Tweet Analysis Notebook.ipynb

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      "name": "Dipo EDA.ipynb",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NxfTWNN0b_cF"
      },
      "source": [
        "# Exploratory Data Analysis and Sentiment Analysis\n",
        "\n",
        "---\n",
        "In this notebook, I tried to draw insight from the extracted tweets using pandas and other import libraries.\n",
        "The Sentiment analyzers used for this project is a Vader Sentiment \n",
        "Analysis, you can read about it [here](https://medium.com/analytics-vidhya/simplifying-social-media-sentiment-analysis-using-vader-in-python-f9e6ec6fc52f).\n",
        " and navigate back to the tweet extraction notebook here"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L0c_ny-VtKH4"
      },
      "source": [
        "#importing some the necessary libraries\n",
        "import json\n",
        "import  numpy as np\n",
        "import pandas as pd\n",
        "import csv\n",
        "import os\n",
        "from datetime import datetime\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import seaborn as sns\n",
        "%matplotlib inline\n"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
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        "outputId": "69008dad-e20d-4f0e-8d63-77047ca8b70d"
      },
      "source": [
        "##lising all the CSVs  in the dir\n",
        "\n",
        "all_tweets = pd.DataFrame()\n",
        "files = [file for file in os.listdir('/content/drive/MyDrive/Colab Notebooks/dipo tweets')]\n",
        "for file in files:\n",
        "  print(file)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "20210322_213915_ogbeni_tweets.csv\n",
            "2021-03-31ogbenidipo OR Dr Dipo OR Ogbeni Dipo\n",
            "20210322_220100_ogbeni_tweets.csv\n",
            "20210325_110759_ogbeni_tweets.csv\n",
            "20210325_124521_ogbeni_tweets.csv\n",
            "20210328_203555@ogbenidipo OR Dr Dipo OR Ogbeni Dipo_ogbeni_tweets.csv\n",
            "20210328_203839Ogbeni Dipo_ogbeni_tweets.csv\n",
            "20210329_000708@ogbenidipo OR Dr Dipo OR Ogbeni Dipo_ogbeni_tweets.csv\n",
            "20210329_004437@ogbenidipo OR Dr Dipo OR Ogbeni Dipo_try.csv\n",
            "20210329_004556@ogbenidipo OR Dr Dipo OR Ogbeni Dipo_try.csv\n",
            "24-28.csv\n",
            "complex.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6tPHKgYRxiPn"
      },
      "source": [
        "#Joining\n",
        "for file  in files:\n",
        "    df = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/dipo tweets/' + file)\n",
        "    all_tweets = pd.concat([all_tweets, df])\n",
        "all_tweets.to_csv('/content/drive/MyDrive/Colab Notebooks/dipo tweets/all_tweets.csv', index=0)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
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          "height": 435
        },
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        "outputId": "5c6b70b3-821b-4dfc-bf05-191a70f8892f"
      },
      "source": [
        "all_tweets = pd.read_csv('/content/drive/MyDrive/Colab Notebooks/dipo tweets/all_tweets.csv', parse_dates=True)\n",
        "all_tweets.head()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>username</th>\n",
              "      <th>acctdesc</th>\n",
              "      <th>location</th>\n",
              "      <th>following</th>\n",
              "      <th>followers</th>\n",
              "      <th>totaltweets</th>\n",
              "      <th>usercreatedts</th>\n",
              "      <th>tweetcreatedts</th>\n",
              "      <th>retweetcount</th>\n",
              "      <th>text</th>\n",
              "      <th>hashtags</th>\n",
              "      <th>likes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ajao_janet</td>\n",
              "      <td>#Jovial #Focus #Team_Player #Giver #Honesty #B...</td>\n",
              "      <td>Lagos State, Nigeria</td>\n",
              "      <td>898.0</td>\n",
              "      <td>779</td>\n",
              "      <td>3777</td>\n",
              "      <td>2015-07-07 10:10:48</td>\n",
              "      <td>2021-03-22 20:53:19</td>\n",
              "      <td>0</td>\n",
              "      <td>@westtyy_ @OgbeniDipo Na uncle Dipo Dey whine ...</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>OfficialOmoJay</td>\n",
              "      <td>ꜰᴀꜱʜɪᴏɴ ᴅᴇꜱɪɢɴᴇʀ ✂️\\nA C T I V E!  👤</td>\n",
              "      <td>Nigeria</td>\n",
              "      <td>4130.0</td>\n",
              "      <td>3183</td>\n",
              "      <td>14104</td>\n",
              "      <td>2013-03-09 15:31:48</td>\n",
              "      <td>2021-03-22 20:26:18</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo This dipo get money, make una bill am</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>SearchPunt</td>\n",
              "      <td>My good tweets are mine. Others are from hackers.</td>\n",
              "      <td>Lagos</td>\n",
              "      <td>823.0</td>\n",
              "      <td>4818</td>\n",
              "      <td>32379</td>\n",
              "      <td>2018-02-17 22:57:55</td>\n",
              "      <td>2021-03-22 20:23:16</td>\n",
              "      <td>0</td>\n",
              "      <td>\"Guide me through your thought process, I want...</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>BoodaLeye</td>\n",
              "      <td>• Jesus Addict • Arts Enthusiast • Guitar Savv...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>256.0</td>\n",
              "      <td>98</td>\n",
              "      <td>2680</td>\n",
              "      <td>2021-02-21 11:30:39</td>\n",
              "      <td>2021-03-22 19:30:41</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo #FriendsOfDipo are ready, anyday a...</td>\n",
              "      <td>[{'text': 'FriendsOfDipo', 'indices': [12, 26]}]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Kimanii07</td>\n",
              "      <td>Photographer //Arsenal fan//Loves Adventures//...</td>\n",
              "      <td>Ibadan, Nigeria</td>\n",
              "      <td>288.0</td>\n",
              "      <td>294</td>\n",
              "      <td>7665</td>\n",
              "      <td>2020-06-02 11:27:13</td>\n",
              "      <td>2021-03-22 19:17:51</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo @greatwhizz10 Uncle Dipo, you sure😏</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ],
            "text/plain": [
              "         username  ... likes\n",
              "0      ajao_janet  ...   NaN\n",
              "1  OfficialOmoJay  ...   NaN\n",
              "2      SearchPunt  ...   NaN\n",
              "3       BoodaLeye  ...   NaN\n",
              "4       Kimanii07  ...   NaN\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
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      "metadata": {
        "colab": {
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        },
        "id": "txmCbIhpplyD",
        "outputId": "09baf2b2-acfb-457b-b57e-a55f98d53ab7"
      },
      "source": [
        "all_tweets.columns"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['username', 'acctdesc', 'location', 'following', 'followers',\n",
              "       'totaltweets', 'usercreatedts', 'tweetcreatedts', 'retweetcount',\n",
              "       'text', 'hashtags', 'likes'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "USR34DDkT4q2",
        "outputId": "b97b56f2-2991-41f0-f616-c33188c18006"
      },
      "source": [
        "#counting for missen values\n",
        "all_tweets.isna().sum()\n"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "username             0\n",
              "acctdesc          9086\n",
              "location          3196\n",
              "following         8690\n",
              "followers            0\n",
              "totaltweets          0\n",
              "usercreatedts        0\n",
              "tweetcreatedts       0\n",
              "retweetcount         0\n",
              "text                 0\n",
              "hashtags          8690\n",
              "likes             7333\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nuoOM8KHUCuM"
      },
      "source": [
        "######So, there are five features with missen values which ought not supposed to be so here are the reason why:\n",
        "For location, those the users did not put their location on twitter, same goes account description. For likes I did use some other extraction techinque to get the data and while extracting I excluded it from the extraction and same goes for the rest."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bMlQ_e2F1igC",
        "outputId": "451fea2d-f8fb-4b44-d573-a1518e5c5688"
      },
      "source": [
        "#following and  hashtags do have null values because I dropped them while making other runs of extraction\n",
        "all_tweets.info()"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 16023 entries, 0 to 16022\n",
            "Data columns (total 12 columns):\n",
            " #   Column          Non-Null Count  Dtype  \n",
            "---  ------          --------------  -----  \n",
            " 0   username        16023 non-null  object \n",
            " 1   acctdesc        6937 non-null   object \n",
            " 2   location        12827 non-null  object \n",
            " 3   following       7333 non-null   float64\n",
            " 4   followers       16023 non-null  int64  \n",
            " 5   totaltweets     16023 non-null  int64  \n",
            " 6   usercreatedts   16023 non-null  object \n",
            " 7   tweetcreatedts  16023 non-null  object \n",
            " 8   retweetcount    16023 non-null  int64  \n",
            " 9   text            16023 non-null  object \n",
            " 10  hashtags        7333 non-null   object \n",
            " 11  likes           8690 non-null   float64\n",
            "dtypes: float64(2), int64(3), object(7)\n",
            "memory usage: 1.5+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 768
        },
        "id": "Nr_3C13J1pto",
        "outputId": "a21e0151-d397-4412-a3fa-649a141e2546"
      },
      "source": [
        "#counting duplicated tweets\n",
        "all_tweets[all_tweets.duplicated(subset='text')]\n",
        "#14602 of the records are duplicated tweets "
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>username</th>\n",
              "      <th>acctdesc</th>\n",
              "      <th>location</th>\n",
              "      <th>following</th>\n",
              "      <th>followers</th>\n",
              "      <th>totaltweets</th>\n",
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              "      <th>retweetcount</th>\n",
              "      <th>text</th>\n",
              "      <th>hashtags</th>\n",
              "      <th>likes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>itxjsm</td>\n",
              "      <td>This is d official Twitter handle of Jay Esem ...</td>\n",
              "      <td>Ikeja, Nigeria</td>\n",
              "      <td>219.0</td>\n",
              "      <td>14</td>\n",
              "      <td>1463</td>\n",
              "      <td>2020-07-23 20:38:50</td>\n",
              "      <td>2021-03-21 18:47:50</td>\n",
              "      <td>2</td>\n",
              "      <td>@OgbeniDipo Wo Oga dipo wahAla e po,let them e...</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>65</th>\n",
              "      <td>Abraham76139460</td>\n",
              "      <td>Unserious mind(OBOsexual)</td>\n",
              "      <td>Lagos, Nigeria</td>\n",
              "      <td>130.0</td>\n",
              "      <td>38</td>\n",
              "      <td>631</td>\n",
              "      <td>2020-08-23 11:55:30</td>\n",
              "      <td>2021-03-21 09:30:19</td>\n",
              "      <td>1</td>\n",
              "      <td>@OgbeniDipo So because we no go school Dr.Dipo...</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>66</th>\n",
              "      <td>JohnnyLingo__</td>\n",
              "      <td>🐺</td>\n",
              "      <td>Lagos📌</td>\n",
              "      <td>666.0</td>\n",
              "      <td>784</td>\n",
              "      <td>42302</td>\n",
              "      <td>2012-04-12 07:13:55</td>\n",
              "      <td>2021-03-21 08:37:58</td>\n",
              "      <td>10</td>\n",
              "      <td>@OgbeniDipo Read some of comments and I’m just...</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67</th>\n",
              "      <td>Smooth_Operata</td>\n",
              "      <td>Here by fate.\\nManchester United. Politics. Mu...</td>\n",
              "      <td>Lagos</td>\n",
              "      <td>1232.0</td>\n",
              "      <td>615</td>\n",
              "      <td>37241</td>\n",
              "      <td>2011-03-16 10:14:17</td>\n",
              "      <td>2021-03-21 07:54:33</td>\n",
              "      <td>16</td>\n",
              "      <td>Omo. @OgbeniDipo is actually a cool person o 😂...</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>70</th>\n",
              "      <td>tomathegr8</td>\n",
              "      <td>#Criminology▪️▪️#Félix</td>\n",
              "      <td>Motion</td>\n",
              "      <td>942.0</td>\n",
              "      <td>963</td>\n",
              "      <td>3591</td>\n",
              "      <td>2016-07-03 23:49:37</td>\n",
              "      <td>2021-03-21 06:48:31</td>\n",
              "      <td>250</td>\n",
              "      <td>OMG, CGPA is trending. What have you done agai...</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16018</th>\n",
              "      <td>sammyalfred7</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Afrika</td>\n",
              "      <td>NaN</td>\n",
              "      <td>346</td>\n",
              "      <td>6013</td>\n",
              "      <td>2018-05-05 14:21:05</td>\n",
              "      <td>2021-03-25 00:24:30</td>\n",
              "      <td>355</td>\n",
              "      <td>RT @quinlateefa: Ogbeni dipo is just a markete...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16019</th>\n",
              "      <td>Furyzico</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Illuminate★☆★ HQ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1819</td>\n",
              "      <td>49674</td>\n",
              "      <td>2011-02-09 22:42:03</td>\n",
              "      <td>2021-03-25 00:24:08</td>\n",
              "      <td>624</td>\n",
              "      <td>RT @chigoziiem: ..and ogbeni dipo is saying th...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16020</th>\n",
              "      <td>atlanta4lif</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Pressure</td>\n",
              "      <td>NaN</td>\n",
              "      <td>501</td>\n",
              "      <td>19155</td>\n",
              "      <td>2020-08-21 14:09:29</td>\n",
              "      <td>2021-03-25 00:23:23</td>\n",
              "      <td>527</td>\n",
              "      <td>RT @AfamDeluxo: Ogbeni Dipo has always been a ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16021</th>\n",
              "      <td>youngsavvy66</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>465</td>\n",
              "      <td>4031</td>\n",
              "      <td>2016-02-16 16:02:20</td>\n",
              "      <td>2021-03-25 00:23:20</td>\n",
              "      <td>556</td>\n",
              "      <td>RT @oboy_jay: Worst prank ever,,,, what would ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16022</th>\n",
              "      <td>atlanta4lif</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Pressure</td>\n",
              "      <td>NaN</td>\n",
              "      <td>501</td>\n",
              "      <td>19155</td>\n",
              "      <td>2020-08-21 14:09:29</td>\n",
              "      <td>2021-03-25 00:23:18</td>\n",
              "      <td>1171</td>\n",
              "      <td>RT @DAFLOWABIOYE: ogbeni dipo that was invited...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>14602 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              username  ... likes\n",
              "46              itxjsm  ...   NaN\n",
              "65     Abraham76139460  ...   NaN\n",
              "66       JohnnyLingo__  ...   NaN\n",
              "67      Smooth_Operata  ...   NaN\n",
              "70          tomathegr8  ...   NaN\n",
              "...                ...  ...   ...\n",
              "16018     sammyalfred7  ...   0.0\n",
              "16019         Furyzico  ...   0.0\n",
              "16020      atlanta4lif  ...   0.0\n",
              "16021     youngsavvy66  ...   0.0\n",
              "16022      atlanta4lif  ...   0.0\n",
              "\n",
              "[14602 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fci-IKDN4i2U",
        "outputId": "edda010c-a06b-45e0-9df0-955f6896fc9f"
      },
      "source": [
        "###c dropping duplicate tweets\n",
        "all_tweets = all_tweets.drop_duplicates(subset='text')\n",
        "print(len(all_tweets))"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1421\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "txXM14GrnnJh",
        "outputId": "a18b4461-2baf-4e09-a752-b0dad3080628"
      },
      "source": [
        "#FE\n",
        "## usercreatedts and tweetcreatedts need to be converted to datetime\n",
        "all_tweets['usercreatedts'] = pd.to_datetime(all_tweets['usercreatedts'])\n",
        "all_tweets['tweetcreatedts'] = pd.to_datetime(all_tweets['tweetcreatedts'])\n",
        "\n",
        "#creatingo only tweet date column without time\n",
        "#all_tweets['date']= all_tweets['tweetcreatedts'].dt.date\n",
        "\n",
        "# create the weekdays and time column, year account created\n",
        "all_tweets['weekday'] =all_tweets['tweetcreatedts'].dt.strftime(\"%a\")\n",
        "print(all_tweets['weekday'])\n",
        "\n",
        "#time\n",
        "all_tweets['hour']= all_tweets['tweetcreatedts'].dt.hour\n",
        "print(all_tweets['hour'])\n",
        "\n",
        "# year acct created\n",
        "all_tweets['usercreatedts'] =pd.to_datetime(all_tweets['usercreatedts'])\n",
        "all_tweets['acctyear']= all_tweets['usercreatedts'].dt.year\n",
        "print(all_tweets['acctyear'])"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0        Mon\n",
            "1        Mon\n",
            "2        Mon\n",
            "3        Mon\n",
            "4        Mon\n",
            "        ... \n",
            "15905    Thu\n",
            "15927    Thu\n",
            "15932    Thu\n",
            "15973    Thu\n",
            "16007    Thu\n",
            "Name: weekday, Length: 1421, dtype: object\n",
            "0        20\n",
            "1        20\n",
            "2        20\n",
            "3        19\n",
            "4        19\n",
            "         ..\n",
            "15905     1\n",
            "15927     0\n",
            "15932     0\n",
            "15973     0\n",
            "16007     0\n",
            "Name: hour, Length: 1421, dtype: int64\n",
            "0        2015\n",
            "1        2013\n",
            "2        2018\n",
            "3        2021\n",
            "4        2020\n",
            "         ... \n",
            "15905    2018\n",
            "15927    2015\n",
            "15932    2014\n",
            "15973    2020\n",
            "16007    2010\n",
            "Name: acctyear, Length: 1421, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FHtM87Z35qX-"
      },
      "source": [
        "#setting index to date so that I can slice better\n",
        "all_tweets = all_tweets.set_index('tweetcreatedts').sort_index()"
      ],
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 418
        },
        "id": "LYZondjSBxU2",
        "outputId": "7610cb5f-9522-4ae4-80fb-ffb7695a24e5"
      },
      "source": [
        "all_tweets.tail()"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>username</th>\n",
              "      <th>acctdesc</th>\n",
              "      <th>location</th>\n",
              "      <th>following</th>\n",
              "      <th>followers</th>\n",
              "      <th>totaltweets</th>\n",
              "      <th>usercreatedts</th>\n",
              "      <th>retweetcount</th>\n",
              "      <th>text</th>\n",
              "      <th>hashtags</th>\n",
              "      <th>likes</th>\n",
              "      <th>weekday</th>\n",
              "      <th>hour</th>\n",
              "      <th>acctyear</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>tweetcreatedts</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2021-04-04 21:31:42</th>\n",
              "      <td>MyunusualSelf_</td>\n",
              "      <td>NaN</td>\n",
              "      <td>The Kings Landing</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1152</td>\n",
              "      <td>4690</td>\n",
              "      <td>2019-04-07 10:27:14</td>\n",
              "      <td>11</td>\n",
              "      <td>RT @AyomipoGideon: Dr. Dipo, you are supposed ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Sun</td>\n",
              "      <td>21</td>\n",
              "      <td>2019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-04-04 21:37:54</th>\n",
              "      <td>AdebamboOluwas4</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Ibafo</td>\n",
              "      <td>NaN</td>\n",
              "      <td>24</td>\n",
              "      <td>636</td>\n",
              "      <td>2019-12-25 14:57:52</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo Dr. Dipo, pls sir, open your DM. I...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Sun</td>\n",
              "      <td>21</td>\n",
              "      <td>2019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-04-04 21:44:11</th>\n",
              "      <td>persie79539668</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>15</td>\n",
              "      <td>2020-10-14 10:18:20</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo Dipo, don’t make these guys turn y...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Sun</td>\n",
              "      <td>21</td>\n",
              "      <td>2020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-04-04 21:47:21</th>\n",
              "      <td>Bashirboy</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Lagos, Nigeria</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1819</td>\n",
              "      <td>23621</td>\n",
              "      <td>2011-04-04 09:08:50</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo Dr. Dipo himself with this tweet p...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Sun</td>\n",
              "      <td>21</td>\n",
              "      <td>2011</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-04-05 04:40:35</th>\n",
              "      <td>EEchekwu</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Lagos,  Nigeria</td>\n",
              "      <td>NaN</td>\n",
              "      <td>48</td>\n",
              "      <td>947</td>\n",
              "      <td>2018-11-15 00:04:44</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo O boy ,who dey make dipo vex na</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Mon</td>\n",
              "      <td>4</td>\n",
              "      <td>2018</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                            username acctdesc  ... hour  acctyear\n",
              "tweetcreatedts                                 ...               \n",
              "2021-04-04 21:31:42   MyunusualSelf_      NaN  ...   21      2019\n",
              "2021-04-04 21:37:54  AdebamboOluwas4      NaN  ...   21      2019\n",
              "2021-04-04 21:44:11   persie79539668      NaN  ...   21      2020\n",
              "2021-04-04 21:47:21        Bashirboy      NaN  ...   21      2011\n",
              "2021-04-05 04:40:35         EEchekwu      NaN  ...    4      2018\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jB1LB4wKWJL_",
        "outputId": "b57a57d2-d4f3-477a-daf1-e098e80ed65f"
      },
      "source": [
        "len(all_tweets)"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1421"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fyh5t7M7t-CH"
      },
      "source": [
        "#before moving forward, we need to remove all the personal tweets of Dr dipo\n",
        "general_tweets = all_tweets[all_tweets['username'] != 'OgbeniDipo']\n",
        "peronal_tweets = all_tweets[all_tweets['username'] == 'OgbeniDipo']"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ld3m22yOzItV",
        "outputId": "51798aba-b74d-4889-cf35-db36eac51b1e"
      },
      "source": [
        "#1. get the top 5 username that tweeted most often\n",
        "top5 =(general_tweets.groupby('username').count().sort_values(by= 'text', ascending = False))\n",
        "print(top5.iloc[1:6]['text'])\n",
        "#printing the text of the first tweeter\n",
        "print(general_tweets[general_tweets['username'] == 'PurpleIntestine']['text'])\n"
      ],
      "execution_count": 134,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "username\n",
            "PurpleIntestine    14\n",
            "fuski_             12\n",
            "Stan_Europe        11\n",
            "tikobadman          6\n",
            "IconicNino          5\n",
            "Name: text, dtype: int64\n",
            "tweetcreatedts\n",
            "2021-03-24 14:22:16                                                  @DAFLOWABIOYE @Oreoluwa__x @OgbeniDipo  Ogbeni Dipo is a scam. The yeye CV review na scam. With his PhD what value has he created? It's high time we reported him to UK authority. He's a Vulture. Looking to feed on already disadvantaged student. Thunder faya you Ogbeni Dipo\n",
            "2021-03-24 14:25:50                                                                                                          @OgbeniDipo Let nobody subscribe to Ogbeni Dipo. He preys on unemployed Student seeking job. He cant try that in the UK. How may people have you helped in UK. Desist from your cannibalistic attitude. Thunder faya you.\n",
            "2021-03-24 14:39:06                                  @Prayerhouse144 @FS_Yusuf_ @OgbeniDipo it's high time Nigerian realized dt Ogbeni Dipo is after his pocket. How many people are employed in UK through his yeye masterclass.The guy is a Vulture preying on innocent unemployed youth. If Dipo was the President, he will pocket the whole nation\n",
            "2021-03-24 14:53:55                                                                                                @henry_iro @omidanabeni @OgbeniDipo it's people like Ogbeni Dipo that will announce 10k scholarship for 2 people yet sell form for 5k for 100 people. Yeye ole. He didn't know that people don get him scam. Thunder Faya you Dipo.\n",
            "2021-03-24 14:57:03                                                                                                                             @kalempire @okorolambert @omidanabeni @OgbeniDipo  Dipo is a real jobberman. A Vulture. Always preying on innocent unemployed Nigerian Youths. Thunder Faya you Dipo. The guy with his PhD na parasite\n",
            "2021-03-24 15:43:10                                                                                                                                                                                                                                                @OgbeniDipo Thunder ⚡ Faya you Dipo.\\nThunder Faya you Dipo https://t.co/EJfrZyR8um\n",
            "2021-03-24 17:52:42                                                                                                                                                                                                                       @DayoAlhassan @OgbeniDipo ⚡ Thunder Faya you Dayo\\nThunder Faya you Dipo repeat😂😂😂💥💥💥Dipo your beans is done\n",
            "2021-03-24 18:03:33                                                                                                                                                        @OgbeniDipo @boss_donnyperry @DAFLOWABIOYE Ogbeni Dipo why d vawulence against thee? Just go and drink warm water ,baff with black soap and sleep 😅 https://t.co/Xuog6v58Of\n",
            "2021-03-24 18:05:18                                                                                                                                                                                    @OgbeniDipo @Omojuwa Dipo stop spreading false information. Dipo how far with the house at Ajangbadi? As the agent how much is your commission?\n",
            "2021-03-24 18:06:06                                                                                                                                                                                                                                                                                                 @OgbeniDipo Dipo can you fry dodo?\n",
            "2021-03-24 18:40:26                                                                   @DayoAlhassan @OgbeniDipo @Omojuwa \\nOgbeni Dipo Geng awon perspire, aspire to refire b4 you retire. What is your is equal to = gann? Lori iro. Just dey hustle people upanddan. With your 9.0/5 CGPA(1stclass^9) no be CV u dey review? https://t.co/jZ6kfV87lU\n",
            "2021-03-24 18:56:36                           @Ryhnogee @Real_Damilare10 @olori_lfc @OgbeniDipo @Jarushub \\nNo mind Dipo. Anytime first-class. Is he an employer of labour? And that Jarushub. We go go soon drag am too. Anything, I finished with a 1st class 9.0/5.are you not still an employee and also reviewing CV.\\nAwon oni rederede.#loriiro\n",
            "2021-03-24 19:06:16    @Ryhnogee @Real_Damilare10 @olori_lfc @OgbeniDipo @Jarushub @OgbeniDipo @Jarushub \\nNo mind Dipo. Anytime first-class. Is he an employer of labour? And that @Jarushub. We go go soon drag am too. Anything, I finished with a 1st class 9.0/5.are you not still an employee and also reviewing CV.\\nAwon oni rederede.#loriiro\n",
            "2021-03-24 19:08:05                                                      @Jarushub @OgbeniDipo @Jarushub \\nNo mind Dipo. Anytime first-class. Is he an employer of labour? And that @Jarushub. We go go soon drag am too. Anything, I finished with a 1st class 9.0/5.are you not still an employee and also reviewing CV.\\nAwon oni rederede.#loriiro\n",
            "Name: text, dtype: object\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "08enL2bjLqwx"
      },
      "source": [
        "Most of the tweets are on the 24th because Dr Dipo trended that day, quite a memorable event."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kPpAciPVRDNt"
      },
      "source": [
        "\n",
        "\n",
        "*Answer: these top5 people tweeted the most, who are they?\n",
        "let us go and ask Dr Dipo* "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7j_jIgf1_d9B",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5fa3efcc-e9be-4fcf-a1a6-b1e79b76ab64"
      },
      "source": [
        "#2. Nigerian location of where most tweets came from, state of capital\n",
        "state_and_capital = ['Umuahia', 'Yola', 'Uyo', 'Awka', 'Bauchi', 'Yenagoa', 'Makurdi', 'Maiduguri', 'Calabar', 'Asaba', 'Abakaliki', 'Benin City', 'Ado - Ekiti', 'Enugu', 'Gombe', 'Owerri', 'Dutse', 'Kaduna', 'Kano', 'Katsina', 'Birnin Kebbi', 'Lokoja', 'Ilorin', 'Ikeja', 'Lafia', 'Minna', 'Abeokuta', 'Akure', 'Oshogbo', 'Ibadan', 'Jos', 'Port Harcourt', 'Sokoto', 'Jalingo', 'Damaturu', 'Gusau', 'Umuahia', 'Yola', 'Uyo', 'Awka', 'Bauchi', 'Yenagoa', 'Makurdi', 'Maiduguri', 'Calabar', 'Asaba', 'Abakaliki', 'Benin City', 'Ado - Ekiti', 'Enugu', 'Gombe', 'Owerri', 'Dutse', 'Kaduna', 'Kano', 'Katsina', 'Birnin Kebbi', 'Lokoja', 'Ilorin', 'Ikeja', 'Lafia', 'Minna', 'Abeokuta', 'Akure', 'Oshogbo', 'Ibadan', 'Jos', 'Port Harcourt', 'Sokoto', 'Jalingo', 'Damaturu', 'Gusau']\n",
        "tweet_with_location = all_tweets.dropna(subset=['location'])\n",
        "\n",
        "real_location = []\n",
        "##iterating over the locations\n",
        "for x in state_and_capital:\n",
        "  for y in tweet_with_location['location']:\n",
        "    #print(y)\n",
        "    if x in y:\n",
        "      real_location.append(x)\n",
        "  \n",
        "print(real_location)\n",
        "print(len(real_location))\n",
        "\n",
        "\n",
        "dic = dict ()\n",
        "for location in real_location:\n",
        "  dic[location] = dic.get (location, 0) + 1\n",
        "\n",
        "print(dic)"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['Yola', 'Uyo', 'Awka', 'Awka', 'Makurdi', 'Calabar', 'Calabar', 'Calabar', 'Asaba', 'Asaba', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Owerri', 'Kaduna', 'Kaduna', 'Kaduna', 'Kaduna', 'Kaduna', 'Kano', 'Katsina', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ikeja', 'Ikeja', 'Ikeja', 'Ikeja', 'Ikeja', 'Ikeja', 'Ikeja', 'Minna', 'Abeokuta', 'Abeokuta', 'Abeokuta', 'Abeokuta', 'Abeokuta', 'Abeokuta', 'Akure', 'Akure', 'Akure', 'Akure', 'Oshogbo', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Jos', 'Jos', 'Jos', 'Jos', 'Jos', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Yola', 'Uyo', 'Awka', 'Awka', 'Makurdi', 'Calabar', 'Calabar', 'Calabar', 'Asaba', 'Asaba', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Enugu', 'Owerri', 'Kaduna', 'Kaduna', 'Kaduna', 'Kaduna', 'Kaduna', 'Kano', 'Katsina', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ilorin', 'Ikeja', 'Ikeja', 'Ikeja', 'Ikeja', 'Ikeja', 'Ikeja', 'Ikeja', 'Minna', 'Abeokuta', 'Abeokuta', 'Abeokuta', 'Abeokuta', 'Abeokuta', 'Abeokuta', 'Akure', 'Akure', 'Akure', 'Akure', 'Oshogbo', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Ibadan', 'Jos', 'Jos', 'Jos', 'Jos', 'Jos', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt', 'Port Harcourt']\n",
            "198\n",
            "{'Yola': 2, 'Uyo': 2, 'Awka': 4, 'Makurdi': 2, 'Calabar': 6, 'Asaba': 4, 'Enugu': 18, 'Owerri': 2, 'Kaduna': 10, 'Kano': 2, 'Katsina': 2, 'Ilorin': 20, 'Ikeja': 14, 'Minna': 2, 'Abeokuta': 12, 'Akure': 8, 'Oshogbo': 2, 'Ibadan': 50, 'Jos': 10, 'Port Harcourt': 26}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GDnVeEK0wNPb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "072f044d-773d-4f0a-b723-be8040d242af"
      },
      "source": [
        "newl = list ()\n",
        "for k,v in dic.items () :\n",
        "    newl.append ((v,k))\n",
        "newl = sorted (newl, reverse = True)    \n",
        "print (newl)\n",
        "location= []\n",
        "location_count = []\n",
        "for v,k in sorted (newl, reverse = True):\n",
        "  print (k,v)\n",
        "  location.append(k)\n",
        "  location_count.append(v)\n",
        "\n",
        "print(location, location_count)"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[(50, 'Ibadan'), (26, 'Port Harcourt'), (20, 'Ilorin'), (18, 'Enugu'), (14, 'Ikeja'), (12, 'Abeokuta'), (10, 'Kaduna'), (10, 'Jos'), (8, 'Akure'), (6, 'Calabar'), (4, 'Awka'), (4, 'Asaba'), (2, 'Yola'), (2, 'Uyo'), (2, 'Owerri'), (2, 'Oshogbo'), (2, 'Minna'), (2, 'Makurdi'), (2, 'Katsina'), (2, 'Kano')]\n",
            "Ibadan 50\n",
            "Port Harcourt 26\n",
            "Ilorin 20\n",
            "Enugu 18\n",
            "Ikeja 14\n",
            "Abeokuta 12\n",
            "Kaduna 10\n",
            "Jos 10\n",
            "Akure 8\n",
            "Calabar 6\n",
            "Awka 4\n",
            "Asaba 4\n",
            "Yola 2\n",
            "Uyo 2\n",
            "Owerri 2\n",
            "Oshogbo 2\n",
            "Minna 2\n",
            "Makurdi 2\n",
            "Katsina 2\n",
            "Kano 2\n",
            "['Ibadan', 'Port Harcourt', 'Ilorin', 'Enugu', 'Ikeja', 'Abeokuta', 'Kaduna', 'Jos', 'Akure', 'Calabar', 'Awka', 'Asaba', 'Yola', 'Uyo', 'Owerri', 'Oshogbo', 'Minna', 'Makurdi', 'Katsina', 'Kano'] [50, 26, 20, 18, 14, 12, 10, 10, 8, 6, 4, 4, 2, 2, 2, 2, 2, 2, 2, 2]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 598
        },
        "id": "suIqjnEU2kfM",
        "outputId": "fc327862-b001-4ffe-8cf4-8eef79ffc6d0"
      },
      "source": [
        "#plotting location against location count\n",
        "plt.figure(figsize=(12, 8))\n",
        "ax = plt.bar(location, location_count, align='edge')\n",
        "plt.xlabel('Location of the tweeters in Nigeria')\n",
        "plt.ylabel('Number of tweets per location')\n",
        "plt.xticks(rotation= 60)\n",
        "\n",
        "fig.tight_layout()\n",
        "rects = ax.patches\n",
        "for rect, label in zip(rects, location_count):\n",
        "    height = rect.get_height()\n",
        "    plt.text(rect.get_x() + rect.get_width() / 2, height + 1, label,\n",
        "            ha='center', va='bottom')\n",
        "plt.title('Tweeters Location')\n",
        "plt.rcParams.update({'font.size': 14})\n",
        "plt.show()"
      ],
      "execution_count": 135,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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gLUmSJBXAYC1JkiQVwGAtSZIkFcBgLUmSJBXAYC1JkiQVwGAtSZIkFcBgLUmSJBXAYC1JkiQVwGAtSZIkFcBgLUmSJBXAYC1JkiQVwGAtSZIkFcBgLUmSJBXAYC1JkiQVwGAtSZIkFcBgLUmSJBXAYC1JkiQVwGAtSZIkFaBiwToizo+IFBHX1muLiKiNiEURsTwiZkbEPpWqUZIkScqrIsE6Ig4ETgUebdB1LvBt4AygH/AqMC0iOjRvhZIkSdKGafZgHRHbAf8P+Ddgab32AM4ELksp/TKl9BgwDOgAnNTcdUqSJEkbohIz1jcCv0gpzWjQ3hPoCkxd3ZBSWg7MAg5uvvIkSZKkDde2OQeLiFOAjwFfbqS7a+l5SYP2JcDO5axLkiRJ2lTNFqwjYk/gUuDQlNL7BZ3zVLK12nTv3r2IU0qSJEkbpTmXghwE7Ag8HhErI2Il8ClgROn1G6XjujT4XBdgcWMnTCndmFLqm1LqW1NTU666JUmSpPVqzmA9BdgX6FPvMRe4tfT6GbIAfdTqD0TE1sBhwJxmrFOSJEnaYM22FCSl9BbwVv22iHgHeLO0AwgRMR64ICKeIgvaFwJ1wOTmqlOSJEnaGM168WIOVwDtgOuAjsCDwMCU0rKKViVJkiStR0WDdUqpf4P3CagtPSRJkqSqUbFbmkuSJEkticFakiRJKoDBWpIkSSpA7jXWEXECcATQmQaBPKV0bMF1SZIkSVUlV7COiB8AZwIzgEVAKmdRkiRJUrXJO2P9VWBoSukX5SxGkiRJqlZ511h/BJhXzkIkSZKkapY3WN8IfLmchUiSJEnVLO9SkO2BkyLiKOBR4P36nSmlbxVdmCRJklRN8gbrXvxjKcheDfq8kFGSJEmtXq5gnVIaUO5CJEmSpGqWex9rgIjYGvgY2Sz1cymlFWWpSpIkSaoyuS5ejIgtSntZLwX+DPwFWBoRV0TEFuUsUJIkSaoGeWesLweGAt8AZpfaDgPGkYXzc4ovTZIkSaoeeYP1ScC/pZR+Xa/tuYh4DfhvDNaSJElq5fLuY70d8Fwj7c+RbcUnSZIktWp5g/Wfgcb2qh6Fd2SUJEmSci8FORf4dUQcCTxQajsQ2Ak4phyFSZIkSdUk14x1SmkWsAfwC6B96XE7sGdKaXZTn5UkSZJag9z7WKeUFgFjyliLJEmSVLXWGawjYn9gXkppVen1OqWUHim8MkmSJKmKNDVjPRfoCrxaep2AaOS4BLQpvjRJkiSpejQVrHsCr9V7LUmSJGkd1hmsU0ov1n8LvJRSSg2Pi4ju5ShMkiRJqiZ597FeANQ0bIyIHUp9kiRJUquWN1gH2ax1Q+2BFcWVI0mSJFWnJrfbi4gfl14mYFxEvFuvuw3wSbzzoiRJkrTefaz3LT0HsDfwXr2+94BHgCvLUJckSZJUVZoM1imlAQAR8T/AqJTS281SlSRJklRlct15MaX0tXIXIkmSJFWz3Lc0j4gBwFCgO7Bl/b6U0qcLrkuSJEmqKrl2BYmI4cBvgA5Af7Ibx3QE9geeKFNtkiRJUtXIu93eOcDpKaWhwPvA+Sml/YCfAXXlKk6SJEmqFnmD9W7A70qv/062fzXAtcDwgmuSJEmSqk7eYP0G2TIQgL8CvUuvdwDaFV2UJEmSVG3yXrx4HzAQ+Avwc+DHEXEUcAQwrUy1SZIkSVUjb7A+Hdi69HocsBI4hCxkX1KGuiRJkqSqkncf6zfrvV4FXF62iiRJkqQqlHe7vS9GxGcbaT82Io4vvixJkiSpuuS9eLEWWNFI+7ulPkmSJKlV25Dt9p5upH1+qU+SJElq1fIG66XA7o207wEsK64cSZIkqTrlDdZ3AD+KiD1WN0TEnsAPgSnlKEySJEmqJnmD9XnA34AnIuKliHgJeBx4G/hOuYqTJEmSqkXe7fbeBg4p3RSmT6n5T8DvU0qpXMVJkiRJ1SLvDWIASClNwzstSpIkSR+SdykIETE4ImZFxOsR8VpE3BsRg8pZnCRJklQt8t4g5t+BXwHPka23Hg0sAH4VEf9WvvIkSZKk6pB3Kch5wNkppWvrtf0kIh4mC9k/LbwySZIkqYrkXQrSHfhtI+2/AXYtrhxJkiSpOuUN1guBoxppHwi8WFw5kiRJUnXKuxTkSuCaiNgfmFNqOwT4CnBGOQqTJEmSqknefaxviIhXgW8DXyg1Pwl8KaV0R7mKkyRJkqpF7n2sU0q/ItsZRJIkSVIDufexliRJkrRu65yxjohlQK7blaeUti2sIkmSJKkKNbUU5PRmq0KSJEmqcusM1imlic1ZiCRJklTNXGMtSZIkFcBgLUmSJBXAYC1JkiQVwGAtSZIkFWC9wToitoiIByNiz+YoSJIkSapG6w3WKaX3gZ7k3NNakiRJao3yLgWZCJxSzkIkSZKkatbUDWLq2wY4OSKOAh4G3qnfmVL6VtGFSZIkSdUkb7DeG3ik9Hq3Bn0uEZEkSVKrlytYp5QGlLsQSZIkqZpt0HZ7EbFjRBwQEVuVqyBJkiSpGuUK1hHRISJuB14F5gA7l9r/KyJqy1eeJEmSVB3yzlhfDuwE7A8sr9f+f8Dniy5KkiRJqjZ5L148Fvh8SmleRNS/WPFJPnwxoyRJktTq5J2x7gi80Uh7B+CDPCeIiJER8WhEvF16/CEiBtfrj4iojYhFEbE8ImZGxD4565MkSZIqKm+wfohs1nq11bPWp5Gtuc7jZeA8suUkfYHpwJSI+Hip/1zg28AZQD+y9dzTIqJDzvNLkiRJFZN3KcgFwD2lGeS2wNml158EDs9zgpTSHQ2axkTEN4GDIuIvwJnAZSmlXwJExDCycH0ScEPOOiVJkqSKyDVjnVKaAxwMbAk8BxwBLAIOSik90tRnGxMRbSLiRKA92Yx3T6ArMLXemMuBWaVxJUmSpM1a3hlrUkp/AYZtymARsS/wB2BroI7sgsi/RMTq8LykwUeWUNraT5IkSdqc5Q7WEbE12bKMXqWmJ4BbSjPLeT0N9AG2A44HJkZE/w34fMOaTgVOBejevfvGnkaSJEnaZHlvELM/2RKQq8jWVX8SuBJ4vtSXS0rpvZTS/JTSwyml84F5wFnA4tIhXRp8pEu9vsbOd2NKqW9KqW9NTU3eMiRJkqTC5d0V5EbgfmCXlNLhKaXDgX8iWwN94yaOvxWwgCxAH7W6ozRDfhj5dx2RJEmSKibvUpB9gK+mlN5Z3ZBSeicivgvMzXOCiLgMuBt4iWz/65OA/sDglFKKiPHABRHxFPAMcCHZOuzJOWuUJEmSKiZvsH6K7JbmTzRo70YWgvPoCvys9Pw34FHgmJTSPaX+K4B2wHVkN6R5EBiYUlqW8/ySJElSxeQN1hcCPy7NUD9Qajuw1D46IjqtPjCl9GZjJ0gpDW9qgJRSAmpLD0mSJKmq5A3Wd5WeJ/OPuy5G6fmOeu8T0KaY0iRJkqTqkTdYDyhrFZIkSVKVyxWsU0r3lrsQSZIkqZrl3W5PkiRJUhMM1pIkSVIBDNYtyLhx4+jXrx/bbrstNTU1DBkyhMcee+xDxz3zzDN84QtfYPvtt+ejH/0o+++/P08++WQFKpYkSWo5DNYtyMyZMxkxYgRz5sxh+vTptG3bliOPPJI33/zHDogLFizgkEMOoWfPnkyfPp3HHnuMSy65hPbt21ewckmSpOqXd1eQtUREO+AQ4NmU0ovFlqSNdc8996z1ftKkSWy33Xbcf//9DBkyBIAxY8YwcOBArrrqqjXH7bbbbs1apyRJUkuUa8Y6IiZExIjS6y2BPwJTgacj4pgy1qdNsGzZMlatWkXHjh0BWLVqFXfddRe9evXi6KOPpqamhn79+nHbbbdVuFJJkqTql3cpyGf4xx0XjwU6kN2avBbvlLjZGjVqFH369OGggw4C4NVXX6Wuro5LL72UgQMHMm3aNIYOHcrJJ5/M3XffXeFqJUmSqlvepSAdgVdLr48GfplSejUibgXGlKUybZKzzz6b2bNnM3v2bNq0yW6GuWrVKgA++9nPcvbZZwPQp08f5s6dy7XXXsvgwYMrVq8kSVK1yztjvRjoHRFtyGavf1dqbw+8X47CtPHOOussbrnlFqZPn77W+ukdd9yRtm3b0qtXr7WO33vvvVm4cGFzlylJktSi5J2x/ilwG7AI+AD4fan9AOCpMtSljTRq1Chuu+02ZsyYwV577bVW35Zbbkm/fv14+umn12p/5pln2HXXXZuzTEmSpBYn7y3NvxsRjwPdgdtTSu+VulYCl5erOG2YkSNHMmnSJKZMmULHjh1ZvHgxAO3bt1+znd65557Ll770JQ477DA+/elPM2PGDG699VamTJlSydIlSZKqXqSU1n9QxOHAnJTSygbtbYGDU0qzylRfbn379k1z585t9nF7jC7/RX8vXJZv7XNENNo+duxYamtr17yfMGECl156KS+99BK77747559/PkOHDi2iVEmSpBYtIh5OKfVtrC/vUpAZQDf+cQHjatuV+tpsfHkqSp7/SAIYPnw4w4cPL28xkiRJrUzeixcDaCy17QC8U1w5kiRJUnVqcsY6Iu4svUzAzyLi7/W62wC9gTllqk2SJEmqGutbCvJG6TmApcDyen3vAbOBm8pQlyRJklRVmgzWKaWvAUTEC8CVKSWXfUiSJEmNyLXGOqX0HymldyKib0ScEBHbAETENqWdQSRJkqRWLVcojoguwB3AJ8nWW+8OPA/8EFgBjCpXgZIkSVI1yLsryI+AJWS7gLxbr/12YGDRRUmSJEnVJu8yjiOAI1JKSxvchOQ5srsxSpIkSa1a3hnrdmS7gDRUQ7YURJIkSWrV8gbrWcDweu9TRLQBzgN+X3RRkiRJUrXJuxTkXODeiOgHbAVcBexDdkvzQ8pUmyRJklQ1cgXrlNITEbEvMAL4O7A12YWL16WUXiljfWpCj9F3l32MFy4bXPYxJEmSWoLce1CnlBYDF5exFkmSJKlq5V1jTUTsGxHXRsSvI6Jbqe1zEbFf+cqTJEmSqkOuYB0RA4GHgJ3Jtt5rV+r6Z2BseUqTJEmSqkfeGevvAWenlD7P2tvuzSS7G6MkSZLUquUN1r2BXzfS/ibQqbhyJEmSpOqUN1i/SbYMpKH9gZeLK0eSJEmqTnmD9WTgBxGxC5CAthHxKeBK4OZyFSdJkiRVi7zB+kJgAfAi0B54ApgOzAa+X57SJEmSpOqR9wYx7wMnR8TFwH5kgfxPKaVny1mcJEmSVC1yBeuI2CmltCil9BzwXJlrkiRJkqpO3jsvvhwR88m215sJzEwpLSpXUZIkSVK1ybvGenfgcrIbw1xGFrSfiYgbI2Jo2aqTJEmSqkSuYJ1Sei6l9JOU0ldSSt2BXmQXLg4HflbG+iRJkqSqkHeN9UeAvsAAoD9wCPAG8P/IloZIkiRJrVreNdZvASuA/wNuAb6RUnqxbFVJkiRJVSZvsH6UbMb6AOBd4J2IqEspvVG2yiRJkqQqkneN9aFAR+BbwFLgTOCliHg0Iq4uY32SJElSVcg7Y01KaTnw+4h4jOzOi4OBLwH7AKPKU54kSZJUHfJevPglsosWBwB7AIuBWcAZePGiJEmSlHvGejxwb+l5Zkrp6fKVJEmSJFWfXME6pbRTuQuRJEmSqlmuixcj4oOI6NxI+w4R8UHxZUmSJEnVJe8tzWMd7VsB7xVUiyRJklS1mlwKEhFnl14m4BsRUVevuw1wGPBUmWqTJEmSqsb61lifUXoO4N+B+ss+3gNeAL5RfFmSJElSdWkyWKeUegJExAzgCymlpc1SlSRJklRl8u4KMqDchUiSJEnVLO/Fi1KTxo0bR79+/dh2222pqalhyJAhPPbYY2sdk1KitraWnXbaiXbt2tG/f38ef/zxClUsSZJULIO1CjFz5kxGjBjBnDlzmD59Om3btuXII4/kzTffXHPMFVdcwVVXXcU111zDQw89ROfOnTnqqKNYtmxZBSuXJEkqRt47L0pNuueee9Z6P2nSJLbbbjvuv/9+hgwZQkqJ8ePHM3r0aI477jgAJk6cSOfOnZk8eTKnnXZaJcqWJEkqzDpnrCPipxHRofT68IgwhCu3ZcuWsWrVKjp27AjAggULWLx4MQMHDlxzTLt27Tj88MOZM2dOpcqUJEkqTHRKOJEAACAASURBVFNLQb4MbFN6PQPoVP5y1FKMGjWKPn36cNBBBwGwePFiALp06bLWcV26dFnTJ0mSVM2amoV+ATgjIqaS7WN9UEQ0ut1eSmlWGWpTlTr77LOZPXs2s2fPpk2bNpUuR5IkqVk0Fay/A/w3cD7ZnRd/tY7jEtldGCXOOussbr31VmbMmMFuu+22pr1r164ALFmyhO7du69pX7JkyZo+SZKkarbOpSAppTtSSjVkS0AC2AeoaeTRuRnqVBUYNWoUt9xyC9OnT2evvfZaq69nz5507dqVadOmrWlbsWIF9913HwcffHBzlypJklS49V6QmFJ6KyIGAM+mlFY2Q02qQiNHjmTSpElMmTKFjh07rlk33b59e9q3b09EcOaZZ3LppZey1157sccee3DJJZfQvn17TjrppApXL0mStOny3nnx3ojYKiK+CvQiW/7xBDA5pfT3chao6nD99dcDcMQRR6zVPnbsWGprawE499xzWb58OSNHjmTp0qUccMABTJ06lQ4dOjR3uZIkSYXLFawjohfwG2A74C+l5lOA2og4OqX0ZJnqU5VIKa33mIigtrZ2TdCWJElqSfLeefFqYB7QPaV0WErpMKA78GdgfLmKkyRJkqpF3pu+HAL0Sym9vbohpfR2RIwBHihLZZIkSVIVyTtjvQLYvpH27Up9kiRJUquWN1jfBdwUEYdERJvS41DgBuDO8pUnSZIkVYe8wXoU8CxwH9kM9QrgXuAZ4MzylCZJkiRVj7zb7b0FfDYiPgbsXWp+MqU0v2yVSZIkSVUk74w1ACml+Smlu0qPDQrVEXF+RDwUEW9HxGsRcVdE9G5wTEREbUQsiojlETEzIvbZkHHU+syaNYtjjz2WnXfemYhgwoQJa/XX1dVxxhlnsMsuu9CuXTv23HNPfvSjH1WmWEmS1GJtULDeRP2B64GDgU8DK4HfRUSnesecC3wbOAPoB7wKTIsI7yCidaqrq6N3795cffXVtGvX7kP9Z599NnfffTeTJk3iySefZMyYMYwePZpJkyZVoFpJktRS5d1ub5OllD5T/31EfAX4G9lWfndFRJCt174spfTL0jHDyML1SWQXSkofMmjQIAYNGgTA8OHDP9Q/Z84cvvKVrzBgwAAAevTowU9+8hMefPBBvvKVrzRnqZIkqQVrzhnrhjqUxl9aet8T6ApMXX1ASmk5MItsllvaKIceeih33XUXL730EpAF7Xnz5nH00UdXuDJJktSSrHfGOiLaAqcCU1JKiwoce/XdHP9Qet+19LykwXFLgJ3XUduppdro3r17gaVpfXqMvrus53/hssGFnevHP/4xp512Gt27d6dt2+wf+WuuuYZ//dd/LWwMSZKk9c5Yp5RWAj8Atihq0Ij4IXAocFxK6YONPU9K6caUUt+UUt+ampqiylMLc8011zBnzhzuvPNOHn74YX70ox9xzjnn8Nvf/rbSpUmSpBYk7xrrB4D9gRc3dcCI+BFwIjAgpfR8va7FpecuwMJ67V3q9UkbZPny5Zx//vncfvvtDBkyBICPf/zjzJs3jyuvvNLlIJIkqTB5g/VNwFURsSvwMPBO/c6U0iN5ThIRVwMnkIXqpxp0LyAL0EcBD5WO3xo4DPhOzjqltbz//vu8//77tGnTZq32Nm3asGrVqgpVJUmSWqK8wXpy6fmHjfQloE0j7WuJiOuArwCfA5ZGxOo11XUppbqUUoqI8cAFEfEU2V0dLwTq6o0vfUhdXR3z52fbqq9atYqFCxcyb948OnXqRPfu3fnUpz7F6NGjad++Pbvuuiv33nsvN998M1dccUWFK5ckSS1J3mDds4CxRpSef9+g/T+A2tLrK4B2wHVAR+BBYGBKaVkB46uFmjt37pqt9ADGjh3L2LFjGTZsGBMmTODWW2/l/PPP5+STT+bNN99k11135Xvf+x6nn356BauWJEktTd5bmm/y2uqUUuQ4JpGF7NpNHU+tR//+/cn+0Wlc165d+Z//+Z9mrEiSJLVGufexjohjIuL/IuKJiPinUtu/R8QR5StPkiRJqg65gnVEnAz8HHiWbFnI6q332pDdhlySJElq1fLOWJ8LnJJSOgtYWa/9AaBP4VVJkiRJVSZvsN6df9whsb46YNviypEkSZKqU95gvQjYo5H2w4HniitHkiRJqk55g/WNwI8j4pDS+3+KiGFk2+P9Z1kqkyRJkqpI3u32roiI7YBpwNbADODvwJUppevKWJ8kSZJUFfLeIIaU0piI+D7Qi2ym+4mUUl3ZKpMkSZKqSO5gXZKAFaXXHxRciyRJklS18u5jvVVEjAfeBP4MPAq8GRFXR8TW5SxQkiRJqgZ5Z6z/ExgI/Dv/2HbvIGAc0AH4t+JLkz6sx+i7yz7GC5cNLvsYkiSp5ckbrL8IfCGlNK1e2/MR8SrwSwzWkiRJauXybrf3DvDXRtr/CiwvrhxJkiSpOuUN1tcAYyOi3eqG0uuLSn2SJElSq7bOpSARcWeDpv7AXyPi0dL7fUuf36Y8pUmSJEnVo6k11m80eP/LBu8XFFyLJEmSVLXWGaxTSl9rzkIkSZKkapZ3jbUkSZKkJuTabi8iOgK1wACgMw0CeUqpc+GVSZIkSVUk7z7WNwP7ABOBJWS3NpckSZJUkjdY9wc+lVJ6pIy1SJIkSVUr7xrr5zbgWEmSJKnVyRuWRwHjIuITEdGmnAVJ1WTWrFkce+yx7LzzzkQEEyZMWOexp512GhHBlVde2XwFSpKkZpM3WM8H2gGPAO9FxAf1H+UrT9q81dXV0bt3b66++mratWu3zuN+8Ytf8Mc//pGddtqpGauTJEnNKe8a61uA7YBv4cWL0hqDBg1i0KBBAAwfPrzRY1588UVGjRrF7373O4455phmrE6SJDWnvMG6L/DJlNJj5SxGamlWrlzJ0KFDufDCC9l7770rXY4kSSqjvEtBngC2LWchUks0duxYdtxxR775zW9WuhRJklRmeWesLwR+GBEXAn8B3q/fmVJ6s+jCpGo3c+ZMJkyYwLx58ypdiiRJagZ5Z6x/DXwSmAosAl4rPV4vPUtqYObMmbzyyit069aNtm3b0rZtW1588UXOO+88dtlll0qXJ0mSCpZ3xnpAWauQWqARI0Zw/PHHr9X2mc98hqFDh3LKKadUqCpJklQuuYJ1SunechciVaO6ujrmz58PwKpVq1i4cCHz5s2jU6dOdO/enc6dO691/BZbbEHXrl3Zc889K1GuJEkqo1zBOiL2b6rfW52rtZo7dy4DBvzj/9AZO3YsY8eOZdiwYU3eLEaSJLU8eZeCzCXbuzrqtdXfy9q7MapV6t+/Pynl39b9hRdeKF8xkiSpovIG654N3m8B7AeMAc4vtCJJkiSpCuVdY/1iI83zI+JvwFjgN4VWJUmSJFWZvNvtrcsCoE8RhUiSJEnVLO/Fi50aNgHdgFrg6YJrkiRJkqpO3jXWr7P2xYqQheuXgBMKrUiSJEmqQnmXggwAPl3v0R/oBfxzSumB8pQmqSmzZs3i2GOPZeeddyYi1tre7/333+e8887j4x//ONtssw3dunXjpJNOYuHChZUrWJKkFi5XsE4p3dvgcV9K6amU0spyFyipcXV1dfTu3Zurr76adu3ardX37rvv8sgjjzBmzBgeeeQR7rjjDl566SWOPvpoVq70f7aSJJVDk0tBGllb3aiU0pvFlCMpr0GDBjFo0CAAhg8fvlbfdtttx7Rp09Zqu+GGG9hnn3148skn2XfffZurTEmSWo31rbFubG11QynHeSRV2Ntvvw1Ax44dK1yJJEkt0/oC8YAm+o4GRgH+/8rSZu69997j29/+NkOGDGGXXXapdDmSJLVITQbrlNK9DdsiYj/gB8BhwA3A98pTmrR56TH67rKP8cJlgws/58qVK/nyl7/MW2+9xZ133ln4+SVJUib3DWIiomdETAb+CLwB9EopfSul9FrZqpO0SVauXMnQoUN59NFH+f3vf88OO+xQ6ZIkSWqx1husI2KHiLgaeAroChycUjohpfRc2auTtNHef/99TjjhBB599FFmzJhB165dK12SJEkt2vp2BRkDfAd4AfhsSum3zVGUpPWrq6tj/vz5AKxatYqFCxcyb948OnXqxE477cQXv/hFHnroIe666y4igsWLFwPZjiENt+eTJEmbbn0z1t8DtgBeBkZExJ2NPcpfpqSG5s6dy3777cd+++3H8uXLGTt2LPvttx8XX3wxL7/8MnfccQeLFi3iX/7lX+jWrduax2233Vbp0iVJapHWtyvIzax/uz1JFdC/f39SWvf/PJvqkyRJxVvfriDDm6kOSZIkqarl3hVEkiRJ0roZrCVJkqQCGKwlSZKkAhisJUmSpAIYrCVJkqQCGKwlbbBZs2Zx7LHHsvPOOxMRTJgwYa3+lBK1tbXstNNOtGvXjv79+/P4449X/diSJDXFYC1pg9XV1dG7d2+uvvrqRu/ieMUVV3DVVVdxzTXX8NBDD9G5c2eOOuooli1bVtVjS5LUFIO1pA02aNAgLr30Uo4//ng+8pG1/zWSUmL8+PGMHj2a4447jt69ezNx4kSWLVvG5MmTq3psSZKaYrCWVKgFCxawePFiBg4cuKatXbt2HH744cyZM6fFji1JksFaUqEWL14MQJcuXdZq79Kly5q+lji2JElN3tJc0uahx+i7yz7GC5cNLvsYkiS1ZM5YSypU165dAViyZMla7UuWLFnT1xLHliTJYC2pUD179qRr165MmzZtTduKFSu47777OPjgg1vs2JIkuRRE0garq6tj/vz5AKxatYqFCxcyb948OnXqRPfu3TnzzDO59NJL2Wuvvdhjjz245JJLaN++PSeddFJVjy1JUlMM1pI22Ny5cxkwYMCa92PHjmXs2LEMGzaMCRMmcO6557J8+XJGjhzJ0qVLOeCAA5g6dSodOnSo6rElSWqKwVrSBuvfvz8ppXX2RwS1tbXU1ta2qLElSWqKa6wlSZKkAhisJUmSpAIYrCVJkqQCGKwlSZKkAhisJUmSpAIYrCVJkqQCNGuwjojDI+LOiPhrRKSIGN6gPyKiNiIWRcTyiJgZEfs0Z42SlMcHH3zARRddRM+ePdl6663p2bMnF154IStXrqx0aZKkCmnufazbA48BN5ceDZ0LfBsYDjwNXAxMi4g9U0rLmqtISVqfyy+/nOuuu46JEyey77778uijjzJs2DC22morLrrookqXJ0mqgGYN1imlXwO/BoiICfX7IiKAM4HLUkq/LLUNA14FTgJuaM5aJakpc+bMYciQIQwZMgSAHj16cOyxx/Lggw9WuDJJUqVsTmusewJdgamrG1JKy4FZwMGVKkqSGnPooYcyY8YMnnrqKQCeeOIJpk+fzqBBgypcmSSpUjanW5p3LT0vadC+BNi5sQ9ExKnAqQDdu3cvX2VSK9Zj9N1lPf8Llw2uyLhNjZ3Heeedx7Jly+jVqxdt2rRh5cqVjBkzhhEjRhRYoSSpmmxOM9YbLKV0Y0qpb0qpb01NTaXLkdSK3Hbbbdx8881MnjyZRx55hJtvvpnrr7+en/zkJ5UuTZJUIZvTjPXi0nMXYGG99i71+iRps/Cd73yHc845hxNPPBGAfffdlxdffJFx48bx9a9/vcLVSZIqYXOasV5AFqCPWt0QEVsDhwFzKlWUJDXm3XffpU2bNmu1tWnThlWrVlWoIklSpTXrjHVEtAc+Vnr7EaB7RPQB3kwpLYyI8cAFEfEU8AxwIVAHTG7OOiVpfYYMGcJll11Gz5492WefffjTn/7ED3/4Q7761a9WujRJUoU091KQvsCMeu//o/SYSLZ39RVAO+A6oCPwIDDQPawlbW6uueYaLrroIkaMGMGrr75Kt27dOOWUU7j44osrXZokqUKaex/rmUA00Z+A2tJDkjZbHTp0YPz48YwfP77SpUiSNhOb0xprSZIkqWoZrCVJkqQCGKwlSZKkAhisJUmSpAIYrCVJkqQCGKwlqQq98sorDBs2jJqaGrbeemt69erFvffeW+myJKlV25xuaS5JyuGtt97ikEMO4dBDD+Xuu++mpqaG559/ns6dO1e6NElq1QzWklRlrrjiCrp168bNN9+8pq1nz54VrEiSBC4FkaSqM2XKFA444ABOOOEEOnfuTJ8+fbj22mvJ7rElSaoUg7UkVZnnn3+e66+/nt1224177rmHUaNGMXr0aK677rpKlyZJrZpLQSSpgR6j7y77GC9cNnijP7tq1Sr69u3LuHHjANhvv/149tlnue666zj99NOLKlGStIGcsZakKtOtWzd69eq1Vtvee+/NwoULK1SRJAkM1pJUdQ455BCefvrptdqeeeYZdt111wpVJEkCg7UkVZ2zzjqLBx54gO9///vMnz+f22+/nR//+MeMHDmy0qVJUqtmsJakKtOvXz+mTJnCz3/+c3r37s2YMWP43ve+x4gRIypdmiS1al68KElVaPDgwQwevPEXQEqSiueMtSRJklQAg7UkSZJUAIO1JEmSVACDtSRJklQAg7UkSZJUAIO1JEmSVACDtSRpo4wbN46I4PTTT29VY0vSuhisJUkb7IEHHuDGG2/k4x//eKsaW5KaYrCWJG2Qv/3tb5x88sn89Kc/pWPHjq1mbElaH4O1JGmDnHrqqRx//PEMGDCgVY0tSevjLc0laTPSY/TdZR/jhcs2/lboN910E/Pnz+dnP/tZgRVt/mNLUh4Ga0lSLk8//TQXXHABs2fPZosttmg1Y0tSXgZrSVIuf/jDH3j99dfZZ5991rR98MEHzJo1i//6r//inXfeYauttmpxY0tSXgZrSVIun/vc5+jbt+9abV/72tfYfffdueCCC9hyyy1b5NiSlJfBWpKUy/bbb8/222+/Vts222xDp06d6N27d4sdW5LyclcQSZIkqQDOWEuSNtrMmTNb5diS1BhnrCVJkqQCGKwlSZKkAhisJUmSpAIYrCVJkqQCGKwlSZKkAhisJUlqwrhx4+jXrx/bbrstNTU1DBkyhMcee8yxW9i4jt26futyMVhLktSEmTNnMmLECObMmcP06dNp27YtRx55JG+++aZjt6BxHbt1/dbl4j7WkiQ14Z577lnr/aRJk9huu+24//77GTJkiGO3kHEdu/nHruTfXC7OWEuStAGWLVvGqlWr6Nixo2O34HEdu3X91kUxWEuStAFGjRpFnz59OOiggxy7BY/r2K3rty6KS0EkSQD0GH13Wc//wmWDKzJuU2NvqLPPPpvZs2cze/Zs2rRpU8g5HXvzG9exW9dvXSSDtSRJOZx11lnceuutzJgxg912282xW+i4jt26fuuiGawlSVqPUaNGcdtttzFjxgz22msvx26h4zp26/qty8FgLUlSE0aOHMmkSZOYMmUKHTt2ZPHixQC0b9+e9u3bO3YLGdexW9dvXS5evChJUhOuv/56li1bxhFHHEG3bt3WPK688krHbkHjOnbr+q3LxRlrSZKakFJy7FYwrmO3nnHLyRlrSZIkqQAGa0mSJKkABmtJkiSpAAZrSZIkqQAGa0mSJKkABmtJkiSpAAZrSZIkqQAGa0mSJKkABmtJkiSpAAZrSZIkqQDe0lyS1Gr1GH132cd44bLBrW7s1vg3t9axN8e/uZKcsZYkSZIKYLCWJEmSCmCwliRJkgpgsJYkSZIKYLCWJEmSCmCwliRJkgpgsJYkSZIKYLCWJEmSCmCwliRJkgpgsJYkSZIKYLCWJEmSCmCwliRJkgqwWQbriBgREQsiYkVEPBwRh1W6JkmSJKkpm12wjogTgKuBS4H9gDnAbyKie0ULkyRJkpqw2QVr4GxgQkrpppTSkymlM4BXgG9WuC5JkiRpnTarYB0RWwL/Akxt0DUVOLj5K5IkSZLyiZRSpWtYIyJ2Av4KfCqlNKte+8XAySmlPRscfypwauntnsDTzVVrPTsCr1dg3NY6dmv8m1vr2K3xb26tY7fGv7m1jt0a/+bWOnYl/+Zy2zWlVNNYR9vmrqRIKaUbgRsrWUNEzE0p9XXslj2uY/tbO3bLG9ex/a0du+WNW2mb1VIQsv+y+QDo0qD9/7d33lF2FEcX/5UyEiIjISQkIXLOCBNFzsE2mJxMMCYnkzOYnGz4iCYbk3MwmCRyEIgsogBhEGCRQQgQbH9/3Bpe72NX2t0382ZX6nvOnJ03MztdHaa7uvpWdV/g4/qLk5CQkJCQkJCQkNAytCvFOoTwI/AcsGbVrTVRdJCEhISEhISEhISEdon2SAU5E7jKzJ4BHgd2A2YHLihVquZRJhVlakx7aszz1Jr21JjnqTXtqTHPU2vaU2Oep9a0S6XqloV25byYwcx2Bw4C+gGvAPvFzowJCQkJCQkJCQkJ7Q3tUrFOSEhISEhISEhI6GhoVxzrhISEhISEhISEhI6KpFhPxTCzTvHfhISEhISEhISEtiMpVFM3zP9eaWablypJQgJgZhad9y9TlvaOuKwSEmqBmU1XtgwJCVMKkmI9lcLMtgWWN7O1gC1QBJY0WE9B6KB1ma2i7A78w8xW9N/tLi9lyGRmXfzv0sD6ZjZNndItpfyzdOuVfpntrN55rcITvpPxr+QpG1G5FKqvlNjGB5jZllVGhXZR9gltQ1Ks64j2QrnwwXkP4GHgWuCqEMIHACEHb9Z657Osci15IKyWpVN03sXM+uVRl22UpU3lYWadQgg/m9lMwEnAP4GX/fZgM5vdzHrmJWdbkclQRvmGEH7y0zuARUIIE+qUbiipnZuZWVbWRX/rcZ3WO79Z2vUuazPrDOwPXOq/DzazacrqP5pAL4AQQkORiZSY38OAebzeZ4hlKWnyXlia1e9uLzpR3khRQXJG1SCwCNAfmBBCeLipZ8qEmf0d+BPwFXAGcAMwJoTws99fHng3hPBRM//f2RWh6VA+5w4h3FEf6ZuUZ2/guhDCJyWlX1q9Zmmb2Z7AusAySCk9DXg8hPBNzul1CiE0mNkswLLAF8CPIYTncnj3JUC/EMJ63rZWB84HpgMuCiHsW2sarZClSwjhJzNbFPg9KtvXgNeBM3xTq3rJkn1vMwFnAYeGEMbmnEZWr91QG5of+AF4LITwXvxMnulG6Wd57AdsAywNfA/cEkK41Z8xyFcRMrM5gbWAT4CxwCshhO+y9Ir4rqO8zgCsCiwKzARcEkJ4yZ8prKybkWkhtEnbp8CRIYTL/Hrd+rbom5sP2Am1w77AZcCVIYRP8iwXMxsALI/6sEeAiXUu85mA70II35vZpajsrwwhvFIvGZqRK7c6j/oVAzoD/UMIY4pIqz0gKdY5I+os90JWgOmA94EPgFNDCI/6c3XtMCP5MgWsK3AfGqAXAY4GRgEnIkv2t8B/gT+FEK6fzDtvR4PC9MCPwNEhhAvi9IrKTyTDssBTwBvA8WggztWaF9Vtf2A9YD7gc+CeEMJIf6buHUQk1wrATcAlwM3Ak0AA7gROBl4OIXyfY3pze1oLocFgHGo714QQXvVnW1Uebg2+EnghhHCCmR0OrAQ8BowG/g6sEkIYVWs+WiBLPEl+C3gUeBUN9h8AG9RTsXY5uqE6nhMp1nfkrGRk/cN5wG9Q/zXOb98EnB9C+DZ+No90m5DjQdR23wTmBlZASs+RIYQReaQfKXCronY1DdAT1e09wG15TBRbIMctwDzAT8AEYChwBbBLtEJRZPrZ9zwtsDjq0/6IVjVfAfYNIfxCFayjgv0S8BGaxP4A7IiU3y1rrZeo7jdE40UPYCDwLNqM7u4Qwpe1pNFCOQYEXy02s5mB84C5UL7vBm7NDFt56wxRvfdCE9hFgQ+BV0MIb/gzuda3mR0K/A59a72Ak0IIFxWRVqkIIaQj5wOYFhgPbI0GhF3R0u3b6KMdWKJs2WTqZODfQHf/PSsaOH9CSszTwFMteN+uwBhgbc/ryUgpfxFYtc55mw1ZNn8C7kdWiM4FpPO4l9G/gRfQ4HMqMKDkdvcUcIqfb4ImdFt4/YwBzgWmzzG9RxCVqDNSNn9CiucjaCWkfxvf+xc0gN6FOvptgO6oM34BWKNO5Zl9K0cDI6PrXwEb+flvgDWKaGfNyDQ38Aww0fuUftXy1vDuzv53ZeAbYFn//ZqX+1tosN+soLxl6W+JFIsZ/Pe7wDXACOAz4GKgT47pvgGc7Oe7IiVuLFKy9gQWKCCvnfzv7z1Pc3n7ntmvvQ3cCExbhzaVtfNrgbP9W+uCFPzbgAbgKmCOOsqyq9d79+heH2QweA0YVGsafv4BomJ0Ao7x7+pnZIxYGehZYF63AB5CekLP6Pq6wK3A88jI8DtgmgLluMbTGo3GsnuAvYBZc3p/9l3vjsahY4EdkFFvPDJY9MsjrfZylC7AlHREncJQ4EKgW3RvEeAQZNEbhw/MJcnXEy2r/c5/d42eWQ642mUd1Mx7OkXnWwG7R7+7otnvDVQU3B51yFss09Jezj8gC/x8Obw/6xz28w6ol//+AinY7yKFe/+43utYt4t6Wc/jv18D9vfzI4CPgadzTG814D1gRv89EjgKWMfb9/uIttGWd/f3we5yYP3o+s7AB3Uu1y7Av4Aj/Pc1yJoFGoz3RZPlwhWgSKbZgO2Q8vU5sGfO778LWZIANkPKx9xo0vw9UjrXzzPNqvTvBg7y84OAl7wefgd8iQbn9Wp4f6xYbY0sdADdPK+bAgv4N/MpPlktKK8XAJc2cX0zT3uJgttSpuDPjCYSy1Td740U/deREtSrSHmidI8Dbo5+d/W/iyO6TpvbH5VxcD/gWT+fHk1w1vY+bCKaUBxYYB639D77KeAfwLpxvQC7oXHsMbQymNsEj8p49lvvrxfx3x8g5XoMcJ3LWPN4hiKQjQF2jusUrUaOBI6qR7uq11G6AFPaAQz2geE5oHfVva5IITkTmLlEGbcHhgN7R9e60Vg57dTM/8aD0iFotvmP6vtomWcz4O8F5SHrGGaMZY7S7w7c4p3jhzl1Dl2RhnAlkAAAIABJREFU1Wxb/32a57+TDwTfIIV20RLqdHpkEejjg8OLwFx+bwU0wchtguNt6ILofBQwi//+F7J0rdKC98TtqStSoJr6bjbyjjkr+y51KNNM6TgO+BswB/A1sGT0zO3A30qo705o6foktEL0PKKm1PremdGqz+b+eyTwFz+fF3iQnBX5qvS7IYVne6/3kfhg7G37WnJQ6tEqi6EJylF+7WC02pJNmm9AS/OLFZjfoxDlbtqq69OiVcMd6tSeNvPvtsnVIDTZ/U09ZPH0/ogMM4tG17K+fThuNKix/g8F9vHfZyIrtfk3cKfXzfwF53M6l+N+NLYcH7c3oB+a0D4PzFZA+o8gShlodeYNYAbgdO/rRgHL5ZDOAM/fr/ooL/vnyHE1teyjdAGmtAMt74zwRnktsFATzxRuwZ2EfH1dvm+QFWJtqpSbFr6nK6I/vItm+utF9yaroOeYn8eQRWvx6FrWAe/ondYS/rum5XpElzkZGIacjN4CNvR7yyAla8M61mVmxVkNmAVXNl2Wd3ALB6KADM857ZmBpfz8LGRdzsr9FKJVjMm8J5sgbYIsJO+jycr5wJx+b0GkQJ5Wp3LNynF+ZKndFPgOd/L1ez2QJe87YKYCZcnKZxY0QTrQ5crq3pAV73bgf2353qiikCAFtg+aSDwLrOnX+6Gl65pXgFogUy//xp4BdvNr86DVorna+M5pgT9XXRsQ9Q//QJbBrP4vB7bJOV+dqn7P5f3X34ms017HMR2nJprPpOodTdAa/DiXyFhR1oEmjncixW9HfMxE49UPVIwGbS4XNFFc0b+hW4ispohy0uZVkRbmL/u2NwMeQCsU3wD/AfYhUqQpgGaIdIGzkXN4F0Tjyyaxy6AJzH45pdUDeAJNIGarurcWMkjNUna7y61syxZgSjyAxZAi8LQPRAe2h84qkq8v4rG+iJSYI4EFJ/M/i3h+ekQd8qyIX3oDWiK+q62DXhvzYZ7+vYgXd0n8cSLnm9treP/pVFkskGV4GmBhtGQ2zK8P9fLJeKG5D4T+3syKOof/nQVNbOaLnunjneQ478y+pACrWzTY7YUsG+v7MZ4W8OujvAxASuvf0NL/qcgyOgJYPXqmZ/x/dWhf/wMO8/MtUZSVcWjicB/iHf+lyPYdnd+NJsLPeVu/CFGessF5GtrOac/q4RBcifbfXb39XIsmF/8ERtSj7CMZrvZyvgwp2TfX8K6t/Fu5j8aGgKwMD/U63gBRfL7Puz+j0nceHvUdf/Hv527gHEQPeSrLaxF9SSSHIf+IwUi5/9nlWKqe9dyMjEsiv59n0eTjNT9Ojestp7Su8bY+xPuzb6nPhHkLtKL6WzSZ3ATxq8ciQ8M2RDzzAuSYG5gRTeReiPrbQUjZz81KjhT4lxBNdgNEMxqCJk9XlN3eci3XsgWYkg9gQxQb9Bm0NL5DSXJkA+dSRIoisnRdgpaZbgb2phmKCuLw7uXnCwGzR/f6+6D1OFKQzs2z02sqL1XXegPboggCX6NZ+Nl+/ofm/m8y6UyLnMMyq+mMTdx/yjvkI71TurAtabWhDLp4Z3yrl/mlfr1rNGDOhrjVJ5ODs1/03m7I0tMlurcsmlSMQbzri1v57quAG6Pf3dCqwL3IklTIJKUZWbIBrw8a1Pv67x6ID3gSirZyMbBOnWQ5Ail883jZfIec+77xe/PkkFZPNJHZNGpjhnjtTyG6wnPkbK2mYnnvi5T3k7wfWs+vz40UzeFoQO5dQ1p9Eaf6esRP/xfRiiIyHjzv/caLwOEF1WtvpNxfFl0biizktyP6y/740ngR/Un0PZ/o3+y0/ntFb9/fI8PC4CLbeFUb6Odt4GBvd/N6O/w9mnycgVZtMtnbVC5IkZyDyAqMlPi3kdX+FXKy1LZAlgepWolDNJW/+/edCxWjBXL0QnrKOciIcBfwn1rbVxPXd/B+5CXE5x6DxrDCnDPLOEoXoKMfVJTWQcDG3iGsHd2fAVkEHqKNzlx5yYmc7J5AM/Le0b2NvEN/B1i4Be+61jugw6NOrjOa9R7gHcK2BeUjS+8IFK0hVvBn9wHpTbTkdHCNaWURU1bx/B4R1XdnxAN9CA3G10T3ilasZwT+gPhwDVTx2MnZwkFFwVsQKQSjkWJ3aHRvBpdpAVpIdfIy7IVWPM5s4v5ayDm0rpx1pFCej1Zzlq1n2k3I0hNRjjKF93xv2z2QgtiArOh9W/neONpCRn24CDgvK4Po/oJ+FOYXgpT3Vz2vLyLl7mxEB+lJjg7BSGHb17/dN4C/EvE70aSu0CgFyEHua0Q/mSa6Pk3Vc0VYq7N+qjtwAgpf16jfQgrQWGQoqYs/kPejr1FxoHsSKdm/UrpaWy5RG98EGQE+ocKjHuT3uqIV0NyjwEyiDi4hcvCnMslYEk0mD8gxzXh1ayCRD4z3xQegycVopOy2qk9pJs0NEFVwfyqrudOjsXNzpDPlFuGnvRylC9CRj+jj6IMG4Q+Q8joWKQsxZ26+MhsQUha2RPFRRyAL9e+j+12ZhFNQlNe5kMX6AMQJew+3Cvv9aXEP4wLLuxOa0TcgjvVmVHmr03jiUJOiiygvR6MoAe8ShRtD1voZ8YGfOoVd87RuQct1o73t7Vh1/0pg6RzTe97b9Z5okvE/xIneqpXvmY7GlJ2jkGVmHhordH29o18zD/lbId9ynq+JwFlV97J6rhcdZTFkqe3ng+F7wMp+b0dkOd+yDe+9G63I9I2u7YQ2gql+dg4ih82c8rUxMJ2fb+P5mtt/z+vt6xXg2BzTjNtWJypOvS8gK/FudW5nGyDr3dZNyViH9Pf2fJ8QXescnc+AR44qKP1VqRgv9kcTqyH+eyhyDn+NKJJErfWPJgrHed4vRsr7f7ztF0a5iNud/+3l3/T2SMn/Q9Vzg9HY1iZ612RkuBpNYL/y/jUev+dBKzdtdiSkosDvi3SEZz2PnyKqX+HlXPZRugAd+aBiPb0NWXw7e2f5nXeYnyCLQLsh5SOns919UM2cZiapfEX5nAYtFy2NFPEFvXOaiKw/ixcseybHOS73g55ug5f/chQU9szrdj5E7ZmIwiDFDpOFR6moTscHvt4oXvf5iEv9BIqDejTweQ7pZQNBX0TNyCImdEIrFBd4e3+eFqx2+P+e6nJu7YPdAKRYPYWshbMgKsuhwH/rUa5V8k2DBvYTffB5jYj2QX0nT128THohK+czVJSPtVDM2RY5HFe15W39+/+WSijBjGc5FNF7jkKK1yfkGAnE22sDssgNc1mOb+K53f25mvsVGivVsbV+Gi/XS5Ai/zQ5TkY9jeYiLE2LIiKMp2BaURNpz4ioTu+hCfLm1W2k4PR/63V7PaIZ7ksTkT6o7IswqNa69+/l+qhP64ZW2a71vudeqsINFpDvTJYbUASQzoji8jMylKyLlP4HgfsLSH9btNq4OXIEvRBt6vY4OfLqvWw/RCEyp0Pj1DHe1l9CE+vSgjgUfZQuQEc9og9kMWTFHOy/H0Ec4yURL7IBzcTrHts4kvVXyiZasr/WG/qbRDE0J/GeA4FHqq51p8KHbaDK6z7HPGSd4TpI2RmCLxGiqBivIsekY3F6CG20/tB4EJ7GB8BZo2vDkKU4cyKrKz/MO60biVYGkFV9AzTJ+9HbXm4bqXineAuVeKfxcvJKRPzcydUjsAsa1J9BKygLognfjd6GRqDB/iUqXNtCJy7R9xw7gc6Aloaz7+Q2YN561nWVjEujiAi7InrSKDxKSRvf1w85LH6OaGCbUlGkX0GD+8HA8gXkZTG0FD/R6/lFnH4R1cWMLkdNG9JEbbUnig18I1Lq96DiBDwAhXi7n4LC66FNk3ZE/ijzo0llZ0SpezBrW9RvNaQPonzcj/uIULBiWZX+Gt4HfIMMUQ/gK41RG5gTjU/D2phG3JZORSu1Xaqe6YsU+wcocPO2SJZZEAVp6ejeumjV+3PkpHwT+W3QEo9nO+IhBv13D7QRzn/8W7yRVk7Uq9LKrNUzo0nRgKr7g5FPTQM1UjXb81G6AB39QDOvW5FFaQMfoAb4vSORN3vdOqsm5FsW8X/Xa6JDmRdZDk+jGQtFNCjN6APCSc08NwNa1iqam3gGPpOncciiZZDl9FuvgzYPjlGed0OD/zhkGT+CCgeutw9KbyKFvm50BeTQNQptf3w+vqQe1dNAcnBoi965POI6/wQcEl2PO+xWbRyB6AUH+2D2LLKw90E0o31RfOHC4gc3I9Mi3uFfTeNQV/2R9/5IRPMqTMmP2vN0PgitXiXLCS7jWOCeNqZRHfJtXuQ4N97ffQg1DK6tlGUjZC1rQFFhYoeyJdAksSbOa/Q9X4kU9evRytN3SKn/TfTs7LWk1UTaW6NoKjN43/UuUiYneLt/BBkFGpDSV+QOe/H3Gq98DfLvb7jLcwo58GtbWjfAn70fbUCrVDNH94ehyWRN0SkQ1eQzb+NNRumqNY1WyLIWMsj8Si/wb74POa0YoMlbptDvjlZ2m/KjmB75h/0zhzTn9DobD2wS1XPM4V+lXm2sjKN0ATragXjKfauuze9/90FWrawhH4JvolGivNv7YPIw8riPZ8mz+iDzq1jbTbznX1Q2W5ns8wXn51MabwxjaOZ9Dtpi+n7Pb6uVAyqKzVDviPdA0VQmAMf5vR5UnGEGoYnVJW1Jr4ZymBFZH95BSu9eBabV2zvCc70cniRy6qMGCxuywp6BlmIfRgp1z6pn6sI7RZPjbRCt5TtEhYidcxem2M1C4oHuFmQ5fhtFaLiECg2nj7fJNvEgozztRSVqTrbydCtaiTmbnCxmLZCnJ1J8vvT2fDpSfK+njZvvUFGmt0BK7Xxep3NF96ZHlLhx5Ez/iOTYFUVU+Qj4k1+bBikfuyNl5nyk8LyBHL1yn7hVta3fo/78VmQcyCKCrAz8n8tRF6fdqC3O5PX+I7JeH+Wy3IXThKh9H4JN0crqy/7uNevVt0QyLEElZvhfouuda+lHW5BuF9R//8/b4nLRvVjhrbntIYv8Cd53vUu0KQzRJm5T8lG6AB3pQNbfBqRYbEBkKfT7m6JZ2t6IsvAlNS5j5iT3XMga9Lx3LIe4/GcCb7fwHTOhbaa/RcuGaxcxALRAjmkRVeAZYOPo+mAfIJdCPLLX8GXeNqZzP3C6nw/zDimjmGyDO5D570OBl+uQ90ZhptCEYhBa4vwJWdUnS+lpZVpx1JVZUQjJu5GScjltVL6qO1dvj1cgq/Atcd2W0Mb6IWv6p0jRq3lHwxakGVNQTvH2uz6a4O2AlJ0PyEnhQcrdJUhxWcyvdfZBcTsfEL8hZ5+FSQ2qXu4Xo8lbA4rgUMukrRviEB+BDCLPe//RmYrTXG8v2z8VVK89EC3wdDQe/LLhTtVz2QrYx3HfkqMcmcHgJKRYnob4+T/SeHfD7rRgx9QaZcn6r5W8L437mIXQJCNTPldrSdtpRdrTI+rNU4h6cSwFTaom0SZXQzGqG7wPjS30uSjXaMy/1+vzl74c9d/3er1fRUH+X8hIsTha/fvZ+5ncVlHb+1G6AB3tQMvwN0cfxdJU6AEzoZnw28iye1kJ8lUrLD2j8xXQsuSTVHhtreJPIm7gHf6xXMNkNpbJIT/ZgNCfisVuZcQFG4mWL69C1Ih7/f4wtLTYpmVdZOH6D7CF/x6Dhz1CTpsXEkWLQIrI1m1Jq4XyZAPRQjSmfWQdZg+0tNiArJx5dc4L+DvPIVKwkLVtZ6SQfEwNXt40tqTNgPjXd6BJwtptfW9ryrWZsu6MFKLnvAyepZV0l1bIsQeiQ+yCJohXEvHVkZVnHhTqMLcVMG9PDyCFfWhcJy7Hanml1UTaqyCr+F/RKlPsw7AkUoJrjgZBZdOX9ZAyEW9Hn/Xb1+Ax6HPOY/VS+5rIae0b1A/3beK526mKRJOXHGgSPp7Kbo4XA7f4eT9gpaLquxm5bkAT9AtQnx5HcloL0Z3atJMtlXFjHsRf3oHGE4gFkQX3HeD/Cs5nJkucvxnQpCLbeyHXuNmIGnm0nw+uSnswWkl5ERkPji4w792RkfEJtPL2D+ro/F3WUboAHekgckBEjiiZInMClViYMyHL9pwUNBBPRsbYye9UNDu9ompAWQYtaze7TWr0nh5IwZq/qmNazwe/Bgqy9kRpDUHWnsOoOBsNQdy8fyAKwR44PQTxBC+tMc3rkaVrV2Shz3b9mxFZwTYpoW7vRBOaX3XCPngcT468NcTz3QuFZvoM2CO61x1NKnNxbKOxcpHtxvUw9QmBdTJVlAMqysiBSNkpcofFdZFFZyRwHrIkNlXH+yHHpkFtTCejL81M5JGPqAivoJWeevDH/4wUmjuRZf59pOQsl3efiSzzLyNfmEu9Le8U3R+EJoetDlnYmjxHv/uhSemziPYR74DY2fuWovYA+BNwn5+v6X3qPP57NTSZzTWs4iTawAbIB2ksctj7DE2yFqHG0KVRmU6DlMdxyPDyMlq57RM9uyEtjGZUY75nQhPYfWis5PZHtJev/X6bN0CaRNq3URVYAPXfiyGn9AbgjznU6XJoNfx+RO0aGD0zI/KdafNOyB3pKF2AjnREH+x1yGp5uXeOX6Cl052rPpp687eyBr44spgPR2HpRqLZ4iktfE/MQbwGReF43zumf1CZRHRBikdh299GZf43Ks5GW9JEqB4quw2Oooqn24qyWxINcht6vTbg8W3R8tp5wMjqsiow/1ldTINoLieiydwoorjj3jm3yZltcuWPLBxZ2KsXKNCyFdX38kjZG1Rw+XbxwWWsf8NbV91fA1kXC1XwkVL1ZzSh+AbFJl+DxhOOTZASWJPyieLjPoImqvMjpepMZClfseB6nQZZybby38cgDvI4L/8DyWFDIBrzRk9BCvU6yJn8BT/+jRSvXMOaIaNKbMgwaBQf2ryux1OJBGJI2dmuwDa2GvCGnz9F5IiOuOgvUWD0qqgvmw1FoPgdmkR39f7rBzRW7UwlAEAtVKBzULSVgcgifiyiEb4E7F1UPpuRZRq0mv01mlStG5VHJzTu7FRQ2kMQBehbqqJFIct5m+llVMbNGZH1/WE0RjX4t7U7jfcsKC06Wl3ru2wBOsoRDQyr+8fRP7rXFzmDTETWpmEly/oov96NbweX+zjvxJvtsKIP/gaknK+BgvkfggbkeykgcH0L8tWHCg3ndkT5iPlp3dDg2aaOwt//Bm7RQB79w5GC/RganJ+kEnKu6FivWZubDk1wOvv5at7evkMKwh1okF69xvSaokZkMnRFVKIsgsF9FBvB4C84tafgMl7BB5flEZ3mK7RsuSIajF8Azi5YhljpyiaHr/q3drLLsp0PWsfVmNbsyCr6IaI4PYYoAU95vX5OFCWjgLweDDzk5/N4eS+ABuaPXYYmIw+1tP1S2cVuAHKMXBNRejb265ugicQdNOGMnkMeb/C6+jON+cNxFKM+Xr+586knIdesLteTaHKerWD09b7twDrJcTTwnJ/HE8ehyAD0jZfhTDW0gd5o4hhvgtYT+Qb9n+f3UeocS9nbfDaGXUcB1vKqMs3quDNaYcxCmt5CjtvVo/Hodj8f6N/19cj35zYUt7xuzv1lH6UL0NEOKrtVZXzfjKc3GFlcPgV2LVG+vj6I/N5/x535aWgDhMla35B19pP4w0e0kHWR9fqoAvPwK0s/jZWPYS7De2jlYIYc0uyCLPQvESnOiNazA+IB/pFKvPJ67pC2NjCqiXpeFy1vX0YLYki3tNwRL/WIZu4dhiYbLVr9qLE+aq7XyeRzZSLnXUSR2BhRFLKQdg9Sp7jCVTIugyhc76IJ+yhg35zevQKaRGyLlNoN0BL1SM/30DzSaSLdzmiymkXHOBcNyJ28b7kYbdjR5i20PY2n0AT5Ey+/TxCFKouu0mqFrZUyDPDyfR75f2zKryPdLIMcouesbpc5ypEpmcOiPm0rZEl8Ea0Cnuxt/Mk6tu0/ID+kbOfN7l5v03ub/yOiCj3k7aJF5ULjMeJ4RJs6sYnn+iCreCH0n2Zka2TMQo7JY9A4dlZ1+6gxrWy83wNRMmIj4DTexz1D7RSQ2fzvEDRuDvXfDwAX+fmZns6PVAV7mJKP0gXoaAeyFv5M5NkddWBnUKC1p4Xy9fCP5vom7q2AOI1NbnJBFAqHysY3mZUnngWfjizGhcz2Ixm2RTtEZZy7XzonZD1/E+cMVsvYwnR2ovHuid2RhTJzWizFyYKqSBtI4Xsf3/K5qPL2865UIhi8RNWOcGiQvqSouq9zOS+GKBcDq67PgKwuS9NEvNuCyn0gmsStTOOdATdCltU3iSKHtDKdXxwyo2tro4npBTSOaVxoKE0UdWQBP78cWQ8zq9rw7Nur4f39EHd3O6S8roYUqYWRdfoFZJUvdGLosiyFVnaeRkrsOn59PuQcfWFcPwXJ0AltcHQ1FWfJ1fwbvs/b1d74bp51KBPz/H+KrKb9qu4/i7i6myLlukVRK4joUYjPfBmVTcP2oaAdeSeVT/+7AVGkJqJ4zsiA8QE5TmqoKNVD0ErrblQmMD3wEJ3ex+0HzNXGdGZH0aG6ICv88Wi1bVm0GpB94+sjms/gepZ/2UfpAnTEA/GM3/EPI2u0iyFlpDBP+lbItwFSGM7AFUcqCtPzzfzPLFW/uyHKx6U+MMVKwGHAiILzYMh6kW2csETV/ZUQHzPrSFrldIUs8i+h5diDcWUWRSq4Ii4XpNzfDKxah7pbDM3uD0TL41n+HgF2r3q2O5octDlkEopy8yqNJ4ozosE323HwLsTFXRxFr8g9gkI9Di/TftHvnt4GhvnvTlX3iubPZ3W7H7KyfoGWp28Cflclyx/amMYvO0oii+2VaMI6D1JAbkB+A4MKzuPs/NpqeyaipOyMLLyfFVnmSAlYCCneE4Ed69DmOiP+8uPISvyBt7n/UDEYFJLnqO5/h/wV7qhq470oz3iwOlpZfQs5LW6HFO3/+v1F0Bi2RAve9VtgeBN1vSFaEXnGv6mNSshnFq3pBqqUSzTxO5ECKHVI6b3Ez7shKueTaDUu829oc90jOtW7VHY/ngON2Sujla85/fouFKwrtMejdAE64uGD0lnIEvGed5ijgVtLkCXernctxKPrhRw1HvfjAbSsNpYoMHz0jvXQcun+NFagt0IxZR/0Z4Z6Z/UxsEOd8rcycjiZgCYK83qne2Ot5e3vvsA7+LuRAr0O4oSdibi2HyIr/011ym935GjyBXI0ySg9FyBnnIW9bm/xju29GtMbjCxX3/vgM3d0b3Zk5XuUCjViRBEDQR3KdRnPw5toEM+2Tr4Dj/iBJlFLA3v6N91s1Jwc5Mm+2yFo8rKNf7sjvU95zes8lygNaHK8C3LYexwpWq96u38T0cRydSyq6kvuQRP7vtG1aZAl9QeX47d1agvT5lWurUizF7LC7o2W4mfy67krtjRhbECGhOf9+819i/oWtoHpvb/JaCnzIqU6C9t5dSYbMnA81cI01qEyOd6UxhuS9PHv+U7Un/8T39CtwDzHIWJnQIauZ72dn4T8ZAagaDwPFJD+7F7Xa/vvfRG3/iY0obuXGmlHXo8TqIoBjqhl36OJxHHet21fr/bWXo7SBWjPR/SBdEOe3utQWU7rgRTZvdBy5vqUwCGiMkBf4h3TStG91b3juhQppU12qEjBvBgNto/R2Fo2P1Ksv0cD/ttUOUbmmJdJbR6xC1LsxkdyZByvFlt8qFhx5s06BSrb0j+DBp4G5HixN1Jk41jgdbHwIGrAVYh29E+k+HzhZTAcOMjrt+YA/8i6sy6yaGRhDTPFsxNS+BZFTmAddhtaNMieg6yVjyElen+kRN+BdiR7E01ECwuvVyXT1Xi8exQZ4As0ic0Uzv/SSktb1CesjSzV/Yl2aUT8/JW9DT2JBsgxBeQt6z+P9TKOJ21LZ23X66WuS/VTw4GsoadSiVu9HPJJOY/KUn2hviJRG9gZKXfjvO++n8b+O9mKYVfEwR7HZLj+TfX73o+PRavKcXtbGNEVnqXAvReojC9zIL+IbCOiWX08+QCNYW96f1NIqD8qivSRLsdefn0ZL4M20cqyPPqY8RywZ3U7QmPJv72PLWxH4PZ8lC5ARzjQzPJF5On6CVJWC4992QK5sgF0ef9Yl2hNRxl1AtnfDdFMc7R/lEtFzy6BFLmBFMyv9UH/UJdnYRpbXrZGivBc/rutsU4vQZaSY3xg7+0d34NoWf5soninJdZxZrFvQPzQYTm/Pxv4VqES03QiUuh2KDv/OeYzXgJfDFlufvSB7kW0QrGuD4BFKxvZ9zYLWnnZ2n8/Apzh5wv5AHgibfCmR5FEGrzPuhVZwO9AysXu/l1lMYxXpRm/ixzyOh3i067nv+dDlviJ8fV05F7uc3n9Z06btyJHxXuQv8YdFOQcHMnQKZJlAnAA2k59O+SjMw5R2eJvc1ZEVWpxLG8UMWlnRLsZgKhVT3qbP5rGMdsL3dDM0zD/fl+jccxs829+e7Q/Qs1hJaN3Z0EUlkNUvpXR+PY8mqhkfgyHUcMuwTQOJ3w5TWyug8bSbFV5qpwwly5Aez2oKBybohnw+v77K++o3qdi0ax71IAqWa+gmR3ZfNAcNIn/7YKoD3shGsL0yOHhIcR/O4tfO9PlrnhE5b0dUnbe93J+DC3ltXmG3Ux6s6LZ/FNodr8TspbMiaw8zyAKxAFF5LcN8m7j5fKet7s8IqFkCl5PNGHcGzknroAmkxMRTSSXbbTb24EG+RHezg6k8e6SRbTxuar7CrQiNDeyKo/AV5yQI9Bt+HbjbUhrceQXsAVyolsXTRb/jhSu99GE4ifgoALL+DdoQji7D7hXI2vl4ojOdD0FbkozNR/AZmi1cmukrB7mv3/yNrBZneS4HLgh+m2IAvV/SAH+lYNwS78/H6sa/D3XRt/PImiV9lW/t0PBeVyFX9OcRlGJlFFEf/LLfhP+tyuiLv4meiZbCeiBdIGPifY/aG16aIJ2iJ+QZYI8AAAgAElEQVRvh+g1s6EVzcORceALFNq3Q/ri5FI3ZQvQ3g/EeTzQz/dBdIk+iBP4LbIqDSpJtuzDOhd3TKFx5AxDFqr9J/GOWZF1+mn/aNb160PQEu7zXga5hPpqQZ5e83I2H4yv9s7iZsSBbtM25ZNIbz5kvR7p+V/Tr/8GWVWaLbsC8h7TVPZC4ZL2xJVoxNM8yQeSw3NM90hv17HlqAeabDT4sU+9yiHHfFVTIuagsjvnLzxUpFR/4kdhFlT/xj6nMdUqk3FapOhegHiKRwPv1JBWF7Sy9gqNNys5E00ahyJq2y7kPGmtkqMnmhy/iBy+b8T9PJCVcThTQISZ9nBQtXrn3/CBSLmM4zkPpqDdHZuQqQuinlzbxL0lkdFq1ehaayM7bY7i+T+MHBWfRlz+wX5/LUSp+5aCJhKejwYfP4ZFfcwNwAnRczP5sxfjq0U5pf+69xs3Ag/6ta5Vz6yIVisuriGdTFd4Co3HpyAF+k0v37dQNJY/IAPdFL91ebNlVbYA7fnwwfgqH+i6e8PZ3u9thyya55QgV6aAZYPyfsgCNaTquVmRsjBJjiZSyFdHyvlziIe3sN9b3j/aL4kUgpzzk/HQhiCLSv+q+2sgC/rXFKDgef7X8PyPRJaUBdDSYiO6TIF1mil6WUjEMSh6wAto8rZ19Ozc5Bv3dCc0+P4yIfO/fZDVdG/aAS2mjXmLKRG3eNneghxrDkSWrUWRxfjOotq4y7Kof1sTvT0vFt3rgiyKzyHu5ftEkVpqSPNkT2sgcqT6nhpD2rUy/c4owsxfEb89iyLQydv1r+IMp6Om8p4OrQhs4+3NvPxfQ5bGMvyAdkSrbesQOT4j5etdImfDGt7/JBoHj0fK9WN4mD0/CrXOU4mG8Z2383n9e74bGUjuRxbsMeTosIgs41v5e3+k8W6a8R4WMyLDQq27tma6wi0+Pv3s57M18WzpK71lHaUL0J4PZCFcD8URHoast5lH8yJoiavu1pboYzkT7e6V7eL1rXcus6IQS9fSihiZ/pHuiqxITyFL5ixoiWntgvKSKXN9vXw/oJnA/ch6+8sWwAXIkuX/QcQzb9MyfI0yvIqWMKdFk7n1vJ09S0He7N6Wv0A0gQFV9+4HNql3OeSYt5ZQIkb6AHFoHeTp7n3JA57mhURL4Sh02Ea1tr3ouxqIJozn+gD4H6IJY475anZ1oIlnB3odtNkin45m62FhZBH9ABl+HvZx4kQfI7Ypou9sRpbYke8BtHqyG7LaLoIcst+t4f0Zr3g6/57/6X34Msh58Vk0WS50Iknjlb5d0KrUKP/evnQ5TkCroP0LGrtuQ5OnL5EFe72q++eQY7hYL+edvT95HO0WW5dY6B3hKF2A9ng01fCRlXCsD9ALeEO+s0QZZ0Rbv2YhdfojhexzpGB/QlX4tFa8uy+iHDyNFKs/FZSHLj7o90dLxrcgZedFZN3o3cz/FW097gfsXUKdLoWW1QZXXe+PHFGuLirvyCr9rA9Of0Jxws/09lSqD0EObWxSlIjlkLK9MwVSIpqQaya06vUWsqYXtp004na/gSzlw/xa7nVK06sDt6HVgb8gZWoFxPk9HFij7PbRkQ8qk5kZESXiXERf2wVZq7dGPiKPIuf2Bh8barJaTkamJvsnZCi4GDmsvoysqw8Dq/j9mnj2yJj0mI950yI+/3ZIoS+c61stP1JkG5BPzDYU7/A/A5pgLIIoMT97WxjqffuEgr752ZCu8CTyx9mv6PG5IxylC9CeDhrzLnsQee2iJZBsw5IP0KzwV8sfdZAxswLMj7hkg6J7vZBSvA6K4lFTXFr/SO8A/lZQXi4FHq26Ni+ylv+AuHmL0YIt2Ass77oplYj7+CGV0EhxCKO90LJiIV7WyIq5nStCo7ydP0gOW6W3h4OSKRHV9em/uyBr3rFIGW3Ehc0pzUz5WhMpuoVNGGnZ6sATfl4Xn40p9aAxXetuL9tXqTjjjiEyiCDD0B74TrpFyRS1t02QE/gdNPYpmM/vrUQr/WWi8Xk1H/vWQKs/GW1xCWR82CX6n0HkEJK0jeUxB4oZPdG/ixXrlG531wGy/QdepuBY0q4r3A6cVUZZt7cj+zinephZZ6AhhBDM7EzEI5oJ0SDOAk4LITSY2W+QRfPZEML7Jcm6OFq+bkAevvf6dQs5V6iXS/cQwnc5v3deNNAvGUJ40a9th3aGfNnMtkFWxR+RAn5aCOGbPGVobzCzLminrvlQUP8XQggT/d4laOvtNWtMo3MI4WczWw4NSmugmKP/CiF8ZGaZ5aMr8GkI4ata0isbZtbJv9uBiDs/Bq0A9EKKX0Pe30wTMmRlnvEclwTuCCF85ve7olWwY5BPQ78iZDKzvdA3dQziNufdV3RBk4SNge1CCCP9+pnImr0XotXNjibUb+SZ/tSErK83s7uQNfLEEMJIM+uLJui7Iu7xpWiiPqGOsi2KlLoXkKV8daTc7RtCeKzGd3dGPgizoNW0e9Cq0xdoUrEt+raXCiE8X0tarZRrIUTh+gRZqV8OIYzze2shS/ppIYTjckqvqX78buDGWC8xs0WQNb3wsihKV+iISIo1YGbTZwqEme2KljZOQp3BckjJGYNm+2NKE9RhZnOi5aVN0Yz8gBDCJX6vE7Ia/FSiiJOFmT0OvB5C2Ml/D0CK9vohhEei505CzpcLlSNpfeF1ew2yAFyCwiMNQqGzhoUQXqrh3bGC9zQaoB5HTk2vIr7vVcA3IYSGmjLSDmFmc6HBZwhyDByeKd4FpvnLZNfMbkRWtW8QF/Z0ZOH5xO9Pi+hPHxUoz0VACCH8qcA0TkZL0Nsjh+Nsp9Zri0pzakKkVC8P3IX4+O9XPTMLcs7dA4Vfe6VAeRZB9LF9Qwg/mdkVwBchhH3NrCdayTiMysZHh4QQPmxjWjMj48MM6Dt63n+v5tfmQ+Hntq8xWy2RpYvnd0P0LU9ARonxyFJ9J/BECOHHnNOdVD/+MurHrwc+nxL78Q6Bsk3mZR9ox8Qnga3897n4bkLRM0MQPeFK2gl/CH3Ay6OP6CuXb5I7VbWXAzk4NdA4cP9twHV+bn50RYH2swngFBnvFjmCrIp2o8sC+e+MKBlPI2tHbl7tiIN3m58P9PZzPYpvextaqi2NflNQGdeNElGVbrZ8fTTyHVgMTZR+QI5GnyJObF3KG9FPCokMQZ0dJqf2AzjKy7cbTYQ2Q/TFscDxBcuxubfl973f2hatWMTPTIcMQe9Sg8NilK/MCvw0HsUpup/1ofVy0nwXD3+Kggl8i+iir6HdTbPwkrnSCifTj9/q/XgKZVnCUboAZR/eKdyDwlxdhrhQR/g9iz7SfZFj2RwlyFjNzYwV0pmBDdDseDziObV6p7Y65+cKtGR2vMu/FPAZ7jxGRZG+DBhZtrwFlUHWrpZHDqJvu7L1Ah55xu/XFOYuUnay7d+HoDBJ2cYFDwAX+fmZaMLzIyWE5apj2e+FeI+H12PwRWHF3sPDXqLJ8P2I95rxIN+j4J3w6lzGdXGYnJoPFGHjtei3VZ+7onVSwXJkkTj+jiaKE4Brovtx1Iz+wEJ+XlOcYypRnB5GhqW/UuX4XWCes351R0TZA00ePkEUs35o99qvgFNzTC/14x3g6MJUimw5LYRwnZndgWL5boiW4Oc3s+tCCG+h2R9oADwCzZbrLi4QzGw9xFdb2syeRpytccCdZvYS4jYOCc7Lbcc4ACmS66AQRIsDlwbnXIYQgpktjCwfi0Nl+askeXNHqFB1LkeTofXRsu3+wPsZRSGE8D9oO38+iF88O/APM9sIWQ5vA8aY2bLI0rGnP/4AsjxdGUL4uu25a98IIZzjy9cD21KmbcDCyGnvETObGy2JbxpCeNvMbkaWvv+EEL6sgyyFw9vuaDPbEylbiwLDQ1qWzhvvA/O5b8o1oeKPYdEzvVGEiMIQxN8eYWZvIyPV1sCWZtYNrf5+5HJ1CqKAfOj/V5Ncnu5FZnYbMnytCixrZncDZ+f9bUf+Gt1Chd4xEbjOz/dFyu7wEMIEM3sEKdeX1pp26sc7GMrW7Ms8ENXgdrR80xU5ffwVWY+eQbywGZBjwM3AzSXImC0lz+9y3YmUrwbErTqEygYrXelAdAkqux6ORlzBTaN7DwFXxWUwpR0oesLbft4dDTg7+u9V0RJnvxzS2QQtV2abc8yBJmvZpgZz+vVdgBFll0udyr4QSgQVy9JiaGeyLTyttZFT1e/RJH1mf25jtJzfrleZaiiPuq4OTE2Ht6cnUcjGjdHKSGap7owMRRMocCWEqk2l/Lw/sANaBf4aOK5O5VGXyBTIB2YnH28NWND/XoQMJd38uWvJMRpH6sc7zlG6AKVmvrJF5zOIk7SWXx+K6AofIL7UaMSVym23uzbI+iC+HSnyAv4UcRh/9IF687LLs435ynZyuh15df+fD8ITcMoLU+gSsg98d/n5GcgBJaOILOOdZc2xldGEcQLylI+vL4BCc92AYg2Pz3MgmNqOSKmZDXE/LwfWqXpmGFoF2whNLEdR8FJ92YcrHIXHEp4aD0Qneta/3SsRNWJ9HxteAg4qOP1MsT7IFbpZ/HcXb99HuTI4ATlRFl0enYscpxH9pgFNaK4DVo/uHYImOVui6Djf0cqQgpNJO/XjHeQoXYCyj0ixy7azvsA7hE5ohvhvZClerQTZsoF6MTT7H+K/n8etAGiHqQbked9hFVAqfLn7PT/7+PUOY4FvQ55XQNzyPZGH+1LRvauA2/NoQ8iy8hywR9yu/Hxdb+OP4fGz09H2sva/d7iS07O6vP33BWh5/lPg4bLlrkO5FOYwmY5f/GwOQyteP/gxAkViKTLdbDV1WRT6bpuozXelYhhZztt8KfGkc87z5q4wP4winDyJ6E4LoBWDO70vH0GODtKpH+9YRwq35zCzaRCndyuk5N2ONigBURQuLlG2RRBv7XRkyTwDWDeEMMbMNvZrZ4cQPi1LxrxgZv3QJhnnli1LPWBmx6FQVWNR+/sYDVDHAUuEEEa34Z0ZF7B38NjfZnY5MD6EsEfVs72RJeRoNBB/W0N2plpEIdCGopB+y4eqOM1RvcyJKGZdgPeDh9tLSKgVvs/C+8DXoU5x/93f56EQwiHOq14TOBhNHM8PIdxnZr1CCOOLDm9ZD5jZjsgIdD3a62INNFG+IoRwsY9hX4cQxteYTurHOyjKcMRrlwghTAghXIRmpA+ipdobgN+WoVSb2aL+sRBCeBk4xRXngCwS2WC8JLDslKBUA4QQPsqUao/JPaXjLLTq0AlZOz5AfMlD2qJUwy+OLp2Aq8zsED9/EFjCzGbztnW4O9e8jygon6XOuO0IFQvFSmjla1wTz2QKxfYo8tCIpFQn5IkQwpMhhA/rqFTPj7YQv94v7Yuc/D9CGwHt4HKN978dVqn2jZxA9NERKJrViWjL8NeBP5vZnYhSWpNSDakf78iYaqOCNAcf6A51K/GJeFSKesJ3aroLOMnMbkIbqXzht8ciqsp/PBLITijc3hSHjtwJV8PMuoYQJvpAtD5SwN5GYaKOQDFJBwI9gAdC7d7cMyMryiZoqfYtFJ3iETTgfYSWDc9FmxmkzjgffAksGEL4HJqN5vIKiubQM6RdyhI6Nt5Bxp6dzWw82qjlohDChR694mAzmz2EMLZUKXNA8KgrIYSvzex45HT8TzRR3g/4rZ//Bvlo5YHUj3dAJCrIJFDmFp1mdiywO6IGnAPcH0J4x++tgULWdUaRSi6ot3wJbYOZjUarDV8DPZEi/QZwdFa//lzN29O7hWNVxOGeC222czvw5xDCx1XP1pxeApjZ2ojruANVIdCy8vUQe/8NIexTmqAJCTXAQ7/1Q+PT4sjp/HPgSOC+EMKPZnYWorMNK03QGhDtcLgaCpF5D3I8/jSE8IqZLYF2txyerWqb2SBE1chtBTn14x0PSbFuZ6gagKdHVIHN0e5llwGPZtZrX5r6KX1I7RdmdiDwrxDCWDPbHXHzVgshfO7b826GJlCPhRB2L0iGaRBH/w8oRNe/XaZ3JvmPCa2GmfVCDrjZltIPA185/7onsmpdBPQPU0jc6oQpHxHfd1kU9WJ35GTeHcVpvhIYFUL41MxmQA6L1yBaxIiOug+BG9c+Qt/z50i5Xg74AtFBtkV96lIhhOcLliX14x0ESbFuZ4iC+3cPIXzvmywchCggC6AQP5cCr9aLR5fQNpjZMijs2ttol8mJaNexI6ue+x3iKC4XQni2QHlmA/ZBId++RU52uW+kMLXDN4G5Fn2vN6FwmB8jx+iF0WZIZ5UnYUJCyxE55nZBIfxeR+16IjAA7T44DwobeayvqB4JPB1COKgjOyy68eMi5Gz8DYrIdRGivMyAaJnThxC2r6NMqR9v50iKdTuEmXUPIfzgH/VoYOMQwsNmtg2KjzkTcFQI4ZxSBU2YLMysDxpk/oz4t18Da1TRPmZAXOtjQwjX1EGmRdBGSKNDCPsVnd7UCDObCcW83QNZuwLwMnB6COG6Sf1vQkJ7QmStvgBthrJ20K6H2arpQNTO9wL+SGVS+bpTQjqsYg2/UDHWQNGbBqC44eeGEF7z+11CCD/Vm4aR+vH2i6RYtxOY2VLA1iGE/aNr1wDTARvFy2hmdjbidd1af0kTWop4QDGzxVAIqi3QZkRHIUeUn5H14zZgcL2iRJTpPzC1wUOgjUGUkJqjBSQk1Btm1hd4AvijG3k6oWA4GW1xduBGxEFeI1S2/J5iYJWQvFsjCswDaNO290qUKfXj7RBJsW4nMLMdkJPiOBSy6DVEI1gthPCCP9MlhPBTaUIm1AynfZwK9EFc3GlRnb8YQji1TNkSikVyLEroqHB6001o05OHm2rLZrYVMhgsFkL4oQw56wGfZOwLrIJ2OUxUjIRGmBriBHcU3IAC6/8H7br3OvBgrFQDP0cc7IR2iCz2tpmtbWbzmdkcZjajX+scQrgZmBcF8l8ULTHekpTqKR9p4E3owPgKGAIsAs225U/Qltv96ihX3RFC+CSEcCiihkwABqZvOyFGsli3Mzg3c0Xkeb0RcDOwXxa+p6Pz1aYGmNmKKM7oNyig//xoovQy4ljfi0IljkNhqq50hTshISGhXcLMLkGGgG2Ap6pDSZrZhcBcIYQ1ypSznkhUjISmkBTrdgozGwyshZxC+gPnhBCOLVOmhJbBzBZHS6LXIx51H2BttEK0J9pd8VNgMbQD30kliZqQkJDQIpjZCsg/5GvgJOTn87aZdUchYc8Blg8hvNpRw+slJOSBpFi3M1TFse6KrJ2/R4raziGES8uUL2HycNrOsWhr8u1CCCP9+ploNWJvYEY0YXo0hPBGWbImJCQktBRmNgT4O9owZTTwPYp68wFwXQjh9KRUJ0ztSIp1B4CZ9QbmDyGMKFuWhJbDzE4GhqJtbr9GsYx3CCFcW6pgCQkJCW2Eb3Q0FO0u+hPq1y4MIbzv95OTbsJUjaRYl4SIl2aIl/Z22TIl5IMo7utAxKEeg6zTvYB1gYY08CQkJExJSAp1QoKQFOuSYWbnofi2h5YtS0L+MLO5UDimIcCaIYThyQE1ISEhISFhykQKt1cCzGwLM3vYzP6Adme7yq+n+piC4Ar0aOSw+DYKr0dSqhMSEhISEqZMJEWuHHRHnNsr0EYwY0EKl5l1zmJVuxNcQgdFpkCHEO4DzgPOMLPDUyzyhISEhISEKRNJsS4BIYQrgMuAAHwHPGZmB/nOij8793oo2j41YQpACOEcVOdpM4GEhISEhIQpFIljXRLM7FjgMeAHFE5vdeBL4G/AXYg6cHbakW/Kga9A9AwhfF22LAkJCQkJCQn5IynWJcDM9gKOBAaEEH703RZXR3GP1wJ+BkaHEFYsUcyEhISEhISEhIRWICnWdUIcCcLMNkYh9s6s2hBmIDAf4mC/EkJ4rzSBExISEhISEhISWoWkWNcZvvve5sCbwDohhB+cW/1TyaIlJCQkJCQkJCTUgOS8WEd4NIiXgP+ira0PcYv1Tyak+khISEhISEhI6KBIFus6w8y6ArMBOwP7oVB7+4cQ7i5VsISEhISEhISEhJqQLKQFI7ZCm1nnEMJEYGwI4WhgeeAF4BYze8h36UtISEhISEhISOiASIp1gXCaR+awuB1wn5ndA5xrZuuHEF4JIWwBbAT0A5YrUdyEhISEhISEhIQakKggBcIt1D+b2ZHAH4HhQAMwB9Abxas+ya9NF0L4qixZExISEhISEhISakNSrAuGmU0PvA9sEUL4t19bENgV2MyvP1qiiAkJCQkJCQkJCTkgUUGKxzLAR8Do7EIIYVQIYV+0u+LOZQmWkJCQkJCQkJCQH5JinTM8pF6Ml4EewBp+v3Pk0HgfMLuZdaujiAkJCQkJCQkJCQWgS9kCTIHoYmZzAkOBt0IIT5nZ9cCZZjYRuBzAzKYDfgfcE0L4sTRpExISEhISEhISckHiWOcMMzsB2AJF+eiEFOl9gMOAA4GPgbeAgcD3IYSlypE0ISEhISEhISEhTyTFOkeY2erADcCfgW+ApZFCvWcI4R8ep3onYEbgaeCxEMLbZcmbkJCQkJCQkJCQH5JinSPM7B3g/BDCaf67F3Arcl7cMYTws1+3kAo+ISEhISEhIWGKQnJezAlmti0wGLgjuxZCGA90A772eNadk1KdkJCQkJCQkDBlIinW+WEu4FXgb2Z2IICZzQ0sCZzuz4SkVCckJCQkJCQkTJlIVJAcYWbrAZsDCwBjgGWBG0IImaLdKdviPCEhISEhISEhYcpCsljniBDC3SgCyMUodnU3YDYzG+r3k1KdkJCQkJCQkDCFIlmsC4LHst4KWB3FCx8BnB5C+KhUwRISEhISEhISEgpBUqwLhpktj+JarwlsG0J4tmSREhISEhISEhISCkBSrOsAM+sKLBNCeKJsWRISEhISEhISEopBUqwTEhISEhISEhISckByXkxISEhISEhISEjIAUmxTkhISEhISEhISMgBSbFOSEhISEhISEhIyAFJsU5ISEhISEhISEjIAUmxTkhISEhISEhISMgBSbFOSEjocDCz98zswLLlADCzY8zsEzMLZrZDK/7vcjO7s0DRpmp4vbxSx/TqVp9mtoOZfVuPtBISElqHpFgnJCQ0i7KVv0koR8sA59VbnmqY2cLA0cBuQD/guiaeGexK99J1kqldKOztQPk7HVillhdEdfeZmU1fdW+4mZ0bXdoH2KaW9FqB64AhdUorISGhFUiKdUJCQodDCGFcCOG7suUA5va/t4YQPg4hTChVmikUvslWqxBC+DaE8FlOIvQEDplMel+FEL7MKb1mYWZdQwgTQgj/KzqthISE1iMp1gkJCW2Gma1sZk+b2fdOhzjLzLpF983MDjCzt8zsBzP7wMxOiu6fbGZvmNkEp3ecamY9/N4OyBq8kFsNf6FaVFNBzGygmd1iZt/4cbOZDYjuH2Nmr5jZFmY22p+51cxmmUz+FjGz+12+z90aPH32TuAWf7TBzJrbbetd/zvC8zC8Ko19zOxDM/vCzC4zs55V5XeQyzzBzF42s2atoi7T9sD6UZkNM7NrzeyC6LkT/N5y0bX/xu82sx3NbJTX7Ztmtp+ZdYruT29mF5nZ/7w8H86s8mY2DLgM6BXJcYzf62Zmp3hb+M7MRpjZ2tF7h/nz65nZM2b2I7C2mc1hZrd5PXxnZq+b2RaTKot4tSOz5E+qvCeBvwP7mFn/SaTXaKXAzHqZ2ZVm9q1/G4d6+pdHz7S1LBqtBpjZXF42H5vZeDMbaWYbtCBfCQkJOSMp1gkJCW2CKxn/Bp4HlgB2ArYETooeOxE40q8tBGwG/De6Px74I7AAsDuwBXC437sOOAN4A9EsmqNadAJuA/oCq/oxO3CrmVn06GBgc+C3wFou818nkb9ewL3At8Cy/n/LA5f6I6cDu/h5Jl9TWNb/ruPP/C66txKwMLBGJNs+0f0TULnuASyIyvFCM1u/mbROB64H7o9kegIYDgyLnhsGfJpdM7O5gQH+HGa2C6q7o1DdHAAcjOoIL9e7gP7ABqgsHwEeNLMszX2B7yI5Tve0L0MUja0871cAd5jZYlV5OQU4ApgfeBpRf3qi+l3I399aC/Hkyrs53AC8DBzXirTOQPn8LbAasJinH6OtZVGNadG3uKancxNws5nN3wp5ExIS8kAIIR3pSEc6mjyAy4E7m7n3V+AtoFN0bQfgB6QATQt8D+zWivR2A96Ofh8DvNLEc+8BB/r5msDPwODo/hCgAVgjes/3wPTRM4fHaTWRxi7AV0Dv6NowIABz++9N1Y1OMk+D/X+WbqJs/wt0jq5dDNzv572ACcBKVf93NnB3a+oMKWQBKbg9vY4OBu71+ztXlfv7wLZV79gXGOXnq6EJxzRVz7wAHBS1hW+r7s/l9TKw6vqtwHlVZfz7qmdeAo5uRVtq1HYmV96TqzukAP8ELOT3hgPnNlXuqO3/CGwR3e8FfAFcnkNZ/Kpsm5D9KeCIlpZXOtKRjnyOLiQkJCS0DQsAT4UQGqJrjwHdEPe4B9AdeKC5F5jZpkhhmxspI539aK0cY0MI72UXQgjvmNlYZOW93y+PCSF8Ff3fWKDPZN77Ugjhm+jaE0gZWhB4u5VyNoVRIYSfq2Qa6ucLojK8p4pm0hVNLFqMEMLrZvYxUtTGAaOR9f9IE395GBVr9azAHMgyfn70mi5AtgKwFFLQxzVeFKAHUhibw5L+jlFV/9cdeLDq2Werfv8NuMDM1kFt6pYQwnOTSKspTKq8J4kQwsNmdi9aNdhoMo/Pherpmej/x1tjR9xayqIRfHXlaLR60M/T7oEmIwkJCXVEUqwTEhKKQHN841/g/N5rgWOB/dCy/kZUKAN5yzGxiXttpcNNNn8txKRkyv5uiCzIk/q/luBhRKP4H/BQCOE9M/sURVhZBTi0Kt3d0ESiKXQCPuHX1AaArychQyeUx2X4dR6qHT/Hx0sfjicAAAQJSURBVD9CCJe4YrseonI8YWYnhRCOmUR61ai1DRwCvGBmTeW7tWhzWTSB0xHV6EC0ivQdcCWa5CYkJNQRSbFOSEhoK14D/mBmnSKr9YpoCXw0sjz/AKyOBvtqrAB8GEI4PrtgZoOqnvmRyVuwXwNmN7PBmdXazIYgnvWoVuXo1+/9o5n1jqzWyyOF6LVWvOdH/9taS/woVH6DQgjVFszJpddUWsMRV/oTZP3Nru1CxK8OIXzi1v65QghXNpPGSMRpbwghvNMKOZ5HVtrZQggPtSAvjRBC+AC4CLjIzA5G/OhjWvuetiKE8LKZXQmciuqmOYxGyvIywDsA7iS5sN+DGsuiCisCV4YQbvK0spWDN2t8b0JCQiuRFOuEhITJYTozW7zq2pfImWxf4Dwz+xviNZ+MeKffAfj1k8zsB+TcNjOwVAjhfDTo9zezrYEngbWR82OM94BBZrYkstp+E0KoVmjuR0veV5tZ5oh2DlL+WqOQVuNqZE2/0syOAmYELgRuDiG0hgbyP2SBXNvM3gO+r6KkNIkQwjdmdjpwujsLPoLoMsshhfaiZv71PWBdM5sP+Az4KoQwESnO5wOD/Bz/ezEw2pXWDEcD55jZl8DdiFqwJNA/hHASKvPHgdvM7CDgdWA2ZDW9P4TwqMvRw8zWRErkdyGEN83sauByMzsA1dFMiIryTgjh5ubKw9vSv1G7mc7TqmXi1FYcRUVhbXIDmhDCt2Z2KXCKrwp8hJwPMys1tZRFE3gT+K2Z3YYU+qMRFSQhIaHOSFFBEhISJoeVkGIUH6eHED4E1kURIV5A0TKuAQ6L/vdQFNHgSGTlvQlZRwkh3AGchpzxXkJOiEdVpX0TUuweQNzgasWbEEIANvb7D/nxMbCJ32sTfHKwNlLinkGRR55EUUxa856fgL2Rg+BYf09LcSSyyB4IvArcB/yeSgi/pnAxKutnUZms4HK8jsrlzRDCOH92ODKwDK+S+R8on9sCLwKPArtm6Xq5rocmLhejyC3XA/N5HgkhPAFcgNrEOOAgf/2OKBrGqUghvxNYGRgzmbLohCZMo7wcPkGhBeuKEMJ/Ufi9ySmuB6Jyux21yZdQnXwfPdPWsqjG/mgC9yiafDzl5wkJCXWG1TDuJCQkJCQkJLQAZtYdKcynhRDOKFuehISEYpCoIAkJCQkJCTnDzJZAkWWeAXqj8Ia9aSIWe0JCwpSDpFgnJCQkJCQUg/0RPeYnRJdauYrLnpCQMIUhUUESEhISEhISEhISckByXkxISEhISEhISEjIAUmxTkhISEhISEhISMgBSbFOSEhISEhISEhIyAFJsU5ISEhISEhISEjIAUmxTkhISEhISEhISMgBSbFOSEhISEhISEhIyAH/DxIUziehEo+bAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JNc6BXqW0oX1",
        "outputId": "739b2bd2-51ed-478a-e13b-f5cb67690f14"
      },
      "source": [
        "#Top 5 influencers that tweeted about Dr Dipo or engaged other people's post\n",
        "followers = general_tweets[['username', 'followers']].sort_values(by= 'followers', ascending = False).drop_duplicates(subset = 'username')\n",
        "## getting what they said\n",
        "tweets_f = general_tweets.sort_values(by= 'followers', ascending = False).drop_duplicates(subset = 'username')[['username', 'text']] \n",
        "pd.set_option('display.max_colwidth', None)\n",
        "print(tweets_f.iloc[1:6])\n",
        "print(followers.iloc[1:6])"
      ],
      "execution_count": 136,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                            username                                                                                                                                                                                                                                                                                                                                                       text\n",
            "tweetcreatedts                                                                                                                                                                                                                                                                                                                                                                                 \n",
            "2021-03-25 08:47:43  MisterRedefined                                                             You Spitting rubbish was just a short while ago drolly over @OgbeniDipo DM. \\nThe Problem with us is we seek the easy way out, without working it out ourselves, Many of you beg for CV review, SOP, &amp; Cover letter writing, Yet come here to blow grammar.\\nOga Grammarian. \\nOgbeni Dipo\n",
            "2021-03-25 06:46:45       PoojaMedia                                                                                                                                                                                                         Ogbeni Dipo is in the mix of youths that drags, follows the mob &amp; surely needs CV reviews. \\n\\nSo his business as str… https://t.co/EriUsog3Er\n",
            "2021-04-01 09:42:38     BhadmusAkeem                                                                                                                                                                                                            Yes, Ogbeni Dipo &amp; any other CV reviewers will help you come up with a fancy CV, but if you can't express yourself… https://t.co/732ir2r1f1\n",
            "2021-03-25 07:43:01      TheOladeile  @oshoarmani @monell_M2R @osinachakanegbu @OgbeniDipo @akintollgate @boluxxxx Dishonest people will always twist things for agenda. Desmond was talking about things he had done in his community without mentioning anything about education. Ogbeni Dipo then offered to train the youths in DE constituent. DE then said he would love to work on that.\n",
            "2021-04-02 13:43:58  wakawaka_doctor                                                                                                                                                                                                                                                                                               @OgbeniDipo 😂😂😂😂😂 I know Dipo. I dey follow your banter noni\n",
            "                            username  followers\n",
            "tweetcreatedts                                 \n",
            "2021-03-25 08:47:43  MisterRedefined      88876\n",
            "2021-03-25 06:46:45       PoojaMedia      74969\n",
            "2021-04-01 09:42:38     BhadmusAkeem      74441\n",
            "2021-03-25 07:43:01      TheOladeile      71092\n",
            "2021-04-02 13:43:58  wakawaka_doctor      67371\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CIK-zh43lvtU",
        "outputId": "2ffdacbc-3e70-418f-cd63-488e9eb44d1e"
      },
      "source": [
        "#Top 5 tweets that were retweeted as at this point\n",
        "retweets = general_tweets[['username', 'retweetcount', 'text']].sort_values(by= 'retweetcount', ascending = False)\n",
        "print(retweets.iloc[1:6])"
      ],
      "execution_count": 138,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                       username  ...                                                                                                                                                                                                                                                                                                   text\n",
            "tweetcreatedts                   ...                                                                                                                                                                                                                                                                                                       \n",
            "2021-04-04 12:33:05  dipo_smart  ...                                                                                                                                                           RT @markessien: Here is the Doctor who did the brain surgery - Dr. Omotayo Ojo (Consultant Neurosurgeon at Lagoos Hospital). https://t.co/V…\n",
            "2021-03-17 09:44:19   Bizcraft9  ...          Dear Sir\\n\\nPlease find attached a copy of my CV for the advertised role. I have two years experience in branding and marketing. My core skills include xxxx, xxxx and xxxxx.\\n\\nI look forward to hearing from you. Thank you for your time and consideration.\\n\\nKind regards\\nDipo Awojide\n",
            "2021-03-20 14:22:53     Dipo_Ol  ...             If your CGPA is anything from 1.5 to 2.9, do your absolute best to scale up to at least 3.0. \\n\\nIf you have tried all your possible best and nothing changes, don’t worry, you might still make it in life. \\n\\nSkills, street sense, self-confidence and networking will make it happen.\n",
            "2021-03-18 01:51:23  dipo_smart  ...  Let me help you rephrase. *CLEARS THROAT*\\n\\n\"Dr Stephen Ukenna, a 41 year old lecturer in the Department of Business Management, Covenant University has been arrested by the Ogun State police for raping a 17 year old student of the university.\" https://t.co/fZLRJbyocl https://t.co/HA2Pk7DzNo\n",
            "2021-03-18 17:03:20     Dipo_Ol  ...                                                                                                             If you add up Jay Z, Diddy, Dr Dre, Eminem, Master P, Drake, Ice Cube, Pharrell and Snoop Dogg Net worth together, Kanye West is still richer than all of them combined \\nThat’s Crazy !!!\n",
            "\n",
            "[5 rows x 3 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rEP9oue2F7j3"
      },
      "source": [
        "Who is this Dipo_Ol sef?\n",
        "He had the 5th highest number of tweet, now the 2nd highest  retweets\n",
        "Recommendation: Round table meeting immediately!!!"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zO9NWcdWMIeQ"
      },
      "source": [
        "general_tweets[general_tweets['acctyear'] == 2013]"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 420
        },
        "id": "0G-lUaoo12VL",
        "outputId": "0077ad91-b062-4958-d6ba-8bddcab7cc62"
      },
      "source": [
        "# account age distribution of the tweeters \n",
        "plt.figure(figsize=(10, 6))\n",
        "years = [year  for year, df in general_tweets.groupby('acctyear')]\n",
        "plt.bar(years, general_tweets.groupby('acctyear')['acctyear'].count())\n",
        "plt.xticks(years)\n",
        "plt.xlabel('Account creation year')\n",
        "plt.ylabel('Year frequency')\n",
        "plt.xticks(rotation= 60)\n",
        "plt.show()"
      ],
      "execution_count": 169,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OIoLEga8UfgP"
      },
      "source": [
        "###omo most of these people are new twitter users which indiccate that the maerket audince is probably teenagers dominated/\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mVCx1grRAMnR"
      },
      "source": [
        "For effective exploratory analysis I will have to divide the data in week 1, 2, and 3. This is neccessary to avoid bias caused by the trend on 24-3-24"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mnQZzWHo1Vzj",
        "outputId": "bbf0c914-46a6-497a-b0f4-3fddf570df61"
      },
      "source": [
        "#getting index So I can drop the trend of 24th\n",
        "general_tweets.index.get_loc('2021-3-24')"
      ],
      "execution_count": 170,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "slice(303, 646, None)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 170
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "h_0eZ7GKA1ed"
      },
      "source": [
        "\n",
        "no_bias =general_tweets.drop(general_tweets.index[303:646])\n",
        "\n",
        "#week1 monday to sunday 2021-03-15 and 2021-03-21\n",
        "week1 = general_tweets.loc['2021-3-15': '2021-3-21']\n",
        "#week2 monday to sunday 2021-03-22 and 2021-03-28\n",
        "week2 = no_bias.loc['2021-3-22': '2021-3-28']\n",
        "#week3 monday to sunday 2021-03-22 and 2021-03-28\n",
        "week3 = general_tweets.loc['2021-3-29': '2021-4-4']"
      ],
      "execution_count": 179,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MmlIq9EsDHwt",
        "outputId": "9a08db15-710f-4df8-e3a8-9072457c41a9"
      },
      "source": [
        "print(week2.loc['2021-3-24'])"
      ],
      "execution_count": 172,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Empty DataFrame\n",
            "Columns: [username, acctdesc, location, following, followers, totaltweets, usercreatedts, retweetcount, text, hashtags, likes, weekday, hour, acctyear]\n",
            "Index: []\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 525
        },
        "id": "VZio4JCaVNKu",
        "outputId": "e37df164-3402-48ab-fa6f-76fa8c646856"
      },
      "source": [
        "# Time of day the people tweeeted the most for all\n",
        "plt.figure(figsize=(12, 8))\n",
        "hours = [hour  for hour, df in general_tweets.groupby('hour')]\n",
        "plt.plot(hours, week1.groupby('hour')['text'].count(), color = 'red', label = 'Week 1', linewidth = 3)\n",
        "plt.plot(hours, week2.groupby('hour')['text'].count(),  color = 'green', Label = 'Week 2', linewidth = 3)\n",
        "plt.plot(hours, week3.groupby('hour')['text'].count(), Label = 'Week 3)', linewidth = 3)\n",
        "plt.xticks(hours)\n",
        "plt.xlabel('Hour of tweet')\n",
        "plt.ylabel('Number of Tweets')\n",
        "plt.title('Hourly Tweeting frequency')\n",
        "plt.grid()\n",
        "plt.legend()\n",
        "plt.show()\n"
      ],
      "execution_count": 183,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mkfP6eHJXmXQ"
      },
      "source": [
        "#So these people tweet the most at 9am, next is 12pm and finally by 8pm"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aV5xo2s0lLx0",
        "outputId": "27dffa4a-85aa-4b6b-a23d-3fc78c6d80ff"
      },
      "source": [
        "print(general_tweets.groupby('weekday').count())"
      ],
      "execution_count": 186,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "         username  acctdesc  location  ...  likes  hour  acctyear\n",
            "weekday                                ...                       \n",
            "Fri           156        54       122  ...    100   156       156\n",
            "Mon            71        54        57  ...     16    71        71\n",
            "Sat           188        70       151  ...    111   188       188\n",
            "Sun           150        24       121  ...    124   150       150\n",
            "Thu           392        72       322  ...    316   392       392\n",
            "Tue            65        45        51  ...     15    65        65\n",
            "Wed           399       295       318  ...     91   399       399\n",
            "\n",
            "[7 rows x 13 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "A8MVJmIy6gxw",
        "outputId": "1ff2fe18-76f5-4424-8ab1-9169ee636c3b"
      },
      "source": [
        "print( week1.groupby('weekday')['text'].count())"
      ],
      "execution_count": 188,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "weekday\n",
            "Fri    56\n",
            "Mon    14\n",
            "Sat    77\n",
            "Sun    26\n",
            "Thu    18\n",
            "Tue    26\n",
            "Wed    21\n",
            "Name: text, dtype: int64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 416
        },
        "id": "PCqxUru-eQ-v",
        "outputId": "23cd951f-da49-4605-dbc0-38f57b05a24f"
      },
      "source": [
        "# Day of the week the people tweeeted the most\n",
        "Days = [day  for day, df in general_tweets.groupby('weekday')]\n",
        "plt.figure(figsize=(10, 6))\n",
        "no_bias_days = [day  for day, df in week2.groupby('weekday')]\n",
        "plt.plot(Days, week1.groupby('weekday')['text'].count(), color = 'red', label = 'Week 1', linewidth = 3)\n",
        "plt.plot(no_bias_days,  week2.groupby('weekday')['text'].count(), color = 'green', Label = 'Week 2', linewidth = 3)\n",
        "plt.plot(Days, week3.groupby('weekday')['text'].count(), Label = 'Week 3', linewidth = 3)\n",
        "plt.xticks(Days)\n",
        "plt.xlabel('Day of tweet')\n",
        "plt.ylabel('Number of Tweets')\n",
        "plt.title('Daily Tweet Freq')\n",
        "plt.legend()\n",
        "plt.grid()\n",
        "plt.show()"
      ],
      "execution_count": 196,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0zdl6U04aAZ2"
      },
      "source": [
        "There seems to be no pattern here, the tweet frequency is determined by how many tweets Dr Dipo drops for that day.\n",
        "But on a general note Saturday seems quite positive as the Thursday in week 2 is actually the remnants of the giveaway saga which I removed already; then Friday follows showing a consistent pattern."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 129
        },
        "id": "uZOFjqZUe-zG",
        "outputId": "55ef44e4-ab00-4522-b90c-11270d64ae4d"
      },
      "source": [
        "#Sentiment Sentiment Sentiment"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "SyntaxError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-22-1a09cefbd5f1>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    Sentiment Sentiment Sentiment\u001b[0m\n\u001b[0m                      ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U4omsZJsTGw8",
        "outputId": "6b7f16c0-9e5a-4fd5-b669-d2c825de12a8"
      },
      "source": [
        "!pip install vaderSentiment"
      ],
      "execution_count": 199,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting vaderSentiment\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/76/fc/310e16254683c1ed35eeb97386986d6c00bc29df17ce280aed64d55537e9/vaderSentiment-3.3.2-py2.py3-none-any.whl (125kB)\n",
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            "\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from vaderSentiment) (2.23.0)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->vaderSentiment) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->vaderSentiment) (2020.12.5)\n",
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            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->vaderSentiment) (3.0.4)\n",
            "Installing collected packages: vaderSentiment\n",
            "Successfully installed vaderSentiment-3.3.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HimKSxyDGiao"
      },
      "source": [
        "from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer"
      ],
      "execution_count": 200,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 792
        },
        "id": "kKFegZsCS0E0",
        "outputId": "7a25b4a0-05ea-4cce-c93d-3bafc29c10b4"
      },
      "source": [
        "# intializing the sentimenter \n",
        "analyzer = SentimentIntensityAnalyzer()\n",
        "# get sentiment score\n",
        "sentiment = general_tweets['text'].apply(lambda x: analyzer.polarity_scores(x))\n",
        "#put sentiment into dataframe\n",
        "sentimented_tweets = pd.concat([general_tweets, sentiment.apply(pd.Series)],1)\n",
        "sentimented_tweets.head()"
      ],
      "execution_count": 201,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>username</th>\n",
              "      <th>acctdesc</th>\n",
              "      <th>location</th>\n",
              "      <th>following</th>\n",
              "      <th>followers</th>\n",
              "      <th>totaltweets</th>\n",
              "      <th>usercreatedts</th>\n",
              "      <th>retweetcount</th>\n",
              "      <th>text</th>\n",
              "      <th>hashtags</th>\n",
              "      <th>likes</th>\n",
              "      <th>weekday</th>\n",
              "      <th>hour</th>\n",
              "      <th>acctyear</th>\n",
              "      <th>neg</th>\n",
              "      <th>neu</th>\n",
              "      <th>pos</th>\n",
              "      <th>compound</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>tweetcreatedts</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2021-03-15 05:24:29</th>\n",
              "      <td>Ts_Czar</td>\n",
              "      <td>Nobody cares about you more than you do. Never outsource your happiness.</td>\n",
              "      <td>NaN</td>\n",
              "      <td>655.0</td>\n",
              "      <td>407</td>\n",
              "      <td>3968</td>\n",
              "      <td>2020-04-01 18:45:48</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo Dipo's IQ has low IQ. That's why he forgets so soon.</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Mon</td>\n",
              "      <td>5</td>\n",
              "      <td>2020</td>\n",
              "      <td>0.160</td>\n",
              "      <td>0.840</td>\n",
              "      <td>0.000</td>\n",
              "      <td>-0.2732</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-15 06:54:49</th>\n",
              "      <td>_ipheoma</td>\n",
              "      <td>Love enthusiast/ambivert/believer/happy human.\\n7th January... anyone?</td>\n",
              "      <td>Lagos, Nigeria</td>\n",
              "      <td>381.0</td>\n",
              "      <td>510</td>\n",
              "      <td>3687</td>\n",
              "      <td>2017-03-17 12:58:31</td>\n",
              "      <td>0</td>\n",
              "      <td>@Aunty_Barbie @OgbeniDipo Likeeee!\\n\\nMe: *tears chicken*\\n\\nOgbeni Dipo: so you took 15th position out of 25 people? You don't make use of your school library dear?\\n\\nMe: https://t.co/eErt37wB6W</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Mon</td>\n",
              "      <td>6</td>\n",
              "      <td>2017</td>\n",
              "      <td>0.061</td>\n",
              "      <td>0.835</td>\n",
              "      <td>0.104</td>\n",
              "      <td>0.3296</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-15 11:12:08</th>\n",
              "      <td>realAdesanya</td>\n",
              "      <td>Data Analysts  Enthusiast || @ManUtd</td>\n",
              "      <td>NaN</td>\n",
              "      <td>50.0</td>\n",
              "      <td>19</td>\n",
              "      <td>138</td>\n",
              "      <td>2021-01-16 09:15:17</td>\n",
              "      <td>0</td>\n",
              "      <td>Another wonder session with @OgbeniDipo about Networking to advance one’s career.\\n\\nNetworking should be a symbiotic relationship - Dr Dipo https://t.co/LFRG3K281l</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Mon</td>\n",
              "      <td>11</td>\n",
              "      <td>2021</td>\n",
              "      <td>0.000</td>\n",
              "      <td>1.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>0.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-15 12:31:26</th>\n",
              "      <td>DeKINGKUDOS</td>\n",
              "      <td>PLUTOCRAT AMBITION.</td>\n",
              "      <td>Nigeria</td>\n",
              "      <td>93.0</td>\n",
              "      <td>57</td>\n",
              "      <td>627</td>\n",
              "      <td>2011-12-14 05:13:24</td>\n",
              "      <td>0</td>\n",
              "      <td>@OgbeniDipo If you are on Twitter NG and you are not following Ogbeni Dipo,I swear you are not serious with your life.</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Mon</td>\n",
              "      <td>12</td>\n",
              "      <td>2011</td>\n",
              "      <td>0.054</td>\n",
              "      <td>0.892</td>\n",
              "      <td>0.055</td>\n",
              "      <td>0.0057</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-03-15 12:44:54</th>\n",
              "      <td>MyunusualSelf_</td>\n",
              "      <td>Blank</td>\n",
              "      <td>The Kings Landing</td>\n",
              "      <td>1397.0</td>\n",
              "      <td>1127</td>\n",
              "      <td>4047</td>\n",
              "      <td>2019-04-07 10:27:14</td>\n",
              "      <td>11</td>\n",
              "      <td>Dipo talked about how yummy our meals are especially the Jollof rice and two people sent me a dm making enquires about our Jollof rice in less than 2mins and 11people followed @_MummyMo also😂😂💃🏾💃🏾\\n\\nYou are the best @OgbeniDipo 😊🙌🏾</td>\n",
              "      <td>[]</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Mon</td>\n",
              "      <td>12</td>\n",
              "      <td>2019</td>\n",
              "      <td>0.044</td>\n",
              "      <td>0.709</td>\n",
              "      <td>0.247</td>\n",
              "      <td>0.9607</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                           username  ... compound\n",
              "tweetcreatedts                       ...         \n",
              "2021-03-15 05:24:29         Ts_Czar  ...  -0.2732\n",
              "2021-03-15 06:54:49        _ipheoma  ...   0.3296\n",
              "2021-03-15 11:12:08    realAdesanya  ...   0.0000\n",
              "2021-03-15 12:31:26     DeKINGKUDOS  ...   0.0057\n",
              "2021-03-15 12:44:54  MyunusualSelf_  ...   0.9607\n",
              "\n",
              "[5 rows x 18 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 201
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 412
        },
        "id": "78MFD0WXUOzi",
        "outputId": "e3fcc4f6-8675-4c6f-b13b-4fe2c762f6d7"
      },
      "source": [
        "# account age distribution of the tweeters \n",
        "plt.figure(figsize=(10, 6))\n",
        "sentimented_tweets['compound'].hist()\n",
        "plt.ylabel('Tweet Count')\n",
        "plt.xlabel('Sentiment Score')"
      ],
      "execution_count": 228,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 0, 'Sentiment Score')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 228
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jVHEtktbgGJR"
      },
      "source": [
        "Seems like the people were a little bit unhappy after all and it shakes off after a while.\n"
      ]
    }
  ]
}