From 80a168933d0d606b4fee7514c1294281bf2c6f87 Mon Sep 17 00:00:00 2001
From: Priya <priya.deshwal0909@gmail.com>
Date: Sun, 9 Jul 2023 20:18:11 +0530
Subject: [PATCH] adding assg

---
 Graded Assignment 2/Priya_210771.ipynb | 2617 ++++++++++++++++++++++++
 1 file changed, 2617 insertions(+)
 create mode 100644 Graded Assignment 2/Priya_210771.ipynb

diff --git a/Graded Assignment 2/Priya_210771.ipynb b/Graded Assignment 2/Priya_210771.ipynb
new file mode 100644
index 0000000..ed89572
--- /dev/null
+++ b/Graded Assignment 2/Priya_210771.ipynb	
@@ -0,0 +1,2617 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 176,
+      "metadata": {
+        "id": "3Tik2tvoPdoq"
+      },
+      "outputs": [],
+      "source": [
+        "!pip install pandas --quiet"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 177,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 35
+        },
+        "id": "BR7wRNtRPlZX",
+        "outputId": "265ac3d6-46af-4a2d-9d91-48a2fc2e59f1"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'1.5.3'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 177
+        }
+      ],
+      "source": [
+        "import pandas as pd\n",
+        "from pathlib import Path\n",
+        "pd.__version__"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import numpy as np"
+      ],
+      "metadata": {
+        "id": "cE9XXPgvzO1S"
+      },
+      "execution_count": 178,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 179,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "M-e79bxgTL7W",
+        "outputId": "4d46068e-b9db-4f3f-b949-7efd437b16b7"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "--2023-06-01 18:08:10--  https://drive.google.com/uc?export=download&id=17bqqiJZ7JCXPt0EwseFBPZbBIuV7-YcG\n",
+            "Resolving drive.google.com (drive.google.com)... 209.85.200.101, 209.85.200.139, 209.85.200.100, ...\n",
+            "Connecting to drive.google.com (drive.google.com)|209.85.200.101|:443... connected.\n",
+            "HTTP request sent, awaiting response... 303 See Other\n",
+            "Location: https://doc-08-98-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/j11sot0dg8mv3g8up187n06tl51reirp/1685642850000/12842633363256377808/*/17bqqiJZ7JCXPt0EwseFBPZbBIuV7-YcG?e=download&uuid=eed00a3c-13a9-4612-b975-214f18e1e64e [following]\n",
+            "Warning: wildcards not supported in HTTP.\n",
+            "--2023-06-01 18:08:11--  https://doc-08-98-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/j11sot0dg8mv3g8up187n06tl51reirp/1685642850000/12842633363256377808/*/17bqqiJZ7JCXPt0EwseFBPZbBIuV7-YcG?e=download&uuid=eed00a3c-13a9-4612-b975-214f18e1e64e\n",
+            "Resolving doc-08-98-docs.googleusercontent.com (doc-08-98-docs.googleusercontent.com)... 172.217.219.132, 2607:f8b0:4001:c13::84\n",
+            "Connecting to doc-08-98-docs.googleusercontent.com (doc-08-98-docs.googleusercontent.com)|172.217.219.132|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 664375 (649K) [text/csv]\n",
+            "Saving to: ‘Machine_temp_failure_missing.csv’\n",
+            "\n",
+            "Machine_temp_failur 100%[===================>] 648.80K  --.-KB/s    in 0.007s  \n",
+            "\n",
+            "2023-06-01 18:08:11 (90.6 MB/s) - ‘Machine_temp_failure_missing.csv’ saved [664375/664375]\n",
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "!wget -O Machine_temp_failure_missing.csv \"https://drive.google.com/uc?export=download&id=17bqqiJZ7JCXPt0EwseFBPZbBIuV7-YcG\"\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 180,
+      "metadata": {
+        "id": "LYVkfnUbTdGl"
+      },
+      "outputs": [],
+      "source": [
+        "filepath = Path('./Machine_temp_failure_missing.csv')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 181,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 238
+        },
+        "id": "fhN491rFcMm-",
+        "outputId": "112fb2ef-5a10-47ee-eeac-e53b5f02967b"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                         value\n",
+              "timestamp                     \n",
+              "2013-02-12 21:15:00  73.967322\n",
+              "2013-02-12 21:20:00  74.935882\n",
+              "2013-02-12 21:25:00  76.124162\n",
+              "2013-02-12 21:30:00  78.140707\n",
+              "2013-02-12 21:35:00  79.329836"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-aa72ccd7-2697-4795-903c-a10e6dc0cf27\">\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>value</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>timestamp</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:15:00</th>\n",
+              "      <td>73.967322</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:20:00</th>\n",
+              "      <td>74.935882</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:25:00</th>\n",
+              "      <td>76.124162</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:30:00</th>\n",
+              "      <td>78.140707</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:35:00</th>\n",
+              "      <td>79.329836</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-aa72ccd7-2697-4795-903c-a10e6dc0cf27')\"\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",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </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",
+              "      cursor: pointer;\n",
+              "      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-aa72ccd7-2697-4795-903c-a10e6dc0cf27 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-aa72ccd7-2697-4795-903c-a10e6dc0cf27');\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",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 181
+        }
+      ],
+      "source": [
+        "ts = pd.read_csv(filepath, header=0, parse_dates=['timestamp'], index_col=0, usecols=['timestamp','value'])\n",
+        "ts.head()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 182,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Bc4LrjQ3gHVk",
+        "outputId": "34ad3b5c-6762-488c-eb85-db1930104ce5"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "value    1285\n",
+            "dtype: int64\n",
+            "                     value\n",
+            "timestamp                 \n",
+            "2013-02-12 21:15:00  False\n",
+            "2013-02-12 21:20:00  False\n",
+            "2013-02-12 21:25:00  False\n",
+            "2013-02-12 21:30:00  False\n",
+            "2013-02-12 21:35:00  False\n",
+            "...                    ...\n",
+            "2014-02-19 15:05:00  False\n",
+            "2014-02-19 15:10:00  False\n",
+            "2014-02-19 15:15:00  False\n",
+            "2014-02-19 15:20:00  False\n",
+            "2014-02-19 15:25:00  False\n",
+            "\n",
+            "[22695 rows x 1 columns]\n"
+          ]
+        }
+      ],
+      "source": [
+        "missing_values = ts.isnull()\n",
+        "missing_counts = missing_values.sum()\n",
+        "print(missing_counts)\n",
+        "print(missing_values)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 183,
+      "metadata": {
+        "id": "XZpEDEBnklou"
+      },
+      "outputs": [],
+      "source": [
+        "#ts = ts.fillna(0)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 184,
+      "metadata": {
+        "id": "rSfUZi1ik01V"
+      },
+      "outputs": [],
+      "source": [
+        "#missing_values = ts.isnull()\n",
+        "#missing_counts = missing_values.sum()\n",
+        "#print(missing_counts)\n",
+        "#print(missing_values)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 185,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 300
+        },
+        "id": "6ItXTd3hk7uC",
+        "outputId": "21d5dda5-3577-4dff-aa3a-a068ac3a4183"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "              value\n",
+              "count  21410.000000\n",
+              "mean      85.968188\n",
+              "std       13.553070\n",
+              "min        2.084721\n",
+              "25%       83.082867\n",
+              "50%       89.251290\n",
+              "75%       93.910748\n",
+              "max      108.510543"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-0e8174b0-3c69-467a-9b72-fbacfa4edb4c\">\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>value</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>21410.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>mean</th>\n",
+              "      <td>85.968188</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>std</th>\n",
+              "      <td>13.553070</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>min</th>\n",
+              "      <td>2.084721</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25%</th>\n",
+              "      <td>83.082867</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>50%</th>\n",
+              "      <td>89.251290</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>75%</th>\n",
+              "      <td>93.910748</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>max</th>\n",
+              "      <td>108.510543</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0e8174b0-3c69-467a-9b72-fbacfa4edb4c')\"\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",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </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",
+              "      cursor: pointer;\n",
+              "      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-0e8174b0-3c69-467a-9b72-fbacfa4edb4c 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-0e8174b0-3c69-467a-9b72-fbacfa4edb4c');\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",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 185
+        }
+      ],
+      "source": [
+        "ts.describe()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 186,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 238
+        },
+        "id": "kDFqWaA8lQ2M",
+        "outputId": "18c2524a-a539-406d-9522-9f298a4e0d05"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                     temperature\n",
+              "timestamp                       \n",
+              "2013-02-12 21:15:00    73.967322\n",
+              "2013-02-12 21:20:00    74.935882\n",
+              "2013-02-12 21:25:00    76.124162\n",
+              "2013-02-12 21:30:00    78.140707\n",
+              "2013-02-12 21:35:00    79.329836"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-c9ee3af0-1f6d-4992-9532-d20d0dfbcc8e\">\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>temperature</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>timestamp</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:15:00</th>\n",
+              "      <td>73.967322</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:20:00</th>\n",
+              "      <td>74.935882</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:25:00</th>\n",
+              "      <td>76.124162</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:30:00</th>\n",
+              "      <td>78.140707</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:35:00</th>\n",
+              "      <td>79.329836</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c9ee3af0-1f6d-4992-9532-d20d0dfbcc8e')\"\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",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </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",
+              "      cursor: pointer;\n",
+              "      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-c9ee3af0-1f6d-4992-9532-d20d0dfbcc8e 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-c9ee3af0-1f6d-4992-9532-d20d0dfbcc8e');\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",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 186
+        }
+      ],
+      "source": [
+        "ts = ts.rename(columns={'value': 'temperature'})\n",
+        "ts.head()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 187,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "44l2nFGhlfD7",
+        "outputId": "1b48a313-cda2-41d5-f895-4aa0fa2337a0"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "                     temperature  delta_temperature\n",
+            "timestamp                                          \n",
+            "2013-02-12 21:15:00    73.967322           0.968560\n",
+            "2013-02-12 21:20:00    74.935882           1.188280\n",
+            "2013-02-12 21:25:00    76.124162           2.016546\n",
+            "2013-02-12 21:30:00    78.140707           1.189128\n",
+            "2013-02-12 21:35:00    79.329836          -0.619417\n",
+            "...                          ...                ...\n",
+            "2014-02-19 15:05:00    98.185415          -0.381246\n",
+            "2014-02-19 15:10:00    97.804168          -0.668700\n",
+            "2014-02-19 15:15:00    97.135468           0.921384\n",
+            "2014-02-19 15:20:00    98.056852          -1.152991\n",
+            "2014-02-19 15:25:00    96.903861                NaN\n",
+            "\n",
+            "[22695 rows x 2 columns]\n"
+          ]
+        }
+      ],
+      "source": [
+        "ts['delta_temperature'] = ts['temperature'].shift(-1) - ts['temperature']\n",
+        "print(ts)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 188,
+      "metadata": {
+        "id": "v3NBgLBxmYHI"
+      },
+      "outputs": [],
+      "source": [
+        "import matplotlib.pyplot as plt\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 189,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 564
+        },
+        "id": "LlB6xkgam_iE",
+        "outputId": "5710e0c1-44a4-4dd8-f7c7-0468b3edba58"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x600 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "plt.figure(figsize=(10, 6))\n",
+        "plt.plot(ts['temperature'])\n",
+        "plt.xlabel('Index')\n",
+        "plt.ylabel('Temperature')\n",
+        "plt.title('Temperature Plot')\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "plt.figure(figsize=(10, 6))\n",
+        "plt.plot(ts['delta_temperature'])\n",
+        "plt.xlabel('Index')\n",
+        "plt.ylabel('Delta_Temperature')\n",
+        "plt.title('Delta_Temperature Plot')\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 564
+        },
+        "id": "pzLzQ2ItjZDY",
+        "outputId": "59e9f95d-945a-43e5-daea-0f6f2d01ab5e"
+      },
+      "execution_count": 190,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x600 with 1 Axes>"
+            ],
+            "image/png": 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AgJ2dHQDg0qVLKCwsRP/+/ZX7+Pr6okmTJjhz5kyFx8jPz0dmZmaZHyIiIiIiIimRZFIml8sxb948dOvWDa1btwYAxMfHw8jICDY2NmX2dXZ2Rnx8fIXHWbp0KaytrZU/7u7umg6diIjqqKhYjsuxaSgslosdChERkVZIMimbNWsWbty4gT///LNOx1m4cCEyMjKUP3fv3lVThEREpCmf7ArBmO9OY9G/N8QOhYiISCskl5TNnj0bO3fuxJEjR+Dm5qbc7uLigoKCAqSnp5fZPyEhAS4uLhUey9jYGFZWVmV+iIhI2jacjgYAbDrPhjQiItINkknKBEHA7Nmz8c8//+Dw4cNo2rRpmfuDgoJgaGiIQ4cOKbfdvn0bsbGx6NKli7bDJSIiIiIiUgsDsQMoMWvWLPzxxx/4999/YWlpqZwnZm1tDVNTU1hbW+OFF17AggULYGdnBysrK8yZMwddunSpUeVFIiIiIiIiKZJMUrZmzRoAQO/evctsX79+PaZNmwYA+Prrr6Gnp4exY8ciPz8fgwYNwnfffaflSImIiIiIiNRHMklZTZZLMzExwerVq7F69WotRERERERERKR5kplTRkREREREpIuYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiJiUERERERERiYhJGRERERERkYiYlBEREREREYmISRkREREREZGImJQRERERERGJiEkZERERERGRiCSTlB0/fhwjRoyAq6srZDIZtm/fXub+adOmQSaTlfkZPHiwOMESERERERGpiWSSspycHAQEBGD16tWV7jN48GDExcUpfzZt2qTFCImIiIiIiNTPQOwASgwZMgRDhgypch9jY2O4uLjU+Jj5+fnIz89X3s7MzFQ5PiIiIiIiIk2QTE9ZTRw9ehROTk5o0aIFXnnlFaSkpFS5/9KlS2Ftba38cXd311KkRERERERENVNvkrLBgwdj48aNOHToED7//HMcO3YMQ4YMQXFxcaWPWbhwITIyMpQ/d+/e1WLERERERERE1ZPM8MXqTJw4Ufn/Nm3awN/fH97e3jh69Cj69etX4WOMjY1hbGysrRCJiIiIiIhqrd70lD3Jy8sLDg4OCA8PFzsUIiIiIiIildXbpOzevXtISUlBo0aNxA6FiIiIiIhIZZIZvpidnV2m1ysqKgpXr16FnZ0d7OzssGTJEowdOxYuLi6IiIjAW2+9hWbNmmHQoEEiRk1ERERERFQ3kknKLl68iD59+ihvL1iwAAAwdepUrFmzBteuXcMvv/yC9PR0uLq6YuDAgfj44485Z4yIiIiIiOo1ySRlvXv3hiAIld6/b98+LUZDRERERESkHfV2ThkREREREVFDwKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhExKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhExKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhExKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhExKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhExKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhExKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhExKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhExKSMiIiIiIhIREzKiIiIiIiIRMSkjIiIiIiISERMyoiIiIiIiETEpIyIiIiIiEhETMqIiIiIiIhEVKekLCIiAu+//z4mTZqExMREAMCePXtw8+ZNtQRHRERERETU0KmclB07dgxt2rTBuXPnsG3bNmRnZwMAgoODsXjxYrUFSERERERE1JCpnJS98847+OSTT3DgwAEYGRkpt/ft2xdnz55VS3BEREREREQNncpJ2fXr1zF69Ohy252cnJCcnFynoIiIiIiIiHSFykmZjY0N4uLiym2/cuUKGjduXKegiIiIiIiIdIXKSdnEiRPx9ttvIz4+HjKZDHK5HKdOncIbb7yBKVOmqDNGIiIiIiKiBkvlpOyzzz6Dr68v3N3dkZ2dDT8/P/Ts2RNdu3bF+++/r84YiYiIiIhUJggCwhKyUFQsFzsUogoZqPIgQRAQHx+PVatWYdGiRbh+/Tqys7MRGBgIHx8fdcdIRERERKSy38/F4v3tNzDQzxnrprQXOxyiclROypo1a4abN2/Cx8cH7u7u6o6LiIiIiEgt1h2PBADsv5UgciREFVNp+KKenh58fHyQkpKi7niIiIiIiIh0ispzypYtW4Y333wTN27cUGc8REREREREOkWl4YsAMGXKFOTm5iIgIABGRkYwNTUtc39qamqdgyMiIiIiImroVE7KVq5cqcYwiIiIiIiIdJPKSdnUqVPVGQcREREREZFOUjkpi42NrfL+Jk2aqHpoIiIiIiIinaFyUubp6QmZTFbp/cXFxaoemoiIiIiISGeonJRduXKlzO3CwkJcuXIFK1aswKefflrnwIiIiIiIiHSByklZQEBAuW3t27eHq6srvvjiC4wZM6ZOgREREREREekCldcpq0yLFi1w4cIFdR+WiIiIiIioQVK5pywzM7PMbUEQEBcXhw8//BA+Pj51DoyIiIiISB2qKINAJAkqJ2U2NjblCn0IggB3d3f8+eefdQ6MiIiIiIhIF6g8fPHIkSM4fPiw8ufo0aO4desWIiIi0KVLl1of7/jx4xgxYgRcXV0hk8mwffv2MvcLgoBFixahUaNGMDU1Rf/+/REWFqZq+ERERA1aYmYeBEEQOwwiIqoBlZMymUyGbt26oVevXujVqxd69OgBX19fAIoEq7ZycnIQEBCA1atXV3j/8uXLsWrVKqxduxbnzp2Dubk5Bg0ahLy8PFV/BSIiogZp57UH6PjZIby19ZrYoRARUQ2onJT16dMHqamp5bZnZGSgT58+tT7ekCFD8Mknn2D06NHl7hMEAStXrsT777+Pp556Cv7+/ti4cSMePHhQrkeNiIhI1604cAcAsOXSPZEjISKimlA5KRMEocLFo1NSUmBubl6noJ4UFRWF+Ph49O/fX7nN2toanTp1wpkzZyp9XH5+PjIzM8v8EBERERERSUmtC32UrD8mk8kwbdo0GBsbK+8rLi7GtWvX0LVrV/VFCCA+Ph4A4OzsXGa7s7Oz8r6KLF26FEuWLFFrLEREREREROpU66TM2toagKKnzNLSEqampsr7jIyM0LlzZ8yYMUN9EdbBwoULsWDBAuXtzMxMuLu7ixgRERERERFRWbVOytavXw8A8PT0xBtvvKH2oYoVcXFxAQAkJCSgUaNGyu0JCQlo27ZtpY8zNjYu05NHREREREQkNSrPKVu8eLFWEjIAaNq0KVxcXHDo0CHltszMTJw7d06l8vtERERERERSofLi0QCwdetW/PXXX4iNjUVBQUGZ+y5fvlyrY2VnZyM8PFx5OyoqClevXoWdnR2aNGmCefPm4ZNPPoGPjw+aNm2KDz74AK6urhg1alRdfgUiIiIiIiJRqdxTtmrVKjz//PNwdnbGlStX0LFjR9jb2yMyMhJDhgyp9fEuXryIwMBABAYGAgAWLFiAwMBALFq0CADw1ltvYc6cOXjppZfQoUMHZGdnY+/evTAxMVH1VyAiIiIiHVC+XjiRtKjcU/bdd99h3bp1mDRpEjZs2IC33noLXl5eWLRoUYXrl1Wnd+/eEASh0vtlMhk++ugjfPTRR6qGTEREpBsq/zolIiIJUrmnLDY2Vln63tTUFFlZWQCA5557Dps2bVJPdERERERERA2cykmZi4uLskesSZMmOHv2LADFXLCqeryIiIiIiIjoMZWTsr59++K///4DADz//POYP38+BgwYgAkTJmD06NFqC5CIiIiIiKghU3lO2bp16yCXywEAs2bNgr29PU6fPo2RI0di5syZaguQiIiIiIioIVMpKSsqKsJnn32G6dOnw83NDQAwceJETJw4Ua3BERERERERNXQqDV80MDDA8uXLUVRUpO54iIiIqI44s5uIqH5ReU5Zv379cOzYMXXGQkREREREpHNUnlM2ZMgQvPPOO7h+/TqCgoJgbm5e5v6RI0fWOTgiIiKqPVZBJiKqX1ROyl599VUAwIoVK8rdJ5PJUFxcrHpUREREREREOkLlpKyk8iIRERERkZTJZDKxQyCqkspzykrLy8tTx2GIiIiIiIh0jspJWXFxMT7++GM0btwYFhYWiIyMBAB88MEH+Omnn9QWIBERERERUUOmclL26aefYsOGDVi+fDmMjIyU21u3bo0ff/xRLcERERERERE1dConZRs3bsS6devw7LPPQl9fX7k9ICAAoaGhagmOiIiIiIiooVM5Kbt//z6aNWtWbrtcLkdhYWGdgiIiIiIiItIVKidlfn5+OHHiRLntW7duRWBgYJ2CIiIiItVxlTIiovpF5ZL4ixYtwtSpU3H//n3I5XJs27YNt2/fxsaNG7Fz5051xkhERERERNRgqdxT9tRTT2HHjh04ePAgzM3NsWjRIoSEhGDHjh0YMGCAOmMkIiIiIiJqsFTuKQOAHj164MCBA+qKhYiIiIiISOfUKSkDgIsXLyIkJASAYp5ZUFBQnYMiIiIi1QmcVEZEVK+onJTdu3cPkyZNwqlTp2BjYwMASE9PR9euXfHnn3/Czc1NXTESEREREalMJnYARNVQeU7Ziy++iMLCQoSEhCA1NRWpqakICQmBXC7Hiy++qM4YiYiIiIiIGiyVe8qOHTuG06dPo0WLFsptLVq0wLfffosePXqoJTgiIiIiIqKGTuWeMnd39woXiS4uLoarq2udgiIiIiLVCVypjIioXlE5Kfviiy8wZ84cXLx4Ubnt4sWLeO211/Dll1+qJTgiIiIiIqKGTuXhi9OmTUNubi46deoEAwPFYYqKimBgYIDp06dj+vTpyn1TU1PrHikREREREVEDpHJStnLlSjWGQUREREREpJtUTsqmTp2qzjiIiIiIiIh0Up0Xj05MTERiYiLkcnmZ7f7+/nU9NBERERERUYOnclJ26dIlTJ06FSEhIRCEslWeZDIZiouL6xwcERHpHpkMEFg8kIiIdIjKSdn06dPRvHlz/PTTT3B2doZMxrXSiYiIiIiIakvlpCwyMhJ///03mjVrps54iIiIqI7Y00hEVL+ovE5Zv379EBwcrM5YiIiIiIiIdI7KPWU//vgjpk6dihs3bqB169YwNDQsc//IkSPrHBwREREREVFDp3JSdubMGZw6dQp79uwpdx8LfRAREYmHwxeJiOoXlYcvzpkzB5MnT0ZcXBzkcnmZHyZkRESkLTuvPcDglccRmZQtdihEREQqUTkpS0lJwfz58+Hs7KzOeIiIiGpl9h9XEBqfhde3cJ4zERHVTyonZWPGjMGRI0fUGQsREZHKcvM5SoOIiOonleeUNW/eHAsXLsTJkyfRpk2bcoU+5s6dW+fgiIiIiIiIGro6VV+0sLDAsWPHcOzYsTL3yWQyJmVEREREREQ1oHJSFhUVpc44iIiIiIiIdJLKc8pKFBQU4Pbt2ygqKlJHPEREpONkYgdARESkZSonZbm5uXjhhRdgZmaGVq1aITY2FoCiVP6yZcvUFiAREVFNCODiXERUCbb2kMSpnJQtXLgQwcHBOHr0KExMTJTb+/fvj82bN6slOCIiIiIiooZO5Tll27dvx+bNm9G5c2fIZI+bH1q1aoWIiAi1BEdERERERNTQqdxTlpSUBCcnp3Lbc3JyyiRpREREREREVDmVk7L27dtj165dytslidiPP/6ILl261D0yIiIiIiIiHVDr4Yt9+/bFtm3b8Nlnn2HIkCG4desWioqK8M033+DWrVs4ffp0uXXLiIiIiIiIqGK17ik7evQoCgoK0L17d1y9ehVFRUVo06YN9u/fDycnJ5w5cwZBQUGaiJWIiIhqQBBYiZKIqD5RudAHAHh7e+OHH35QVyxEREQqYx7yGJ8KIqL6RaWk7NatW4iPj69yH39/f5UCIiIiIiIi0iUqJWX9+vWrcmiETCZDcXGxykERERERERHpCpWSsnPnzsHR0VHdsRARESmq+XIsIhER6RCVkrImTZpUuEYZEREREZHUcAVdkjqV1ykjIiIiIiKiuqt1UtarVy8YGRnVeP9NmzYhJyentqchIiKqlcJiudghEBERqaTWSdmRI0dgY2NT4/1nzpyJhISE2p6GiIioVqJTcsUOQTI4JY+IqH7R+PBFLmBJRERERERUOc4pIyIiIiIiEhGTMiIiIiIiIhExKSMiIiIiIhIRkzIiIiIiIiIRaTwp8/DwgKGhoaZPQ0REREREVC8ZaPoEN27c0PQpiIiIqBQBrHy890Y8olNy8HIvb7FDISKqlspJWXFxMb7++mv89ddfiI2NRUFBQZn7U1NT6xwcERHpHpnYATQAXI0GePm3SwCADp62CPKwEzkaEptMxk8WkjaVhy8uWbIEK1aswIQJE5CRkYEFCxZgzJgx0NPTw4cffqjGEImIiKQnI7cQSVn5YodB1UjKKqh+JyIikamclP3+++/44Ycf8Prrr8PAwACTJk3Cjz/+iEWLFuHs2bPqjJGIiEirjt1JQrdlh3E6IrnSfQI+2o8Onx5Edn6RFiMjIqKGSOWkLD4+Hm3atAEAWFhYICMjAwAwfPhw7Nq1Sz3RERERiWDqz+dxP/0hnvnhXLX7xqbkaiEiIiJqyFROytzc3BAXFwcA8Pb2xv79+wEAFy5cgLGxsXqiIyIiIiIiauBUTspGjx6NQ4cOAQDmzJmDDz74AD4+PpgyZQqmT5+utgCJiIiIiIgaMpWrLy5btkz5/wkTJsDDwwOnT5+Gj48PRowYoZbgiIg0benuEBjq6+GNQS3EDoWINIKlKIlI+lROyo4fP46uXbvCwEBxiM6dO6Nz584oKirC8ePH0bNnT7UFSUSkCUlZ+fj+eCQA4NU+3jAz0vjSjURERETlqDx8sU+fPhWuRZaRkYE+ffrUKSgiIm0oKJYr/891nagh4duZiKh+UTkpEwShwoX4UlJSYG5uXqegiIiIiIiIdEWtx+qMGTMGgGJl9GnTppWptFhcXIxr166ha9eu6ouQiIiIiIioAat1UmZtbQ1A0VNmaWkJU1NT5X1GRkbo3LkzZsyYob4IiYg0ROCYRUmqYBAGkcr4Z04AwI8VkrpaJ2Xr168HAHh6euKNN97gUEUiahCYCBAREZFYVJ5TtnjxYq0mZB9++CFkMlmZH19fX62dn4iIqL5g7xARUf1Sq56ywMDACot7VOTy5csqBVSVVq1a4eDBg8rbJeX4iYiIiIiI6qtaZTWjRo3SUBg1Y2BgABcXF1FjICIiovojp6BY7BCIiKpVq6Rs8eLFmoqjRsLCwuDq6goTExN06dIFS5cuRZMmTSrdPz8/H/n5+crbmZmZ2giTiOqJ0kO8ZJwGTg0Kxy+WeGNLMMYFuYkdBhFRlVSeUwYA6enp+PHHH7Fw4ULlQtKXL1/G/fv31RJcaZ06dcKGDRuwd+9erFmzBlFRUejRoweysrIqfczSpUthbW2t/HF3d1d7XETUMLDQBxEREYlF5UlZ165dQ//+/WFtbY3o6GjMmDEDdnZ22LZtG2JjY7Fx40Z1xokhQ4Yo/+/v749OnTrBw8MDf/31F1544YUKH7Nw4UIsWLBAeTszM5OJGRERSVpGbiEsTAygr8eWAiIiXaFyT9mCBQswbdo0hIWFwcTERLl96NChOH78uFqCq4qNjQ2aN2+O8PDwSvcxNjaGlZVVmR8iIiKpikjKRsBH+zFx3RmxQyEiIi1SOSm7cOECZs6cWW5748aNER8fX6egaiI7OxsRERFo1KiRxs9FRESkDVsv3QMAXIhOEzkSIiLSJpWTMmNj4woLZ9y5cweOjo51Cqoib7zxBo4dO4bo6GicPn0ao0ePhr6+PiZNmqT2cxGRbuBaTqQqgW8eIiJSI5WTspEjR+Kjjz5CYWEhAEAmkyE2NhZvv/02xo4dq7YAS9y7dw+TJk1CixYtMH78eNjb2+Ps2bMaSQCJiIiIqOFgMSeSOpULfXz11VcYN24cHB0d8fDhQ/Tq1Qvx8fHo0qULPv30U3XGCAD4888/1X5MIiKSHsXyBPW7J6pYLkBPpmiwJCLxsXObpE7lpMza2hoHDhzAqVOnEBwcjOzsbLRr1w79+/dXZ3xERET1SlGxHANXHoetmRH+fqVrrR7LFI6IGiJBEPDFvtvwd7PG4NasB1ERlZIyuVyODRs2YNu2bYiOjoZMJkPTpk3h4uICQRDYMkhERDorPCkbkUk5AHJEi4G9AkQkJQdDEvHd0QgAQPSyYSJHI021TsoEQcDIkSOxe/duBAQEoE2bNhAEASEhIZg2bRq2bduG7du3ayBUIiL1EkoNkWNbEtVF8N10fLjjJrLzijDMn63ARESlJWTmiR2C5NU6KduwYQOOHz+OQ4cOoU+fPmXuO3z4MEaNGoWNGzdiypQpaguSiEgTSvcmyDhwjOrgqdWnlP9feTBMxEgU2FFGRFS/1Lr64qZNm/Duu++WS8gAoG/fvnjnnXfw+++/qyU4IiIiXcIeWyIi3VTrpOzatWsYPHhwpfcPGTIEwcHBdQqKiIiIiIgaBvbeV6/WSVlqaiqcnZ0rvd/Z2RlpaWl1CoqISBv4JUHqUFXv1qnwZOQXFWsvGCIiqpdqnZQVFxfDwKDyqWj6+vooKiqqU1BERNrGYWNUG6XnI1ZV6fDZH8/hvX9uaD4gIiKq11Sqvjht2jQYGxtXeH9+fn6dgyIiImootl66hy+fDqjRviw4Q6QZbHgTGdfpqFatk7KpU6dWuw8rLxIREYlH4AUQEUkIP5GqV+ukbP369ZqIg4iISIEt2kREpGNqPaeMiKih+ONcjNghEJXBIVZERLqJSRkR6awfTkQp/89rYaopDg0kIqodfmxWr9bDF4mIGiIZuyioBrLzizDi25Po6eMgdihERNSAMCkjIiKqoW2X7yEqOQdRyTkaOX7Gw0KNHJeIiKSNwxeJiIhqSC4vPwZHnZ2s8Rl56jsYERHVG0zKSKvORqZgwV9XkZZTIHYoRERqwbkSRERV41zc6nH4ImnVxHVnASguYr6e0FbcYIiIGihe/hCVxZxAXHz6q8eeMhJFbGqu2CEQETVYvAAlIqpfmJQRERFJBIuAEmkG/7ZI6piUERERQTHn4UpsGnLyi8QOhYioQWHvffU4p4xEwQmfRCQ1Wy7ew1t/X0MrV6tK99H0enYyLmNORKST2FNGRESSIlZa8tfFuwCAmw8yRYqAiIh0FZMyIiKIlwgQlcZ5L0REuolJGRERUR0wkSIiqhonrVSPSRkREREa1kUD5+0SkZTwM6l6TMpIFPzTJKL6oCa9YOq81ih9Pl7EEBHpDiZlRERElXgyJ9P0UEVWXyQi0k1MyoiIiMCeKSIiEg+TMtI5v56Nwcj/nURKdr7YoRCRRBQVy3E5Nl3sMIiISEcxKSNRiNkg/cH2G7h2LwOrDoWJFwQRVUqMj4d/rtwX4awVKDV68fO9t5FbUCReLFRnP5+MwoAVx5CYlSd2KDqPQ4NJ6piUkc56WFgsdghEVIGCIrnWz5mYJb2e87XHIrDqULjYYVAdfLTzFsISs/H1gTtih0IkKo4Orx6TMhJFxsNCsUMgKoNrTUmTXC7uN7ms1BsjLCEL2fna7bkKS8hS6XG8/pGWgiK+IgTcTc3FjfsZYochCoGfStViUkaiiErOETsEIqoHbj7IrNX+mkriLsWkYcDXx7F87+1y99Ukoc+rYc+82toGeP0jKftuxosdAklAj+VHMPzbk7if/lDsUEiCmJSRzhJjiBSVlaPlXgeqf+SVjHkJvpteYS/Slkt3NRLHgVsJdXr8u9uu12i/1JyCctsEQcDbW69h9REOZayvtN3DStIWnpgtdggkQUzKSGdtv/pA7BB02pHQRLRavA+f7w0VOxSqZ+6nP8RTq09hwNfHkZlXdij07+ditR5PTeZKbKthIZHTESllbhfKBfx79QE2X7yLL/aV76WjmknMZKENIjFxTln1mJQRkSiW7LgJAFhzNELkSKg+OHgrAV/tVyQl3ZYdVm5ftqdsUn/tnnrna8gAZOUVIr9InMJAx+8kYd7mq6Kcuy4EQcDXB+7gyO1EsUMBAHQt9Z4h3cQ5TSR1BmIHQKRrBEHAzF8vwdrUEF88HSBKDGk5BYhOyUFgE1tRzk9UkcJiOc480VNU4sWNFwEA+nplZ11Fa3h+apFcQJsP92v0HA3RpvN38c2jZUeilw0TORrF60gkpj/Pa78X/0k5+UW4cT8D7T3tyn2WalNcxkM0sjYV7fxSxZ4yHVNULIfAPmRRRSXnYP+tBGy5dE+0ynLtPz2I0d+dxomwJFHOT1SRL/fdxpSfz5fbXvoza+XBsusLPjncj4AH6Q+RJfIcpnf/qdkcOl1y84FuVt0jhXdKzSsVKx2a/NM5TFh3FutPRYkUgcK4NWdEPb9UMSnTIXmFxej2+WFMWHdW7FBEE5uSK3YIZQoXiFWGvfhRMrgzOE6cAIgeEQQB3x4Kw57rcfj+eGS5+w+GJOC1P69qP7B6jEP1pOHJRq8rseniBEIAOKcJePwefLJxSxtKP/2sPlkxDl/UIZdj05CQmY+ETOktkqotXDC6rLBE1dZAaogEgWuVieFEWDK+qmJh3W8P163iYFhCFhrZmMLCuOqvu7oMg4xN5RIfVYlOzoGng7nYYWgdF4x+TBCEMmv+iSFMQhUPxag8XFxqZI4Y1UCZFFePPWU65EE6q09l53PRaqmIlkCvZWn30thyJ4Z4DVbFuxidigFfH0fvL45Wu29ugeoNNi//dlnlx9bWg3rYwjzifyfFDoFEFHw3HUGfHMRfFzSzXEVN7AgWt9ry7fiyDaCbL2r/uegmcg96whOf9TVdu1GXMCnTIW9sCRY7BNGlZJdfA0iXSanlUGyszNVwHA5NwPE7ScoFe5OzpTE64F5a3Rsi6uPQxKy8IsRlaDeZvBidqtXzVUQKo1IyHhaWWzZC2+ZsuoLUnAK89fc1UWMQ0yu/XSpzW4xeoycbwCpa51GTNpyOLnN7iwiJqdQxKSPRnAxL1vo5pbD4alyGdHoss/K4oGkJXR9a0ZAKAE3fcBFTfj5fu0YHLYysCo3T3eHC6yqYL6hJs/8Q9yIcEH/eTHpuAQKW7If/h/vx3VHxvvtiU6U1KkIMkRquEquK10VuqOcC2uUxKRPJpZg0nI3U7aph2y7f0/o5g9W8hpEq3tr6uLWwoFguYiRUWsNJSWonJiUHnu/sQtOFuxEvQoOBJs959La0qouyLLtu0/aUqsuxacr/L98rzsLjWU/00kmhYVQKpDB/Ob9Q3OuPc1Hi92ZLDZMyERTLBYxdcxoT151FRq7uznHS1cuT0j1lM3+9VMWepE0NqaeoNmY8Wv8LACas036Z4hUSKYYggWukBi1P5AtAAp5fX365CU1LzSk7ZeCLfeIkh1LDzxsgNF53Rw5UhkmZCIrkj7+c0h/q7hwnXb0ILk2Mlvy7HEpSIV19N0YkPR5WEyOx4ivaJHZlOECxeLYmSGFOnbarzWmygIyqxJ5jdkRiPcckrrRc3b3+lComZSLT5bxEh391UT3ZckkKuvq3WKwjQ+qqawSKkMD8hjgNVciVQlKmG++yqp0K1/48aqLKJGaJ/7lAZTEpE9l5kcbUyiVwIaarF8FSc/wOW08V+IbUZRkPNT+UvLrOOFYAbdguxaRVv1MDw7VBKyaFnnmSHiZlIksVqftYCl/9mhqqQ1V78rVfuidU670lRRJ87dlIoNt4jaRZmVpIeqksmQRmLv1z+b7YIUhSNisfUwWYlIlACh+UUpjPtedGvNghEICQuExsv6LdL86DIYlaPV9NiP8XQZpUXaVTKSRlEvhY1phj7JHXuosx4le3Y4XhivF5oYowKSMifLX/NvK0OMwkv0h6Q1oa8gUxAQVFvAgi3bL6SITYIUhWYpb0CsFokq7MHa7vmJSJjBeCpG1XYsvOa3C1NsGDjDysPxWttRikeIEs5x8jiYzvQCLtSMkWt+CVnpZ75v8WYV1Yqj0mZSITa2K3VL78M/M4z0Dbluy4Veb26wNbAAC+OxKutcqMUqz6xJxMt2ljWHl1Z5DCsHLSrBv3M8QOQedU1Esk9p+aNgt95OQX4UuuD1cvMCkTgRTmLkjFe//c4IWIyEYHNkbLRlbIyi/Ct4fDxA6HSGflFkhvWC+p15IdN3XqO+/mg0yxQ6jw+U7XoTW6vj8eKcmGUCqPSZkIpPB5LIUYAGBH8ANsucRudTHp6cnw7lBfAMBvZ2MQk5JTzSMaJpYj121SaCxj+fCG70J0Gv4LfiB2GFoRn5En2rI/1ckXeQi9toYvxmU8xLrjnFtYXzApE5kUKjGKbfG/NxEugYVbdVkPH0f08HFAYbGA5To6zEEqDRUkDil8EvM9qBuW7g5FbkHDLomeW1CEFzdeqPC+H09EarXwhBTXBNPWtd8X+24jr1COjp52Fd4fGi9+TyY9xqRMZOLNKZPGt3+3ZvZ4WFiMOZuuaLX6H5W3cEhLyGTArmtx5YqB6AJeEOs2bVy4VfcW06VhbbrKzdYU8Zl5WHO04fZeyOUC5v15FTfuV3zB/8muEDy99jQbYzXs2r10bHu0Ttz7w1tWuM/rfwVzzVgJYVImgtLf/br+HbxifFvYmRshJC4Ty/aEih2OTvNztcKYQDcAipZcXbtAlEpDBYlDCm3pfAc2fO8PU1wcf388EndTc0WORjM+3xuK/bcSYGSgV+GwYAtjA1yOTcfQVSew9lgEijScFEjhb7scDQclCAI+2RkCABgT2Bj+bjYV7nfzQWaDbiCob5iU6SipXG87W5ngq6cDAAAbTkfj4K0EkSPSba8PbA5jAz2cj06V5ALPmiSVvwnSjOpeXgmOcKIGaFArF3T1tkdBkRyf7goROxy1+/N8LL4/HgkA+GKcP3ycLMrts29+T/Rs7oiCIjmW7QnF2DWncSchS2MxSfJvW8PfN/tuxuN8dCpMDPXwxqAWVe676lAYbkmgIAsxKSMJ6OPrhBe6NwUAvLk1GPEZurWoo5S42phi+qPXYtmeEI23YEoJczLdJoV5J5pqGGCDg3TIZDIsHtEK+noy7L0Zj1PhyWKHpDanwpPx/vYbAIB5/X3wVNvGFb73GtuY4pfnO2D5OH9Ymhgg+F4Ghq86if8dDtPaUDqxR0acj9ZcAZT8omIsfTTy6KUeXnC1Ma1034F+ziiSC3hjS7Ak1w/VNUzKSBLeGtwCrRtbIS23EK/9eYWrz4vold7esDUzRERSDjZfvCt2OFqTpqU12kgc1SUm4qdk4l8oNnTaWoexOi1cLPFcZw8AihL5DaHxKzwxG6/8dglFcgFPtXXFa/18AFTe2CWTyTC+vTsOzO+Fvr5OKCiW48v9dzBq9SmExLHXpi5+PRODmJRcOFkaY2Yv7yr3/XR0G9iaGeJWXCZWHwnXWExyXtPVCJMykgRjA32smhgIMyN9nItK1eiHA1XNysQQcx99oX59IAw5+Q27SliJcxIt3UzaIYGOMo1pyL9bbUzfcAEPJbIW3Pz+zWFrZog7Cdn47WyM2OHUSWpOAV745QIy84oQ5GGLz8f617jn2cXaBD9NbY+vJwTA2tQQNx9kYsS3J/H1gTsa7blpqL3HqTkF+OaQYr3RNwa1gLmxQZX7O1oaY8lTrQEAq4+Ea2xx8xUH7mjkuA0NkzKR6Voxhap4OVrg40cfDisP3sFFDXbvU9We7eQBD3szJGfnY92j+QEN3dpjEYhK1s012ojLk+iCq3fTMWfTZUn0TFmbGeL1gYq5PisO3JFML15t5RcVY+avFxGTkgt3O1Osey4IJob6yvtrco0jk8kwOtANBxb0VA6n++ZQGEb+76RakgQpDE3WllWHwpCVVwS/RlYY286tRo8Z4d8IQ1q7aGwY4+YLsfgfG9prhEkZScrYIDeMDmwMuQC89udVZOQWih2STjIy0MNbgxQLSv9wIhKJmboxz2/upiscV08aU92lYU3b6PgeVY2xgR4OhiTig39vSKJBdFLHJmjZyAqZeUX4cn/9Wx9SEAQs/Ps6LkSnwdLYAD9P7QB7C2OVj+dkaYLvnwvCqkmBsDUzRGh8Fp5afQpf7ruN/CL19nBK4OVXu/DEbPz6qNf1/WEtoV/DFaplMhk+HtUaduZGCI3Pwv8Oh6ktpuN3kvDuPzfUdryGjkmZCAxK/aFYmhiKGIk0fTyqNTztzXA//SHe/vuaJL48ddHQNi5o626D3IJifH1QfR/SUnb9fga+2MelGXSRFBrTa/pRl5lXu8aqmJSGWXq9tr6ZGAg9GbDp/F2sOiR+y72+ngwfjvADAGw6H4ubDzQzdExT/nc4HNuu3Ie+ngzfTW4HH2fLcvvU9ttbJpNhZIArDizohWFtGqFYLuB/R8Ix4tuTuHo3XS1xN1RLd4egWC6gf0tndG3mUKvHOlgYK0cqrT4agev36v5eDI3PxKu/X0axXMDowMZ1Pp4uYFImAil0pUs5z7EwNsC3k9rBUF9Rner3c7Fih6STZDIZ3h2qWFNn84VYhCdqrmSxFLw9uKRnMApHbuvWcgDUsEUmcVguAAxu7aKcP/P1wTvYfEH875ZOXvYY7t8IggAs+e9WvWmE3HntAb56NE/oo6daoYePY8U7qvjrOFgYY/Wz7bDm2XZwsDDCnYRsjPnuFJbuDkFeYd17zYrkDau3+WRYMg6FJsJAT4aFQ31VOsYw/0bKRPiNLcF16p2Mz8jD8+svIDu/CJ2a2mHZ2DYqH0uXMCkTmVgfwFKv8tXGzVo5fO7jnbdwO75hJwRS1bGpHQb4OUMuoMEv7t2/pROmdfUEALzxV7DODNkkBUk0lmnoc1kCv5pkPNfZA7P6KCrSvfvPDRwOFX9tzHeHtoSJoWJ9yJ3X4sQOp1qXY9Ow4K9gAMAL3Zvi2U4eGjvXkDaNsH9+LzzV1hVyQbHo9tBVJ3Appm5zzl/+7bJkir7UVbFcwCe7bgEAJnf2gLdj+bXhauqjp1rB3twItxOy8K2KvcnZ+UWYvuEC4jLy4O1ojnXPtYexgX71DyQmZboq+K70h0m80L0pejV3RH6RHHM2NZwP0CdJfZ2atwf7Ql9PhoMhiTgbmSJ2OBr1zhBftGxkhZScAiz4K5hlfHWIFPKWetJJorI5m64gLuOh2GHgjYEtMLadG4rlAl79/TKuxKaJGo+rjSle6dUMgGIIWm6BdCve3k3NxUsbL6KgSI7+LZ2Uoyk0yc7cCN9MDMQPU9rDydIYkUk5GLf2DD7eeatO1wXP/Hi23hZYKW3rpbsIjc+ClYmBcikCVdlbGOOTUYre5DXHInDtXnqtHl9ULMfsPy7jVlwmHCyMsOH5jrA24zSdmmJSpqOy60GZcz09Gb4aHwBHS2PcScjGx49aghqaV367hPDEbLHDqFQzJwtM7OAOQHHB0JATFRNDfXw7KRCmhvo4GZ6M73Wk8qROqG6dMi1kZVLojRPTjuAH6PfVMaw5GqH2wg21IZPJsGxsG/Rs7oi8Qjle+OWi6JVXZ/byQmMbUzzIyMPaoxGixlKZrLxCvPjLRSRnF8CvkRW+mRhY42IS6jDAzxkH5vfC2HZuEATgp5NRGPLNcZxTsbHwSmw6xq09jbup9XfOZXZ+Eb7crxhGOrefD2zNjep8zCFtGmG4v2IY4+t/1XwYoyAIWPzfTRy9nQQTQz38OLUD3O3M6hyPLmFSJjJVLm8FQcDDgmIkZ+cjNiUXofGZuBSThhNhSdh3Mx7/XLmH387G4IfjkVh58A4+2x2C97dfV3vs2uBgYYyvx7eFTAb8cS4We65Lf2hHbWXmFeGFXy5IusVuXv/mMDPSR/C9DOxqgK8B8PhvsZmTBZaMbAUA+Gr/bdFb0Uk7YiVwYaap5g4plIAHgCAPW+QWFOPzvaEYsvIEjt1J0ur5F/17A4WPngtDfT2sebYd2jS2RmpOAab8fA5JWflajac0E0N9vD9M0ev0/fFIySUKih6QK7idkAUnS2P8NK19tWtgAep/T1ubGeKr8QFYP60DXKxMEJ2SiwnrzmLxvzdqtabmiABXNLYxRWRSDsauOY1bD+rngtXfH4tAUlY+PO3NMKWLp9qO+9FTreFgYYSwxGysrGGhr3XHI/H7uVjIZIqiOm3dbdQWj66o/i+KNGrntTgUFQvIKSjCw4Ji5BQUITe/GLkl/y8ofvRThJz8YjwsKEJuYXGdh7nUl8nEANDdxwEze3pj7bEIvP33NbRxs4abbcNpfXGzNUVMSi5e/vUSfn2xoyTHXjtaGmNmT298ffAOlu8LxcBWznWKU+rvv6fbu+FEeDJ2BD/AnE1XsPu1HrBipdQGLStP/NEDmvq7yCuURlK29eUu+OfKfXy2OxSRyTmY+vN5DPRzxgfD/bTSor7xTAzCE7Px3bPtYGNmBHNjA/w8rQPGrjmN2NRcPL/hPP58qQssapBsaMLg1i7o4mWPM5Ep+Gx3CNZMDhIljop8tPMWjt1R9ID8NLUDGlmbihpPH18n7F/QE5/tCsGfF+7ilzMxOHw7EZ+P8a9R5UEDPRn+fqUrpq0/j9D4LEz4/gzWTWmPLt72WohePR6kP1SuI7pwaEsYGaivn8XO3AifjGqDl3+7hO+PRWBQK5cqk6xd1+Kw9NG88w+G+WFQKxe1xaJL2FMmsksxafh0dwhWHgzD98cj8dvZWGy7ch97b8bjRFgyLsWkISQuEzEpuUjOzkdOQdmEzMxIHw4WxmhiZwZfF0sEediih48DBrVyxpjAxni2UxO81NML8/rXbZyx2F4f2Bxt3W2QmVeEeX9elUzLrzqsn9YBlsYGOB+dioXbrks2YZnRsykcLY1xN/Uhfjur3qpl0zdcwKbzsZIpriGTyfDp6NZwtzPFvbSHeFfCrwvVnbZe2xkbL2LiujOYu+kKPt55C2uPRWDb5Xs4EZaE0PhMjfWWS2XUpEwmw5h2bjj8Ri+82L0p9PVk2H8rAf1XHMPKg3fUUlWvKmZG+jgdkYKnVp9SVpN1tDTGL9M7ws7cCDfuK0p4F4r0/SKTybB4pB/0ZMCeG/E4LZH5xhtORWHjmRjIZMDKCYFo42YtdkgAACsTQywb649fX+iIxjamuJv6EM/8eA7v/nMdWdUsGyEIAlysTbB5Zhd0amqHrPwiTP35PHbVg0IrJZbvDUV+kRydmtphoJ+z2o8/uLWLssDK639drfTv81JMKub/dRUAMK2rJ6Z3b6r2WHQFe8pEZmVigH4tnWFmpA9zYwOYGurD3FgfZkYGMDNS/Ku4/ej/RgYwNVLsY2KgD71ajOeuaRe0FBnq6+HbSYEY+s0JXIxJwzeHwvD6wBZih6UWPs6W+G5yO0xbfwHbLt+Hl4M5ZveVXhJtZmSABQOaY+G26/j2cBjGBbnB2lS13qMn59YcDk3E4VBFGfoAdxsMaOmE/n7OaOFsqbV5OE9el1uZGGLVxEA8vfYMdl6LQ08fR4x/NLeOGo7ErDy8u017w7vPRtatahygKLZgYWwAE0Pp9arXhJWJId4f7ofxHdyx+N+bOBOZgpUHw7D10j0sGu6HAX7OGvm73/ZqV7z4y0XEpORi9OrTWDUpEH18ndDUwRw/T+uASevO4vidJLz99zV89XSAKHMAfV2sMLmzBzaeicGSHbewa253GOiL135+ODQBH+1UzOd+e7AvBreWXg9IDx9H7JvfE8v2hOC3s7H441wsjoYmYtlYf/RsXnGp/pKPe2tTQ/wyvSPmb76KPTfiMXvTZSRl+WFaN2knFlfvpmP71QeQyYAPhvtp7L364YhWOBWegoikHHx98A4WDilb2CU6OQcv/lJS+EXR602qY1ImsrWTg2q9yJ86FBbXv1Z/dzszfDamDeZsuoL/HQlHF297dPXW/nOnCT18HLFkZCu8v/0Gvtx/B54O5hju7yp2WOU8HeSGn09GISwxG98dDS/3Aa2qNwe1wIFbCbh6Nx3Bj36+3H8Hbram6N/SGf1bOqNjUzu1Ds+oicAmtnh9YAt8vjcUi/+7iXYeNmjmVH6BVKqfdl+Pw3v/XEdabu0WY1bV89080dbdBklZ+UjKykfio38V/8+rcRyjvzsNALA0NoCjpXGZHydLk3L777sZL8lGrObOlvhjRifsuh6HT3eF4F7aQ7z06yX0au6IxSP84FWH0t4V8XWxwr+zuuGV3y7jfHQqpv9yAQuH+GJGDy+0dbfB6mcDMWPjJWy7fB+NrE3w5iDV1nuqqwUDmuO/4Ae4nZCF38/FYuqjpTq0LSQuE3P+uAK5AIxv74aZPb1qfQxtpbUWxgb4ZFQbDG3TCG//fQ13Ux9iys/nMb69G94bVnWiYGKoj/890w5LdtzExjMx+HDHLSRm5ePNQS0kWZxHEAR88ihRHhPohtaNNddzaWtuhM9Gt8ZLv17CD8cjMaiVC9o1sQUApOYUYNr680jLLYS/mzVWTWqr1cIvDRGTMh0164/L+PmULYI8bNGuiQ3aNbGFk1X5L3OpGRHgipNhydh88a6iZeu1nrBTQ7UhKZjc2QORSTn4+VQUXv8rGI1tTBH46MNPKgz09fDOEF+88MtFrD8VjSldPNHYpu5zC2b1aYZZfZohMTMPh0MTcTAkASfCknEv7SE2nI7GhtPRsDQ2QK8Wjhjg54zezZ20VmZ3Zk8vnApPxsnwZMz+4wq2z+pWb3sodFnpNcDScwuw+L+b+PfqAwCAXyMr3IrT/ET/Ll72GFjFXIt9N+Mx89dLNT5eVn4RsvKLEFlN5cA7CdnwfGcXfF0s0cjaRJm8lU3mFP+aGWn3skAmk2G4vyv6tHDC6iPh+OFEJI7dScKglcfxYg8vzO7TrEYFJWrK3sIYv73YCYv/u4FN5+/is92hCI3Pwmej26CvrzM+G90ab/99HauPRMDFygTPqbF4Qk3ZmBnh9YEt8MH2G1hx4A5GBriqpapebSRm5eGFDReQU1CMLl72+GRUG5USFG03/3b1dsC+eT2xfO9tbDgdjb8u3sPxO+WHgT45MkJfT4YlI1vB2coEX+y7je+ORiAhMx/LxraBoYg9lRXZcyMeF2PSYGKohzcHab6xZWArF4wObIx/rtzHG1uCsXtuDwDASxsvIjolF41tTPHj1PZa/+xoiPgMiuxumngVli7FpOFSzOPKco1tTNHOwxZBTWzQzsMWLRtZSe7DCAAWj/TDxZhURCTl4K2twfhhSntJtmap4r1hLRGTkoNDoYmYsfESts/qKrmiJn19ndCpqR3ORaXiq323sWJCW7Ud28nKBBM7NsHEjk3wsKAYJ8OTcfBWAg6FJiA5uwA7r8Vh57U4GOjJ0LGpnbIXrYm95p4jPT0ZVowPwJBvTiA0PgvL9oTiw0fVGan+OXI7Ee/8fQ0JmfnQ15Ph1d7emNPXB83f3yN2aDDUr9nn2IX3+sPYUE/Rw5aZj6Tsx71tSVn52Hb5foWPC43PQmh8VpXHNjfSh5OVCRwtjMv1wpVO3uzNjdXaKm5ubIC3BvtiXJAbluxQFJVYczQC/1y+j/eGtcRw/0Zq+5w3MtDDZ6PboIWzJT7eFYJtl+8jKjkH3z8XhAkdmiA+Ix9fH7yDRf/dhKOliShD9p7p2AS/n41BaHwWvjpwG5+MaqO1cz8sKMaMXy7iQUYevBzMsXZykMqjFMSYi2tmZIAPR7bC0DaN8NbWYESn1Ow6SyaTYVafZnC0NMbCbdfx9+V7SMnJx3fPtpNMwpFfVIyle0IAADN7esPFWjuN6YtH+OFUeDIik3Lw5b7biM/Mw8WYNFiaGGDD8x0q7KGn2pPGu6wWVq9ejS+++ALx8fEICAjAt99+i44dO4odlspux4uzPtXEDu5o72mHy7FpuByThjsJWbif/hD30x9iR7Ci9djEUA/+jW0Q6KHoSWvXxBaOlsaixFuamZEBvp3UDqO+O4WDIYnYcDoaz0t8/HdN6evJ8M2kQIxbcxqh8Vl48ZeL2PJyF1hKqPKfTCbDu0Nb4qnVp/DP1fuY3r1prYdP1OSL2tRIHwP8nDHAzxlyuYCr99Jx8FYCDoYk4E5CNk5HpOB0RAo+2nkLLZwt0d/PCf1bOiPAzaZWcy2VMVXRputkZYKvxgdg2voL2HA6Gt2aOWCABiZWS8GtB5nwc7USOwy1yykoxud7r2PTeUWRGi9Hc6wY31ZSZZvlNawvIZMp5mVZmRjCu4IhfpUlZSV6+DigqYN5mSGUiVl5yCuUI6egGFHJOdWu26UnU/Q6lSRvTk8kb6rycrTAhuc74GBIIj7aeRN3Ux9izqYr+P1cDJaMbI0WLuoZPiyTyTCtW1M0c7LEq79fwpXYdDz1v1P4YUp7zO3XDPGZD7Hp/F3M/fMKfn+xEzp42qnlvDWlryfDhyNbYeK6s/jjXCye6eihlb9LuVzA61uuIvheBmzMDPHztA41HpWQV1iMxEzFeykxKx+JmXk1Tog0oWNTO+x5rSdWHLiNH05Elbmvqt7X8e3d4WBhhFd/v4yjt5Mw6Ydz+Hlqe9hbiH/988vpaNxNfQhnK2PM7FX74aSqsjEzwtIxbfDCLxfx40nFc2moL8P3k4Pg48wh/epSr5KyzZs3Y8GCBVi7di06deqElStXYtCgQbh9+zacnJzEDk8lVV0IapKHvTnGBblhXJAbAMWikMF3MxRJWmwarsSmI+NhIc5Hp+J89OOJ6U3szBTDHT0USZqvi6Uok5D9XK3w3tCWWPzfTSzdHYoOnnYaHVetTRaPyjQ/tfoUQuOzMHfTFfwwpb2ok72fFOBugxEBrtgR/ADL9oTi1xc6arS3Uk9PpmwYeGuwL2JScnAwJBEHbyXgfHQqbidk4XZCFlYfiYCDhTH6t3RCv5bO6N7MAaZGNRtqWF2e2LuFE2b0aIofTkThza3B2PNaD9HLQmvCU6tPYv6A5pjZ07tBzQ8Y+e1JpDyqbvh8N0+8Nci3xu+N+q6vrxPeG9YSr/x2Sdmg0cPHAUtGtlL+3QqCgJyCYiRmKnrbkrKf7IV7PP8tJScfcgHK26hhwbpxa07Dyap0Ild2CKW9uREM9PUgk8kwwM8ZPXwc8P2xSHx3NBxnI1MxdNUJTOvqidf6+6htiYruPg74d3Z3vPDLBUQm5WDc2tP46um2+Pip1kjKysfBkES8+MtF/P1KF63PJ+3sZY9h/o2w61ocPtxxE5tf6qzxUSFfHbiN3dfjlRfcHvZmyHhYWKYntmzi9fj/UlhW4kmmRvp4b5hfuaSsf8uqrxn7+jpj04zOmL7hAoLvpmPc2jPYOL2jqIshp2Tn49tD4QCANwf5ar33rl/Lsg2RH45sJUpNhIasXiVlK1aswIwZM/D8888DANauXYtdu3bh559/xjvvvCNydPXLk8mgpYkhuvs4oLuP4g9MLhcQmZzzKEFTDHMMS8xGbGouYlNzsf3RXAxTQ334u1k/mptmi8AmNlprTZrSxQMnwpJxMCQBczddwY453dU690BMrjam+Glqe4z//gyO3E7CJ7tCJDdk7q1BLbD3RhxOhifjeFgyelVS5UoTPOzN8UL3pnihe1Nk5Bbi6J1EHLiVgGO3k5CcnY8/L9zFnxfuwthADz18HNC/pTP6tnSq8xCLNwf54mxkKq7fz8C8P6/ijxmdG1TiAiiKAC3fexuHQhKxYnwAPOzNxQ5JLVJyCtDYxhRfPO0vWoEgsYZZC4IAb0cLbJ/VDe/9c0O5VtjlmHQsf9ofViaGkMlksDA2gIWjRbUFNoqK5UjNKVAkatn5SKpgCOWF6PKLrl+MKb+tNJkMsDc3goOFcZkhlM928sDPp6JQLBfw08ko/H4uBp+MaoMxgY1V6hV/UlMHc/zzajfM3XQFx+4kYdYflzG3nw++mRiIZ388h6t30zH15wvY9mpXOGt57vW7Q1viUEgCzkelYtf1OLUVgJLLBaTmFpRJqtYejVDOTywsFvDG1mAkZeXXap07YwM9OFkpEm4nS2PsuRGvlnjVrSbvm8Amttj6SldM+ek8opJzMGbNaayf1kG0BuCVB8OQlV+E1o2tMCawsdbPf/R2YpnbkUlV96ZT7dWbK9iCggJcunQJCxcuVG7T09ND//79cebMmQofk5+fj/z8fOXtzMz6uWK7JlTXK6CnJ0MzJws0c7LA+PaKMuCZeYW4Gpv+qDctHVdi05CVV4RzUak4F/W4N83T3kyRoHnYIqiJLVq4WGrkwlUmk+GLcf4Y8s0JRCbn4MP/buKLpwPUfh6x+LvZYOWEtnj5t8vYcDoa3o7mokw6r4y7nRmmdPHETyejsHR3CLo3cxAlQbE2M8RTbRvjqbaNUVAkx/moVBwMScCBWwm4n/5Q0aMWovgyaetuoxwS6eNU+8puRgaKpRmGrTqBc1GpWH0kHHP7SW/5grr4Ypw/luy4hUsxaRjyzQm8P8wPkzq61/t5myMDXPHp6NaSGgr8JE2Nmyh57cyMDLBifADaedji4x23sPdmPELjM7FmchBaNqr50DgDfT04WZlUWRzK851d5ba92L0p3GxNy/XCJWXlIzlb0fuWnF2A5OyCKue+5RXK8caWYLyxJRgmhnro3dyp3BDK2rI2VQzVW7o7BD+ejMKqQ2G4E5+F/z0TiCk/nVcudv3Xy120upB8YxtTvNzLGysPhuGzXSHo5+tcbQ9vsVzAheiKl14Y+b+TSMxUPN9F8qrfcXdTHyr/b2lsAEcrxXNcknCVTr6crIzhaGkCKxODMp8Vr/15RVlQp8TpiGS099B+NV1VeDtaYNurXTFt/QWExGVi4rqz+P65IHTTcg9RWEIW/ng09Pq9oX5qaYyojVsPMjHr98sAFA0nKTkF+PlUFAa3dtH60N6GrN4kZcnJySguLoazc9nuU2dnZ4SGhlb4mKVLl2LJkiXaCE8nWJkYomdzR+W6H3K5gPCkbFyOSVMmauGJ2YhOyUV0Si62XVHMazA30keAu42yjKo62ZobYeXEtnjmh7PYcukeuvs44Km22m9B0pTBrRvhrcEtsHzvbXy44xbc7czQu4V0hurO6dsMWy7eRWh8FrZdvoen24u7jpeRgZ6yx3fxCD+Exmcp56EF38vA1bvpuHo3HV/suw13O9WGHno6mOOT0a0xf3MwVh68gy7e9g3qS+np9u7o4m2PN7YE42xkKt795zr234rH8rH+9aJCa2WWj/OXfNVMTRVFKH35JpPJ8FxnD/g3tsarv19GdEouRn93Cp+MaqMczq4pP5+Kwks9vTF/gA+MDcq+FsVyAak5BWV6255M3pKz8nEv/SEKih733OQVyrH3Zs16Y5776Zyi963UEMrSwyitTAzw/nA/tHCxxHv/3MDem/GISc3FZ2PaYPYfVxAan4WZGy9hw/QO5eLXpJk9vbHl4j3cT3+ItcciMH9A83L7yOUCLsemYee1OOy+HofErPwKjgRcu5dR5raduRFy8ouQX+o5XTTcD85WJo+SLsXzo+pQ34re0s/8cA5mRvro4mWvvKbwtDeTbMOPs5UJNs/sjJkbL+FMZAqmrT+Pr8a3xcgA7S1b89nuEBTLBQz0c0YXb3utnRcA4jIeYvqjSpxdve2x4fmOeO+f69hy6R7e3BKMPa/11Jmh4JpWb5IyVSxcuBALFixQ3s7MzIS7Oxd/VRc9PRmaO1uiubMlJnZsAgDIyC3ElbuKBO1yTBqu3k1Hdn6RsiiDJnT2ssfsvj5YdSgM7/1zA23dbRrMkCsAeKWXN6KScrDl0j3M/uMK/n6lq9omu9eVjZkRZvVphqV7QvHV/jsYEeAqmQtfmUyGlo2s0LKRFeb080FCZh4OhSjK7Z8MTy7TClxbowPdcOJOMrZduY/XNl3B7td6wMasYSzNAAButmb448XO+PlUFJbvu42jt5MwcOVxfDqqDYb5NxI7vAZLmzOMA9xtsHNOd8zbfBXH7iThjS3BuBSThsUj/Or8N3zrQcWjUuQCsPZYBA6HJuCrp9uijdvjYWD6ejJlkuSHqnvtcguKcON+JuZvvor76WX/jns1d0RqTgGu388o97gTYeVLo5dmbKCnjMHK1ADJ2QXK3pEePg44EZaPM5EpeG3TVXz3bDut9VYo5kW1xKu/X8baYxF4ur0b3GzNIAgCrt5NVyZicRl5ysdYmRggs4I5XuueC1L0cloaw8HCGLkFRRj93WlEJecgwN0Gm1/qrPHPcAcLYyRn5+NQaCIOhSpGMbjbmaKnjyJB6+ptL7kebSsTQ2yY3gEL/grGrmtxmLvpCpKz8jG9u+aLjB2/k4Qjt5NgoCfDwqHqWRu0prLyCvH8+guIz8yDj5MF1jyqxPn+cD+cDE9GdEoulu8LxeIR0ppeUV/Vm6TMwcEB+vr6SEhIKLM9ISEBLi4Vl6s1NjaGsbH41XJ0ibWZIXq3cFL25hTLBYQlZuFyjGLY49ZL9zRy3rl9m+FsRArOR6di7qYr2PJy13oxNKImZDIZPh3dBrGpuTgXlYrpGy5g+6xukqiECQBTu3pi45kY3E9/iJ9ORmFWn2bVPkaEKslwtjLBM52a4JlOTZBbUITjd5Lw8m+XVY7po1GtcTk2DdEpuXj772tYOzlIsi29qtDTk+HFHl7o2dwR8zdfxc0HmZj1x2UcuOWKJSNba22dONIcW3MjrJ/WAf87Eo6vD97BpvOxuH4/HWueDVK5oME/V+5h4bbrFd637rkgvPvPddxJyMbo705hVp9mmN23Wa2XXjEzMkDHpnY49U5fnIlIwYf/3cTtBMVwx9ScAix5qhXGPFpgu7Svng54XLAkOx9Jj+ZSJT0qUpFfJMe9tIe4l1a+waZ0Qrf3Zjy83t2N5s4WZQuWPFGJUp2GtHZBZy87nI1MxTM/nMOQ1i7YeS2uTFJqaWyAAa2cMcLfFd2aOVS4zEPpdfIKiuR4+bdLiErOQWMbU/wwJUjtCVlFH6vn3+2HW3GZOB6WhON3knApJg13Ux/i93Ox+P1cLAweFXbq2dwBPZs7orWrtdaH61XE2EAf304MhKOFMTacjsZHO28hISsPbw/y1Vh8xXIBn+5SlMCf0sUTTR201+BcWCzHrEc9xI6Wxlj/fAdYmyo+961NDbFsrD+m/nwe609FY3ArF3Ty0m4PXkNUb5IyIyMjBAUF4dChQxg1ahQAQC6X49ChQ5g9e7a4wVGl9PVk8HWxgq+LFZ7p1ERjSZmBvh6+ntgWQ785geB7GfjqwG0sHKLdFiVNMjLQw9rJQRizRtGi+dKvF7FphuZbNGvCxFAfbwxqjvmbg7HmaAQmdnCvttiLODVHHzMzMsBAv7KNObWthGphrFiaYcyaU9h3MwG/n4vF5M4e6gxTEpo7W+KfV7vh28NhWH0kHNuvPsDZyFR88bQ/evhor7hLQ1DdZZumGiuqaivQ05Nhbj8ftHW3wWt/XsGN+5kYtuoEVk5si76+NV/2obBYjk93hWDD6ehK9xnYygXtPe3wwfYb2HU9Dt8cCsOhR71mqvb+d/G2x8653fHrmRh8feAOrt/PqDAhA4CxVQzPzCssfqLKpGIIZUxqbrk5USXuJGTjTkLtlrV595/rlS4jUNmQSEEQEBKXBfNH1fZiU3Px/fFIAIrpAf39nDGsTSP0bO5Y4+8EQRDw3j/XcTYyFRbGBvhpWnutrTWlpydD68bWaN3YGq/2boac/CKciUhRJmnRKbnKys9f7r8DO3MjdG+mSNB6+jiIOoxaT0+GxSMUwzs/3xuK749FIikzH5+P89fIuq5/XbyL2wlZsDY1xNx+1Td41lZeYTEEAZALwqMfxXujWC7gnW3XcfxOEgDgk1GtIZPJcDc1V7m/u60pOnja4kJ0GiasO4u/X+kKE0O9UsdT/Cs8+j9Vr94kZQCwYMECTJ06Fe3bt0fHjh2xcuVK5OTkKKsxkm5rbGOKz8f64+XfLuH7Y5Ho5u2gnP/WENiaG+Gnqe0x+rvTuBKbjje3XsOqiW0l0TvzVEBj/HgiCjcfZOLbw+HVVooUo6fsSep42tq4WePtwb74ZFcIPt55Cx087SQztFSdjAz08PrAFujj64TX/wpGVHIOnvvpPKZ28cA7Q1pyPoHaiPeH0bO5I3bO7YFZv1/G1bvpmL7hImb18caCAS2qLeCTmJWH2b9fUS6fMrdvM6w6HF7hvnbmRlj9bDsMDn6AD/69gRv3MzHiW8UyDC/19FKpWJChvh6md2+KEQGu+HxvqEqNfyaG+nC3M6uwh/Dr8W2x6nAYVh4MK3dfX18ndGpqV+EcuIyHheX2/+NcbKUxWJsalknW0nILcT4qpdLqh/97JhD9WzrXqnGusFgOuSDguyMR2PLoefpsTBs0sjJFWk5BmQtzeamL9coutEvfV9E+FysoOHL8TlKF+3f1tkdnL3tEp+Tg6O0knH9UQCw1pwD/BT/Af8GPk2NLEwP08HFAuya2MNCTlYuluoRg+d7bOBuZothfXvHvVfI8CE/clj9xzG1X7mPblfvo1swepob65R4vr+QLb9TqU1WeLyuvCPGZiiGpGQ8LMfzbkxUmUMrHyyv6/R/vXxHfD/bW6H0z89dL1e4zdk3FjSFUc/UqKZswYQKSkpKwaNEixMfHo23btti7d2+54h+kuwa3dsHkzk3w29lYLPhLsZaUVIb5qYOXowXWTg7ClJ/PYUfwAzR1MMeCCiZ9a5uenmJB6Wd/PIffzsZgWldPeGpxmIU6yKrtx6jY9G5NcTI8GUdvJ2H2H5fx3+zuDTZJadfEFrvmdseyPaHYeCYGv5yJwYmwZKyYIK1FmGtDLhfw18W7YodRK8W1bHYulgsoKJKXu0h78qLOUF+GbycF4pNdt7DvZgJWH4nAf8EPsHJCIOzMjcpftMqBSzGp+ODfm8pzvdLbGz2bO1aYlB1TXowLMDXUxxsDW+D97TdQUCzH53tD8fneUMzv3xyeDmbK41eXEDx5oezlaI5+vk7KuUqlLd8b+vjCF9VfjD95cWukr4eC4rIJ0uHQRJyPSkWnpnaQCwKMDPTQyNoELlYmOBle9Ry2J2U8LETGw0KEJ9as9232H1dqdXwA8Hmv/JDGuZtqf5y6mPLz+TofIyuvCLuvx2P3ddVK7ofEZSIkTr0VuU+F127e/NW76bXav6JhtdqgryeDnkwxlUJPBujJZNCTySB79P8nGx9crEwe76+n2EcGiLqQeH1Rr5IyAJg9ezaHK1KV3h/mh4vRaQiNz8LrW4KxYVoHSYxHV5cu3vb4dHQbvLX1GlYdCoOXgzlGibBmyZO6NXNAr+aOOHYnCcv3heK7Z4PEDqlKT/YwqrqQu56eDF8+HYAh35xAWGI2Ptp5C0vHtKnRY8MTs3EvLVdSFTWrY2ZkgI+eao3+LZ3x5tZgRCbnYOya05jV2xtz+vloZAiPptx8kIH3t9/Aldh0rZyvundYTXuQO312CNamhpUmWU86cjupwvlFNXE39WGtWsDXHI3AmqMRFd43tQYX418fvFPjc9XWd5XEVVfZ+UUVJoH1WUUX3yXbZDLF517JxXbZi/WyF+MxFVyIt2xkVX7/is5XckFfsh+AtNzCGiUzliYG6N7MAdamijX4Np0v20Pp5WiOvi2coKdX0e9Xcr5H26rYR08mw7V7Gfj78uPe2dl9msHVxhS34jJwKSa90uTvhyntyzynpY/5IP0h3tx6DQAws5cXBvq5VPkcPX4en3idSm3r+NmhcjFc/3BgmWNejknD5J/OQS4oGhwXjfCr9rkGgIXbrmPT+Vi42Zpi37yeFa4ZW9EyGVRWvUvKSD00VXpZCkwM9fHtpECM+N9JHL+ThB9PRuKlnt4V7rti/204PqpCVfpfqS9CPb69OyKTcrD2WATe2noNbramaC+BsuwLh/rieFgSdl+Px+XYtEqXQVA1AdKkuvxJOFgYY+WEtpj80zlsOh+LHj4OGNqm+iqF/VccAwD8N7sb/N1sVA9ABD2bO2L/vF744N8b+C/4AVYdDsfh24n4enxb+DhLbwhn6dc3M68QK/bfwcYz0ZALink5OQXFWoih6jdZdXMxS6toaFxdlVzEyaD498leIUAxxK6wWI7cJ54va1NDWJoYKC8AK2oV92tkVe5Cu+R8cRl55SopejmYo4m9WfUX7xVcKG+uoPfz+W6ej3+/ai60q7rITc0pwP+OlO8JnNffB262Zsr9522+Wm6f758Lgp5MhriMh9h9PQ5nI8sP7zMz0scIf1cMbu0CazPDMjEUFsuRlJWPl0oNJxvV1vXR+m75yn9V4WhpDOdHa485WpSsPWb8+P8WioImtRkJMPuPy9h5La7Mtj2v9VApvieVzLUrmYt2MTpN+Z7NyivC/lsJaNfEBj0rmPv6wTA/9PFVX2PYlC4eeGr1KQCo8L1RkQF+lY/yKum97OJlj3cG+2psmkLpKpeRSdl49Y/LkAvAoFbOeG9YzeflvzvUF8fvJOFe2kMs2xOKj0e11kS4DZ60rzx1gFi5UQPOyQAAPs6WWDS8Fd795zqW772NTk3tEVDB8KrK5j2YGuorJ187WBhVmLiVTNYWq9jGW4NaIDo5B3tvxuOlXy9h+6vd0MRetYpp6uLrYoVx7dyw5dI9LN0dgr9mdpHEnDdt6NbMAa/08sZ3RyPwzt/X4O9mDTfbmr0eIXGZ9S4pAxTVVldNCsQAP2e8v10xP2jYtyfx9mBfPN/VU3I91IIg4N+rD/DJrhDlheuIAFe8P6wlOlXQiqxu1f0tWNSwMWj98x3gXuriv2zvBdBl6eEy+3dqaod1pVrlK+v9qCi+7PwivPP3NeWFtaeDObIeFiIyOQd6MuDtwb54qadXucdW1Cq+u5qLcUEQ8Nu5WHy2KwQPC4uRkJmHF3t4qbR4eUVJmTrLds/p1wzv/XOjzPy17VfuY/usbsrlMSpKyu6m5mLntbgyvT36ejJ09bbHsDaNMKiVC2zNq19eY9OMzpj0w1noyYCZvbzLLf4tCAKaLtxd6ePbutvgYUExkrLzkZpTAADKhbyBqof1WRobKL4LLZ8oWGJhDCcrE+V3o525kUab32QyGfxcreDnaoWXe3kjt6AIZyNTcPxOMo7fSUJkcg4uRKfhQnSa2s99P/0hLkan4kJ0Ki5Gpymrfz5poJ8z2nva4rPdFa+nW5HLsWn4L/gBZDLgvWEttfIdmpKdj+c3XEB6biEC3G2wckJgreZ3WpoY4vOx/pj80zn8ejYGQ1q7oKuWF9huCJiUUYM1qaM7ToUnY9f1OMzZdAW75nYvt8/kzk0Ui5JmFyi/kB4WFuNhYTFiU3MRm1r9GGhLYwPFl5OFMRwsjRT/llqYtOT/9hZGal1wVE9Phq8ntMX978/g+v0MPL/hPLa92k1ZslYsCwY2x45rD3AhOg37byVgUKvyS1Y01EaB+QOa40xkCq7EpuO1P69i80udYVCPhvOpakSAKzo2tcNbW6/h2J0kfLzzFg7eSsCX4wPQ2Ea1RbrVLSwxC5/tDlH2THg5muPjp1qjWz28cPBxsqhxwg8ANmaGKn8uKKqMBqK9hy0+3HELwaWSiV9f6KTW569kYeuePg54c8s1nI9WLF6+92Y8Ph/bBo2spfFeAhTl0b8Y5w9fF0t88qhkeXRKLsasOY3dc3tU2lhXsq9MpkiWh/u7Ykhrl1r1kgKKYexD27hg9/V4LNlxE5tmdC5z8V7ZhbyDhRG2z+pW5v1TWCxHcna+8juwbBXKR4t5Pypikl8kR1Z+EbLyixCZnFNljPp6sgrnP244FaVI3kr1wpkZ1f1y1MzIAH19nZVVQ++m5uJ4WBKO3k7CgVsJ1Ty6csVyAaHxmbgUo0jwLkanllkTrkRTB3P4ulhizw3FPDcDPRmGtmmEUYGNa5yUCYKAT3beAgCMa+eG1o2tq3lE3eUVFmPGxouIScmFu50pfpzSXqV50d19HPBspyb4/Vws3tx6Dfvm96xxQxMp8NnSUbrQeSGTyfDZmDa4ejcdsam5eH/7jXL7fDKq/NyfnPyiR4lafpl/k0oSt+x8JD/6t6DUF1RUNV9QANSeMJka6ePHqe0xavUpRCTlYNbvl7H++Q6izutpZG2KF7o3xeojEfh8Tyj6+jqVi6eB5mQw1NfDqomBGPrNCVyKScPKg2F4Y1ALscPSCmcrE2x4vgN+PxeLT3eF4ExkCgZ/fRyLR7bC2HaNRe8xHfk/xdAiE0M9zOnrgxd7NFVrI0lNqOsZEKNRI6+o/FBGRa+K+nnYm2PTS52x/tHi5cfvJGHg18exZGQrjA4U/71UQiZTrOXn7WSB59dfAABEJuVgyDcncHBBrwof08HTVpmI1bW0+7tDW+JQSCLORqZi9/X4Gi3s/sOU9uUSekN9PTSyNq026RUEAVmPvh+fTNyUyduj78yUnIJKC9J8uONWuW3mRvpl13x78udR8mZvblzjHhx3OzM828kDTwe512pO5cOCYly9m67oCYtJw5WYNGTll12I20BPhlaNrdHewxYdPG0R5GGnLCpWUCTHG1uC8V/wA8zbfLXS4aSCIJR7L++6HofLsemKQjha+O6QywUs+OsqLsemw8rEAOundaxTcbSFQ1vi2KNhjEt3h+DT0TWbX00KTMp0VEPtqXiStalieNX4789UutbMk8yNDWBubFBt9cDSX1DJTyRrpXvfFOP881FYLGhkHoizlQl+mtoB49aexsnwZCz+7yY+fbSmiFhe7uWNTefvIjI5B39euIvnnly/qwG/Ad3tzPDZmDaYs+kKVh8NR9dm9ujqXf96Y1Qhk8kwubMHujdzUH7Rv7ElGAduxeOz0W1q3RugbgP9nLFohF+FvUwymebflmL9SapaWRRQDF98a2uwsspdP18nZOYV4kJ0GuZtvoqLMan4YLif2hNc/UeLl/du4YjX/wpG8L0MRUXdG4r3kpSq6vZp4YSDC3qi/4rjAICo5Bx0//xwhftuebmr2s7rZmuGl3t545tDYfhsdwj6+jpV28MRWMk835qQyWSwMjGElYkhvB0tqty3sFiO1JwCPL32TLkRJ0Nau5RZQuBhYTFyCoqRk5JbbYU+PRlgZ15+jbdyQygtjWFupA/Zo6G5VUnOzsfFRz1gF2LScPN+BoqeSCgtjA0Q2MQGHTzt0N7TFm3dbSrt3TMy0MPKCW3haGmMn05GKXtHn9Txs0MIcLNBgJs1/N1t4OtiiWV7FD1qL/fyhrMW1mP7fG8odl+Ph6G+DOumtEczp6pf1+pYGBtg+Th/PPPDOfx+LhZDWjdCdx/d+P5TByZl1OAFedhiwYDm+GLfbbUetzZfUIKgSMiSsvIx4Ovjao0DAPxcrbBqYiBm/HoRf5yLhZeDOV7s4aX289SUpYkhXuvng8X/3cQ3B+9gdGDjMsMYGvpCkiMCXHEyLBmbL97F/M1Xsee1nrCrwTyRhsLTwRx/zeyC749HYuXBO9h3MwGXYtKwdIx/lZPbNWn1M+2q7EmQQfM9uNVdHEqtAE5EUjZm/noJ4YnZMNSXYfGIVni2UxPIBeCbg3ew6nA4fjsbi+v3MrD62Xa1GlJZU82cLPH3K12V76UDtxJwMToVn4xqU6OeIW1p5mSJq4sGoO1HBwCgwuFtmvByL29suXgX99Mf4vvjEZjXX/wlUgBF75uzlQlaN7Yql5Stmfy4Mq8gCMgpeLRwd2aeslGz/BDKfKTk5EMuQNnQibgnz1qWqaE+nKyMK/zsffm3S/BytEBMSk65ojWAoqx7e09bZRLm62JVqzlWenoyfDDcDy5WJvh0d8VJWVJWPg6GJOBgSPmhlXoy4EJ0Klq5WqllaGdlShYh/2JcADp72avlmF29HTCliwc2nonB239fw955PcoUFKHKMSkjnfByL2+cDEvGmcjarSOiLjKZDDZmRsoJ4JrQ388Z7w1tiU92heDT3SHwtDdHf5EugAFgUscmWH8qCtEpuVh3LAILBj4eiiG1i09A/b0ki0f64WJMKiKScvDmlmD8OLW9ZIZdaYOBvh5m9WmG3i0cMX/zVdxJyMaMjRcxvr0bPhjup/Uv6b7VVFqTaaGrrC49Vtq2/2Y8Xv8rGFn5RXC2MsaayUHKaqr6MmDBwBYI9LDF/M1XEXwvA8O/PYmVE9pqZHmHkvdSnxZOWPDXVYTGZ2HWH5ex96YrPhrZqkaFMbTBxswI4Z8OQbMK1gLTFFMjfbw7rCVm/3EFa45GYFyQm0aSY1VV9yclk8lgYWwAC2MDNK1mdEpRsRypuQVlFuh+8qdkCGVOgWJueExKboVl+fOL5JWWqu/U1A5tm9jAydIEtuZGyMorQnRKDhwtjWFpbFCrz/EZPb3gYGmE+ZuDy9239eUuCL6XgeC76TgSmlhmiORXB+4ABxTJWXNnSwS42cDf3RoBbjZo4WKp1ikKrw9orvZldd4e7IsjtxNxN/UhPtsdgqVj/NV6/IaKSRnpBH09GVZObKuVCmtieqF7U0Qm5+CPc7GY++cVbHm5C1q5an6icEWMDPTw9mBfvPL7ZfxwIgrPdvbQynAMqTAzMsD/nmmHp1afwqHQRKw/FY3p3ZuKHZbWtXK1xn+zu2PFgTv44UQk/rp4D6cjUvDV0wHopKaWWXXQkwGaL4ovfcVyASsP3sG3jyrTdvS0w/+eDYSTZfm/3T4tnLBjdnfM+uMyrt3LwPMbLmBOXx+81s9HI7H5uVrhv9nd8e3hMHx3NAI7gh/gbGQKlo1pg34txWuAKs1AXw/Ry4ahzeJ95eYhacqwNo3wa9MYnItKxdLdoVj9bDutnFfbDPT14GRpUuF78Uklc8NLkrdXf79c4/Oci0rFuajySxUAijmppasvl54DV3pIpYOFsTJxGh3oVmFS1t7TTrmUzXv/XMfv5xRrqS0Y0BzX72fg2r10JGTmIzQ+C6HxWcqKosYGevBztVIkam7WCHC3QVN7c5Wq3Y5v74bZfZvV+nHVMTc2wBfjAjBx3VlsOn8XQ1pLp1dbypiU6Sjp9VNoni4kBDKZDEtGtsLd1FycCEvGi79cxL+zutV5QrmqBrd2QbsmNrgcm46vD9zBsrGK1jIpTinTRO9dy0ZWeH9YSyz69yaW7QlFx6Z2WqmmJTUmhvp4d2hL9PN1wutbgnEv7SEm/nAWM0QcYvskmTYGMIo1p6yG503PLcBrf17FsTtJABTrer07tGWVrfLudmbY8nIXfLTjFn4/F4tVh8JwJVb9JchLGBno4fWBLdC/pTMW/HUVEUk5eOGXixgX5IZFI/xgJZFhUsGLB8Lr3cpL0quTTKYYWjr82xPYdT0OkyNS0MVbGg0eYn3WVzc3fP20Dujj64RiuYDUnIIyCVxJb1vJsMnkR//Pyi9CXqEcd1Mf4m7qwwqPW5qduZEyeatIeGIWHC1MEJ+Zp1zcevNLncs0VsVn5CH4Xjqu3UvHtUe9apl5RbgSm15m0XtLYwO0cbOGv5sN2ror/m1kbVJtr96no9tobARHZy97TOvqiQ2no/H239c0co6GhkmZjpLiRTGph6G+Hv73TDuMXXMa4YnZeOGXi9g8s7NGx6VXRiaT4d2hLTFu7Rn8dfEupndviubOljrVKPBcZw+cCEvGgVsJmLvpCnbM6V5ucfL6NKytLjp52WPPaz3wyc4QbL54F+sezWeQBC28BNWdQlOfyzW55rr1IBMzf7uIu6kPYWKoh6Vj2mB0oFuNjm9soI9PR7dBkIct3v3nOk6EJdcx4uoFuNtg19we+Gr/bfx4MgpbL93D6fBkLB8XIInCAtpeo8/P1QrPdGqC387GYsmOm9g5p/wSMGKQ4lD10vT1ZMrereo8fDT3LSk7r8I5byX/T87OR9GjZC81p6DSNcxKCsOU9tPJKPwX/KBML5yzlQme6eSB1/oZw1BfhuiUXFy7l47guxkIvpeOmw8ykJVfhNMRKTgd8XiKhoOFsTJB83eruDFQ05Wa3xrcAkduJ1Y4hJTKY1Kmo6T+QUl1Y21qiJ+ndsCo707h+v0MLNgcjO+ebSfKYr7tPe0wqJUz9t1MwLI9ofh5WgdJNgpo7oJYhuVj/TH0/glEJudg8X838eXTAZo5WT1gaWKIz8f5o7+fMxZuu4bk7AKxQwIgWieWVlQ33Gv7lft4Z9s15BXK4W5niu8nt4efq1WVj6nImHZuaOVqjVd+u1TtGlbqYGKoj/eG+WFgKxe8/lcwYlNzMfmnc5jcuYnGzy1Frw9ogR3BcQiNz8KmC+UXz6a6MTXSRxN7MzSxr3rOnlwuIC234HHPW2Y+Xt9SfviipYkBsvLKDnHdX816ajZmhsrlARwtjNGuiQ36t3RGem4B7qc/RHxGHuIy8hCfmYfk7HwcDEnEwZDE2v+yamJmpBjGOGHdGUl+70tNw1/VlEhHNbE3w7rngmCkr4e9N+OxXM3VJ2vj7cG+0NeT4XBoIk5HaL4VXRWa/L6wNTfC1xPaQk8GbL10D/9eva/Bs9UPA/ycsW9eT7HDUNJrwEVYKitzXVgsx5IdNzFv81XkFcrRq7kjdszurlJCVqKFiyX+nd1N5cerooOnHfa81kO59MZvZ2O1en6psDU3woIBiuqLX+0X7/Ne1+npyWBvYQxfFyv08HHE2KCKe5yvfDAATewUCV6Qhy3WTg7Cx6NaY24/H0zq6I7+LZ0Q4GaNRtYmMHjUoJqeW4iwxGycCk/B9qsP8MOJKHy+NxTfH4/EzmtxuBiThvvpDytdI+5JeYWan0nbsakdnu+qe/OpVcGeMh2lK8OldF17TzssH+ePeZuvYu2xCHg5Vl3dSlO8HC3wTMcm+PVsDJbtCVVb6d36pLOXPWb39cGqQ2F4758baOtuI3ZIohN73bLStJGTnYlM0Uh1QlUkZuVh9u9XcD5aUdBgTt9mmNe/ea3KfldGjPLX5sYG+HhUawxq5YK3tgbjgZZK0kvNs52a4I9zsZUOmSPp+PPCXcSm5sLWTDGyxdqs8r8bufzRsjqP1nZTDqHMLD0XTvFvbdZD9f1gL6xMDBRru1mUL1hSupCJjamhyqNt3hzUAj+filLpsbqESZnIBJH6czl8UXeMCmyMyOQcrDoUhne3XRctjtf6+2Db5Xu4di8DSVn5osVRGW38Lc7t2wxnI1JwPjoVczdd0fj5qOa00UwVElf1hXJN34KWJnX76r4Uk4ZXf7+EhMx8WBgbYMX4AAxs5VKnY0pFdx8H7J3fE/4f7hc7FFEY6Oth8Ug/PPPDObFDAdCwe6Dr6usDdwAA8/o3rzIhAxS9b7bmRrA1N0JzZ8sq980vKkZydoFi3bdSi3R/cyiswv0z84qQmZeN8MTsKo9rqC+Dg0XpRbofV6F0fJS8lSR0JoZlFzGvblFzUmBSRqQD5vf3QVRyDnYEPxAtBgcLY7zcyxtfHbijtYVVpcZAXw8rJ7bFkG9OIPhehtjh6JTqGqLq0xpyFsa1++ou+dUEQcDv5xSFIAqLBTRzssD3zwXB27Hi4Y31lVQqMIqlq7cDhrR2wZ4b8WKHAmMDzpKpTEpOAbwczfFMJ/XOgTQ20EdjG1M0tjEts72ipCx40cDH1Sazn+x5e1yFMi23EIXFAuIezVmrjqWJQankTdELR9VjUqaj7CWy2CZph0wmwxfj/HEvLbdMGV1te7GHF347F4OETAn2lGnpPK42pvh8rD9e/u2Sls5INVF/UjJFcl8bMsiQV1iMD7bfwJZL9wAAQ9u4YPm4gFoneFQ/vDu0pSSSMo7Jqdp71Sw5oWnWZoawNjOETzW9bwVFciRnV1BtMjuv3BDKgiI5svKKkJVXhMgkzRf8aUj4aayjXJ9oQaGGz8RQH+uea48Onx4ULQZTI30sGNAcb/8t3jDKymhzJPHg1i6Y3LmJzhYkkCIpdJRpalj5g/SHeHrtGVy/nwE9maLwzks9vepV7yDVjrtd1RUCSXzdmtmjr6805phWx8hAD642ptVeOwqCgMy8olLJ2+NeuO+PSWgJFIliUkakQ2qyFoumjQtyl2RSpm3vD/NTJmVudmwkEZs2EhSx1in735FwAICtmSG+ndROEut4Eem694b6NbiGEZlMBmtTQ1ibGpar+sqkrHoc7EtEWqWvJ8PIAFexw6iAdgfamBjqw+lRkqzrc2CkQBvXRuqobKiq1o2tsGNOdyZkpFVSXZtKCqOF6rL0BDVMTMpE5mRV9aKemiLVD0rSDdJMyrRPzIt0Kksbr0RhsbzK+zX5sbz15a5ws+WQNtIuqV5qNLAOKmogmJSJzFukdaNIPB08bcUOQXS+jaqeVCwGF2vxW05JPNoYRnQiLBljvjuFFftv41xkCgqKqk7S1OXXFzqWK1FNpA1iLftTHeZkJEWcU0akZe62ZrgQnSZ2GKKS4to1T5YPJt2irXfk5dh0XI5Nx6rD4TA11EfHpnbo1swe3Zo5QK6hC1j/xjYaOS5RfdXQloGghoFJGZG2SS8f0bpG1uIM2yWqjDZ6yiZ3bgL/xjY4GZ6M0xHJSM4uwLE7STh2J0nj5yaix/Q4dJwkiEkZEWldQ6s4RfWfNt6SbrZmGN/BHeM7uEMQBNxOyMKp8BScCk/GucgU5BQUaz4IkfRu4Sh2CCQCJ0s2wBHVFOeUERERAKBFNQuIasIHw/20fs6KaKOZ4HxU6uPzyWTwdbHCC92b4udpHXB18UBsfblLjY5z5HYicvKLan5iCbSBmHORap00oYO72CFIUstGrLxI5fFTUmT6erqbF3dqaid2CDqps5cdzkamVr8j6ZxvJrXV+jmtTaWxHIA2esruJGRVep+hvh7ae9bsM/H59RdgqC9DoLstujVzQLdm9ghwt4GhvuL75JuJbfHan1fVETJRnbRwkV5RJyl4cg0vIoBJmWhm9vTC9fsZ6KPDQzqkcjGmbUEetth2+b5o5+/Y1F6ZlLG4BZXm66K7rbd9fZ2w6fxdjZ5DXUsguNma4l7aQ5yPTsX56FR8fRAwN9JHJy9FwRDO2ZQmXohTCQl0XpMEMSkTycKhLcUOgUQS5PG4JL6lCEN6LIwfl8a2NdfNxJikQyrz7QOb2Go+KVNTd9zJt/siNiUXJ8OTcSoiGafDk5GWW4jDoYk4HJqolnOQ+k3p4qHV81kaGyCrNsNcSWukMK367cG+YodAT2BSpqOkMGqys5e92CGIQiZyG5lzqQXLdXn4LEnD0DaNsOCvYI2fx6Ca97qLleZ7l9R5IdbE3gzP2DfBM52aQC4XcCsuE6cjknEyPAXHWc1RkrT9yT82yA0bTkdr+axUE61drcUOAe52HCkjNbwi01E9fMQfNvlMpyZihyC6rs20n5iWGeMv0YU9SXvEHlKlrUWNjQyq/rrzc9X80E11/K5ejubltunpydC6sTVe6umNjdM7Yu+8HmXuF6NVvmdz8b9jdJ1UFgxfOaGt8v+uEhha+2L3pmKHwOsfqhCTMh1VMiFc2/6b3U35f3XNr1DV+8PEGUJa+gJpZi9vrZ9fl+cNSY2liQGsTAxEHcqyfloHAMD0buJfqIhJGy/BAD/nOh/j+a6e1e7TyEr8FnBnS+Mytz3szESKREKkMGZNBKMCGyv/P6RNIxEjURC7IQrQzWqkviz6Ui3de1eQqCxNxJ3D9HSQG7ZcugcA6N3CSdRYAMBIpOS4hK73k51/tx86fnZItPPvn99LtHOXcLczQ/SyYWKHoVEOFsbV76QF6vj8G9POrdp9rM3Enyv6ZP7xUk8vcQJ5pK27jajnBwADqUygFJHYjbGA+Lmx2N/7JbQdh7eTBULjK69AS+wpIy0zrmYIkabpif1pDMDTvvzwI7G0biz+uHYxOVmZYOvLXcoN9yLpOLOwb517mOb0bVbtPvVlQfP62sIu9lzaHj4Oop4fAEa1bVz9Tg3UvP4+8LA3w0yRk3Ox7HlN8R2zcIgvri4eIHI0Cn19tdwwreutwDVQPz/dqd5ytTHFq729YWakL9oQyhJiXYNVN7dFmwa1chE7BNHVdG0oEoetmRFWjA9Amw/31+px66d1gLudGc5GpmBiDRawrR8pmWrEaIwSOwl7ktifdc9384SpkXbneEmpnWFe/+aY17+52GEAEGeUTMtGVpIbkWCg5Wswdw5hrpZ0rg5JZ7w12Bez+/qIHQYRSYT3o+IV8yu5aKttA+tr/XzQu4UjmjlZYHJnD61ffFRGEKmwjoUIvWtPJgTGhuK+BmKMCvjq6QCtn5OqtmBA8zIViHXVjtndtX5OQ30JtRJIlDS+qUgrtr3aFT2bO+LA/J5ihyKa0hcK9uZG4gUiEWJdJBKVtn9+L4R+PBiv9S/fWFPbCnImhnqYP6B5vRmO2FC91t8HDhZG6NncEf/O6qb1SoBiFXIqbXSpAhfWpuLP89Nly8f6Y3ArF9HnNopp4RDFumTPdGqCNm7ab6Tg5Ub1OHxRh7RrYouN0zuKHYaoGts8rkpmY8akTAoGcwilztPXk0Ffr2YX7WZG+sgtKFbetjA2QHapBXJVnbxelxzuzUEt8MW+26ofQINe6yfOqIRG1qa48F5/0ZJjKXy+6+nJsHycP/beiMeMHuInA8938xQ7BNGM7+CO8TUYxtyQvdTTCwP8nCUzr31aDSrJ6homZaRTZvT0woOMh2opTa0OtiL31kllHRuiqpQuEGRlYlgmKftmYlu88MvFOp+jLnOgXunljbCELGy/+qDcfU8mkdrWSgvrr1VGzN5KqfSTjm/vjvHtxU8GIj4bKonKhyQemUwGL0fxlwMAgBNv9YGbrfhLd0gNkzLSKSaG+lg6xl/sMLDuuSBkPCws03OnTW8NboHwhGx0asoiFyR9xgaPGw98G1kiPjMPgKIyYyPrsn9DYgzL0dOT4esJbXExJg330h6Wua8ul8G9WzjC29ECG89Eo7CYY39qo3Q+GP7pEPECEVEXL3usORoBQBql6Em3CaVmB7PoR8WYlBGJYKDIQ/Ze7V19iXBNa2xjivvpDzHUX/zFREn6biwZhKJiOd7957py25MJGQB8PaGtaieo4zWrTCbD8rH+eObHc+W2q2rD84rh5j18HDBt/YU6xafLpFLoRdt6NnfE7y92grdEekdIt3FOWfWYlBGRKHa/1gPhiVlo18RW7FCoHiipILhgQHPsu5mA6ZXMj3GyFK+yWjsPzbyXO3jawUhfDz7OvLim2unWTPz12YgALlNWE0zKiEgU1qaGCPLg8EmqnWZOlgj9eLDa1zmszcL2/Vs642BIQrntBhUMEVPHoDFzYwNcXzIQhnq62eOjChbfJKL6hp/wREQkGZY1WFNLEwvPly56079l1YvL/ji1fYXbK2oJVlfrsLGBPvQ4L6jGpLZ4NRFRdZiUERERldK/ZfXVWdtUsBhxdXMmuHYaEekqzimrHpMyIiKiUlpXkHA96dXe3jU6lgyK9YG8HM0xQYR1knQ1EdTRX5uI6jHOKSMiIukQ8WL66Bu9cT/9YY2SsooIlQxWfHdoS7w7tGVdQiMiogaOPWVEREQAPB3My1Wr6+ptj3eH+uKptq5ltte0J8bazFBd4VEt6GoPIZFUPd3eDYDiM5Uqxp4yIiKSDCsTQ2TlFYkdhpKJoT5e6umNVYfCymyvaH6Ekb4eWrlaISe/CItHtsLXB+7g87HiL1aviwb6OaOZkwXaa2iZAiKqHW9HCwQvHlijYk66is8MERFJxg9T2mPoqhO1eszOOd0x/NuTWDzCT+3xWJvWvKdLJpNhx+zuEADo68nQp0XVVRxJc0wM9XFgfk/2mBFJSG0+T3URkzIiIpIMP1erWj+mdWNrRH42VK0l4//3TCD+OBeLhUN9AdR8qhvL1ksHEzIiqk+YlBERUb2n7mRouL8rhvu7Vnp/gLuNWs9HRES6jYU+iIhIUmb1qVm5eW3ycbYoc9vVxhTH3+yDq4sGqPU8zZwsqt+JiIgaHCZlREQkKV28HKrfScsGtXLBkpGt8M+rXZXbmtibwcbMSK3nUfeAOw7gIyKqH5iUERGRpFS23peYZDIZpnb1RGATzVbze66Lh0aPT0RE0sSkjIiISCJ8XWpf6KQqtuasdkZEVB+w0AcREZFEqKtg4MoJbRGZnIN2Gu7ZIyIi9WBSRkREklLRwsxUO6MCG4sdAhER1QKHLxIREREREYmISRkREREREZGImJQRERERERGJiEkZERFJSuvG1mKHIBquK0ZEpJtY6IOIiCTFztwI59/rBzMjfkUREZFu4DceERFJjpOlidghEBERaQ2HLxIREUkEeweJiHQTP/2JiIgkws/VCi92bwoXa/YUEhHpEiZlREREEvL+cD+xQyAiIi3j8EUiIiIiIiIRMSkjIiIiIiISEZMyIiIiIiIiETEpIyIiIiIiEhGTMiIiIiIiIhExKSMiIiIiIhIRkzIiIiIiIiIRMSkjIiIiIiISEZMyIiIiIiIiETEpIyIiIiIiEhGTMiIiIiIiIhHVm6TM09MTMpmszM+yZcvEDouIiIiIiKhODMQOoDY++ugjzJgxQ3nb0tJSxGiIiIiIiIjqrl4lZZaWlnBxcRE7DCIiIiIiIrWpN8MXAWDZsmWwt7dHYGAgvvjiCxQVFVW5f35+PjIzM8v8EBERERERSUm96SmbO3cu2rVrBzs7O5w+fRoLFy5EXFwcVqxYUeljli5diiVLlmgxSiIiIiIiotqRCYIgiHXyd955B59//nmV+4SEhMDX17fc9p9//hkzZ85EdnY2jI2NK3xsfn4+8vPzlbczMzPh7u6OjIwMWFlZ1S14IiIiIiKqtzIzM2FtbS2J3EDUpCwpKQkpKSlV7uPl5QUjI6Ny22/evInWrVsjNDQULVq0qNH5pPTEExERERGReKSUG4g6fNHR0RGOjo4qPfbq1avQ09ODk5NTjR9Tkn9ybhkRERERkW4ryQlE7KNSqhdzys6cOYNz586hT58+sLS0xJkzZzB//nxMnjwZtra2NT5OVlYWAMDd3V1ToRIRERERUT2SlZUFa2trUWMQdfhiTV2+fBmvvvoqQkNDkZ+fj6ZNm+K5557DggULKp1PVhG5XI4HDx7A0tISMplMgxHrjpJ5enfv3hW921eX8XWQBr4O0sHXQlx8/qWBr4M08HWQjidfC0EQkJWVBVdXV+jpiVuUvl70lLVr1w5nz56t83H09PTg5uamhojoSVZWVvygkQC+DtLA10E6+FqIi8+/NPB1kAa+DtJR+rUQu4esRL1ap4yIiIiIiKihYVJGREREREQkIiZlVCfGxsZYvHhxreb2kfrxdZAGvg7SwddCXHz+pYGvgzTwdZAOKb8W9aLQBxERERERUUPFnjIiIiIiIiIRMSkjIiIiIiISEZMyIiIiIiIiETEpIyIiIiIiEhGTsgZq6dKl6NChAywtLeHk5IRRo0bh9u3bZfbJy8vDrFmzYG9vDwsLC4wdOxYJCQll9pk7dy6CgoJgbGyMtm3bljvP7du30adPHzg7O8PExAReXl54//33UVhYWG2Mq1evhqenJ0xMTNCpUyecP3++wv0EQcCQIUMgk8mwffv2Gj8HYqvvr0F0dDRkMlmFP1u2bFHtSRGJ1F+L48ePY8SIEXB1da30fS4IAhYtWoRGjRrB1NQU/fv3R1hYWK2fCzFp63UoLTw8HJaWlrCxsalRjNV9Lq1btw69e/eGlZUVZDIZ0tPTa3RcKWgIz3+J+vq9ANT/16GhfDdI/XXQle8FQHuvRWXv3bNnz1Yboza+G5iUNVDHjh3DrFmzcPbsWRw4cACFhYUYOHAgcnJylPvMnz8fO3bswJYtW3Ds2DE8ePAAY8aMKXes6dOnY8KECRWex9DQEFOmTMH+/ftx+/ZtrFy5Ej/88AMWL15cZXybN2/GggULsHjxYly+fBkBAQEYNGgQEhMTy+27cuVKyGSyWj4D4qvvr4G7uzvi4uLK/CxZsgQWFhYYMmRIHZ4Z7ZP6a5GTk4OAgACsXr260n2WL1+OVatWYe3atTh37hzMzc0xaNAg5OXl1fBZEJ+2XocShYWFmDRpEnr06FGj+GryuZSbm4vBgwfj3XffreFvLR0N4fkvUV+/F4D6/zo0lO8Gqb8OuvK9AGj/tTh48GCZ929QUFCV+2vtu+H/7dx/TNT1Hwfw551wyG9iKgcFG1sxYa2a1DEIf6xYP1YT1K0tccmyjNS5rGY6bTaWRWnW1tpaTsFCEnEDWSbLeRG3hmzhHa64HDLyx3boUskKFHafV398v312p4bHj7vPD56P7bNxd+/P5/36vF98ePG6g4/QtHDp0iUBID/88IOIiAwODkp0dLQ0NjaqY7xerwCQjo6OW/bftm2bPPjggyHNtWHDBikuLh5zjMPhkLVr16qP/X6/ZGRkyPvvvx80zu12y9133y0+n08ASFNTU0gx6JFRcxDooYcekhdffDGkGPRMb7kIdLvvc0VRxG63y44dO9TnBgcHJSYmRr7++uuQj6034c7Dxo0bZcWKFVJTUyPJycl3jGc818T3338vAOTq1at3PK5eGXX9zVQXRIybh0BmqA16y0Og6VQXRMKXi/7+fgEgbrd7XPFEqjbwk7Jp4o8//gAApKamAgC6urowOjqKkpISdczcuXORlZWFjo6OCc9z5swZtLa2YuHChf85ZmRkBF1dXUFzW61WlJSUBM09NDSE5cuX47PPPoPdbp9wTHphxBwE6urqgsfjwapVqyYcm17oKReh6O/vx8DAQFB8ycnJKCgomFR8WgtnHpxOJxobG8d8lznQRK4JozPi+putLgDGzEMgs9QGPeUhFGatC0D4a/TixYsxZ84cFBcXo6WlZcyxkawNbMqmAUVR8Nprr+HRRx/F/fffDwAYGBiAzWa75e+a09LSMDAwMO45ioqKMHPmTNx3332YP38+qqqq/nPs77//Dr/fj7S0tDHn3rBhA4qKilBaWjruePTGqDkItGfPHuTm5qKoqGjcsemJ3nIRin9jGE++9C6cebh8+TIqKipQW1uLpKSkkPaZyDVhZEZdfzPVBcC4eQhkhtqgtzyEwox1AQhvLhISEvDRRx+hsbERR44cQXFxMcrKysZszCJZG9iUTQNr167Fzz//jAMHDoRtjoaGBpw8eRL19fU4cuQIdu7cCQBwuVxISEhQt/3794d0vJaWFjidTnzyySdhizmSjJiDQMPDw6ivrzf8O6GA8XNhFuHMw8svv4zly5djwYIFt32deTDm+putLgDGzEMgs9QGo+fBTMKZi1mzZuH1119HQUEBHnnkEVRXV2PFihXYsWMHAO1zERXR2Sji1q1bh2+++Qbt7e2455571OftdjtGRkYwODgY9M7DxYsXJ/QnIZmZmQCAvLw8+P1+rF69Gm+88QYefvhheDwedVxaWhpiYmIwY8aMW+6aEzi30+lEX1/fLe+KLFu2DPPnz0dbW9u4Y9SKUXMQ6NChQxgaGsILL7ww7rj0RI+5CMW/MVy8eBHp6elB8d3pbl96FO48OJ1OtLS0qM2wiEBRFERFReGLL77A888/P+lrwsiMuv5mqguAcfMQyAy1QY95CIXZ6gIQuRodqKCgAMeOHQOAKfl9aTL4SZlJiQjWrVuHpqYmOJ1OZGdnB72en5+P6OhoHD9+XH3u9OnTOHfuHAoLCyc1t6IoGB0dhaIoiI2Nxb333qtuiYmJsNlsyM/PD5pbURQcP35cnXvTpk04deoUPB6PugHAxx9/jJqamknFFylGz0GgPXv2YPHixZg9e/ak4tKKnnMRiuzsbNjt9qD4rl27hs7OzknHF0mRykNHR0fQz46qqiokJibC4/FgyZIlU3JNGJHR198MdQEwfh4CGbk26DkPoTBLXQC0rdEej0dtajWvDeO+NQgZwquvvirJycnS1tYmPp9P3YaGhtQxlZWVkpWVJU6nU3766ScpLCyUwsLCoOP09vaK2+2WV155RXJycsTtdovb7ZYbN26IiEhdXZ00NDRIT0+P9PX1SUNDg2RkZEh5efmY8R04cEBiYmKktrZWenp6ZPXq1ZKSkiIDAwP/uQ8Mdpcts+Sgt7dXLBaLHD16dIpWJvL0nos///xTPRYA2bVrl7jdbjl79qw6prq6WlJSUuTw4cNy6tQpKS0tlezsbBkeHp7ClQqvSOXhZqHe7SyUa8Ln84nb7Zbdu3cLAGlvbxe32y2XL1+e2KJEkBnW/2ZGqwsi5smD0WuD3vMwXeqCSORyUVtbK/X19eL1esXr9cr27dvFarXK3r17x4wvUrWBTZlJAbjtVlNTo44ZHh6WNWvWyF133SVxcXGyZMkS8fl8QcdZuHDhbY/T398vIv/7Rp03b54kJCRIfHy85OXlyXvvvRfSD4RPP/1UsrKyxGazicPhkBMnTtzxnIxUfM2Sg82bN0tmZqb4/f5JrYeW9J6Lf2+he/O2cuVKdYyiKPL2229LWlqaxMTEyOOPPy6nT5+eqiWKiEjl4WbjuQX1na6Jbdu23fEc9MoM63+7czJSXRAxTx6MXhv0nofpUhdEIpeL2tpayc3Nlbi4OElKShKHwxF0m/2xRKI2WP6/GERERERERKQB/k8ZERERERGRhtiUERERERERaYhNGRERERERkYbYlBEREREREWmITRkREREREZGG2JQRERERERFpiE0ZERERERGRhtiUERERERERaYhNGRERTTsWiwXNzc1ah0FERASATRkRERlMRUUFysrKtA6DiIhoyrApIyIiIiIi0hCbMiIiMqxFixZh/fr12LhxI1JTU2G32/HOO+8Ejent7cWCBQswc+ZM5OXl4dixY7cc5/z583juueeQkpKC1NRUlJaW4rfffgMA/Prrr4iLi0N9fb06/uDBg4iNjUVPT084T4+IiKYJNmVERGRo+/btQ3x8PDo7O/Hhhx+iqqpKbbwURcHSpUths9nQ2dmJzz//HG+99VbQ/qOjo3jyySeRmJgIl8uFH3/8EQkJCXjqqacwMjKCuXPnYufOnVizZg3OnTuHCxcuoLKyEh988AHy8vK0OGUiIjIZi4iI1kEQERGFqqKiAoODg2hubsaiRYvg9/vhcrnU1x0OBx577DFUV1fju+++wzPPPIOzZ88iIyMDANDa2oqnn34aTU1NKCsrQ11dHd599114vV5YLBYAwMjICFJSUtDc3IwnnngCAPDss8/i2rVrsNlsmDFjBlpbW9XxREREkxGldQBEREST8cADDwQ9Tk9Px6VLlwAAXq8XmZmZakMGAIWFhUHju7u7cebMGSQmJgY9f/36dfT19amP9+7di5ycHFitVvzyyy9syIiIaMqwKSMiIkOLjo4OemyxWKAoSsj7//XXX8jPz8f+/ftveW327Nnq193d3fj7779htVrh8/mQnp4+8aCJiIgCsCkjIiLTys3Nxfnz54OaqBMnTgSNmTdvHhoaGjBnzhwkJSXd9jhXrlxBRUUFtmzZAp/Ph/Lycpw8eRKxsbFhPwciIjI/3uiDiIhMq6SkBDk5OVi5ciW6u7vhcrmwZcuWoDHl5eWYNWsWSktL4XK50N/fj7a2Nqxfvx4XLlwAAFRWViIzMxNbt27Frl274Pf78eabb2pxSkREZEJsyoiIyLSsViuampowPDwMh8OBl156Cdu3bw8aExcXh/b2dmRlZWHp0qXIzc3FqlWrcP36dSQlJeHLL7/Et99+i6+++gpRUVGIj49HXV0ddu/ejaNHj2p0ZkREZCa8+yIREREREZGG+EkZERERERGRhtiUERERERERaYhNGRERERERkYbYlBEREREREWmITRkREREREZGG2JQRERERERFpiE0ZERERERGRhtiUERERERERaYhNGRERERERkYbYlBEREREREWmITRkREREREZGG/gELB9eE/GlBxAAAAABJRU5ErkJggg==\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts['color'] = ts['temperature'].apply(lambda x: 'red' if x > 70.00 else 'blue')"
+      ],
+      "metadata": {
+        "id": "JDCOCBmKlPOZ"
+      },
+      "execution_count": 191,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "plt.scatter(ts.index, ts['temperature'], c=ts['color'])\n",
+        "plt.xlabel('Index')\n",
+        "plt.ylabel('Temperature')\n",
+        "plt.title('Temperature Plot (Color-coded)')\n",
+        "plt.show()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "AGZjf2gTlQdH",
+        "outputId": "74eb167c-8539-4746-9c74-a755b2643efc"
+      },
+      "execution_count": 192,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def read_dataset(folder, date_col=None):\n",
+        "    '''\n",
+        "    folder: is a Path object\n",
+        "    date_col: specify a date_col to use as index_col \n",
+        "    \n",
+        "    returns: a pandas DataFrame with a DatetimeIndex\n",
+        "    '''\n",
+        "    ts = pd.read_csv(folder, \n",
+        "                     index_col=0, \n",
+        "                     parse_dates=[date_col])\n",
+        "    return ts"
+      ],
+      "metadata": {
+        "id": "xw0dW7PSlfqZ"
+      },
+      "execution_count": 193,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def plot_dfs(df1, df2, col, title=None, xlabel=None, ylabel=None):\n",
+        "    '''\t\n",
+        "    df1: original dataframe without missing data\n",
+        "    df2: dataframe with missing data\n",
+        "    col: column name that contains missing data\n",
+        "    '''    \n",
+        "    df_missing = df2.rename(columns={col: 'missing'})\n",
+        "    \n",
+        "    columns = df_missing.loc[:, 'missing':].columns.tolist()\n",
+        "    subplots_size = len(columns)\n",
+        "    \n",
+        "    # subplots_size = df2.shape[1]\n",
+        "    fig, ax = plt.subplots(subplots_size+1, 1, sharex=True)\n",
+        "    plt.subplots_adjust(hspace=0.25)\n",
+        "    fig.suptitle = title \n",
+        "    \n",
+        "    df1[col].plot(ax=ax[0], figsize=(10, 16))\n",
+        "    ax[0].set_title('Original Dataset')\n",
+        "    ax[0].set_xlabel(xlabel)\n",
+        "    ax[0].set_ylabel(ylabel)    \n",
+        "    \n",
+        "    for i, colname in enumerate(columns):\n",
+        "        df_missing[colname].plot(ax=ax[i+1])\n",
+        "        ax[i+1].set_title(colname)\n",
+        "\n",
+        "    plt.show()\n"
+      ],
+      "metadata": {
+        "id": "XrcaVHR1l_yr"
+      },
+      "execution_count": 194,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "def rmse_score(df1, df2, col=None):\n",
+        "    '''\n",
+        "    df1: original dataframe without missing data\n",
+        "    df2: dataframe with missing data\n",
+        "    col: column name that contains missing data\n",
+        "\n",
+        "    returns: a list of scores\n",
+        "    '''\n",
+        "    df_missing = df2.rename(columns={col: 'missing'})\n",
+        "    columns = df_missing.loc[:, 'missing':].columns.tolist()\n",
+        "    scores = []\n",
+        "    for comp_col in columns[1:]:\n",
+        "        rmse = np.sqrt(np.mean((df1[col] - df_missing[comp_col])**2))\n",
+        "        scores.append(rmse)\n",
+        "        print(f'RMSE for {comp_col}: {rmse}')\n",
+        "    return scores"
+      ],
+      "metadata": {
+        "id": "nmsm5kwImVrZ"
+      },
+      "execution_count": 195,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts = ts.drop('delta_temperature', axis=1)\n",
+        "ts = ts.drop('color', axis=1)"
+      ],
+      "metadata": {
+        "id": "0aGYk6ucw-lv"
+      },
+      "execution_count": 196,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts.info()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "99fBv22UmeFZ",
+        "outputId": "c17c7ff4-7e76-4950-f67f-6c9e822666b5"
+      },
+      "execution_count": 197,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "<class 'pandas.core.frame.DataFrame'>\n",
+            "DatetimeIndex: 22695 entries, 2013-02-12 21:15:00 to 2014-02-19 15:25:00\n",
+            "Data columns (total 1 columns):\n",
+            " #   Column       Non-Null Count  Dtype  \n",
+            "---  ------       --------------  -----  \n",
+            " 0   temperature  21410 non-null  float64\n",
+            "dtypes: float64(1)\n",
+            "memory usage: 354.6 KB\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts.describe(include=\"all\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 300
+        },
+        "id": "eVD2m4yHoLoa",
+        "outputId": "516dcfcd-5cce-4a0e-d41c-88818928342f"
+      },
+      "execution_count": 198,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "        temperature\n",
+              "count  21410.000000\n",
+              "mean      85.968188\n",
+              "std       13.553070\n",
+              "min        2.084721\n",
+              "25%       83.082867\n",
+              "50%       89.251290\n",
+              "75%       93.910748\n",
+              "max      108.510543"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-cffb7d11-99cd-4ba5-8fe5-1f51afb112b3\">\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>temperature</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>count</th>\n",
+              "      <td>21410.000000</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>mean</th>\n",
+              "      <td>85.968188</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>std</th>\n",
+              "      <td>13.553070</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>min</th>\n",
+              "      <td>2.084721</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>25%</th>\n",
+              "      <td>83.082867</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>50%</th>\n",
+              "      <td>89.251290</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>75%</th>\n",
+              "      <td>93.910748</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>max</th>\n",
+              "      <td>108.510543</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cffb7d11-99cd-4ba5-8fe5-1f51afb112b3')\"\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",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </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",
+              "      cursor: pointer;\n",
+              "      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-cffb7d11-99cd-4ba5-8fe5-1f51afb112b3 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-cffb7d11-99cd-4ba5-8fe5-1f51afb112b3');\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",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 198
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts.isnull().sum()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Utrl08hGoxv-",
+        "outputId": "623b6bca-f0db-46ea-bae7-d5896be6db1d"
+      },
+      "execution_count": 199,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "temperature    1285\n",
+              "dtype: int64"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 199
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "!wget -O Machine_temp_failure_original.csv \"https://drive.google.com/uc?export=download&id=1kulRVMpepw903zqZAIETRHR3CKCw9hCT\""
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "lZcEliE1p8CK",
+        "outputId": "af8f8b08-49b8-49ac-cdac-a5299b9e7f4b"
+      },
+      "execution_count": 200,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "--2023-06-01 18:08:16--  https://drive.google.com/uc?export=download&id=1kulRVMpepw903zqZAIETRHR3CKCw9hCT\n",
+            "Resolving drive.google.com (drive.google.com)... 209.85.200.101, 209.85.200.139, 209.85.200.100, ...\n",
+            "Connecting to drive.google.com (drive.google.com)|209.85.200.101|:443... connected.\n",
+            "HTTP request sent, awaiting response... 303 See Other\n",
+            "Location: https://doc-0s-98-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/4irpnrub9etarlsmfok0i0jarv0ddr3f/1685642850000/12842633363256377808/*/1kulRVMpepw903zqZAIETRHR3CKCw9hCT?e=download&uuid=fc7c26d7-e205-4ea2-9202-8e30e3bc3648 [following]\n",
+            "Warning: wildcards not supported in HTTP.\n",
+            "--2023-06-01 18:08:16--  https://doc-0s-98-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/4irpnrub9etarlsmfok0i0jarv0ddr3f/1685642850000/12842633363256377808/*/1kulRVMpepw903zqZAIETRHR3CKCw9hCT?e=download&uuid=fc7c26d7-e205-4ea2-9202-8e30e3bc3648\n",
+            "Resolving doc-0s-98-docs.googleusercontent.com (doc-0s-98-docs.googleusercontent.com)... 172.217.219.132, 2607:f8b0:4001:c13::84\n",
+            "Connecting to doc-0s-98-docs.googleusercontent.com (doc-0s-98-docs.googleusercontent.com)|172.217.219.132|:443... connected.\n",
+            "HTTP request sent, awaiting response... 200 OK\n",
+            "Length: 726698 (710K) [text/csv]\n",
+            "Saving to: ‘Machine_temp_failure_original.csv’\n",
+            "\n",
+            "Machine_temp_failur 100%[===================>] 709.67K  --.-KB/s    in 0.006s  \n",
+            "\n",
+            "2023-06-01 18:08:17 (118 MB/s) - ‘Machine_temp_failure_original.csv’ saved [726698/726698]\n",
+            "\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "folder = Path('./Machine_temp_failure_original.csv')\n",
+        "ts_org = read_dataset(folder,'timestamp')"
+      ],
+      "metadata": {
+        "id": "wh3HQsfnsEhm"
+      },
+      "execution_count": 201,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts_org.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 238
+        },
+        "id": "RdSfavavu0_F",
+        "outputId": "4c1ae5b0-e51e-4886-b53b-bb789122127e"
+      },
+      "execution_count": 202,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                         value\n",
+              "timestamp                     \n",
+              "2013-12-02 21:15:00  73.967322\n",
+              "2013-12-02 21:20:00  74.935882\n",
+              "2013-12-02 21:25:00  76.124162\n",
+              "2013-12-02 21:30:00  78.140707\n",
+              "2013-12-02 21:35:00  79.329836"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-dc2120c0-8b81-4bd8-bfc5-7a33e758d6be\">\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>value</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>timestamp</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:15:00</th>\n",
+              "      <td>73.967322</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:20:00</th>\n",
+              "      <td>74.935882</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:25:00</th>\n",
+              "      <td>76.124162</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:30:00</th>\n",
+              "      <td>78.140707</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:35:00</th>\n",
+              "      <td>79.329836</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-dc2120c0-8b81-4bd8-bfc5-7a33e758d6be')\"\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",
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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",
+              "      cursor: pointer;\n",
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+              "      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-dc2120c0-8b81-4bd8-bfc5-7a33e758d6be 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-dc2120c0-8b81-4bd8-bfc5-7a33e758d6be');\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",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 202
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts_org = ts_org.rename(columns={'value': 'temperature'})\n",
+        "ts_org.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 238
+        },
+        "id": "o4u69rRYwPAS",
+        "outputId": "ff330372-2f30-4d68-a622-1f8a2599ec10"
+      },
+      "execution_count": 203,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                     temperature\n",
+              "timestamp                       \n",
+              "2013-12-02 21:15:00    73.967322\n",
+              "2013-12-02 21:20:00    74.935882\n",
+              "2013-12-02 21:25:00    76.124162\n",
+              "2013-12-02 21:30:00    78.140707\n",
+              "2013-12-02 21:35:00    79.329836"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-30048c12-f54f-4bde-82c1-2c5ecc84856d\">\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>temperature</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>timestamp</th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:15:00</th>\n",
+              "      <td>73.967322</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:20:00</th>\n",
+              "      <td>74.935882</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:25:00</th>\n",
+              "      <td>76.124162</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:30:00</th>\n",
+              "      <td>78.140707</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-12-02 21:35:00</th>\n",
+              "      <td>79.329836</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-30048c12-f54f-4bde-82c1-2c5ecc84856d')\"\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",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </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",
+              "      cursor: pointer;\n",
+              "      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-30048c12-f54f-4bde-82c1-2c5ecc84856d 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-30048c12-f54f-4bde-82c1-2c5ecc84856d');\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",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 203
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts_org.isnull().sum()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Bvdo73Q1u93Q",
+        "outputId": "cb32d025-d52e-4a94-bc74-0523e627fee7"
+      },
+      "execution_count": 204,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "temperature    0\n",
+              "dtype: int64"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 204
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "plot_dfs(ts_org, \n",
+        "          ts, \n",
+        "         'temperature',\n",
+        "         title=\"Temperature\",\n",
+        "         xlabel=\"Index\",\n",
+        "         ylabel=\"temperature\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "TRxNS_xuvJc-",
+        "outputId": "767e1b55-2423-472f-92c3-c7bc2de3565a"
+      },
+      "execution_count": 205,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x1600 with 2 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts['ffill'] = ts['temperature'].fillna(method='ffill')\n",
+        "ts['bfill'] = ts['temperature'].fillna(method='bfill')\n",
+        "ts['mean'] = ts['temperature'].fillna(ts['temperature'].mean())"
+      ],
+      "metadata": {
+        "id": "STnuQXALyGq8"
+      },
+      "execution_count": 206,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "_ = rmse_score(ts_org, \n",
+        "                    ts, \n",
+        "                    'temperature')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "IBfgvgmLy5uk",
+        "outputId": "d16a5fa0-28b7-4a52-b873-daa49b510294"
+      },
+      "execution_count": 207,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "RMSE for ffill: 1.4666115658526897\n",
+            "RMSE for bfill: 5.538329974927272\n",
+            "RMSE for mean: 2.6118121108260417\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "plot_dfs(ts_org, ts, 'temperature')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "x5YVQW_Tzbzd",
+        "outputId": "f811d44d-c142-4dca-d4e1-4011c204414e"
+      },
+      "execution_count": 208,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x1600 with 5 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from sklearn.impute import SimpleImputer"
+      ],
+      "metadata": {
+        "id": "bCkFCDrnz4H_"
+      },
+      "execution_count": 209,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "folder = Path('./Machine_temp_failure_original.csv')\n",
+        "ts_org1 = read_dataset(folder,'timestamp')\n",
+        "ts_org1 = ts_org1.rename(columns={'value': 'temperature'})"
+      ],
+      "metadata": {
+        "id": "aGRgyPjoIwCl"
+      },
+      "execution_count": 210,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "folder = Path('./Machine_temp_failure_missing.csv')\n",
+        "df = read_dataset(folder,'timestamp')"
+      ],
+      "metadata": {
+        "id": "ZOi_jb0N1Hs5"
+      },
+      "execution_count": 211,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df = df.rename(columns={'value': 'temperature'})"
+      ],
+      "metadata": {
+        "id": "HQhoeSg61oqb"
+      },
+      "execution_count": 212,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "strategy = [\n",
+        "    ('Mean Strategy', 'mean'),\n",
+        "    ('Median Strategy', 'median'),\n",
+        "    ('Most Frequent Strategy', 'most_frequent')]"
+      ],
+      "metadata": {
+        "id": "kRrxQ17O1qhX"
+      },
+      "execution_count": 213,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df_vals = df['temperature'].values.reshape(-1,1)\n",
+        "\n",
+        "for s_name, s in strategy:\n",
+        "    df[s_name] = (\n",
+        "        SimpleImputer(strategy=s).fit_transform(df_vals))"
+      ],
+      "metadata": {
+        "id": "s42HAosd14hr"
+      },
+      "execution_count": 214,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 238
+        },
+        "id": "Mzrr_gk62Vo7",
+        "outputId": "aa5d9c97-89fe-4725-a404-14c653fecfd9"
+      },
+      "execution_count": 215,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                     temperature  Mean Strategy  Median Strategy  \\\n",
+              "timestamp                                                          \n",
+              "2013-02-12 21:15:00    73.967322      73.967322        73.967322   \n",
+              "2013-02-12 21:20:00    74.935882      74.935882        74.935882   \n",
+              "2013-02-12 21:25:00    76.124162      76.124162        76.124162   \n",
+              "2013-02-12 21:30:00    78.140707      78.140707        78.140707   \n",
+              "2013-02-12 21:35:00    79.329836      79.329836        79.329836   \n",
+              "\n",
+              "                     Most Frequent Strategy  \n",
+              "timestamp                                    \n",
+              "2013-02-12 21:15:00               73.967322  \n",
+              "2013-02-12 21:20:00               74.935882  \n",
+              "2013-02-12 21:25:00               76.124162  \n",
+              "2013-02-12 21:30:00               78.140707  \n",
+              "2013-02-12 21:35:00               79.329836  "
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-1566259d-e14c-4af8-a785-3c25fbcdf0a1\">\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>temperature</th>\n",
+              "      <th>Mean Strategy</th>\n",
+              "      <th>Median Strategy</th>\n",
+              "      <th>Most Frequent Strategy</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>timestamp</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:15:00</th>\n",
+              "      <td>73.967322</td>\n",
+              "      <td>73.967322</td>\n",
+              "      <td>73.967322</td>\n",
+              "      <td>73.967322</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:20:00</th>\n",
+              "      <td>74.935882</td>\n",
+              "      <td>74.935882</td>\n",
+              "      <td>74.935882</td>\n",
+              "      <td>74.935882</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:25:00</th>\n",
+              "      <td>76.124162</td>\n",
+              "      <td>76.124162</td>\n",
+              "      <td>76.124162</td>\n",
+              "      <td>76.124162</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:30:00</th>\n",
+              "      <td>78.140707</td>\n",
+              "      <td>78.140707</td>\n",
+              "      <td>78.140707</td>\n",
+              "      <td>78.140707</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:35:00</th>\n",
+              "      <td>79.329836</td>\n",
+              "      <td>79.329836</td>\n",
+              "      <td>79.329836</td>\n",
+              "      <td>79.329836</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-1566259d-e14c-4af8-a785-3c25fbcdf0a1')\"\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",
+              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
+              "  </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",
+              "      cursor: pointer;\n",
+              "      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-1566259d-e14c-4af8-a785-3c25fbcdf0a1 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-1566259d-e14c-4af8-a785-3c25fbcdf0a1');\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",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 215
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "_ = rmse_score(ts_org1, df, 'temperature')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "WnBQ2CQ62a0n",
+        "outputId": "b7bdb558-e390-4d12-9ded-4e469d433a09"
+      },
+      "execution_count": 216,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "RMSE for Mean Strategy: 2.6118121108260417\n",
+            "RMSE for Median Strategy: 2.0176725629240635\n",
+            "RMSE for Most Frequent Strategy: 22.936820075564288\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "plot_dfs(ts_org1, df, 'temperature')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "IfFOle3k3K76",
+        "outputId": "2d9aad73-dc09-4129-cc78-d48f2f8056eb"
+      },
+      "execution_count": 217,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x1600 with 5 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "folder = Path('./Machine_temp_failure_original.csv')\n",
+        "ts_org2 = read_dataset(folder,'timestamp')\n",
+        "ts_org2 = ts_org2.rename(columns={'value': 'temperature'})"
+      ],
+      "metadata": {
+        "id": "Bx_2Si31JHuk"
+      },
+      "execution_count": 218,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "folder = Path('./Machine_temp_failure_missing.csv')\n",
+        "df1 = read_dataset(folder,'timestamp')"
+      ],
+      "metadata": {
+        "id": "pMiayHiF5gju"
+      },
+      "execution_count": 219,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df1 = df1.rename(columns={'value': 'temperature'})"
+      ],
+      "metadata": {
+        "id": "T8g6nawf52Hv"
+      },
+      "execution_count": 220,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df1.interpolate()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 455
+        },
+        "id": "OlqVmtsI57YY",
+        "outputId": "91bec133-c379-40b1-9a12-56ce591f0834"
+      },
+      "execution_count": 221,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                     temperature\n",
+              "timestamp                       \n",
+              "2013-02-12 21:15:00    73.967322\n",
+              "2013-02-12 21:20:00    74.935882\n",
+              "2013-02-12 21:25:00    76.124162\n",
+              "2013-02-12 21:30:00    78.140707\n",
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+              "...                          ...\n",
+              "2014-02-19 15:05:00    98.185415\n",
+              "2014-02-19 15:10:00    97.804168\n",
+              "2014-02-19 15:15:00    97.135468\n",
+              "2014-02-19 15:20:00    98.056852\n",
+              "2014-02-19 15:25:00    96.903861\n",
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+              "<p>22695 rows × 1 columns</p>\n",
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+              "  <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",
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+              "\n",
+              "    .colab-df-convert:hover {\n",
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+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
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+              "      fill: #D2E3FC;\n",
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+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
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+              "  </style>\n",
+              "\n",
+              "      <script>\n",
+              "        const buttonEl =\n",
+              "          document.querySelector('#df-88dbefd9-5c9d-4af6-8bbf-e79f7fa27b8e 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-88dbefd9-5c9d-4af6-8bbf-e79f7fa27b8e');\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",
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+              "      </script>\n",
+              "    </div>\n",
+              "  </div>\n",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 221
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "df1.columns"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Ocl68Q3h8d0D",
+        "outputId": "0a546b66-d71d-4dde-dd64-301544c73642"
+      },
+      "execution_count": 222,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "Index(['temperature'], dtype='object')"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 222
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "interpolations = [\n",
+        "    'linear',\n",
+        "    'quadratic',\n",
+        "    'nearest',\n",
+        "    'cubic',\n",
+        "]\n",
+        "df1 = df1[~df1.index.duplicated()]\n",
+        "\n",
+        "for intp in interpolations:\n",
+        "    df1[intp] = df1['temperature'].interpolate(method=intp)\n",
+        "\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "aHt_vZdb6M_Y",
+        "outputId": "05946c12-3818-4737-b7e0-28ccbb98c44a"
+      },
+      "execution_count": 224,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "<ipython-input-224-bac28c816b8f>:10: SettingWithCopyWarning: \n",
+            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+            "Try using .loc[row_indexer,col_indexer] = value instead\n",
+            "\n",
+            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+            "  df1[intp] = df1['temperature'].interpolate(method=intp)\n",
+            "<ipython-input-224-bac28c816b8f>:10: SettingWithCopyWarning: \n",
+            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+            "Try using .loc[row_indexer,col_indexer] = value instead\n",
+            "\n",
+            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+            "  df1[intp] = df1['temperature'].interpolate(method=intp)\n",
+            "<ipython-input-224-bac28c816b8f>:10: SettingWithCopyWarning: \n",
+            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+            "Try using .loc[row_indexer,col_indexer] = value instead\n",
+            "\n",
+            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+            "  df1[intp] = df1['temperature'].interpolate(method=intp)\n",
+            "<ipython-input-224-bac28c816b8f>:10: SettingWithCopyWarning: \n",
+            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+            "Try using .loc[row_indexer,col_indexer] = value instead\n",
+            "\n",
+            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+            "  df1[intp] = df1['temperature'].interpolate(method=intp)\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "_ = rmse_score(ts_org2, df1, 'temperature')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ityf8Hvc-_7f",
+        "outputId": "7ac75d35-6c39-4e95-f80c-0b58ad8eaa84"
+      },
+      "execution_count": 225,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "RMSE for linear: 3.4745265473020495\n",
+            "RMSE for quadratic: 13.078876205037874\n",
+            "RMSE for nearest: 2.2136803493321584\n",
+            "RMSE for cubic: 16.264769197704556\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "cols = ['temperature', 'linear', 'quadratic','nearest', 'cubic']\n",
+        "plot_dfs(ts_org2, df1[cols], 'temperature')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "WC71Hb-F_M95",
+        "outputId": "ddd6eda3-748b-48be-92ac-0742d0e61577"
+      },
+      "execution_count": 226,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 1000x1600 with 6 Axes>"
+            ],
+            "image/png": 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\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "frequency = ts['temperature'].value_counts()\n",
+        "print(frequency)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "nIyJkPUK_rnP",
+        "outputId": "048fb45b-3a29-4fe5-b368-fdba9c545931"
+      },
+      "execution_count": 227,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "73.967322    1\n",
+            "79.926638    1\n",
+            "77.842853    1\n",
+            "78.705237    1\n",
+            "78.184969    1\n",
+            "            ..\n",
+            "85.841295    1\n",
+            "86.896794    1\n",
+            "86.182052    1\n",
+            "85.922123    1\n",
+            "96.903861    1\n",
+            "Name: temperature, Length: 21410, dtype: int64\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts.head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 238
+        },
+        "id": "KHR28O0KM6Il",
+        "outputId": "d8bdfe0a-ffcd-446e-bfc6-1b0ffc7c4ca1"
+      },
+      "execution_count": 228,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "                     temperature      ffill      bfill       mean\n",
+              "timestamp                                                        \n",
+              "2013-02-12 21:15:00    73.967322  73.967322  73.967322  73.967322\n",
+              "2013-02-12 21:20:00    74.935882  74.935882  74.935882  74.935882\n",
+              "2013-02-12 21:25:00    76.124162  76.124162  76.124162  76.124162\n",
+              "2013-02-12 21:30:00    78.140707  78.140707  78.140707  78.140707\n",
+              "2013-02-12 21:35:00    79.329836  79.329836  79.329836  79.329836"
+            ],
+            "text/html": [
+              "\n",
+              "  <div id=\"df-38f30496-b0de-414e-98dc-0086a601c862\">\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",
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+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>temperature</th>\n",
+              "      <th>ffill</th>\n",
+              "      <th>bfill</th>\n",
+              "      <th>mean</th>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>timestamp</th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "      <th></th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:15:00</th>\n",
+              "      <td>73.967322</td>\n",
+              "      <td>73.967322</td>\n",
+              "      <td>73.967322</td>\n",
+              "      <td>73.967322</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:20:00</th>\n",
+              "      <td>74.935882</td>\n",
+              "      <td>74.935882</td>\n",
+              "      <td>74.935882</td>\n",
+              "      <td>74.935882</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:25:00</th>\n",
+              "      <td>76.124162</td>\n",
+              "      <td>76.124162</td>\n",
+              "      <td>76.124162</td>\n",
+              "      <td>76.124162</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:30:00</th>\n",
+              "      <td>78.140707</td>\n",
+              "      <td>78.140707</td>\n",
+              "      <td>78.140707</td>\n",
+              "      <td>78.140707</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2013-02-12 21:35:00</th>\n",
+              "      <td>79.329836</td>\n",
+              "      <td>79.329836</td>\n",
+              "      <td>79.329836</td>\n",
+              "      <td>79.329836</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "</div>\n",
+              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-38f30496-b0de-414e-98dc-0086a601c862')\"\n",
+              "              title=\"Convert this dataframe to an interactive table.\"\n",
+              "              style=\"display:none;\">\n",
+              "        \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",
+              "      cursor: pointer;\n",
+              "      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-38f30496-b0de-414e-98dc-0086a601c862 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-38f30496-b0de-414e-98dc-0086a601c862');\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",
+              "  "
+            ]
+          },
+          "metadata": {},
+          "execution_count": 228
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "ts_org.resample('H').ffill().head()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 311
+        },
+        "id": "wc-a-P8fMk6H",
+        "outputId": "1418c76e-6dcf-4c61-d8e7-cf2659cddd0c"
+      },
+      "execution_count": 232,
+      "outputs": [
+        {
+          "output_type": "error",
+          "ename": "ValueError",
+          "evalue": "ignored",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+            "\u001b[0;32m<ipython-input-232-d929af2cd73a>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mts_org\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'H'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mffill\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/resample.py\u001b[0m in \u001b[0;36mffill\u001b[0;34m(self, limit)\u001b[0m\n\u001b[1;32m    543\u001b[0m         \u001b[0mDataFrame\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfillna\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mFill\u001b[0m \u001b[0mNA\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mNaN\u001b[0m \u001b[0mvalues\u001b[0m \u001b[0musing\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mspecified\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    544\u001b[0m         \"\"\"\n\u001b[0;32m--> 545\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_upsample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"ffill\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlimit\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    546\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    547\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mpad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/resample.py\u001b[0m in \u001b[0;36m_upsample\u001b[0;34m(self, method, limit, fill_value)\u001b[0m\n\u001b[1;32m   1363\u001b[0m             \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres_index\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1364\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1365\u001b[0;31m             result = obj.reindex(\n\u001b[0m\u001b[1;32m   1366\u001b[0m                 \u001b[0mres_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlimit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfill_value\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfill_value\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1367\u001b[0m             )\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    345\u001b[0m         \u001b[0;34m@\u001b[0m\u001b[0mwraps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    346\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mCallable\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m...\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mAny\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 347\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    348\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    349\u001b[0m         \u001b[0mkind\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0minspect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mParameter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPOSITIONAL_OR_KEYWORD\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mreindex\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   5203\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"axis\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5204\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"labels\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5205\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5206\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5207\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0moverload\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mreindex\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   5287\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5288\u001b[0m         \u001b[0;31m# perform the reindex on the axes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5289\u001b[0;31m         return self._reindex_axes(\n\u001b[0m\u001b[1;32m   5290\u001b[0m             \u001b[0maxes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfill_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5291\u001b[0m         ).__finalize__(self, method=\"reindex\")\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_reindex_axes\u001b[0;34m(self, axes, level, limit, tolerance, method, fill_value, copy)\u001b[0m\n\u001b[1;32m   5002\u001b[0m         \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxes\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"index\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5003\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5004\u001b[0;31m             frame = frame._reindex_index(\n\u001b[0m\u001b[1;32m   5005\u001b[0m                 \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfill_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5006\u001b[0m             )\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_reindex_index\u001b[0;34m(self, new_index, method, copy, level, fill_value, limit, tolerance)\u001b[0m\n\u001b[1;32m   5018\u001b[0m         \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5019\u001b[0m     ):\n\u001b[0;32m-> 5020\u001b[0;31m         new_index, indexer = self.index.reindex(\n\u001b[0m\u001b[1;32m   5021\u001b[0m             \u001b[0mnew_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlimit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlimit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5022\u001b[0m         )\n",
+            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mreindex\u001b[0;34m(self, target, method, level, limit, tolerance)\u001b[0m\n\u001b[1;32m   4417\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4418\u001b[0m                     \u001b[0;32mif\u001b[0m \u001b[0mmethod\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mlimit\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4419\u001b[0;31m                         raise ValueError(\n\u001b[0m\u001b[1;32m   4420\u001b[0m                             \u001b[0;34m\"cannot reindex a non-unique index \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4421\u001b[0m                             \u001b[0;34m\"with a method or limit\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mValueError\u001b[0m: cannot reindex a non-unique index with a method or limit"
+          ]
+        }
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
\ No newline at end of file