OodZvFag8L+zszn/hEiuCpB+/JW15+eLfDmJWStd3E0L3Ong8MMlKPGK1H7Nijwni9j/FaxHitwkQ9olGNaFQrUIugWiGKQuJVbURUY6g1IgbiiL4GVBvhtW8woro9ohIDVFId3HYdUYip5CwL70eIGJ6tY590qjvurOeWZTrw6Y5z3H5dcjvYOZ8nahdfZv2ouW5lclnr520tC0XhtVqtMD7eSIpaU+/cZDynMD9pj3L/0kYRLeXtkv7WLXZWc7JWaj95+83b87SvIW5XK79wWnzxTPVaC/L3EXVUL+fQUemrEvVNr9/p9Rh51TqKr229vKI2vzUd/jLkfw+7/vny6y1wm+hwezPFN9BfY3hkbHHim609zHkfna08t+9gPjEu7Pc1n8+XLVy+rM7QUOv1zJ3/rubtYuHia7e9+cSXeyw7XrfdforXZles6GdwcGQB4ivS/995mytHfJ3u52nr9+54e90UzWVYUebkicC9Dz+8g0ajGN+xpt6Uk45reenYlpOOaznpuJaXjm05Fem4VioRa9euBNgf2DptWTcCEhERERERkZkpWRMRERERESkgJWsiIiIiIiIFpGRNRERERESkgJSsiYiIiIiIFJCSNRERERERkQJSsiYiIiIiIlJAStZEREREREQKSMmaiIiIiIhIASlZExERERERKaBqtwMoKjM7GLgIeA4wBFwBvNPdd3Y1MBERERER2S0oWcthZquAm4D7gBOBvYDzgXXAK7sYmoiIiIiI7CaUrOV7I7AaOMLdHwIws3HgcjM7z93v7Gp0IiIiIiJSerpmLd9xwA3NRC3xNWAE2NCdkEREREREZHeiZC3feuCudIG7jwBbgEO6EpGIiIiIiOxWNA0y32rg0ZzybcCaDrfRB1CpRAsV04IoWjyyMHRcy0vHtpx0XMtJx7W8dGzLqSjHNRVHX3aZkrXFsw/A6tUruh3HNGvXrux2CLIIdFzLS8e2nHRcy0nHtbx0bMupgMd1H8JMvklK1vJtA1bllK8GNne4jduBo4HfABMLFJeIiIiIiJRLHyFRuz27QMlavrsJ161NMrN+4EDgCx1uYwT4/gLHJSIiIiIi5bMlr1A3GMl3LXCMma1NlZ0A9CfLREREREREFlUUx3G3Yyic5KHYm4CtwHlMPRT7BnfXQ7FFRERERGTRaWQth7s/CrwQ2AH8C/Ax4Erg9d2MS0REREREdh8aWRMRERERESkgjayJiIiIiIgUkJI1ERERERGRAlKyJiIiIiIiUkB6zlrJmdnBwEXAc4Ah4Argne6+s6uBybyY2SnkP/PvYnd/0xKHI7vIzA4C/hp4FnAYsNndD8uptwH4EHAo8D/ABe5+0VLGKp3r5Lia2aXA63JWP8ndr170IGXOzOwk4NXAM4A1hGcifQq4xN0bqXpqrz2kk+Oq9tqbzOxlwNuBQ4CVhPZ4DXCeuz+WqlfoNqtkrcSSRxDcBNwHnMjUIwjWAXoEQTkcCzyWev+/3QpEdsmTgT8CbiPMdGiZ7WBmzwY2ApcBZwFHAReY2Zi7f3oJY5XOzXpcE/cQOolpv1jEuGR+ziL8PX0H8H/AC4ALgQOSMrXX3jTrcU2ovfaeNcAthL7vI8DhwLnJ60ugN9qs7gZZYmb2TuC9wH7u/lBSdjJwOXCYu9/Zzfhk16VG1tY1j630HjOrZM7cHpkzAnMdsMbdn5kq+wzwJ8C+6TP6UgwdHtfccikuM1vn7g9mys4HzgBWufuI2mvv6fC4XoraaymY2RuASwjt8f5eaLO6Zq3cjiM8yDvdmf8aMAJs6E5IItI02x8BM+snPPPxysyiLwN7A09fpNBkHorwx10WXrZDn/gpMACsUXvtTbMd1yUORxZfs09c75U2q2mQ5bYe+Hy6IDlDtIUwf1d63yYzWwf8GrgU+JC7j3c3JFlABwJ14K5MeXNU/BDgR0sakSykA83sUWAFsAn4iLtnOw1SbEcTplc9ABhqr2WRPq5Naq89ysz6gBphivp7gY3uvtXMDqUH2qxG1sptNfBoTvk2dLao1/0GeB9wCuG6tWuA9wCf62JMsvBWJ6/ZdrwteVU77l0/JdyE5HjCNcX/DVyRTHGWHmBmRwKnAh9z9wnUXksh57iC2muve5hwk70fEfpPJyflPdFmNbIm0oPc/Xrg+lTRd83sMeBcMzvP3bd0KTQR6YC7fzxT9A0zuxF4P2GUXArMzPYmXFbwH8BHuxyOLJB2x1Xttec9H1hOuDvvOcA3zezFXY1oDjSyVm7bgFU55asJw/tSLl9NXgsxx1oWRPPsXrYdN88Gqh2Xy1XA7yVTm6WgzGwP4DpgJ/Cn7j6WLFJ77WEzHNd21F57hLvf4e63uvtngBMId/w8gR5ps0rWyu1uwnVrk5KLKQ8ENnclIhGZiy3AKJl2THgWDKgdiywpMxsg3OZ7L+BYd384tVjttUfNclylXO4AGsBB9EibVbJWbtcCx5jZ2lTZCUB/skzK5ZVADPy424HIwnD3EeBG4BWZRa8iPFPvJ0selCwKM4sIx/m+Nnenky4zsyphBsPhwAZ3vy+9XO21N812XNuso/bau55NyH/u6ZU2q2vWyu0S4K8Ic6vPY+qh2Fe6e/bON9JDzOx6wn8wmwhniDYAZwL/5O73dDM26ZyZLSc8YgNgP+DxZnZi8v72pNPwAeAWM/ss4RmJRwGnA3+pW8QX02zHNXn9IvAV4FeEKTinEa6reO3SRSpzdDHh2UtnA8vN7FmpZXe5+29Re+1FMx5XwpQ4tdcelPSVbiDc3XEYOILwoPOfA19PqhW+zeqh2CVnZk8CLiTchnYIuAI42913djUwmRczu4CQoD2BcNLll4SHZF+QunuVFJyZPRG4t83iU9390qTeccCHCVM17ifcpezCpYhR5m6240qYbvUFwvWlewFjhDO4f+/u31yKGGXuzGwrIfnO8wJ3vzmpp/baQ2Y7roSOvdprD0oGKl4K7J8UbSXcQOb85ORKs16h26ySNRERERERkQLSNWsiIiIiIiIFpGRNRERERESkgJSsiYiIiIiIFJCSNRERERERkQJSsiYiIiIiIlJAStZEREREREQKSMmaiIiUgpmda2aFex6NmUVm9rPkmT89zcwOM7NxMzus27GIiOwOqt0OQEREpJ05JF+nLmog8/Mq4CDg490OZL7cfZOZXQt8AHhZt+MRESk7JWsiIlJkr828fwPwLOD1mfJbgS8BH1mKoOboHcDV7v5QtwNZIJ8GvmVmB7n7r7odjIhImSlZExGRwnL3L6Xfm9mLgN/PlqeML35UnTOzpwFHAOd0O5Z2zCwCBtx9qMNVvgtsA06hwJ9LRKQMlKyJiEgpmNm5wPvcPUqVbQU2E0bc/gF4MrAFeLO732hmxxOm9D0JuAs43d1/nNnuk4APAscAK4C7gQ+5+9UdhHU8MAHcmNrewcAvgLPc/fzMvg4Hfgac6e6fSsr2Ac4D/hhYDdwDXNhcntSpA+8GjiNMuRwA/hP4sLt/PbOPGLgEuImQbBlhxPJSMzsGeB/wFKAf+A1wnbu/qbm+u4+Z2c3ACShZExFZVLrBiIiIlN0BwFeAbwHvAlYBG83sZOBC4MvAe5N6V5lZX3NFM1sP3EZIXv4OOAt4OKn3mg72/QfAXelRK3f/JfBDIG/91wCjwJXJ/vcC/h04Fvgk8BZgE/BJM0snSo8H3gj8gJC0vZvwN/4aM9uQs5/nAhcDXwPeDGw2s0OT72gZcG6yr6uAo3LW/zGw3sxWz/oNiIjILtPImoiIlN3BwHPd/d8AzOxu4Hrg88B6d783KX+UMOL0AuB7ybofB+4HjkwlXBeb2XeAj5jZ5e4+001QDiEkNlmXAZ8ys0Pd/a5k/xXCzUi+5e6PJPU+SBjheoq7P5iUfdrMPgv8rZl9wt0fJUxL3M/dR5o7MLNPAD8hJJjX5cT1dHe/I1X/Lcm+NmSur3tXTvz3ABGwnnC9oIiILAIlayIiUna/aCZqiduS15ubiVqm/AAAM1sDvAh4P7DCzFak6n4beDFh+qTPsO+1hEQq60rgAsINVP4mKXs+8ATCSFfzWrITgWuA2Mz2TK3/HeA04JnA9e4+QZhu2ZwSuZIwsnYLIQHMujWdqCUeS16PN7PPu3tjhs/V/Ex7zlBHRETmSdMgRUSk7H6dfuPuzaTkvzL1muXNqX0HEUaPzgUezPz8Y1Jnrw72H2UL3H0bsBE4OUnKIEyBfIQwFRFgXRLL63P2/9Xs/s3sNDO7ExgmTNV8EDgD2CMnpi05ZVcC3wc+CzxgZl81s5PNLO/EbjPmwj3XTkSkTDSyJiIiZTcxx/JmItI8ofkx4No2dTfNsu+HmEr+si4DTgKea2a3AS8Hvuzuo5n9f4UwZTPPnQBm9mpCkvVN4KPAA4Q7Y54KnJyzXsudH919yMyeR7ie7TjgD4HLgbeb2dGZu0U2P1NZHkcgIlJIStZERETy3ZO8jrv792as2d7dwP5tln2bkFS9Fvgdwk1C/jm1/EFgO1DtYP8nJfG+NH0NnZnN6WHhydTHm5Ofs83sDMKNTV5GSNya9ieMqm2ey/ZFRGRuNA1SREQkh7s/QLi9/elmtm92uZmt62AzPwAONbNlOdsfJyRAJwJ/DvzK3W9NLZ8AriZcQ/bUWfbfHCVMP7bgAMLt9TtiZmtzin+SvK7KlD8D2JxM5xQRkUWikTUREZH2ziAkXD9P7sC4hXCd2DOBQwnXtc3kG4QblLyQqWvR0i4D3ga8hHBtXNa7CDce+WGy/zsJUxCPICRiA0m9jYTRr41mthHYFziTcPOTI2b/mAC8x8yen8S5NdnPXwCDwL82K5lZDXge4c6ZIiKyiDSyJiIi0oa7O3AkIRn6M8Kzyc4knOx8Twfr/4wwOvWKNsvvAH6evP1SzvIHCInh5wgP2P4EIbnbm3BL/ma9LwJnExLICwnXv72NkCx26huEqZSvS/bzVuCnwFHufl+q3ouANcClc9i2iIjsgiiOdSMnERGRxWJmryLc/GM/d384Z/ntwKi75z18unCSkbuGux/f7VhERMpOI2siIiKL6wrC9Mm3ZheY2RGEkbsvLnVQu8LMDiPcKfKcbsciIrI70MiaiIjIEkuSnmcQpiruA+zv7ju7G5WIiBSNRtZERESW3onAF4BlwCuVqImISB6NrImIiIiIiBSQRtZEREREREQKSMmaiIiIiIhIASlZExERERERKSAlayIiIiIiIgWkZE1ERERERKSAlKyJiIiIiIgU0P8DjcHo6TrTT2cAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1008x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Use pandas to_datetime\n",
        "interest_df['Date Changed']=pd.to_datetime(interest_df['Date Changed'], format='%d %b %y')\n",
        "\n",
        "# Preview new Date Changed column\n",
        "interest_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "3HPgXdkT07i5",
        "outputId": "70ab0b9b-d6b8-4927-a1e4-1f085e9485f6"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-04cb98f9-86cf-42a1-b602-cda055613ada\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date Changed</th>\n",
              "      <th>Rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2021-12-16</td>\n",
              "      <td>0.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-03-19</td>\n",
              "      <td>0.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-03-11</td>\n",
              "      <td>0.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2018-08-02</td>\n",
              "      <td>0.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2017-11-02</td>\n",
              "      <td>0.50</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-04cb98f9-86cf-42a1-b602-cda055613ada')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      border-radius: 50%;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-04cb98f9-86cf-42a1-b602-cda055613ada button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-04cb98f9-86cf-42a1-b602-cda055613ada');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "  Date Changed  Rate\n",
              "0   2021-12-16  0.25\n",
              "1   2020-03-19  0.10\n",
              "2   2020-03-11  0.25\n",
              "3   2018-08-02  0.75\n",
              "4   2017-11-02  0.50"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Figure size\n",
        "plt.figure(figsize=(14,6))\n",
        "\n",
        "# Step lineplot\n",
        "sns.lineplot(x='Date Changed', y='Rate', data=interest_df, drawstyle='steps-post')\n",
        "\n",
        "# Aesthetics\n",
        "plt.title('Historical interest rates in England')\n",
        "plt.xlabel('Date changed (year)')\n",
        "plt.ylabel('Rate (%)')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "iQrHmilM1NrM",
        "outputId": "40e90618-7a8e-46e5-aeb7-c6e6855345d4"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Rate (%)')"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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xNOCXmfmjNvc/ISL+iSLq/AHw2sxcXVrrJEmSJKlGXzNdnYqIpRST085u85CvAi8GjgWeBxwIfD8ijiynhZIkSZK0u2HLdD0VmEObQwsz86U1D78fEecDlwOvAZ7RyYUXLpzfye4aEGNj+/W7CZrF7F8qi31LZbJ/qSz2rakNW9B1AvDDzPxVNwdn5paIuBA4ptNjt2yZdHLgkBkb24/Nm2/sdzM0S9m/VBb7lspk/1JZRr1vzZ07p2mSZmiGF0bEcoq1vCygIUmSJGloDE3QRZHl2gac2+0JIuIuwMMoVoqWJEmSpNL1dXhhROwLPLry8CDgThFxXOXxJZl5TWW/ucBTgG9m5pYpzvUd4KDMPKzy+CnAY4HzgQ3AwcApFOXm31nKC5IkSZKkOv2e07UIOK9uW/Xxs4CzKv89AYwDr2xyrnns/np+Ddwd+DfgAOAG4HvAcZl5+XQaLUmSJEnt6mvQlZlXU1QjbLXfha32y8yJuscXAw+ZRvMkSZIkadqGaU6XJEmSJA2dfg8vlHpq5ZoNrFq7EYC995nHtlu2T7nvimWLmVg+PlNNkyRJ0ogy06VZZdXajazbNNlyv3WbJncFZ5IkSVKZzHRp1lm6aD6nnHB000X6Tj979Qy3SpIkSaPKTJckSZIklcigS5IkSZJKZNAlSZIkSSUy6JIkSZKkEhl0SZIkSVKJDLokSZIkqUQGXZIkSZJUIoMuSZIkSSqRQZckSZIklcigS5IkSZJKZNAlSZIkSSUy6JIkSZKkEhl0SZIkSVKJDLokSZIkqUQGXZIkSZJUor363QCpX9ZtmuT0s1fvsX3FssVMLB/vQ4skSZI0Gxl0aSStWLa44fZ1myYBDLokSZLUMwZdGkkTy8cbBlaNMl+SJEnSdDinS5IkSZJKZNAlSZIkSSUy6JIkSZKkEhl0SZIkSVKJDLokSZIkqUQGXZIkSZJUIoMuSZIkSSqRQZckSZIklcigS5IkSZJKtFc/Lx4RhwEnAfcHjgIuz8yj6vY5C3hmg8OPz8zPtzj/3sCbK8cvAC4BXpaZa6bfekmSJElqrd+ZrmXAY4ArgV802e9XwAPqfi5s4/zvBV4EvAl4AnAL8J2IuPs02ixJkiRJbetrpgv4WmZ+BXZltO47xX43ZebFnZw4IsaB5wMvzcyPVrZdDPwaeDlwcreNliRJkqR29TXTlZk7Sjz9I4B5wLk117sR+Drw6BKvqxH07nMu5d3nXNrvZkiSJGkA9TvT1a5DI2IrcEfg58A7M/PcFsccAWzMzC1129cCT42IuSUHfRohv7j6+n43QZIkSQNqGIKuSykKYKwF9gf+CTgnIu6QmWc1Oe4AYGuD7dcDewPzgT/0tqmzw8o1G1i1diMAK5YtZmL5eJ9bNNhWrtnQ7yZIkiRpgA180JWZ76vb9JWIuBA4DThrptqxcOH8mbpU362+4jqu3TwJwN5XzOP4Yw/vc4vat/c+8wAYG9tvt9/dHt+O1Vdct+u/O72ehpv3W2Wxb6lM9i+Vxb41tYEPuqZwHvDBiBjLzM1T7HM9RZn4egcA24DJTi64ZcskO3bs7KyVQ2rbLds5cGz+rv/evPnGPreofdtu2Q7A5s03Mja2X8dtrz2+02NiyYKheq/Uvtrsb9Xe+8zbde9bMWOsTnTzt0tql/1LZRn1vjV37pymSZp+l4wv02XAooi4c932I4FfOp9LUrtWrd3Iuk0dfU+zy7pNk3sEbJIkabQMXaYrIuYATwSuaZLlArgA2FHZ98OVY+cDjwM+XnY7Z4tcv5WVazb4Lb1G3tJF8znlhKN3PW73G73Tz15dZrMkSdIQ6GvQFRH7clv59oOAO0XEcZXHl1R+fxL4LMUCygsoCmlMAE+vO9eVFIHYwwAyc0NEfBg4PSJuBa4BTgLmAGeU9ZpmkxXLFpPrt7Jq7UaDLkmSJKlL/c50LaKYn1Wr+vhZwFeBG4A3VPbdBqwGHp+ZX6s7bi+KdblqvYJi7tZbKSofXgI8PDN/06sXMJtNLB93WJQkSZI0TX0NujLzaorMUzNPaPNcBzfYtg14TeVHKpVDMSVJktTIbC6kIc24T30zXbdLkiRJuzHoUkvVDI6mFksW8Iy/DQCHZEqSJGk3Bl1qasWyxYCBRDsmlo8TSxotDSdJkqRRZtClpgwkOmdmUJIkSbUMuqQeMjMoSZKkegZdUg+ZGZQkSVI9gy5JkiRJKpFBlyRJkiSVyKBLkiRJkkpk0CVJkiRJJdqr3w3QcKiWQZ9YPj7j1165ZgOr1m5kxbLFu65f3VZv3aZJli6aP63rrds0yelnr971uPa6jdqW67fuUTyjn++XJEmSBouZLrXU7zLoq9ZuJNdv3e36q9ZuZN2myT32Xbpo/q72dmPFssW7BW3rNk02fd3V52qv2e/3S5IkSYPFTJdamlg+PpABxNJF8znlhKN7es6J5eO7ZadqM15TiSULdjum+n4NW7arNnvYLLs3at59zqUNs5mdqM+eVvk+S5I0Gsx0SSUYxmxXNXvYKrs3an5x9fXTOr4+e1rl+yxJ0ugw0yWVYFCzg61Mdz7cbDDVfMFu1WdPq9rJokqSpNnBTJck1ZhqvuB05gpKkqTRZqZLkuqUMV9QkiSNLjNdkiRJklQigy5JkiRJKpFBlyRJkiSVyKBL0h6qa4xJkiRp+gy6JO1mGNcYkyRJGmQGXZJ2M7F8nFiyoN/NkCRJmjUMuqQSrds0yelnr3aoniRJ0ghznS6pJNVhetWFdieWj/ezOZIkSeoTM11SSSaWj3PKCUdz0823kuu3mvGSJEkaUQZd0gxZt2nS4hSSJEkjyKBLu1m5ZgO5fmu/m9HQsJcxX7pofr+bIEmSpD4w6NJuqpmY6nykQTOMmaIjDz6AIw8+oN/NkCRJUp9YSEN7iCULBq7owzCXMD/pyfcB4PSzV/e5JZ2pZhYHrS9M18o1G5oG7+s2Tc5YVnK2vseSJGl3Zrok7WE2L5C8au3GXRUlG1m6aP6MZHpn83ssSZJ219dMV0QcBpwE3B84Crg8M4+qeX4e8CrgMcCRFO39GXBaZn6njfPvbLD5j5np5BqpiYnl47M6GFi6aD6nnHB0X9sw299jSZJ0m35nupZRBFRXAr9o8PwdgNcBa4BnAU8GNgDfjojHtnmNDwAPqPl5yDTbLEmSJElt6/ecrq9l5lcAIuIs4L51z98EHJKZ11c3RMQFwD0pMmBfb+Ma6zLz4t40V7pNtdLjMM83kyRJUvn6munKzB0tnt9eG3BVtu2kyHzdvcy2Sa10U+lx3aZJF0mWJEkaMf3OdHUsIuYCDwQua/OQ10TEO4A/At8BTs7Mq8pqn0ZLJ5Ueq8FZtYiDFeskSZJGw9AFXcBLgAD+uY19P0UxBPF3wBHAG4CLIuLemekM9gFVX9J7Jkt4l2li+TgTy8eHrnS8JEmSpmeogq6IeDDwLuDdmfn9Vvtn5jNrHn4/IlZSVD98EfDGTq69cOHwf+hvx977zANgbGy/traXYfUV13Ht5kkOGd8fgEMP3J8H3+dAvnfptbva0G57ptveZtfp9j2ZyfeyE/XtGtR2TlcvX1eZ/UujzT6hMtm/VBb71tSGJuiKiL8EvgJ8GTilm3Nk5i8jYg1wTKfHbtkyyY4djSrQzy7bbtkOwObNN7a1vaw2HDg2n1cef+/dtv/Pqmt2taGd9oyN7Tft9ja7TrfvyUy+l52ob9e2W7azbtMkJ53xPaAYHjnVkMja7GSz/QZBr97/XvWvXL+V8759+UC/Z5pZvehb0lTsXyrLqPetuXPnNE3S9LtkfFsi4lDgW8Bq4OmVYhqSSrRi2eJdwzrXbZpsuqZUdcHhVvtpdy6QLEnSaBj4TFdE3BW4gGJe1t9l5i3TOFcAy4F39Kh50qxVnYMGtDUPbTbMu5tpLpAsSdJo6GvQFRH7Ao+uPDwIuFNEHFd5fAmwCfgmsAh4JXBkETcVatffiogrgWsy82GVxycBhwIrK+c5Ang9cB3wwdJelCRJkiTV6HemaxFwXt226uNnUQRM1Yk9X25w/Jya/94LmFfzOIF/BJ4I3Iki2LoAeENmbppWqyVJkiSpTX0NujLzanYPnBpp9Xz1XAfXPf4a8LWuGiZJkiRJPTIUhTQkSZIkaVj1e3ihSlJGCe91myY5/ezVfS0JXm3DTC6YXL1mo+3DVDyi2icGvaS7JEnSbGPQNUtVS3hXTfdDdrW0dfWc/fjQXm0DFJXyah/PxDXrzVQbemXV2o3k+q1Af+6fJEnSqDLomsV6mYWplg9vp3R4WWpLmM/maw6qXL+VlWs2DN37UZv1hcHMUA5CFlmSJJXHOV2SWhrmRXzrs76DlqGsLkLtwtKSJM1eZrpGwLBmKDQ4hn0R36WL5nPKCUf3uxkNDUIWWZIklctM1yw3zBkKSZIkaTYw6JrlJpaPE0sW9LsZkiRJ0sgy6JL6oDrkU5IkSbOfc7pGxFTzuoahsttss2LZYnL9Vlat3eg8O0mSpBFgpmsENJvXNeiV3WYjh3xKkiSNFjNdI6BV5blBruwmSZIkDTuDLkltqy7i22h7dViqSxR0z0WSJUmanQy6JLWl2bDT2mGpzlfrTvX9qw739f2TJGn2MOgaIhf97Lf84Ke/9Vtw9UV1Ed9WXBOuOy6SLEnS7GUhjSFTzSJIkiRJGg4GXUPkr+91N6veSZIkSUPGoEuSJEmSSuScrlmkdqHjRoscW1Vu8NUvVu38PUmSpOFnpmsWqV3ouH6R42YLJGtw1N7DdZsmvV+SJEmzgJmuWWaqhY5bLZCsmTdV5rF6D4e5il2zrGp9Nq+Wmb2C63VJkjS7mOmS+mA2Zx5bvbbabF4tM3uFFcsWs3TRfN8PSZJmETNdUh/M5sxjO6+tUUZ2mDN7veR6XZIkzT5muoZQdeiWJEmSpMFn0DVkZvOwNEmSJGk2MugaMhPLx10geRYxaylJkjT7GXRJfdJO1tKgTJIkafgZdI2wlWs2kOu3dnycgUBvtMpaljWUtFqOvPrjvZQkSSpXx9ULI+KuwF2AncB1menkoiFV/TBfu4hyKyuWLSbXb2XV2o2uH1SysiocLl00f9d/V0u3ey8lSZLK0zLoioj5wBOBvwceABxQ9/z1wMXAl4DPZeaNJbRTJYklCzr6wD2bS52PgliyYLdS7WWWJW+2QHIvj2mmms0d1nmQ1axkKy6iLEnSYJtyeGFELIyIdwO/Bc4E7g58EXg98ELgRcAbKtvuBnwY+G1EvCci7lJ2wyUNrm6GRpYxnLKbbO6gqC6S3IqLKEuSNPiaZbquBq4CTgY+n5mbm50oIsaA44B/Bp4L3KnVxSPiMOAk4P7AUcDlmXlUg/0eBbwNOBLYAJyRmR9o4/x7A28GngksAC4BXpaZa1odO+h6nRGQeqmbjGhZWdROs7mDorpIcisuoixJ0uBrVkjjSZm5PDM/1CrgAsjMzZV97wM8uc3rLwMeA1wJ/KLRDhHxAOCrwKXAo4BPAGdExPPbOP97KTJybwKeANwCfCci7t5m+waSa3VJkiRJw2PKoCszv9HtSTs49muZuSQzjwOm+rr2jcDqzHxOZn43M98KfAx4U0Q0Gx45DjwfeE1mfjQzvw38A0UBkJe3/WIGkGt1SZIkScNjWiXjI+LuEXG/iFjSzfGZuaPF+W8HPBQ4t+6pzwB3BY7e46DbPAKYV3tspcjH14FHd9NeSZIkSepUV0FXRNwtIr4LXAusAq6OiIsi4uBeNg44FNiHPYcerq38PrzJsUcAGzNzS4Nj79ksSyYNktp1tVxTS5Ikafh0vE5XxYeBzcBfAL+hKHDx8crPQ3vTNOC28vT1K/heX/l95xbHNlr593pgb2A+8Idpta7Pcv1WTjvrEm6/9zyg+HDeTrWzQbFyzYaG89KG7XX0QvW9qH/ttVX3XFNLkiRpODUNuiLiZODfMvPWuqfuCzw2M6+uPF4TEf8JvKP3TRwMCxcOVhDw8BUHkeu3cs3vbuSOt9+LQ8b359AD9+fB9zmQsbH9Gh6z9z5FcFZ9vv5xu7o9rt7qK67j2s2THDK+/27bW72OTvTiHGWqvpfV96L+tR9/7OEcf2yR0H3tB38AdP+aGt232m29uq/Nrtdse6vnetmGXhmE/nnTo2EAACAASURBVFX2a1R/eD9VJvuXymLfmlqrTNdTgOdExMsz8/ya7T8BTomIV1Os43U48BymLobRrWpGq75qRDUD9vsWxzaqNnEAsA2Y7KQhW7ZMsmPHzk4OKdUxhy0kliwg12/lwLH5vPL4e+96bvPmxutTb7tl+27P1z9uV7fHNTpPfdtrTff8Y2P7TfscZau+l8Bu70Wjdk/3fW90fO22Xt3X2nOv2zTJSWd8b7ft1WzeVK8x12/lvG9fviuj1ygj2s5iwCvXbODnV20hliwopR8MSv+a6n0GF00eVoPStzQ72b9UllHvW3PnzmmapGk1r+kY4P3ApyPi6xFxaGX784Fx4BrgZuCnwHbg2dNu8e6uoijzfkTd9iMrvy9vcuxlwKKIqB+CeCTwy1ZFPCRNz1SL+y5dNH/KxYobLYdQHXZZ1e5iwMO8MHInpnqfXTRZkqTB0TTTVQlM/iMizgHeDvw0It4PvDUzH1SpWng3ioIV1/S6cZl5c0RcCDyRYs2tqqcAv6N5Zu0CYEfl2A8DRMR84HEUc88klajdxX3rj2kUKCxdNJ9TTiiKlXayGPCwLozcianeZxdNliRpcLRVSKNSAfB5EXEm8AEgI+LkzPwMsL7bi0fEvtxWvv0g4E4RcVzl8SWVQO7NwP9GxEeBs4G/Bp4LvKg2WxURVwLXZObDKm3eEBEfBk6PiFspsnInAXOAM7pt8yCpfoM/27/JlyRJkoZZR9ULM3M18NcR8Qzg3RHxAuAlmbmmy+svAs6r21Z9/CzgrMz8YUQ8gSLT9gyKaomvyMwP1x23F8W6XLVeQTF3663A/sAlwMMz8zddtnegdJNJ0ODJ9UWRTRe8liRJmp1aVS/cC3gV8HhgX4o1uU7LzE9FxBeBU4EfRsQngdc3WBOrqUr1wzlt7PcN4Bst9jm4wbZtwGsqP9LAWbFs8a6gqx3rNk3y7HdeCBRBmoUSJEmSBl+rQhrvBl5LMT/q48DfAN+MiHmZOZmZJwH3oViv65cR8eJSWyvNMhPLx9vOcNUXTLBQgiRJ0nBoFXQ9BXhbZp6WmR+oPD4KWFbdITMvz8xHAP8EvLK0lqoncv1WVq7Z0O9mqAsTy8d3FZMAeraA9LpNk5x+9urdKgRKkiSpd1oFXdsohhVW7UsxHPCW+h0z80vsWdpdA6RROW6NttrsWbNS7pIkSepeq0IaHwVeWykNfz3wVOD7mdlwfazMvLnH7VMPTVWOW8PlyIOLtcG3b5/+Yt2DWoylmpEdxLZJkiR1qmmmKzNPoxg2eEfgHsAHgcfMQLskTeGkJ9+Hk558n343ozRmZCVJ0mzTsmR8Zn4a+PQMtEUzxHldGmRmZCVJ0mzTak6XZhmzCJIkSdLMmjLoiojvRcQjOj1hRDwyIr43vWapLJ2UKJckSZI0fc2GF/4U+GpE/Ab4HPA/wI8zc7eVXCPiAOAY4FjgeOBuwEfKaa40+1Szj91UDqyWe2923mpWM9dvNeCWJEnqgymDrsx8SUS8B3gZ8GzgZGBnRNxAUclwDnAAcKfKf28G/gt4f2auK7vhmp7qmkzdrvU03epyK9dsMAio6LaCYLMgrXbNLdffkiRJ6q+mhTQy82rgFRHxauBBwAOAw4GFlV2uAy4DLgJ+mJm3ltdU9Urth/Vusisrli0m129l1dqNXQdd1eyL60J1r1mwVpv9qgbWuX5rw30lSZJUrpbVCwEqwdR3Kz8actNdm6lX1eViyQLXYdKUqkMn122a3CMjW5tpXblmw25BvH3qNq53JknSYLB6oTQCVixbTCxZMDSZxRXLFu8KtJYumt8wO1sNtFat3ci6TZOs2zRpVc4aViqVJGlwtJXpkjTcppvdnGnN2tso09rt3MTZzPXOJEkaHGa6NOOqRTQkSZKkUWDQpRlnEQ1JkiSNEoMu9YVFNCRJkjQqDLqkWapaXEKSJEn91XEhjYi4BzABLALOzsyrI2If4K7A7zLzlt42UVKnprsWmyRJknqn7aArIuYCHwaeA8wBdgI/BK4G9gF+BrwZeE/PWympI8NWrVCSJGk262R44euAZwP/AjyAIvACIDMngS8A/9DT1knSFGoXT66qLgZshUxJkjRIOhle+Czg45n59ohY2OD5nwGP7U2zJGlqtUMmaxdPzvVbd1ubyqGVkiRpEHQSdB0I/KjJ8zcB+02vORom1ayCw9g006YaPlkbcFkhU5IkDYpOhhf+DjioyfPHANdMrzkaFtUMQu2HXEmSJEl76iTo+gLwgkr1wqqdABHxKOAZwOd62DYNsInl48SSBf1uhiRJkjTwOgm6TgXWAZcCZ1MEXK+LiIuBrwP/D3hHrxsoSZIkScOs7aArM/8APBB4O7AY+DPwN8B8ioDs/2TmTSW0UZIkSZKGVkeLI2fmnymCrreX0xwNm2rZbijmeVm4QJIkSdpd25muiLgwIh7W5PmHRMSFvWmWhsGKZYtZumg+UARfFtWQJEmS9tTJnK4JimGFU1kEPHhardFQmVg+ziknHM0pJxy9K/iS+i3Xb3Vh5BrVpR0kSVL/dBJ0tXIg8Mcenk+SOuJiyLtzaQdJkgZD0zldEfEE4Ak1m/45Ih7eYNcDgIcDq3rYtmobVjJ1Bu21mfnOKY47C3hmg6eOz8zP96Z1kgbJxPJxVq3daKarovp+SJKk/mpVSONI4PjKf+8EVlAsglxrJ0WGayXwil42ruKFwJ3qtj29sv0bLY79FXBC3bZf9qhdkiRJktRS06ArM99BZe2tiNgBPCczPzMTDatpwy/qt0XE+4GfZeZPWxx+U2ZeXE7LJEmSJKm1tkvGZ2Yv5391LSLuAdwPOKXfbZEkSZKkVjpap2tAPA3YAbSTcTs0IrYCdwR+DrwzM88ts3GSJEmSVKujoCsiHgm8imJe1/7AnPp9MnNeb5o2pROA72XmtS32uxS4BFhL0dZ/As6JiDtk5lnlNlFTWblmA7l+K7FkQb+bIkkdW7lmw5TFSVwgXpI0lbaDrkolwy8CvwDOAV5AkW2aA/wdcDnw1RLaWNuG+wOHAm9vtW9mvq9u01cqizefBpzV6bUXLnQdqmb23qeItcfG9mu63+orrgPg4SsOarlvL8zENTRYqn1x733mlX7/h6F/tftvU+1ZfcV1XLt5kkPG999t+6833MDeV8zj+GMP78l1vF8qk/1LZbFvTa2TTNfrgJ8ADwQWUARdH8/MCyPiL4CLgSt638TdPA34M9BtyffzgA9GxFhmbu7kwC1bJtmxY2eXl539tt2yHYDNm29suV8sWcAxhy1sue90jY3tV/o1NHiqfXHbLdtLvf/D0r/a/bep9my7ZTsHjs3nlcffe7ftp5+9umd9blj6loaT/UtlGfW+NXfunKZJmk6KY9wL+Exm3gpsr2zbCyAzfwV8CHhNl+1sKSL2Ap4EfC0z/1DWdSQNtxXLFhNLFrhQsiRJGhidZLr+XPkBmKRYn2tRzfPXAof1qF2NPBK4C/Dpbg6OiDnAE4FrOs1ySRoeE8vHnVejrjWbswWwbtMkSxc1/iYz129l5ZoN9j9J0h46CbquBO4JkJnbIuIy4B+5LQh6PPCb3jZvN08DtgDn1z8REW8E3ggcmpnXRMRBwCeBz1bavYCikMYExcLKkiTtYdXajU0Dq6WL5jfMoq5Ytphcv5VVazcadEmS9tBJ0HU+8NyIOCUztwFnAB+JiOo8rkOBV/e6gQARMZ8iqPtk5dr15gLzuK2a4o3ADcAbKLJx24DVwOMz82tltFGSNDssXTSfU044uqNjJpaPN82QSZJGWydB11uB9wO3AmTmf0bETcBxFHO83pKZn+p9EyEzJynW2prq+VOBU2se/x54QhltkSRJkqROtB10VTJMW+q2nQ2cXX0cEXMzc0fvmqdhsm7TJKefvXrXWjXVuRGuXSNpUNXP4Wo2tFCSpG51Ur1wShGxT0Q8n/JLxmtArVi2mKWL5rNu0+SuDzCr1m7cNcdBkgZRdQ5X1VRztiRJmo6Wma6I2IdiPtWhwPXA1zPzN5Xn7gC8BHg5cFeKohUaQdWKcaefvbrfTZGkjnQzh0uSpE40Dboi4u7ASoqAq1qk4qaIeDxF+fjPAgcCPwReBHy5tJZKkrpSHfoLONxXkqQ+aJXpehtwCPAu4PuV/34jcCawEPg58JTMvKjMRkqSulM7VK46jM6gS5KkmdUq6DoW+ERmvra6ISJ+B5wHfA34ewtnSNLgql0s2uG/u1u5ZgO5fiuxZEHPzukCyZKkRloV0lgMXFy3rfr4LAMuSdKwqhb56VXhjOp5LB4kSarXKtM1j2LuVq3q4xt63xxJ0mxUX5q9XWXPQYslC3p2fhdIliRNpZ11uv4iIv6q5vH+ld+HR8Rk/c6Z+aOetEySNGtUS7N3sgaWc9AkSbNFO0HXaZWfeh+oezwH2EmRHZN2qa2c5sKj0ujqtDR7WXPQqlk3/x5JkmZKq6DrWTPSCs1qtR9qXHhUUr/VBlz+PZIkzYSmQVdmfnKmGqLZKZYscNFRSV0rqxqgCyJLkmZSq+qFkiT1hdUAJUmzhUGXJGkgTSwf7+kaWpIk9YtBlyRpZFQXRC5TdUikJElVBl2SpJHR6wWR6zkkUpLUSDsl4yVJ6ljtgsjTKc9eXXaiVwsl93JB5HoukCxJasRMlySpFNXS7ND9chErli1m6aL5rNs0aTAjSRpaZrrUc85nkFQ13dLsE8vHmVg+XtpCyWWZbqn72ixhN3qVFZQk9YZBl3pqxbLF5PqtfiMtqeeqwwyrGgUWrYKV6QxzbFft38FuA5/aBZw7Vc0uGnRJ0uAw6FJPOZ9BGmz1gUs7BiFrUj80carAolWw0u0wx0706u9gt1nCYcsKStIoMOiSpBHRTbAxKFmT6jDDqmaBxXSHNEqS1GsGXZI0IuoDl3aYNZl53/zh1eT6rdNaGLrXFR/VmWbDXL0n0mgy6JIkDaVGQyVnYs5W2b536bVA92uJVY8blCzlKJpqmKv3RBpdBl2SpJ7p1dpcrUwVkMzEnK2ZMJ21xIa14uNs02iYq/dEGl0GXZKknqn9hr/MAKiboZKSJPWLQZckqacsZCFJ0u4MuiRJKkHtnLNWxRNqh2Veu3mSA8d6MyzTghozq3ofmw2t7aRfSJo9DLokSeqx2mGV7RRPqP2gfsj4/hx9j7v0rA0Wb5g5tfex0dDaTvuFpNnDoEuS1JTfzHeuds5Zu8UTqsMyx8b2Y/PmG3vWBos3zKxmw2u76ReSZgeDLknSlPxmXpKk6Rv4oCsiTgQ+0eCp/8jMF7c49hnA64CDgauAN2fmub1uoyTNVn4z3xuNsoUzVV5/qutrehotgNzpfXTOnTQ6Bj7oqvG3wA01j3/XbOeIOA74JPBO4ALg74DPRsQfMvP80lopSVKNqbKFM1Ve32xlORoVzOjkPjrnThotwxR0/SQzr+tg/7cA52XmayuPvxsRRwCnAQZdktSF2ozJVM+XmbEZRs2yhTNRXt9sZXmmc/+ccyeNlrn9bkAZIuIQ4HDgnLqnPgPcLyLGZr5VkjTcVixb3DKgKjNjI0nSsBqmTNfPK8HSOuAs4G2ZeesU+x5R+f2Luu1rK78D2NzzFkrSLFabMZEkSe0bhqDrt8CbgB8B24FHAf8CHAKcOMUxB1R+b63bfn3l951720TVq45Rd5iRJO2uOkSzX0MxLd7QvbKKn7Qatuu9kobfwAddmfkt4Fs1m74dETcAp0bEWzLzqplox8KFBg/teviKg/jepdcC8OD7HMjY2H59a0s/r63Zz/6lTtX+fTz0wP2n/BtZVt+qXv/XG25g7yvmcfyxh5dyndlq9RXXce3mSQ4Z37/p/etEbZ9opIx75d8ulcW+NbWBD7qm8DngVOBoilLw9aoZrQXsXuWwmgH7facX3LJlkh07dnZ62Eg65rCFHHPYwl2Pe7HIZzd6tcCo1Ij9S92o//sIe/6NLLNvVa9/+tmr2XbLdvtwh7bdsp0Dx+bzyuPvvWvbdN/DRn2iVq/vlX+7VJZR71tz585pmqSZlYU0gMsqv4+o235k5XfOYFskSZIkjbBhzXQ9GdgJ/KTRk5n564i4HHgS8KWap54CXJKZFtGQJI20XL+VlWs2DMVcoUYLEXei2zlR9dd1SQRJ3Rr4oCsivgVcCPwc2EFRSOOFwMcy81eVfT4GPDMza1/PG4FzI+Iq4NvAE4BHAI+ZweZLkjRwVixbTK7fyqq1G4ci6Gq0EHG7prP4cP11XRJBUrcGPuiiGCr4bOBAivZeAZwCnFGzz7zKzy6ZeV5E7Au8DjiJYu7XUzPThZElSSNtYvn4tDJH/dDtQsTTXXx4JhawljT7DXzQlZkvB17eYp8TaVA+PjM/CXyylIZJkiRJUhsGPuiSJEnlGOR5Xb1cE6vVOljNjhuEOVyDfJ8ktWe2Vi+UJElNVOcmDeoww+p8KpjeXKoVyxZ3HTgNwhyuQb9PktpjpkuSpBE0DPO6ejGfamL5+FBniIbhPklqzUyXJEmSJJXIoEuSJEmSSmTQJUmSBsrKNRvI9Vv73QxJ6hmDLkmSNFCqc5j6XcRCknrFoEuSJA2cWLJgqAtgSFItgy5JkiRJKpEl4yVJGmHdLhzcyIpli7vKTtUuhFxt0yAsSixJvWKmS5KkETWdhYPrrds02fV6UrULIcNgLEosSb1kpkuSpBHVy4WDp5st68VCyJI0qMx0SZIkSVKJzHRJkqSemGp+WP1cL+dwSRo1ZrokSdK0TTU/rNFcL+dwSRo1ZrokSdK0TTU/bKq5Xs7hkjRKzHRJkiRJUokMuiRJkiSpRA4vlCRJpaovsGHhDEmjxqBLkiSVplGBDAtnSBo1Bl2SJKk0vVyAWZKGlXO6JEmSJKlEBl2SJEmSVCKDLkmSJEkqkUGXJEmSJJXIoEuSJEmSSmTQJUmSJEklMuiSJEkacLl+KyvXbOh3MyR1yaBLkiRpgFUXkl61dmOfWyKpWwZdkiRJA2xi+TixZEG/myFpGvbqdwNaiYjjgROAY4A7A1cBHwLOzMwdTY5bCTy4wVP3y8wfl9BUSZIkSdrDwAddwKuAa4BXAxuBhwDvB/6isq2Zi4CT6rZd1usGSpIkSdJUhiHoelxmbq55/N2ImA+8OCLekJk3Nzl2a2ZeXHL7JEmSJGlKAz+nqy7gqroUuD3FcENJkiRJGljDkOlq5EHA74FNLfZ7cERMUrzOHwNvyszvlN04SZIkSaoa+ExXvYi4L/As4L2Zub3Jrt8DXg48Gng6MAe4ICIeWn4rJUmSJKkwVJmuiLgr8AXgR8DpzfbNzDfVHftV4P8BpwIXdnrthQvnd3qIBsDY2H79boJmMfuXymLfUr2995kH9KZv2L9UFvvW1IYm6IqI/YHzgT8Bj8/MbZ0cn5k3R8RXgBd3c/0tWybZsWNnN4eqT8bG9mPz5hv73QzNUvYvlcW+pUa23VIM7plu37B/qSyj3rfmzp3TNEkzFEFXRNwe+CqwCHhgZm7pc5MkSZIkqS0DH3RFxF7A54C/BB6cmdd0eZ7bAX8HXNLD5kmSJElSUwMfdAH/ATwOOBnYNyLuX/PcLzLzDxHxMeCZmbkXQEQ8iGLh5C8BVwN3BV5GsaDy82aw7ZIkSZJG3DAEXY+s/H5Xg+ceAqwE5lV+qn4L7AO8HVhIMQ/sYmAiMy8qraWSJEmSVGfgg67MPLiNfU4ETqx5fCXwt6U1SpIkSZLaNHTrdEmSJEnSMDHokiRJGgLrNk1y+tmrWblmQ7+bIqlDAz+8UJIkadStWLYYKAIvgInl4/1sjqQOmemSJEkacBPLxznlhKNZumjqxVclDS6DLkmSJEkqkUGXJEmSJJXIoEuSJEmSSmTQJUmSJEklMuiSJEmSpBIZdEmSJElSiQy6JEmShkiu3+oCydKQMeiSJEkaEtVFklet3djnlkjqhEGXJEnSkJhYPk4sWdDvZkjqkEGXJEmSJJXIoEuSJEmSSmTQJUmSJEklMuiSJEmSpBIZdEmSJElSiQy6JEmSJKlEBl2SJElDxgWSpeFi0CVJkjREXCBZGj4GXZIkSUPEBZKl4WPQJUmSJEkl2qvfDZAkSZI0M1au2VDK0NS995nHtlu2A8UQ2Inl4z2/xjAz0yVJkiSNiFVrN7Ju02Rp51+3adL5hg2Y6ZIkSZJGyNJF8znlhKN7es6xsf3YvPlGTj97dU/PO1uY6ZIkSZKkEpnpkiRJGkLrNk12nFWonXej/urVvKdO52it2zTJ0kXzp31ddcZMlyRJ0pBZsWyxH5yHWC/nPXU6R2vpovm71nrTzDHTJUmSNGQmlo93lSWpzrtRf/V63lMZc7TUW2a6JEmSJKlEQ5Hpioh7AB8A/ga4CTgHOCUz/9TGsc8AXgccDFwFvDkzzy2vtZIkSZJ0m4EPuiJiAfBd4BrgOGAR8G/AGPDkFsceB3wSeCdwAfB3wGcj4g+ZeX6Z7ZYkSZKm0k0hlKnOM6rz+y762W8B+Ot73a3PLWlt4IMu4HnAAcDyzLwOICJuBc6OiLdk5tomx74FOC8zX1t5/N2IOAI4DTDokiRJ0ozrZSGLUS6M8YOfGnT10qOB71QDroovAB8HHgU0DLoi4hDgcOD1dU99BvhERIxl5uYS2itJkiRNqdtCKMOiV1m8dq4zLFm+YSikcQTwi9oNmXkzxfysw1scR/2x3BakRU9aJ0mSJAmY2eUMhinLNwyZrgOArQ22Xw/cucVxNDj2+srvZsdKkiRJ6tBsz+J1axiCroGwcOFwpC61u7Gx/frdBM1i9i+Vxb6lMtm/VBb71tSGIei6HljQYPsBwOUtjqNy7O/qjgP4fSeN2LJlkh07dnZyiPrMBSBVJvuXymLfUpnsXyrLqPetuXPnNE3SDMOcrsu4bX4WABFxO+BQmgddl1V+H1G3/cjK7+xJ6yRJkiSpiWEIur4BPCwiFtZs+3vgdpXnGsrMX1MEZU+qe+opwCVWLpQkSZI0E4ZheOGZwEuAr0TEW7htceRzM3NXZcKI+BjwzMysfU1vBM6NiKuAbwNPAB4BPGamGi9JkiRptA18pisztwIPBSaBLwLvBc4Fnl2367zKT+2x5wHPAo4DvgU8EnhqZrowsiRJkqQZMWfnTotDtHAw8GsLaQyfUZ/QqXLZv1QW+5bKZP9SWUa9b9UU0jgEuHqP52e6QZIkSZI0Sgy6JEmSJKlEBl2SJEmSVCKDLkmSJEkqkUGXJEmSJJVoGNbp6rd5UFQk0fDxvqlM9i+Vxb6lMtm/VJZR7ls1r31eo+ctGd/a3wDf73cjJEmSJA28BwE/qN9o0NXa7YD7Ab8Ftve5LZIkSZIGzzzgbsAlwM31Txp0SZIkSVKJLKQhSZIkSSUy6JIkSZKkEhl0SZIkSVKJDLokSZIkqUQGXZIkSZJUIoMuSZIkSSqRQZckSZIklWivfjdAaiQiDgNOAu4PHAVcnplHNdjvlcCLgAOBq4H3ZuaH6/a5I/AvwPEUi9ZtAP4LeGdm3lKz337AvwLHAbcHvgu8JDOv7vHLUx/1uG/tDZwKPAMYAxJ4c2Z+ocH5Tqqc767AWuCUzPxOz16Y+i4ijgdOAI4B7gxcBXwIODMzd9Ts9yjgbcCRFH+PzsjMDzQ4X8s+49+t0dDLvhURLwQeDawA7gIcn5mfb3BN+9aI6FX/ioi7Aa8AHgEcCtwIXAS8NjOvrLvmyPUvM10aVMuAxwBXAr9otENEvBE4HfgU8FjgW8CHIuJ5dbt+CHghcEblnP8JvKFybK3PAo8HXgI8Cbg78J2I2LcHr0eDo5d960zgZcC7gSdQfDA+r/I/ptrznQS8HfiPyrWvAP47Iu7do9ekwfAq4Gbg1RT95svA+6n5WxMRDwC+ClwKPAr4BHBGRDy/9kQd9Bn/bo2GnvUtii+J7gJ8o8U17Vujo1f96xjgH4HzKP6f+BLgL4AfRcSBddccuf41Z+fOnf1ug7SHiJhb/XYlIs4C7lubjYiIOwCbKb6FeVXN9q8ADwTulpm3RsReFN+0vCsz31Sz3weBf8zMxZXHK4CLgcdk5jcq25ZSfNvzssz8YKkvWDOmh33rIODXFP3jA5V95lD8D2lnZt6nsu12wEbgI5l5cmXbPOBnwM8z84llv2bNjIgYy8zNddv+DXgBsCAzb46I84E7Z+aKmn0+AjwOGM/MHe32Gf9ujY5e9a3KtrmVfnYwxd+wPTJd9q3R0sO/XQuAycy8tfbcwLXA2zPztMq2kexfZro0kGrT2VNYBtwRuKBu+wUU3+A9oPJ4DsUw2hvq9ttaea7q0ZV9vlnThnUUafFHd9J2DbYe9q37UfShXftl5k7g28DyiFhS2fxAYH/gnJr9tgOfAx5VCdQ0C9R/aKm4lGLozJ0rwdRDgXPr9vkMxRDCoyuP2+0z/t0aET3sW+38DQT71kjpVf/KzK21AVfNua+lyGRVjWT/MujSsKr+T+Pmuu3VOVpHAmTmNoohYi+JiBURMT8iHgI8F/j3muOOoJjbU/8/o7XA4T1tuQZdW32rg/2OqPy+rG6/tcB8YLy7ZmpIPAj4PbCJYo7DPuw5rHVt5Xf1b027fca/W6Otm77VLvuWetK/Kl9AHsTuf89Gsn8ZdGlYXQnsBP6qbnv18Z1rtj0P+A5FKvtG4ELgvzLzzTX7HMD/b+/ew6WsqjiOf0kTTE1R8dLNC8RK8lKhj6iVQpp20XzKMBQVAvTBu1YkmYmYUqaZpJZliYRZlKWkonjhZmWpoYLiqkwxrylimBdUpD/WfmHzMsOZc5jheM78Ps/jM5559/u+e+Zsx1ln7b12ZL/KFpWuJZ1frWPr76Xnq7XrDixx91dK7RaV2kknY2a7AkOJIixLibEAq37WlMdCrWNGn1tNag3GVq00tppYncfX+NTuyuy5phxfql4oHZK7LzazScDXzWwuaW4wcFhqkv/1ZFw6NoL4otwPONPMnnb389Zit6UDqHVsufs8Sxh6oAAADZdJREFUM5sNfNfMHgceAo4C+uftpDmZ2VbANcBfWbVoj0ibaWxJI9VzfJnZaKJYxsHuvqil9p2dMl3SkZ0C3ENUYHoe+D5RGh7gKQAz25EoD36Mu1/u7rNSoHUuMDaVLIX468omFe7RPV1bmkuLYys5CniOmIe+EDgROKvUbhHQ1cy6le5R/OVQ46uTMbONganAy8BBaZozrPircPmzpjwWah0z+txqMnUYW7XS2GpC9RxfZnYUUV7+BHf/Q+lwU44vBV3SYbn7Qnf/JLG+YSdiP6V/p8N3psdiXc29pdPnAF3TORBzja1CUYM+RAZDmkiNYwt3f8TddwO2I8ZKL+BVYp3XnNSsmMderNMp9CGmuz7RiNcg7SMFSlOALYAD3H1hdvhhYs1fpbEAKz5rah0z+txqInUaW7XS2Goy9RxfZnYQsT3PuCqVCJtyfCnokg7P3Z9093nAUqK86Qx3L9bbLEiPfUun9SXW7RTHbyT+6rJ/0SAt/vwoLe9lIp1UC2Mrb/eou88nFhoPA6529xfT4T8RVZoOLdqn8t8DgZtSxUPpBNIWFZOBnYFPufuC/Li7LyHWlJa3CRgEPA38Lf1c65jR51aTqOPYqpXGVhOp5/gys72JKocT3f30KrdsyvGlfbrkLSltjleUDT2OqJxzavr5LndfYGaDgfWJwgdbEwUzdgT2cveH0nXWIb7AbAt8i9hgdHdiqtgv3X14ds/rgQ8TmwQuBsYSqe6d3P3lhr1YWavqNbbStY4nxspjxBg7FdgI6Ofuz2Ttio1uRxP/cxpObCC5u7vf15hXKmubmV0GHA2MAmaXDj+Y1gvuAcwCJgBXAXsRnzXHufuPs2vVNGb0udUc6jy2diU+r3oAlwIXEBn8l9x9atZOY6tJ1Gt8mdkHiLH0RLre0uw6i919efXDZhxfKqQhb1VbEDua54qfhxL/0S8j1t5sB7xCVCjs5+7/KE5w96VmdiBwNvHlZUtimtj5RIGN3KD0/KXE1MPpxKaRnfI//iZWl7GVdAXOJKYfvgBcD5yeB1wA7n6+mUGs+dqSKIv7GQVcnU7xV9tKBXr6E5nSP5vZ54iA6kjgSeCU/EsxtGrM6HOrOdRtbAHHE+tRC8Um8AuIYKygsdU86jW++hF7DG4M3FG6zkxgn+znphtfynSJiIiIiIg0kNZ0iYiIiIiINJCCLhERERERkQZS0CUiIiIiItJACrpEREREREQaSEGXiIiIiIhIAynoEhERERERaSAFXSIi0mGZ2TIzK+9D1Omk1zmmxrYbmNnTZjaswd1aI2bWw8xeNrNPt9xaRKRj0+bIIiKdnJkNAa7InloCPA/MBW4ArnD3F9t47T7AQGCCuz+6Zj2VOjkJeB34RXt3ZHXc/Vkzuxw428ymurs2DhWRTkuZLhGR5jEGOAIYCfwwPfcDYK6Z7dzGa/YBzgS2XdPOyZozs7cDJwM/d/fX2rs/Nfgx8BFgQHt3RESkkZTpEhFpHje7+53Zz+PMbABwPTDFzHZw91faqW9SH58FegCT27sj1ZjZOsC67r7E3R80s3nAUOC2du6aiEjDKOgSEWli7n67mZ0NnAsMBn4KkDJfpwAfB94N/A+4FRjl7o+lNkNYMW1xupkVlx3q7hNSm92As4C9gPWAe4Az3H16S30zsy7AscAIwICXgDnAWHefXWp7MPBt4P3AP4GvuPtN2fFtgFFERmUb4DXgDmC0u8/N2u0DTAcOA7ZL998c+CNwjLv/s3Tf44CvAFsT0zW/CoxN7+0+WbuuwGnEe/w+4DkiMDrd3V8utftOatct9eXYlt6rzMHAU+7+QHbN/YBpwBfc/Xel/h8EXAd82t2npud6E+/lJ4ANgPnAOe7+2+y8TYHRwP7pfeoC3E38bmdn7bYFHklt/0dMfdwO2BeYkZrdAgw3s3XcfWkrXquISIeh6YUiIlKs/flk9tx+RKAzETgBuBw4AJhhZu9IbWYB49O/n0tMXTwiPY+Z7Q3MBjYlApGvA12BaSm4aclPgIuBp4kv7ecALxCBYG4P4BLgV0Rg1Q24xsw2y9rsls77LfHF/0JiWttMM9u6wr1HAZ8HzgfGAf2Aq/IGZjYy9e+J1H4WcC3wnlK7LsDvU5sbiPdzMhFMXZuOFy4npgdOI4K0JemcWu1JBD+521IfB1doP5h4f6elvu4A/AXYCTiPCCgXAr8xs/z87YFDgKlEoHk28C7g1ipTVY9I7a4ggvmnsmP3ABule4qIdErKdImINDl3f9zM/gv0zJ7+kbtfkLczsylExufzwCR3/5eZzQZOBG5x9xlZ2y7AZUQ2ab+iSEKqNDiHCNL2rNanFJQNBy519+OyQxeWghSAHYA+RRbKzKYD9wGDiKAI4IY8U5Pa/QJ4EBhGZHZy3YBdinVRZrYIuMjMdnT3eWa2HhFozAEGuPvrqd1cYALweHatQUTA2t/dZ2b3vxuYRAS408xsFyII+pG7F9mtS8xsItDimjszW5f4Ha4UpLn7m2Y2CTjZzLq7+6LU/p3Agel+RYbpIuBJYNdsquklZjYN+I6ZXZV+l3OBnu7+Znb/nwAPEeNheKl72wDvd/enWNW/0mMf4N6WXqeISEekoEtERCCmfm1U/FCa8rYhkaH6O5Fp6ksEC6uzC5EpOw/YLJt6CDGd7AQze0d+n5JD0uOZ5QMVqtxNz6f9ufv9ZraYyMYUzy1fq5YydesDiwFPr6dsYqkQRTFlbntgHrArsBkxne71rN1VRBYtN5B47x4ws82z52cCy4D+RKapKJ1+8cqnM57IFLVkU2Ka36IKx64kMo0DiWAY4j3uRsp0pimD+xLTQTcwsw2y828igsPegLv7kuKAmXUjpiF2Ae6i8vt5bZWAi6y/m1c5LiLS4SnoEhERgA2B/xQ/mFl3Ym3RIcSX+dzGNVyvd3r82WrabAZUC7p6As+4+3M13OuxCs8tAroXP6TAYCyRSSpPJ1xYwzWLwKC45jbpcaU1Xu7+hpk9Wjq3NxGAPlvhPgBbZNdcVr4mEbC1RjkTiLvPN7O7iNdfBF2DgQfcfU76uVc6d0z6p1pf3czeRkyXPJpYo5V7pMJ5D9fQX5WMF5FOS0GXiEiTM7P3EIFU/mV/MlH84gJiCt2LxJfiX1HbeuCizWnEmp1KqgUhrVWt+EIefPwQ+HJ6/BORsXuTKJlf6fXUcs1avY2YxnhSleNPtuGalSwkfkfdqxyfCIxPxS3eAPYGvpEdL96HC4Ebq1xjXnocTUzJvBL4Zrr30vR8zwrnra4qZtHfWgJsEZEOSUGXiIgUU9duhuVZrn2BMe5+VtEoZYvKX+irZSeKzMaL7n5rG/r0MHCAmfVw93oEZ18kpgyenD+ZXmtbvuwvSI+9iOmSxfXWJfYsuz9r+zAx5e62FjYAXkAEdb2IIK3Qu3Lzlbn7UjP7B6tmngpXE0H0YKJ6I6xcHKRYW/VGDb+zLwIz3H1I/qSZnVW5+WoV/Z3fhnNFRDoEVS8UEWliaZ+uM4gpYcUX8CLLU87qnMKq/994KT2Wg7F7iMzZqWa2UekYZtajha4VRS/GVDi3LdmmpZRej5kNIirutcXdRHZnRNqQuHA4q74Xvwa2JDalXomZdc3en6np8fhSsxNa0a8/EuvNVuHuC4kiG4NTP6e7++PZ8f8QJepHmNm7K/Q1/51Vej/3JCpJtlZfYk3h3JYaioh0VMp0iYg0j/3NrBfx2b8lsWfVfkSG5SB3fxXA3Reb2QxgVKrStwD4KDEdrbz+aQ5pWpmZbUJMI/uLuz9iZsOIAgwPmtnPiYp+70rX6UIUkKjI3WeY2QTgWDPryYqAZA8ii3RuK1/7FODIVGBjHvAh4FBWZHdaxd1fM7MxxHTF281sMrEmayiR2cozWpOItXGXpDL6dxCv34jCFkXW6F4zuxoYaWYbEwFUf2rMdCXXAUPN7IP5Xl2ZiUT5eoAhFY6PTPe938x+ml7LFsDuRHXBXqndFGBMqqw4m9gf7WgiQ7dhK/oLMQb/oD26RKQzU6ZLRKR5jCEq1V1G7AXVJT3u7O7zSm0PA64HjgG+R2RvBhAZieXc/Rli8+LuxMbKVxNBFe4+i9jf6k5iT6qLiXVVzwPfraG/w4BTgfcSVRDPIIp6zFzdSVWcRBT1OJRYs/RBooz7v9twLQDc/WKiPPp7iffoY0QJ9heAV7N2bxJl9r9GBC7fIyoE9gMuZeWpiF8mqhXuT7zmrsBnWtGtG4iCKANXc/w5ooDJNRVekxOZsinAkcT+Z8cSgfoZWdNxqX8DUn/7A19i1T3CVivtC7YjKzbZFhHplLosW6ZiQSIiIvWQqvo9C/zO3Ue0Ux9GExmrnqVy9pjZOkTG8XZ3P7w9+lfqz3gii9q3hfVuIiIdmjJdIiIibWBm3SqsLzuSyMbNWPs9Wu4iYL3Ul7IDga2IqoPtKq0RGw58UwGXiHR2ynSJiIi0gZntQ0xV/A2x1u0jxJTI+UTm5rXqZ69dZrY7sBNR3n0xsIsCHRGRtUeFNERERNrmUWJN2IlEdut5olDFaW+lgCsZSVQtvB8YooBLRGTtUqZLRERERESkgbSmS0REREREpIEUdImIiIiIiDSQgi4REREREZEGUtAlIiIiIiLSQAq6REREREREGkhBl4iIiIiISAP9H0UAlzhHyjJqAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1008x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Compute consecutive interest changes\n",
        "interest_df['Rate Change']=interest_df.iloc[:,1]-interest_df.iloc[1:,1].append(pd.Series([11.25])).reset_index(drop=True)\n",
        "interest_df.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "xkh_rD8B1PzX",
        "outputId": "e9704451-7409-49e2-83a2-5f606a73619c"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-7a20ac6d-099e-48e5-bb6c-ee052caf59e9\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date Changed</th>\n",
              "      <th>Rate</th>\n",
              "      <th>Rate Change</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>234</th>\n",
              "      <td>1975-03-10</td>\n",
              "      <td>10.25</td>\n",
              "      <td>-0.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>235</th>\n",
              "      <td>1975-02-17</td>\n",
              "      <td>10.50</td>\n",
              "      <td>-0.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>236</th>\n",
              "      <td>1975-02-10</td>\n",
              "      <td>10.75</td>\n",
              "      <td>-0.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237</th>\n",
              "      <td>1975-01-27</td>\n",
              "      <td>11.00</td>\n",
              "      <td>-0.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>238</th>\n",
              "      <td>1975-01-20</td>\n",
              "      <td>11.25</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7a20ac6d-099e-48e5-bb6c-ee052caf59e9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7a20ac6d-099e-48e5-bb6c-ee052caf59e9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-7a20ac6d-099e-48e5-bb6c-ee052caf59e9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "    Date Changed   Rate  Rate Change\n",
              "234   1975-03-10  10.25        -0.25\n",
              "235   1975-02-17  10.50        -0.25\n",
              "236   1975-02-10  10.75        -0.25\n",
              "237   1975-01-27  11.00        -0.25\n",
              "238   1975-01-20  11.25         0.00"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Figure size\n",
        "plt.figure(figsize=(14,6))\n",
        "\n",
        "# Lineplot\n",
        "sns.lineplot(x='Date Changed', y='Rate Change', data=interest_df, drawstyle='steps-post')\n",
        "\n",
        "# Aesthetics\n",
        "plt.title('Size of interest rate changes in England')\n",
        "plt.xlabel('Date changed (year)')\n",
        "plt.ylabel('Rate change (%)')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "id": "qckZH6cl1SLX",
        "outputId": "1707dab2-bf0c-4a30-ecec-d972bb33dd32"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Rate change (%)')"
            ]
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "TaLc0EHv1Uxo"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}