introduction_data_science_project.ipynb

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    "<div style='display:flex;'>\n",
    "    <!--<img src=\"https://apibab.pt/wp-content/uploads/2016/03/logo_ulht.png\" width=\"200\" height=\"200\"/>-->\n",
    "    <h1 style='text-align: center;'>Analysis of Alt-text use in mastodon.social by client</h1>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac93135a-bdde-4ef0-b9e3-b9ce668c0f30",
   "metadata": {},
   "source": [
    "A project by [Cristal Rivera](https://linkedin.com/in/cristal-rivera-picado/) and [Tommaso Marmo](https://tommi.space/) to analyse the use of alt-text in [mastodon.social](https://mastodon.social/about), using [Stefan Bohacek](https://stefanbohacek.com/)’s <cite>[mastodon.social alt text use by client app](https://www.kaggle.com/datasets/fourtonfish/mastodon-social-alt-text-use-by-client-app)</cite> dataset, published on Kaggle under the [MIT license](https://www.mit.edu/~amini/LICENSE.md).\n",
    "\n",
    "This analysis is being conducted as a group project for the [Introduction to Data Science](https://ois2.tlu.ee/tluois/subject/ULP6613-23265) course of the <cite>[Artificial Intelligence and Sustainable Societies](https://aissprogram.eu)</cite> master."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a25b457-59aa-4850-a93b-ba20ed98513a",
   "metadata": {},
   "source": [
    "## Abstract\n",
    "\n",
    "This project analyzes the different impact of the use of image descriptions (also known as <q>alt text</q>) for accessibility across different social network clients.\n",
    "\n",
    "<q>Clients</q> are the interfaces through which users access social media platforms, and their design could heavily influence the process individuals go through to publish a post, includeing the addition of alt text. While it is out of the scope of this project to inquiry the nature of any specific client, we will observe trends, recurrencies, and relevant information provided by this dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "683a61b2-5d8b-4262-aae5-889d2f871b23",
   "metadata": {},
   "source": [
    "## Initialization\n",
    "\n",
    "First and foremost, we are importing the libraries we will be using to manipulate the data, and the dataset source, in CSV format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "959193d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import libraries\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import squarify as sq\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ad76c8a2-5bc3-4aa2-8f9a-701a7050b9f3",
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   "outputs": [
    {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>client</th>\n",
       "      <th>status_count</th>\n",
       "      <th>descriptions_all_count</th>\n",
       "      <th>descriptions_all_percent</th>\n",
       "      <th>descriptions_some_count</th>\n",
       "      <th>descriptions_some_percent</th>\n",
       "      <th>descriptions_none_count</th>\n",
       "      <th>descriptions_none_percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Web</td>\n",
       "      <td>8272</td>\n",
       "      <td>1438</td>\n",
       "      <td>17.383946</td>\n",
       "      <td>7</td>\n",
       "      <td>0.084623</td>\n",
       "      <td>6827</td>\n",
       "      <td>82.531431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>dlvr.it</td>\n",
       "      <td>5806</td>\n",
       "      <td>1</td>\n",
       "      <td>0.017224</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5805</td>\n",
       "      <td>99.982776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mastodon for Android</td>\n",
       "      <td>1894</td>\n",
       "      <td>270</td>\n",
       "      <td>14.255544</td>\n",
       "      <td>3</td>\n",
       "      <td>0.158395</td>\n",
       "      <td>1621</td>\n",
       "      <td>85.586061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>unknown</td>\n",
       "      <td>1428</td>\n",
       "      <td>366</td>\n",
       "      <td>25.630252</td>\n",
       "      <td>1</td>\n",
       "      <td>0.070028</td>\n",
       "      <td>1061</td>\n",
       "      <td>74.299720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AboveMaidstoneBot</td>\n",
       "      <td>1339</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1339</td>\n",
       "      <td>100.000000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>socialbot</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>PhonocasterMusicShare</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>openvibe</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>iflaapp</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>Today's Dérive app task</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>266 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      client  status_count  descriptions_all_count  \\\n",
       "0                        Web          8272                    1438   \n",
       "1                    dlvr.it          5806                       1   \n",
       "2       Mastodon for Android          1894                     270   \n",
       "3                    unknown          1428                     366   \n",
       "4          AboveMaidstoneBot          1339                       0   \n",
       "..                       ...           ...                     ...   \n",
       "261                socialbot             1                       1   \n",
       "262    PhonocasterMusicShare             1                       0   \n",
       "263                 openvibe             1                       0   \n",
       "264                  iflaapp             1                       0   \n",
       "265  Today's Dérive app task             1                       1   \n",
       "\n",
       "     descriptions_all_percent  descriptions_some_count  \\\n",
       "0                   17.383946                        7   \n",
       "1                    0.017224                        0   \n",
       "2                   14.255544                        3   \n",
       "3                   25.630252                        1   \n",
       "4                    0.000000                        0   \n",
       "..                        ...                      ...   \n",
       "261                100.000000                        0   \n",
       "262                  0.000000                        0   \n",
       "263                  0.000000                        0   \n",
       "264                  0.000000                        0   \n",
       "265                100.000000                        0   \n",
       "\n",
       "     descriptions_some_percent  descriptions_none_count  \\\n",
       "0                     0.084623                     6827   \n",
       "1                     0.000000                     5805   \n",
       "2                     0.158395                     1621   \n",
       "3                     0.070028                     1061   \n",
       "4                     0.000000                     1339   \n",
       "..                         ...                      ...   \n",
       "261                   0.000000                        0   \n",
       "262                   0.000000                        1   \n",
       "263                   0.000000                        1   \n",
       "264                   0.000000                        1   \n",
       "265                   0.000000                        0   \n",
       "\n",
       "     descriptions_none_percent  \n",
       "0                    82.531431  \n",
       "1                    99.982776  \n",
       "2                    85.586061  \n",
       "3                    74.299720  \n",
       "4                   100.000000  \n",
       "..                         ...  \n",
       "261                   0.000000  \n",
       "262                 100.000000  \n",
       "263                 100.000000  \n",
       "264                 100.000000  \n",
       "265                   0.000000  \n",
       "\n",
       "[266 rows x 8 columns]"
      ]
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   "source": [
    "''' Import and print dataset\n",
    "Assigning the variable `original_data` too,\n",
    "so that the original dataset can be preserved,\n",
    "while we operate on the `data` variable.\n",
    "'''\n",
    "data = original_data = pd.read_csv('./fediverse-client-alt-text-data-2024-05-13.csv')\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02220a53-dcb2-4495-b2ae-4960a134d455",
   "metadata": {},
   "source": [
    "We will be understanding and describing the fields and the values of the dataset later, in the data wrangiling section."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48dad0fd-e3d9-4072-b108-7d57e44e82d0",
   "metadata": {},
   "source": [
    "## Data wrangling\n",
    "\n",
    "In the first phase of our analysis, we will be analysing, cleaning, and structuring the data set. This will help us understand more specifically the kind of information our dataset contains, also by veryfing the accuracy and the quality of its data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9f52dc12-5223-43ae-a823-c1c1377fc26c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confirm data type of the dataset: <class 'pandas.core.frame.DataFrame'>\n"
     ]
    }
   ],
   "source": [
    "print(f'Confirm data type of the dataset: {type(original_data)}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2b8e578-f6ab-44b7-a414-8f30841d7747",
   "metadata": {},
   "source": [
    "### Information about the dataset\n",
    "\n",
    "In this section, we will be retrieving general information about the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f8b0398d-31d8-4aca-88da-d43664d1ef18",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rows:\t\t\t266\n",
      "Number of columns:\t\t8\n",
      "Data size (rows×columns):\t2128\n"
     ]
    }
   ],
   "source": [
    "# Tuple with number of rows and number of columns\n",
    "data_rows, data_columns = original_data.shape\n",
    "# Integer that is the result of n of columns * n of rows\n",
    "data_size = original_data.size\n",
    "\n",
    "print(f'Number of rows:\\t\\t\\t{data_rows}\\nNumber of columns:\\t\\t{data_columns}\\nData size (rows×columns):\\t{data_size}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "718c88af-c2b2-4e81-a8cb-3fa4184bce83",
   "metadata": {},
   "source": [
    "The following code provides a summary of each column in the DataFrame, including:\n",
    "- Data type\n",
    "- Number of missing values\n",
    "- Number of unique values\n",
    "- Descriptive statistics for numerical columns using pandas’ `describe()`\n",
    "\n",
    "Since the `client` column is a string, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "da1544c6-7617-4cf1-91ab-743b633f6a42",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
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       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
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       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>client</th>\n",
       "      <td>object</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>status_count</th>\n",
       "      <td>int64</td>\n",
       "      <td>False</td>\n",
       "      <td>266.0</td>\n",
       "      <td>112.240602</td>\n",
       "      <td>643.625189</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>39.75</td>\n",
       "      <td>8272.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>descriptions_all_count</th>\n",
       "      <td>int64</td>\n",
       "      <td>False</td>\n",
       "      <td>266.0</td>\n",
       "      <td>21.473684</td>\n",
       "      <td>105.282555</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1438.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>descriptions_all_percent</th>\n",
       "      <td>float64</td>\n",
       "      <td>False</td>\n",
       "      <td>266.0</td>\n",
       "      <td>36.290411</td>\n",
       "      <td>45.079671</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.00</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>descriptions_some_count</th>\n",
       "      <td>int64</td>\n",
       "      <td>False</td>\n",
       "      <td>266.0</td>\n",
       "      <td>0.093985</td>\n",
       "      <td>0.622382</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>descriptions_some_percent</th>\n",
       "      <td>float64</td>\n",
       "      <td>False</td>\n",
       "      <td>266.0</td>\n",
       "      <td>0.060461</td>\n",
       "      <td>0.527118</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7.142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>descriptions_none_count</th>\n",
       "      <td>int64</td>\n",
       "      <td>False</td>\n",
       "      <td>266.0</td>\n",
       "      <td>90.672932</td>\n",
       "      <td>568.477040</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>20.00</td>\n",
       "      <td>6827.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>descriptions_none_percent</th>\n",
       "      <td>float64</td>\n",
       "      <td>False</td>\n",
       "      <td>266.0</td>\n",
       "      <td>63.649128</td>\n",
       "      <td>45.113843</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>100.00</td>\n",
       "      <td>100.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Data Type  Missing values?  count        mean  \\\n",
       "client                       object            False    NaN         NaN   \n",
       "status_count                  int64            False  266.0  112.240602   \n",
       "descriptions_all_count        int64            False  266.0   21.473684   \n",
       "descriptions_all_percent    float64            False  266.0   36.290411   \n",
       "descriptions_some_count       int64            False  266.0    0.093985   \n",
       "descriptions_some_percent   float64            False  266.0    0.060461   \n",
       "descriptions_none_count       int64            False  266.0   90.672932   \n",
       "descriptions_none_percent   float64            False  266.0   63.649128   \n",
       "\n",
       "                                  std  min  25%    50%     75%          max  \n",
       "client                            NaN  NaN  NaN    NaN     NaN          NaN  \n",
       "status_count               643.625189  1.0  2.0    8.0   39.75  8272.000000  \n",
       "descriptions_all_count     105.282555  0.0  0.0    0.0    4.00  1438.000000  \n",
       "descriptions_all_percent    45.079671  0.0  0.0    0.0  100.00   100.000000  \n",
       "descriptions_some_count      0.622382  0.0  0.0    0.0    0.00     7.000000  \n",
       "descriptions_some_percent    0.527118  0.0  0.0    0.0    0.00     7.142857  \n",
       "descriptions_none_count    568.477040  0.0  0.0    2.0   20.00  6827.000000  \n",
       "descriptions_none_percent   45.113843  0.0  0.0  100.0  100.00   100.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data type and count of missing values\n",
    "summary = pd.DataFrame({\n",
    "    'Data Type': original_data.dtypes,\n",
    "    'Missing values?': any(original_data.isnull().sum())\n",
    "})\n",
    "\n",
    "# Descriptive statistics for numerical columns\n",
    "numerical_summary = original_data.describe()\n",
    "summary = summary.merge(numerical_summary.T, left_index=True, right_index=True, how='left')\n",
    "\n",
    "summary"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81ba253b-69a9-40c0-915d-7167fca7306b",
   "metadata": {},
   "source": [
    "**Note**: Even though it is a serie of strings with no missing values, pandas returns `object` as the data type for `client`, because it assigns the less strict type possible, by default. At a later moment, we will arbitrarily instruct pandas to treat all `client`s as strings, both for consistency and for memory optimization purposes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0bedd493-2179-495e-ae93-60fb1b38ebb7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Are there any duplicated clients? False\n"
     ]
    }
   ],
   "source": [
    "print(f'Are there any duplicated clients? {any(original_data['client'].duplicated())}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02f9b2ad-a9ca-4bca-9507-ae33292e391e",
   "metadata": {},
   "source": [
    "### Naming and understanding data fields\n",
    "\n",
    "All columns correspond to relevant data, and to achieve this we will be going through each column, one by one, to understand its meaning and rename it in more explicatory name.\n",
    "\n",
    "**Note**: since we are now *modifying* the dataset, we will be using the `data` variable, and not the `original_data` one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e6a8074e-8ee6-40a5-8e09-0697e9b21fe9",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.rename(columns={\n",
    "    'status_count': 'posts',\n",
    "    'descriptions_all_count': 'atxt_yes',\n",
    "    'descriptions_all_percent': 'atxt_yes_pct',\n",
    "    'descriptions_some_count': 'atxt_some',\n",
    "    'descriptions_some_percent': 'atxt_some_pct',\n",
    "    'descriptions_none_count': 'atxt_no',\n",
    "    'descriptions_none_percent': 'atxt_no_pct'\n",
    "})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d80f0081-9b8c-421f-9b83-a1344178355d",
   "metadata": {},
   "source": [
    "| variable | meaning |\n",
    "|--- |--- |\n",
    "| `client` | Name of the client the posts come from. |\n",
    "| `posts`| Total number of posts containing images for that client. |\n",
    "| `atxt_yes` | Number of posts containing alt text in *all* images. |\n",
    "| `atxt_yes_pct` | The percentage of `atxt_yes` in relation to `posts`. |\n",
    "| `atxt_some` | Number of posts containing alt text in *some* images. |\n",
    "| `atxt_some_pct` | The percentage of `atxt_some` in relation to `posts`. |\n",
    "| `atxt_no` | Number of posts containing *no* alt text in *any* images. |\n",
    "| `atxt_no_pct` | The percentage of `atxt_no` in relation to `posts`. |\n",
    "\n",
    "#### Notes\n",
    "\n",
    "- All the posts under analysis come *exclusively* from the [mastodon.social](https://mastodon.social) Fediverse instance.\n",
    "- For the sake of simplicity, columns’ labels have been renamed using shorter variables."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4aa590eb-19e2-4563-9acf-6d62f0bb0587",
   "metadata": {},
   "source": [
    "### Optimize the dataset for analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5828f4ac-9271-4a77-80dd-e0106a1c9062",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort clients by status_count\n",
    "data = data.sort_values('posts',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c0f5dc0d-65e6-451f-bd8a-4a668a778da1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Client data type: string\n"
     ]
    }
   ],
   "source": [
    "# Consider all client names as strings (they were objects)\n",
    "data['client'] = data['client'].astype('string')\n",
    "print(f'Client data type: {data['client'].dtype}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "78dc5814-1961-4da5-8b7b-0163361a4b79",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Round percentage values to the first decimal digit\n",
    "data['atxt_yes_pct'] = data['atxt_yes_pct'].round(1)\n",
    "data['atxt_some_pct'] = data['atxt_some_pct'].round(1)\n",
    "data['atxt_no_pct'] = data['atxt_no_pct'].round(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27557044-c4eb-4e14-85c9-e107ed39b855",
   "metadata": {},
   "source": [
    "### Exclude posts from unknown client(s)\n",
    "\n",
    "Based on our initial observation, we recognize that the third most used client is labelled as “unknown”. Since our project stongly focuses on the impact of specific clients on the use of alt text, **we arbitrarily choose to drop (exclude) from the dataset posts that come from an undefined client**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e8308cb6-6400-4e54-95b5-69b6a5cd3a04",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.drop(data[data['client'] == 'unknown'].index)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "926d78d3-2509-487b-90a3-fab42bd9f859",
   "metadata": {},
   "source": [
    "### Find the mode"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dfcfb333-2295-459d-9e0c-be61ed0e7ca7",
   "metadata": {},
   "source": [
    "By calculating the mode, we intend to discover **the most frequent total number of posts clients have**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "05539ae0-5d94-4c42-96ac-814839ee5884",
   "metadata": {},
   "outputs": [],
   "source": [
    "mode = data['posts'].mode()[0] # Using [0] to get only the first mode, as this function can return multiple values."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69af77cf-ff85-4eef-9d86-149ae8590d93",
   "metadata": {},
   "source": [
    "We can observe that the majority of clients has only one posts. We will save the `mode`=1 value to use it at a later stage of the analysis."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23cd2ce2-f8de-49f1-b9c1-51f97faa1c48",
   "metadata": {},
   "source": [
    "## Data exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a099578f-a045-4849-a355-3837712fa98f",
   "metadata": {},
   "source": [
    "Since we sorted the dataset by the number of posts published from each client, we use the following function to see the five most used clients."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2dfcaa39-45f3-43b8-a090-c07c08f9b1d0",
   "metadata": {},
   "outputs": [
    {
     "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>client</th>\n",
       "      <th>posts</th>\n",
       "      <th>atxt_yes</th>\n",
       "      <th>atxt_yes_pct</th>\n",
       "      <th>atxt_some</th>\n",
       "      <th>atxt_some_pct</th>\n",
       "      <th>atxt_no</th>\n",
       "      <th>atxt_no_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Web</td>\n",
       "      <td>8272</td>\n",
       "      <td>1438</td>\n",
       "      <td>17.4</td>\n",
       "      <td>7</td>\n",
       "      <td>0.1</td>\n",
       "      <td>6827</td>\n",
       "      <td>82.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>dlvr.it</td>\n",
       "      <td>5806</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5805</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mastodon for Android</td>\n",
       "      <td>1894</td>\n",
       "      <td>270</td>\n",
       "      <td>14.3</td>\n",
       "      <td>3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1621</td>\n",
       "      <td>85.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AboveMaidstoneBot</td>\n",
       "      <td>1339</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1339</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mastodon for iOS</td>\n",
       "      <td>1052</td>\n",
       "      <td>227</td>\n",
       "      <td>21.6</td>\n",
       "      <td>1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>824</td>\n",
       "      <td>78.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 client  posts  atxt_yes  atxt_yes_pct  atxt_some  \\\n",
       "0                   Web   8272      1438          17.4          7   \n",
       "1               dlvr.it   5806         1           0.0          0   \n",
       "2  Mastodon for Android   1894       270          14.3          3   \n",
       "4     AboveMaidstoneBot   1339         0           0.0          0   \n",
       "5      Mastodon for iOS   1052       227          21.6          1   \n",
       "\n",
       "   atxt_some_pct  atxt_no  atxt_no_pct  \n",
       "0            0.1     6827         82.5  \n",
       "1            0.0     5805        100.0  \n",
       "2            0.2     1621         85.6  \n",
       "4            0.0     1339        100.0  \n",
       "5            0.1      824         78.3  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 5 is the default value for head()\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "673cb072-2e18-4aa6-a594-7f10b25b1317",
   "metadata": {},
   "source": [
    "Between `2` and `4`, we can observe a gap in the index number, since posts published from unknown clients occupied that position."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a51e1b00-82bb-42aa-a25f-aad7f28f2e1d",
   "metadata": {},
   "source": [
    "### General analysis\n",
    "\n",
    "Analyzing general alt text use, independently of the client."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "df66ffbf-bc0b-4143-8933-5a4a246666a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Posts count is matching!\n"
     ]
    }
   ],
   "source": [
    "# The dataset already includes percentages. Let’s calculate and verify them.\n",
    "posts_tot = data['posts'].sum()\n",
    "atxt_yes_tot = data['atxt_yes'].sum()\n",
    "atxt_some_tot = data['atxt_some'].sum()\n",
    "atxt_no_tot = data['atxt_no'].sum()\n",
    "\n",
    "atxt_yes_tot_pct = round(atxt_yes_tot / posts_tot * 100, 1)\n",
    "atxt_some_tot_pct = round(atxt_some_tot / posts_tot * 100, 1)\n",
    "atxt_no_tot_pct = round(atxt_no_tot / posts_tot * 100, 1)\n",
    "\n",
    "if posts_tot == atxt_yes_tot + atxt_some_tot + atxt_no_tot:\n",
    "    print('Posts count is matching!')\n",
    "else:\n",
    "    print('Something is wrong in the dataset. Please revise the number of posts!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6d1324ec-6a50-447a-99e4-21bb6d6e42f0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The percentages in the dataset are accurate!\n"
     ]
    }
   ],
   "source": [
    "# The dataset already includes percentages. Let’s calculate and verify them.\n",
    "if data['atxt_yes_pct'].equals(round(data['atxt_yes']/data['posts']*100, 1)) and data['atxt_no_pct'].equals(round(data['atxt_no']/data['posts']*100, 1)):\n",
    "    print('The percentages in the dataset are accurate!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "12a9f097-8923-4e97-958d-c96f44c83609",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Total number of posts under analysis: 28428\n",
      "    of which 5346 (18.8%) contain an alt-text for all images,\n",
      "    24 (0.1%) for some,\n",
      "    and 23058 (81.1%) have no alt-text at all.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(f'''\n",
    "Total number of posts under analysis: {posts_tot}\n",
    "    of which {atxt_yes_tot} ({atxt_yes_tot_pct}%) contain an alt-text for all images,\n",
    "    {atxt_some_tot} ({atxt_some_tot_pct}%) for some,\n",
    "    and {atxt_no_tot} ({atxt_no_tot_pct}%) have no alt-text at all.\n",
    "''')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af11be92-2426-4d01-bf2e-b94b6ee50bc5",
   "metadata": {},
   "source": [
    "The usage of alt text for some images only is very negligible (0.1%), therefore we are arbitrarily deciding to **drop (exclude) this column from the dataset**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7a08d85b-ea7c-4463-8bb2-56b11e40ae75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      0.1\n",
       "1      0.0\n",
       "2      0.2\n",
       "4      0.0\n",
       "5      0.1\n",
       "      ... \n",
       "261    0.0\n",
       "262    0.0\n",
       "263    0.0\n",
       "264    0.0\n",
       "265    0.0\n",
       "Name: atxt_some_pct, Length: 265, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Subtracting from the total of posts the ones that only have alt text for some images only\n",
    "data['posts'] = data['posts'] - data['atxt_some']\n",
    "\n",
    "# Remove columns related to some alt text\n",
    "data.pop('atxt_some')\n",
    "data.pop('atxt_some_pct')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "96c734ec-2033-4eda-95b1-6f8e542aa652",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.patches.Wedge at 0x7fdf5dbcdbe0>,\n",
       "  <matplotlib.patches.Wedge at 0x7fdf5dbd9810>],\n",
       " [Text(0.913245498990903, 0.6131742481325002, 'Alt-text for all images'),\n",
       "  Text(-0.9132456281256516, -0.6131740558025791, 'No alt-text')],\n",
       " [Text(0.49813390854049244, 0.3344586807995455, '18.8%'),\n",
       "  Text(-0.49813397897762807, -0.3344585758923158, '81.2%')])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6KP/+97959913adKkSZX7/b3k5GRCQ0OJjY0t3+6dd96hqKiIKVOmEBMTA8Brr73GwIEDGTNmDPXr1wcgJiaGd999l/Dw8Er336lTJzp16lT+8ejRo/n888+ZOXPmCcXiTPTv35+7774bgCeeeII333yTrl27csMNNwDwyCOPcOGFF7Jv3z6Sk5Np1KhRhXL2wAMPMHv2bKZPn063bt3Iy8tj8uTJTJs2jV69esGxUtWw4fGFvTIyMpg4cSIZGRnlnx85ciTffvstEydO5LnnniMjI4PrrruODh06wLF/x5rQiIA/OrAZPh+hKwTEq3KSu/N9dpzpGAHp9QVbmbNxn0f3uWnTJpYuXcott9wCQGhoKDfddBMTJkyo0X6ee+45YmNjy9+qelW8Zs0ann766Qrb33nnnWRmZlJY6L4bY/PmzRk7dixjxozhD3/4A7feeusZfqduaWlpdOrUqbwEAPTo0QOn08mmTZvKP9ehQ4cqSwDHRgRGjhxJ27ZtiY+PJzY2lrS0NI+PCHTseHytjV+Lyq9Pvr/93P79+wFwOByMHj2aDh06kJiYSGxsLLNnzy7PtW3bNkpLS+nWrVv5PuLi4iqcAlm3bh0Oh4NWrVpV+HdauHAh6enpAPzpT3/imWeeoUePHjz55JOsXVuz9S80IuBvio7AR7dCSZ7pJBLkPnb1MR0hYLlc8ND01cy8/yKa1Y2pxiNObcKECZSVlVV4NehyuYiIiOC1114jLq56pW3EiBHceOON5R//dn+/l5+fz6hRo7j22mtP+Fpk5PGbTy1atAi73c6OHTsoKysjNNR3Tx2/LQqVGTlyJHPmzGHs2LG0aNGCqKgorr/+eo9PLgwLO77Whs1mq/RzTqcTgBdffJFXXnmF8ePH06FDB2JiYnjwwQdrlCs/Px+73c6KFSuw2+0Vvvbr8P8dd9xB3759+frrr/nuu+94/vnnGTduHA888EC1jqERAX/z5X1waIvpFBLkHDHJvLyrhekYAS2vqIy7319OYUnZGe+rrKyMKVOmMG7cOFavXl3+tmbNGho2bHjCBLNfhYeH43BUvCdCYmIiLVq0KH/79Uk7LCzshG1TU1PZtGlThe1/fQsJcT89fPzxx8yYMYMFCxaQkZFxwiV1J9tvdbRt25Y1a9ZQUHD81s9LliwhJCSk0kmBlVmyZAnDhw/nmmuuoUOHDiQnJ7Njx44aZ/K0JUuWMGjQIIYMGUKnTp1o3rw5mzdvLv968+bNCQsLqzC3Ijc3t8I25557Lg6Hg/3795/wb/Tb0zGNGzdmxIgRzJgxg4cffph33nmn2jlVBPzJ6mmQNtN0CrGAZYlXUezUj/+Z2rwvn799eubLEH/11VccPnyY22+/nfbt21d4u+666yo9PZCSkkJ+fj7z5s3j4MGD5cP5lW07b948srKyOHz4MBw7zz1lyhRGjRrFhg0bSEtL46OPPuKxxx4DYPfu3dxzzz2MGTOGiy66qPyc9E8//VTlfqtj8ODBREZGctttt7F+/Xrmz5/PAw88wNChQ8uH2KurZcuWzJgxo7w83XrrreWvyk1q2bIlc+bM4YcffiAtLY27776bffuOn1KqVasWt912G3/961+ZP38+GzZs4PbbbyckJKR8dKFVq1YMHjyYYcOGMWPGDLZv387SpUt5/vnn+frrrwF48MEHmT17Ntu3b2flypXMnz+ftm2rfzWQfhP4i5wM+OYR0ynEAlw2O8/t61aNLaU6vlqbyZQfz+zV54QJE+jdu/dJh/+vu+46li9fftLzvt27d2fEiBHcdNNNJCUl8cILL1R6jHHjxjFnzhwaN27MueeeC0Dfvn356quv+O677+jatSsXXHABL7/8Mk2bNsXlcjF8+HC6detWPuGub9++3HPPPQwZMqT8Mr+T7bc6oqOjmT17NtnZ2XTt2pXrr7+eXr168dprr1V7H7966aWXSEhIoHv37gwcOJC+ffuSmppa4/142mOPPUZqaip9+/alZ8+eJCcnc/XVV1fY5qWXXuLCCy/kqquuonfv3vTo0YO2bdtWODUzceJEhg0bxsMPP0zr1q25+uqrWbZsWfmkTYfDwX333Ufbtm3p168frVq14o03qn93WpursmtTxHdcLpg8EHYsNp1ELGBfw96cv+3/TMcIKlFhdr7+00U0T6r+JVsiJ1NQUECjRo0YN24ct99+u0+OqREBf/DTGyoB4jOTSy43HSHoHC118ND0NbptsdTYqlWr+PDDD0lPT2flypUMHjwYgEGDBvksg4qAaft/0W2FxWdK41J4c09T0zGC0updObw+f6vpGBKAxo4dS6dOnejduzcFBQUsXryYunV9d/8PnRowyVEK7/aCzDWmk4hF/K/x/fzfFi0i5C1hdhuf39uD9o20PoMEDo0ImLRwjEqA+IzLHsEze8xPoApmpQ4XIz9ZQ6nD/Ix1kepSETBl1zJY/JLpFGIhuxv0YVthZDW2lDPxS1Yeb8xPNx1DpNpUBEwoKYTP7wZXzRfhEDldbxWcuF69eMfr87eyKUurg0pgUBEwYcHzkK1XDOI7RYlt+CCz8qVmxbNKHE7+9qmuIpDAoCLga4fS4ee3TKcQi5kTPcB0BMtZszuXST+YX+ZW5FRUBHxt9j/A4dkbYYhUxRUew+hdHauxpXjaK3M3k12gn3fxbyoCvrR1Lmz+1nQKsZit9fuzvzisGluKpx0pKuPlOZursaWIOSoCvuIog2//YTqFWNArORebjmBp05ZmsHmfJg6K/1IR8JVl78DBTaZTiMXkJ53LVwd8t0KZnMjhdPHM12mmY4hUSkXAFwoOua8UEPGxmWH9TEcQYNHmA8z/Zb/pGCInpSLgC/OfgaJc0ynEYpyRCTyfUf17kot3PfP1Rsq04qD4IRUBb8taDysmm04hFrSh3gDyykJNx5Bj0g8UMPWnnaZjiJxARcDbvn1UKwiKz7mwMeZgD9Mx5HfGz9tCbmGp6RgiFagIeNOmb2HHYtMpxIJyky/k+2zdAc/f5BSWMn6eLicU/6Ii4E2LXjSdQCxqOleYjiCV+OCnDPYdKTIdQ6ScioC3bFsIe5abTiEW5IhJZlxGC9MxpBIlDifvLNpmOoZIORUBb1k8znQCsajliVdR7NSPtj/7cGkGOYVaelj8g35beMPuFbB9oekUYkEum51n93UzHUNOoaDEwcQluiGR+AcVAW/QaIAYcqBBT9YeiTUdQ6ph8o87KCguMx1DREXA4/anwaZZplOIRU0u7WU6glRTTmEp037OMB1DREXA4xa/BLhMpxALKq3dlDd2NzUdQ2rg3e+3UVKm1QbFLBUBTzq8A9Z/ZjqFWNTiuKtwuWymY0gN7DtSzKcrdpuOIRanIuBJ34/XKoJihMsewTN7upiOIafhP4vScTg1iijmqAh4Sl4WrJ5mOoVY1O4GvdlWGGk6hpyGnYcK+XpdpukYYmEqAp6y/D1wFJtOIRb1dmFP0xHkDEz9UTcjEnNUBDzB6YBVU02nEIsqTmzN+3sbmY4hZ2Dpjmy2Hcg3HUMsSkXAE7bMgSN7TKcQi/ouaoDpCOIB05dr0qCYoZuVe8KKSaYTiEW5wmJ4dndHY8cv2rWeIz9/Rsm+dBz52SRd80+iW11Y/nVnyVFyFk6icPNPOIvyCI2rT60uA6l1bv8q93tk2ZfkrZ6F48gBQqJqE926BwmX3oYtNByA/A3zyVk4GVfJUWI69Cax153ljy3L3ce+jx+nwW3jCYmI9uJ371mfrdzNyCtaEWrX6zPxLRWBM3VkL2z5znQKsaityVeStSXc2PFdJUWE1WtObMc+HPj8uRO+fvh/71K0cy11Bz5MaFx9jm5fRfZ3b2CPrUN0y/NPus+CjQs4vHASdfv/mYhGbSnN3sOhWeMBSOx1J47CXLK/fZU6/R8kND6Z/Z+OIrJpJ6JbuJdWPvTdGyRcOjygSgDAgbxi5m86QJ9z6puOIhaj6nmmVn2gSwbFmFdyLjF6/KizzyPhkqFEt+p+0q8X70kjpv3lRDbp6B4N6NyP8HrNKM7cXOk+i/ekEXlWW2LO6UloXH2imqUS3fYSSjK3AFCWk4UtIpqYtpcQ0aAVkU06UnpoFwAFGxdiCwkluvXJ8/i7j5ftMh1BLEhF4Eyt+dB0ArGogqTOfHWgrukYVYpo1JajW5dSlncQl8tF0c61lB7eS1Szc6t8THFWOsV7NwFQmpPF0fTlRJ19HgChiY1wlRa7T0cczaMkczPhSSk4ivLJWTyVxD4jfPb9edqCTfvZn1dkOoZYjE4NnIldSyE73XQKsaiZYVeajnBKib1HcGj2q+x5YziE2MFmo06/B4hs3L7Sx8Sc0xNH4RGyPnjEvVy300Fs5yuJu/BGAOyRsdQd8BcOfvUSrrISYtpfTlTzLhyc9Qq1Uq+iLHcf+z8bDc4y4nrcSkybi3z4HZ+ZMqeLz1bs4Z6eZ5uOIhaiInAmNBoghjgjE3guo63pGKd0ZMV/Kd67iaTrHie0dj2Kdq0ne85b2GPrEJXS+aSPKcpYS+5P00m84h4iGram7PBesue+Q86SD4nvcQsA0a26VzgdUZSxjtIDO0jsczd7376LugP/ij0mgcwpDxHZuD32mHiffc9navryXSoC4lM6NXC6ykpg/QzTKcSiNiT1J6/Mv3u8s7SYnEVTSLj8DqJbnE94vWbU7jKQmDYXc2Rp5T87OYunEtvucmp16kt4UgrRrboTf+kwjvz0KS7XiTfocZWVkv3dmyT2vY+yw5m4nA4im3QgrM5ZhCU2ojhzk3e/UQ/bfrCAn7cdMh1DLERF4HRt/gaKckynEAtyYePFQz1Mxzg1pwOcZdj43Y2QbCHgqnxtfVdpMdgqPsZmO/ar6iSPy/3hIyKbpxKR3AJcTvdxf92XswycgXd3v6/Waslh8R0VgdO18UvTCcSicpMvZFG2fwx1O0uOUrJvGyX7tsGxa/hL9m2j7Mh+QiKiiWjcnsML3qMoYy2lOVnkr5tLwYb/VVhr4OBX4zi88PhaHFEtupG3ahYFGxe6JwpuX0XO4qlEteiGLcRe4fglBzMo+GUx8RcNASA08SywhZC35jsK05dRemg34Q1a+uzvw1Pmpe0zHUEsxL/HFv2V0wFb55lOIRY1nT6mI5QrydrCvg//Uf7x4f+9C0BM+17UHfAXkv7wCIcXTubgf8fiLMrHXrse8RcPJbbz8YmOZUcOuEcJjonrfjNgI2fxVBz5hwiJiiOqRTcSLhla4dgul4vsb18j4fI7CAl333ApJCyCOv0fJHvOm7gcpST2GUFoLf++suJk9uYWsX5PLu0bxZmOIhZgc7mqGKOTk9v5A0z0/xnbEnwcMfU55/A4ip0azAt2D/ZuyYO9W5mOIRag3yanY/Ns0wnEopYnDlQJsIi5Oj0gPqLfKKdDSwqLAS6bnef3dTMdQ3xk/Z4jZOVqcSHxPhWBmsrZBfs3mk4hFnSgQU9WH4k1HUN8aI5GBcQHVARqaotOC4gZU0p7mY4gPjZ3o4qAeJ+KQE1t1mkB8b3S2k15fXdT0zHEx37cdoiC4jLTMSTIqQjUROlR2L7IdAqxoO/jBuBy2aqxpQSTkjInizYfMB1DgpyKQE1sXwxlR02nEItx2cN5Zk8X0zHEkAWbVATEu1QEakLzA8SA3Q36kF4YZTqGGLJsZ7bpCBLkVARqIn2+6QRiQW8X9jQdQQzafrCAnMIS0zEkiKkIVNfRw5CdbjqFWExxYmve39vIdAwxyOWClRmHTceQIKYiUF17VppOIBY0J3qA6QjiB1bsVBEQ71ERqK69KgLiW66wGJ7Z1dF0DPEDKgLiTSoC1aURAfGx9OR+ZBWHm44hfmDt7lwcTt0fTrxDRaC6VATEx17JvcR0BPEThSUO0jKPmI4hQUpFoDpy90B+lukUYiEFdTvx3/1JpmOIH9HpAfEWFYHq0PwA8bH/hvc3HUH8jIqAeIuKQHXsWWE6gViIMzKe53e1NR1D/IyKgHiLikB1aH6A+NCGpAHkloaajiF+Zk/OUY4UlZqOIUFIReBUXC7Yu9p0CrGQFw/1MB1B/NT2AwWmI0gQUhE4lUPpUJxrOoVYRE7yhSzKjjcdQ/zUtoP5piNIEFIROJWDm00nEAv5hCtMRxA/phEB8QYVgVPJyTCdQCzCEVOfsRktTccQP7btoIqAeJ6KwKmoCIiPrEi8imKnfiSlcts0IiBeoN86p5Kz03QCsQCXzc5z+843HUP83I5DKgLieSoCp6IiID5wsMGlrD4SazqG+LnCEgdZuUWmY0iQURE4lcM6NSDeN6Wsl+kIEiB05YB4mopAVY7m6NJB8bqy2k14Y1dT0zEkQGiegHiaikBVdFpAfGBx3EAcLv0oSvXs0JUD4mH67VMVXTEgXuayh/PMnlTTMSSA7M8rNh1BgoyKQFVUBMTL9jToQ3phlOkYEkAOF5aYjiBBRkWgKod1akC86+3Cy0xHkACTU6gbD4lnqQhU5cge0wkkiBUntGbK3oamY0iA0YiAeJqKQFWO6v7f4j1zY/qbjiABSCMC4mkqAlUpOmI6gQQpV1gMo3d1Mh1DAlB+cRmlDqfpGBJEVASqojUExEvSk/uRVRxuOoYEKJ0eEE9SEahKkYqAeMerRy42HUECmE4PiCepCFTG5YLiPNMpJAgVJHXmy331TMeQAHa4QCMC4jkqApUpKQCXzsOJ530V1s90BAlwhzUiIB6kIlCZMt3hSzzPGRnPc7vOMR1DAlyO5giIB6kIVEZFQLxgY9IAcktDTceQAFeiqwbEg1QEKlOqIiCe92J2d9MRJAg4nC7TESSIqAhURiMC4mG59S9g4aEE0zEkCKgIiCepCFRGRUA87BNbX9MRJEioCIgnqQhUxukwnUCCiCOmHuN2tTAdQ4KEw6UiIJ6jWUuVCdWqb+I5IWXFrEweYzqGBInSiDsAFUvxDBWByoTqHvHiObbiXKK0ZLV4SJRD/5fEc3RqoDJhkaYTiIicXIhew4nnqAhUJlRFQET8VIjddAIJIioClVEREBF/ZVMREM9REaiMioCI+CuNCIgHqQhUJiwSsJlOISJyorBo0wkkiKgIVCU0wnQCEZETRdcxnUCCiIpAVXR6QET8UYyKgHiOikBVwrSWgIj4oei6phNIEFERqIpODYiIP9KpAfEgFYGqRCWaTiAiUlFoJETEmk4hQURFoCpxjUwnEBGpSKMB4mEqAlWpfZbpBCIiFakIiIepCFRFIwIi4m9UBMTDVASqUltFQET8TIyuGBDPUhGoSpxODYiIn9GIgHiYikBVNCIgIv5GawiIh6kIVKVWsu7yJSL+JSHFdAIJMioCVQmxQ60GplOIiByX1Mp0AgkyKgKnoisHRMRv2KBOS9MhJMioCJyK5gmIiL+IbwzhugWxeJaKwKnoygER8Rd1W5tOIEFIReBU6p1jOoGIiFuSioB4norAqTToZDqBiIibioB4gYrAqSS1htAo0ylERHRqQLxCReBUQuxQv53pFCIiunRQvEJFoDp0ekBETIupB1EJplNIEFIRqA4VARExTfMDxEtUBKpDRUBETKvX1nQCCVIqAtVR7xywh5tOISJW1uQC0wkkSKkIVEdoOCS1MZ1CRKys6UWmE0iQUhGoLp0eEBFTEs+GWvVNp5AgpSJQXSoCImJKSg/TCSSIqQhU11ldTScQEatqqiIg3qMiUF3JHXUNr4iY0bS76QQSxFQEqiskBFIuNp1CRKwmrgnENzGdQoKYikBNNO9pOoGIWI1GA8TLVARqQkVARHxNEwXFy1QEaqLO2e5hOhERX9FEQfEyFYGaanG56QQiYhWxye4XICJepCJQU636mU4gIlbRsrfpBGIBKgI11exSCI00nUJErKDNVaYTiAWoCNRUeDSkaM1vEfGy8FhofpnpFGIBKgKno2Vf0wlOm8Pp4vH/FdHslTyinj3C2f/OY/TCYlwuV/k2M9JKueL9Auq8kIdt1BFWZzlOud93VpRw8cQCEsYcIWHMEXpPKWDpnoqPG/tDMfVezKPei3mM+6G4wtd+3l1Gl7fzKXO6EBGgRS8I0+ijeJ+KwOloFbhFYMySEt5cXsprV0aSdl8sY3pH8sIPxby6tKR8m4ISFxc1CWVM74hq73fBzjJuaR/G/Nti+PH2GBrHhXDF+wXsOeIEYO0+B0/ML+aj66P48LooHptfzLp97qJQ5nQx4usi3hoQRWiIzQvftUgA0mkB8ZFQ0wECUkJTOKsb7F5qOkmN/bDLwaDWoQxoFQZASnwIH64vZekeZ/k2QzuFA7Ajx1npfn7vg2ujK3z87sBIPttYyrztZQzrFM4vB510rG/n8mbu/3Id64fwy0EnHerbeXFJCZc0CaVrI7uHvkuRAGcPh5ZXmE4hFqERgdPV6WbTCU5L98Z25m0vY/Mh96vxNVkOvs9wcGULz3bCwlIodUJilPsVfod6IWw+5CAj18nOHCebDzlpXy+E9GwnE1eX8szl1R99EAl6Z/eCqHjTKcQiNCJwutpfC9/+HRzF1djYfzx6UThHil20ea0Aewg4nPDs5REM7hjm0eM8MreIhrVs9G7u/i/WNsnOc70i6fN+IQDP94qkbZKd3lMKeKFPBLPTy3hqQTFhdnilXySXNNV/TbGw9teZTiAWot+2pysqAVr3g41fmk5SI9M3lPHBulKmXRdFu6QQVmc5eHB2MQ1r2bitc7hHjvGv74v5aH0pC4bHEBl6/Jz/iPPCGXHe8WNMXl1CrQgbF55lp/Vr+Sy7M4bdR1zc/OlRtv85lohQzRcQCwqLhjb9TacQC9GpgTPR6RbTCWrsr3OKeLRHBDe3D6NDfTtDO4XzlwvCef77kmo8+tTG/lDMv74v5ruhMXSsX/k5/4OFTkYtLObVKyP5eY+DVnVCaFnHzmXNQil1wuZD1Z+fIBJUWvWF8BjTKcRCVATORIs+EF3XdIoaKSyF30/Mt9vAE1ftvbCkmNGLivl2SDTnNax64t9fZhfzlwsiOKt2CA6nez7Br8qcLhy6ilCsSqcFxMd0auBM2EOhw/Xw81umk1TbwFahPLu4mCZxNtrVs7Mq08FLP5Xwf52PzxHIPuoiI9fJ3jz3s/Omg+73ybE2kmPd3XHY50dpVMvG873d1zmP+b6YJxYUM+3aKFLiQ8jKdz8mNtxGbHjF5jEn3T1ZcfLV7sd2bWTnl4NOvtlSyq4jLuw2G63rqKOKBcUkBfQ6JRKYVATOVKebA6oIvHplJI/PL+beWUXsL3DRsJaNu7uE8cSlx2ftz9xUyh+/LCr/+ObPjgLw5KXhPNXT/eSdkeskxHb8yfrN5SWUOOD6T45WON5vHwNwtNTF/d8U8fH1UYTY3AXhrNohvHplJH/8soiIUJh8dSRRYZofIBaUOgxCPTNXR6S6bK7fLiknp+f1C+BAmukUIhLIbHZ4cB3ENTKdRCxG46+e0Okm0wlEJNC16a8SIEaoCHhCx5vcbV5E5HR1vdN0ArEoFQFPqN0QzhlkOoWIBKqkNtD8UtMpxKJUBDylx59NJxCRQNX1DtMJxMJUBDylYWdopkYvIjUUUTsgFyeT4KEi4EkaFRCRmup0C0TEmk4hFqYi4EktekFyB9MpRCRg2KCbJgmKWSoCntZdowIiUk3NL4W6LU2nEItTEfC0dtdAfBPTKUQkEFz0kOkEIioCHmcPhQvuM51CRPxds0t0yaD4BRUBb0gdBlGJplOIiD+7/AnTCURARcBLwqN1XbCIVK5VP2jc1XQKEVAR8KLzR0B4LdMpRMTv2OCyf5oOIVJORcBbYurAxX8xnUJE/M05g6BBR9MpRMqpCHjTBfdBnK4gEJFjbHaNBojfURHwprBI6KUJQSJyTMebIKmV6RQiFagIeFuH66HReaZTiIhpIWHQ8xHTKUROoCLgbTYb9H3OdAoRMS11KCSkmE4hcgIVAV9ocj6cc7XpFCJiSngsXPI30ylETkpFwFd6PwX2CNMpRMSEy/4BtRuYTiFyUioCvpLYDM6/y3QKEfG1Bp3c64qI+CkVAV+65K8QXcd0ChHxFVsIXDUeQuymk4hUSkXAlyLjoOffTacQEV/peic0SjWdQqRKKgK+dt7t0Ph80ylExNtqNYRej5tOIXJKKgK+FhICf3hNEwdFgt2VYyBC9xsR/6ciYEJSK7hUlxKJBK1WV8I5fzCdQqRaVARM6fEgJOvGIyJBJywG+r9oOoVItakImGIPhUGvu5cdFZHgcdnfIb6x6RQi1aYiYFKDjnCp1h4XCRoNz4Xz7zGdQqRGAqoIpKSkMH78eNMxPOvih3RTIpFgEB4L101wj/aJBJAaFYHhw4djs9n417/+VeHzX3zxBTabzdPZTslms/HFF1+ccrvhw4dz9dWeX+vfI/sNscO1b0NYtKdiiYgJV46BOmebTiFSYzUeEYiMjGTMmDEcPnzYO4msqM7Z0Odp0ylE5HS1uxbOHWI6hchpqXER6N27N8nJyTz//PNVbvfZZ5/Rrl07IiIiSElJYdy4cVVun56ezqBBg6hfvz6xsbF07dqVuXPnVrp9Sor7dp7XXHMNNput/OPfe+qpp5g8eTJffvklNpsNm83GggULANi1axc33ngj8fHxJCYmMmjQIHbs2AHAL7/8QnR0NNOmTSvf1/Tp04mKimLjxo1V7ve0dLsTWvY9/ceLiBlxTWBgkJ2yFEupcRGw2+0899xzvPrqq+zevfuk26xYsYIbb7yRm2++mXXr1vHUU0/x+OOPM2nSpEr3m5+fT//+/Zk3bx6rVq2iX79+DBw4kIyMjJNuv2zZMgAmTpxIZmZm+ce/N3LkSG688Ub69etHZmYmmZmZdO/endLSUvr27UutWrVYvHgxS5YsITY2ln79+lFSUkKbNm0YO3Ys9957LxkZGezevZsRI0YwZswYzjnnnEr3e0aufRsSmp3ZPkTEd0LC4PoJ7uXDRQLUac1queaaa+jcuTNPPvkkEyZMOOHrL730Er169eLxx93La7Zq1YqNGzfy4osvMnz48JPus1OnTnTq1Kn849GjR/P5558zc+ZM7r///hO2T0pKAiA+Pp7k5ORKs8bGxhIVFUVxcXGF7aZOnYrT6eTdd98tn98wceJE4uPjWbBgAVdccQX33nsvs2bNYsiQIYSHh9O1a1ceeOCBKvd7RqLi4eYP4N0+UFrgmX2KiPf0GQWNu5lOIXJGTvuqgTFjxjB58mTS0tJO+FpaWho9evSo8LkePXqwZcsWHA7HSfeXn5/PyJEjadu2LfHx8cTGxpKWllbpiMDJZGRkEBsbW/723HPPVbrtmjVr2Lp1K7Vq1SrfPjExkaKiItLT08u3e++991i7di0rV65k0qRJ3p8UWb8dDHrVu8cQkTPXdiBceJ/pFCJn7LSvc7nkkkvo27cvf//73yt9lV8TI0eOZM6cOYwdO5YWLVoQFRXF9ddfT0lJSbX30bBhQ1avXl3+cWJiYqXb5ufn06VLFz744IMTvvbraAPHCkNBQQEhISFkZmbSoEGDGn1fp6X9dbB3FfygQiDilxKauRcEEwkCZ3TB67/+9S86d+5M69atK3y+bdu2LFmypMLnlixZQqtWrbDbT35f7iVLljB8+HCuueYaOPZE/evEvcqEhYVVGGEIDQ2lRYsWJ2wXHh5+wkhEamoqH3/8MfXq1aN27don3X92djbDhw/nn//8J5mZmQwePJiVK1cSFRVV6X49pvcoyFwL2xd6Z/8icnpCI+HGKZoXIEHjjBYU6tChA4MHD+bf//53hc8//PDDzJs3j9GjR7N582YmT57Ma6+9xsiRIyvdV8uWLZkxYwarV69mzZo13HrrrTidziqPn5KSwrx588jKyqrycsaUlBTWrl3Lpk2bOHjwIKWlpQwePJi6desyaNAgFi9ezPbt21mwYAF/+tOfyidBjhgxgsaNG/PYY4/x0ksv4XA4KnwPJ9uvx4TY4fqJ7hnJIuInbHD1m+5VQUWCxBmvLPj000+f8ISdmprK9OnT+eijj2jfvj1PPPEETz/9dJWnEF566SUSEhLo3r07AwcOpG/fvqSmplZ57HHjxjFnzhwaN27MueeeW+l2d955J61bt+a8884jKSmJJUuWEB0dzaJFi2jSpAnXXnstbdu25fbbb6eoqIjatWszZcoUZs2axfvvv09oaCgxMTFMnTqVd955h2+++abS/XpUTB246X33KxARMa/PKGh/rekUIh5lc7lcLtMh5BRWfwhfjDCdQsTaut4BA6peD0UkEAXUvQYsq/MtcL6KgIgxrfrBlS+YTiHiFRoRCBROJ3x2O2yYYTqJiLU06Ax/nAXhMaaTiHiFRgQCRUiIe+XBFn1MJxGxjrgmcOt0lQAJaioCgcQe5p482ORC00lEgl9kHAz5FGrVN51ExKtUBAJNWBTc+jEkdzCdRCR42cPhpg8gqXU1NhYJbCoCgSgyDoZ8DnVOXDxJRM6Uzb1qYLOLTQcR8QkVgUAVmwRDv4DaZ5lOIhI8bCEw6DXoeKPpJCI+oyIQyOIbw7AvILqu6SQigc9mh2v+A+cOMZ1ExKdUBAJd3ZYw5DOIOPn9EkSkGkJC4bp3NBIglqQiEAwadobBn+omKCKnIyTMfV+P9teZTiJihBYUCib7NsD710J+lukkIoHBHu6+k2DrK00nETFGRSDYHN4J718D2emmk4j4t9BIuGkqtNQiXWJtKgLBKP8AfHAdZK4xnUTEP4VGwS0fwtmXmU4iYpyKQLAqzoMPb4Edi00nEfEvYTHuRbm0ToAIqAgEubJi+OwOSJtpOomIf6jVEG6ZBg3PNZ1ExG+oCAQ7pxO+fghWTDSdRMSshqlw8zSo3cB0EhG/oiJgFf97FhbpfupiUe2uhavfcN+rQ0QqUBGwkhWTYNZfwVFiOomIj9jgsn/ApX8zHUTEb6kIWM2upfDxUK01IMEvLBqufhPaXW06iYhfUxGworwsdxnYvdR0EhHvqN3IPR+gYWfTSUT8noqAVZWVwDd/dZ8uEAkmjbq4S0CtZNNJRAKCioDVrZ4GXz8MpYWmk4icuU63wFXjISzSdBKRgKEiILA/DabfBgc3mU4icnrCa8GAcdDpJtNJRAKOioC4lRTAfx+EddNNJxGpmYapcP0ESGxuOolIQFIRkIpWToFv/wEleaaTiJyCDbo/AL2eAHuY6TAiAUtFQE6Uuxv++2fYOtd0EpGTi2sCV78OzS4xnUQk4KkISOVWfQCz/w5FuaaTiBzXeQj0ex4ia5tOIhIUVASkanlZ8NVfYNMs00nE6mLqwcBXoE1/00lEgoqKgFTPuk/hm79B4SHTScRybNDpZrjiWYipYzqMSNBREZDqKzgIs0bChs9NJxGrSO4I/cdCk/NNJxEJWioCUnNp/3UvQpS/z3QSCVZRCXD549DljxASYjqNSFBTEZDTU5wH34+Hn97QqoTiObYQ6DLcXQKiE02nEbEEFQE5M0f2wvxn3UsVu5ym00gga3w+9H8RGnQynUTEUlQExDP2bYS5T8KW70wnkUATWx96j3JPCLTZTKcRsRwVAfGsbQthzhOQudp0EvF3EbWh213Q489aE0DEIBUB8TyXy3254f+ehpwM02nE30TGwwX3wvl3Q1S86TQilqciIN5TVgxL34Ef/q0rDASi68CF97lHASJqmU4jIseoCIj3lZXAuk/gx9dh/wbTacTXYuu7bw503v9BeIzpNCLyOyoC4ltb57kLQfo800nE22o1hIsehNTbICzSdBoRqYSKgJixb6O7EKybDo4S02nEk+q1g253QOfBEBphOo2InIKKgJiVtw+Wvg3L34Oj2abTyOkKi4H217oXAzrrPNNpRKQGVATEP5QUwtqPYNVU2LPCdBqprobnuof+O1yvCYAiAUpFQPzPgc2wZhqsnQ5H9phOI78XEQcdb3AXgAYdTacRkTOkIiD+y+mE7QvdheCXr6E413QiC7NBkwshdRi0uxrCokwHEhEPURGQwFBWDFvnwvoZsOkbKC0wnSj4hYRC0x7QdiC0uQpqNzCdSES8QEVAAk9JofueBlvnwrYFkLvLdKLgER4LzXtCmwHQqp/uAChiASoCEvgOboVt892lYPtinUKoqTotoeUV0LKPewQgNNx0IhHxIRUBCS5OB+xZ6S4G6fNh9zJwlppO5T9sIZDUxn2J31ldIeUiSGxuOpWIGKQiIMGtOB92LoFdP0PWOshaD3l7Tafyneg60OjYk/5Z50GjLrrTn4hUoCIg1lOYfawUrIN9693l4MAvgT9yEBkPdc6GhqnHn/jrnG06lYj4ORUBEQBHqbsMZK13l4Pc3ZCX5R49yNsHjmLTCd2X8NVqAInNIKEZJKYce3/sY03sE5HToCIgUh0FhyAv8/jbkd/8ueAAlB49/lZ2FEqLqi4PIWHulfgia7vfR8T95s+1f/O12lC7ofuJPqGprt8XEY9TERDxJqcTXA73JEbXsT+HhOoJXUT8hoqAiIiIhYWYDiAiIiLmqAiIiIhYmIqAiIiIhakIiIiIWJiKgIiIiIWpCIiIiFiYioCIiIiFqQiIiIhYmIqAiIiIhakIiIiIWJiKgIiIiIWpCIiIiFiYioCIiIiFqQiIiIhYmIqAiIiIhakIiIiIWJiKgIiIiIWpCIiIiFiYioCIiIiFqQiIiIhYmIqAiIiIhakIiIiIWJiKgIiIiIWpCIiIiFiYioCIiIiFqQiIiIhYmIqAiIiIhakIiIiIWJiKgIiIiIWpCIiIiFiYioCIiIiFqQiIiIhYmIqAiIiIhakIiIiIWJiKgIiIiIWpCIiIiFiYioCIiIiFqQiIiIhYmIqAiIiIhakIiIiIWJiKgIiIiIWpCIiIiFiYioCIiIiFqQiIiIhYmIqAiIiIhf0/z1B5XmiiCTgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.pie(\n",
    "    [atxt_yes_tot, atxt_no_tot],\n",
    "    labels = ['Alt-text for all images', 'No alt-text'],\n",
    "    autopct = '%1.1f%%'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47a90940-7989-4f42-a6c6-281b98bdbb85",
   "metadata": {},
   "source": [
    "This first chart shows the overall general use of alt text (image description) in the set of posts under analysis. We notice that more than ⅘ of them *do not* contain any image description. Only 19% of them do."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c586b9c5-a977-4f13-8f2c-9911cb5bb72d",
   "metadata": {},
   "source": [
    "### Analyzing client data\n",
    "\n",
    "In this section, we will analyze the total number of posts per client. During the initial data exploration, we observed that many clients have only one post. Our objective is to explore how many clients fall into this category and determine whether it would be beneficial to treat this group differently to reduce potential noise in the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2be72951-69ec-44f8-ab60-634cb5beac60",
   "metadata": {},
   "outputs": [
    {
     "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>client</th>\n",
       "      <th>posts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Web</td>\n",
       "      <td>8265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>dlvr.it</td>\n",
       "      <td>5806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mastodon for Android</td>\n",
       "      <td>1891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AboveMaidstoneBot</td>\n",
       "      <td>1339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Mastodon for iOS</td>\n",
       "      <td>1051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Buffer</td>\n",
       "      <td>794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Indie 102.3 Playlist Bot</td>\n",
       "      <td>571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Tusky</td>\n",
       "      <td>503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>KUVO Playlist Bot</td>\n",
       "      <td>365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>The Colorado Sound Playlist Bot</td>\n",
       "      <td>361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ivory for iOS</td>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>toot - a Mastodon CLI client</td>\n",
       "      <td>339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Blog2Social</td>\n",
       "      <td>288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>AboveEDXWbot</td>\n",
       "      <td>284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>traffic_incidents_atx</td>\n",
       "      <td>240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Fedica</td>\n",
       "      <td>221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ZohoSocial</td>\n",
       "      <td>210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>CheapBotsTootSweet</td>\n",
       "      <td>196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Publer</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>pkmnFrames</td>\n",
       "      <td>163</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             client  posts\n",
       "0                               Web   8265\n",
       "1                           dlvr.it   5806\n",
       "2              Mastodon for Android   1891\n",
       "4                 AboveMaidstoneBot   1339\n",
       "5                  Mastodon for iOS   1051\n",
       "6                            Buffer    794\n",
       "7          Indie 102.3 Playlist Bot    571\n",
       "8                             Tusky    503\n",
       "9                 KUVO Playlist Bot    365\n",
       "10  The Colorado Sound Playlist Bot    361\n",
       "11                    Ivory for iOS    356\n",
       "12     toot - a Mastodon CLI client    339\n",
       "13                      Blog2Social    288\n",
       "14                     AboveEDXWbot    284\n",
       "15            traffic_incidents_atx    240\n",
       "16                           Fedica    221\n",
       "17                       ZohoSocial    210\n",
       "18               CheapBotsTootSweet    196\n",
       "19                           Publer    164\n",
       "20                       pkmnFrames    163"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "##Count how many posts_counts by client\n",
    "\n",
    "#select columns we want to analyze\n",
    "data_selected = data[['client', 'posts']].head(20) # view only the first 20 clients to get a general overview of how they behave\n",
    "data_selected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "314d5e4a-b913-45a0-8b42-5683111102ab",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from '/home/tommi/dev/mastodon-alt-text/.venv/lib64/python3.13/site-packages/matplotlib/pyplot.py'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#barplot: review top 20 clients with more posts\n",
    "plt.bar(data_selected['client'],data_selected['posts'],color = 'skyblue')\n",
    "plt.xticks(rotation=90)\n",
    "plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ad25c35-604d-4314-bb21-de1a17061889",
   "metadata": {},
   "source": [
    "The bar plot reveals that, among the top 20 clients, the Web client has the highest number of posts (8272), while pkmnFrames has only 163 posts. This highlights a significant disparity in the number of posts even within the top 20 clients, showcasing the wide variation in engagement levels between the extremes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9e99eef6-e53f-4db8-a285-8beb72db3d91",
   "metadata": {},
   "outputs": [
    {
     "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>client</th>\n",
       "      <th>posts</th>\n",
       "      <th>atxt_yes</th>\n",
       "      <th>atxt_yes_pct</th>\n",
       "      <th>atxt_no</th>\n",
       "      <th>atxt_no_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>Mastoot</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>AEGIS FS Poster App</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>Epic News Canada</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>PixelDroid</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>Sanweb</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>Rodent</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>UnitedSpaceCats</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>tgbot-mastodon-sync</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>AutstralianArtGallery_clientcred.secret</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>TweeseCake</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>fsposter a4n</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>pycasso</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>Tusker</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>TZN FS Poster</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>co2ticker</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>Mast</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>koyu.space</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>adactio.com</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>Hexah Digital</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>Erik's Weblog</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>MyGuidedTours</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>gitlab.com</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>Unsplash Daily Image</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>VMC_automated</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>Medieval Images</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>Wabi Wabi pictures</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>yongchieng</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>madonctl</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>Github Action</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>Grafa Page Manager</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>Bridgy</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>Daily Loss Bot</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>PhotosSync</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>DSP</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>DeltaChat Bridge</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>Twidere for Android</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>ABC Gazetesi</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>Pogo Fans</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>Subguide Mastadon</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>x-poster</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>Roma</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>atareao</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>Gerakies</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>Birdhouse Update</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>jazz010live</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>Elk (canary)</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>SocialHub for iOS</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>socialbot</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>PhonocasterMusicShare</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>openvibe</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>iflaapp</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>265</th>\n",
       "      <td>Today's Dérive app task</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      client  posts  atxt_yes  atxt_yes_pct  \\\n",
       "243                                  Mastoot      1         0           0.0   \n",
       "242                      AEGIS FS Poster App      1         0           0.0   \n",
       "240                         Epic News Canada      1         0           0.0   \n",
       "241                               PixelDroid      1         0           0.0   \n",
       "233                                   Sanweb      1         0           0.0   \n",
       "232                                   Rodent      1         0           0.0   \n",
       "239                          UnitedSpaceCats      1         1         100.0   \n",
       "238                      tgbot-mastodon-sync      1         0           0.0   \n",
       "237  AutstralianArtGallery_clientcred.secret      1         1         100.0   \n",
       "236                               TweeseCake      1         1         100.0   \n",
       "235                             fsposter a4n      1         0           0.0   \n",
       "234                                  pycasso      1         1         100.0   \n",
       "229                                   Tusker      1         1         100.0   \n",
       "228                            TZN FS Poster      1         0           0.0   \n",
       "231                                co2ticker      1         1         100.0   \n",
       "230                                     Mast      1         0           0.0   \n",
       "227                               koyu.space      1         1         100.0   \n",
       "226                              adactio.com      1         1         100.0   \n",
       "224                            Hexah Digital      1         0           0.0   \n",
       "225                            Erik's Weblog      1         0           0.0   \n",
       "254                            MyGuidedTours      1         1         100.0   \n",
       "255                               gitlab.com      1         0           0.0   \n",
       "252                     Unsplash Daily Image      1         0           0.0   \n",
       "253                            VMC_automated      1         0           0.0   \n",
       "251                          Medieval Images      1         1         100.0   \n",
       "250                       Wabi Wabi pictures      1         0           0.0   \n",
       "248                               yongchieng      1         0           0.0   \n",
       "249                                 madonctl      1         0           0.0   \n",
       "245                            Github Action      1         1         100.0   \n",
       "244                       Grafa Page Manager      1         1         100.0   \n",
       "247                                   Bridgy      1         0           0.0   \n",
       "246                           Daily Loss Bot      1         0           0.0   \n",
       "214                               PhotosSync      1         0           0.0   \n",
       "215                                      DSP      1         0           0.0   \n",
       "216                         DeltaChat Bridge      1         0           0.0   \n",
       "217                      Twidere for Android      1         0           0.0   \n",
       "218                             ABC Gazetesi      1         0           0.0   \n",
       "219                                Pogo Fans      1         0           0.0   \n",
       "220                        Subguide Mastadon      1         0           0.0   \n",
       "221                                 x-poster      1         0           0.0   \n",
       "222                                     Roma      1         0           0.0   \n",
       "223                                  atareao      1         1         100.0   \n",
       "256                                 Gerakies      1         0           0.0   \n",
       "257                         Birdhouse Update      1         0           0.0   \n",
       "258                              jazz010live      1         1         100.0   \n",
       "259                             Elk (canary)      1         1         100.0   \n",
       "260                        SocialHub for iOS      1         0           0.0   \n",
       "261                                socialbot      1         1         100.0   \n",
       "262                    PhonocasterMusicShare      1         0           0.0   \n",
       "263                                 openvibe      1         0           0.0   \n",
       "264                                  iflaapp      1         0           0.0   \n",
       "265                  Today's Dérive app task      1         1         100.0   \n",
       "\n",
       "     atxt_no  atxt_no_pct  \n",
       "243        1        100.0  \n",
       "242        1        100.0  \n",
       "240        1        100.0  \n",
       "241        1        100.0  \n",
       "233        1        100.0  \n",
       "232        1        100.0  \n",
       "239        0          0.0  \n",
       "238        1        100.0  \n",
       "237        0          0.0  \n",
       "236        0          0.0  \n",
       "235        1        100.0  \n",
       "234        0          0.0  \n",
       "229        0          0.0  \n",
       "228        1        100.0  \n",
       "231        0          0.0  \n",
       "230        1        100.0  \n",
       "227        0          0.0  \n",
       "226        0          0.0  \n",
       "224        1        100.0  \n",
       "225        1        100.0  \n",
       "254        0          0.0  \n",
       "255        1        100.0  \n",
       "252        1        100.0  \n",
       "253        1        100.0  \n",
       "251        0          0.0  \n",
       "250        1        100.0  \n",
       "248        1        100.0  \n",
       "249        1        100.0  \n",
       "245        0          0.0  \n",
       "244        0          0.0  \n",
       "247        1        100.0  \n",
       "246        1        100.0  \n",
       "214        1        100.0  \n",
       "215        1        100.0  \n",
       "216        1        100.0  \n",
       "217        1        100.0  \n",
       "218        1        100.0  \n",
       "219        1        100.0  \n",
       "220        1        100.0  \n",
       "221        1        100.0  \n",
       "222        1        100.0  \n",
       "223        0          0.0  \n",
       "256        1        100.0  \n",
       "257        1        100.0  \n",
       "258        0          0.0  \n",
       "259        0          0.0  \n",
       "260        1        100.0  \n",
       "261        0          0.0  \n",
       "262        1        100.0  \n",
       "263        1        100.0  \n",
       "264        1        100.0  \n",
       "265        0          0.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we want to know how many clients from the 266 clients have only one post, we will filter the data where posts=1\n",
    "data_clients_mode = data[data['posts'] == mode]\n",
    "data_clients_mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e0411592-ca16-4803-be53-ad214f81cd08",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total of clients: 265\n",
      "Clients containing 1 post: 52\n"
     ]
    }
   ],
   "source": [
    "clients = len(data)\n",
    "clients_mode = len(data_clients_mode)\n",
    "\n",
    "print(f'Total of clients: {clients}\\nClients containing {mode} post: {clients_mode}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "97d98621-2e08-48b4-b4c2-a6dc73ac6827",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Around 19.6% of the clients in the data set have only one post\n"
     ]
    }
   ],
   "source": [
    "clients_mode_pct = (clients_mode/len(data))*100\n",
    "print(f'Around {round(clients_mode_pct,1)}% of the clients in the data set have only one post')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6935c05d-c85b-4e34-a32c-8c63143def9d",
   "metadata": {},
   "source": [
    "The `posts_count` analysis groups the number of posts and counts how many clients fall into each group. For example, there are 52 clients with only one post, 31 clients with two posts, and so on. This distribution clearly indicates that a significant portion of clients have only one post. Such a notable concentration suggests it might be more meaningful to treat these single-post clients as a separate cluster and analyze them independently to reduce potential noise in the dataset and gain more targeted insights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "90efde94-a866-4d5f-bfc9-cda6a245448e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "posts\n",
       "1       52\n",
       "2       31\n",
       "3       18\n",
       "4       14\n",
       "5        7\n",
       "        ..\n",
       "1051     1\n",
       "1339     1\n",
       "1891     1\n",
       "5806     1\n",
       "8265     1\n",
       "Name: count, Length: 79, dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "Comparing this with the entire data set:\n",
    "we want to count how many clients have the same number of posts.\n",
    "'''\n",
    "posts = data['posts'].value_counts().sort_index()\n",
    "posts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ccae38ba-77a4-4935-a283-8c19f2209b51",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Frequency of total posts counted by client')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a bar plot\n",
    "plt.figure(figsize=(20, 20))\n",
    "bars = posts.plot(kind='bar', color='skyblue')\n",
    "\n",
    "for idx, value in enumerate(posts):\n",
    "    plt.text(idx, value, str(value), ha='center', va='bottom', fontsize=10, color='black')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel(\"Number of Posts\")\n",
    "plt.ylabel(\"Number of Clients\")\n",
    "plt.title(\"Frequency of total posts counted by client\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56aee64e-836c-4fed-8f18-ea1f27cd6483",
   "metadata": {},
   "source": [
    "The Frequency of total post clients shows how there is a big amount (52 out of 265) clients that have only one post. Furthermore, we can observe that the majority of clients that contains between 1 and 4 posts. For these reason, we will follow the analysis by separating the data set. Initially, we will be anaylzing all the clients that have more than 4 posts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "851a31ee-44bd-488d-8b5c-5bf7d1875957",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Frequency of total posts counted by client')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Let's take a closer look : Filter out post counts with less than 4 posts, based on the data it still be a higher number of clients for those.\n",
    "posts = posts[(posts.index >= 1) & (posts.index <= 4)]\n",
    "\n",
    "# Ensure the values are numeric\n",
    "posts.astype(int)\n",
    "\n",
    "# Create a bar plot\n",
    "plt.figure()\n",
    "posts.plot(kind='bar', color='skyblue')\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('Number of Posts')\n",
    "plt.ylabel('Number of Clients')\n",
    "plt.title('Frequency of total posts counted by client')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c15bb9d-ac0a-40c7-8561-c8328ce3e80f",
   "metadata": {},
   "source": [
    "Clients that have more than 4 postsThe previous graphs highlights that the majority of clients in the dataset have either one or two posts. This behavior suggests a distinct pattern that warrants separate analysis for these clients. To better understand their impact and characteristics, we will proceed by dividing the dataset into two groups: one consisting of clients with one or two posts, and the other including all remaining clients. This approach will allow for a more focused and meaningful analysis of each group."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e610ac04-7296-4047-9aa3-cdfaf6b2950a",
   "metadata": {},
   "source": [
    "### Clients that have more than 4 posts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c344c523-50be-440a-b7e2-336e1471b7d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "150"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Separate data set by excluding 52 clients with only one post\n",
    "\n",
    "cl_more_post = data[data['posts'] > 4]\n",
    "len(cl_more_post)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ce029bd1-bc92-480d-b4c8-f078dbc5aa58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(cl_more_post)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d3036351-1efa-4e02-b702-39faf7f40926",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sort the data frame from the clients with the highest percentage of alt text use\n",
    "cl_more_post = cl_more_post.sort_values('atxt_yes_pct', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8445d35d-4ef6-4b80-b3b2-84db0de08e39",
   "metadata": {},
   "outputs": [
    {
     "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>client</th>\n",
       "      <th>posts</th>\n",
       "      <th>atxt_yes</th>\n",
       "      <th>atxt_yes_pct</th>\n",
       "      <th>atxt_no</th>\n",
       "      <th>atxt_no_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>pkmnFrames</td>\n",
       "      <td>163</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>163</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>traffic_incidents_atx</td>\n",
       "      <td>240</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>240</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>AboveEDXWbot</td>\n",
       "      <td>284</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>284</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AboveMaidstoneBot</td>\n",
       "      <td>1339</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1339</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>MicroTrailers</td>\n",
       "      <td>49</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49</td>\n",
       "      <td>100.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>BisaBoard</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>SocialBu</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>The Pink Zune</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>LostFilm push</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Postpone.app</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>72 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    client  posts  atxt_yes  atxt_yes_pct  atxt_no  \\\n",
       "20              pkmnFrames    163         0           0.0      163   \n",
       "15   traffic_incidents_atx    240         0           0.0      240   \n",
       "14            AboveEDXWbot    284         0           0.0      284   \n",
       "4        AboveMaidstoneBot   1339         0           0.0     1339   \n",
       "53           MicroTrailers     49         0           0.0       49   \n",
       "..                     ...    ...       ...           ...      ...   \n",
       "143              BisaBoard      6         0           0.0        6   \n",
       "146               SocialBu      5         0           0.0        5   \n",
       "145          The Pink Zune      5         0           0.0        5   \n",
       "148          LostFilm push      5         0           0.0        5   \n",
       "147           Postpone.app      5         0           0.0        5   \n",
       "\n",
       "     atxt_no_pct  \n",
       "20         100.0  \n",
       "15         100.0  \n",
       "14         100.0  \n",
       "4          100.0  \n",
       "53         100.0  \n",
       "..           ...  \n",
       "143        100.0  \n",
       "146        100.0  \n",
       "145        100.0  \n",
       "148        100.0  \n",
       "147        100.0  \n",
       "\n",
       "[72 rows x 6 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How many and which are the clients that do not have alt text in their images\n",
    "no_atxt_cl_more = cl_more_post[cl_more_post['atxt_yes'] == 0]\n",
    "no_atxt_cl_more"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "82bf6f3b-54d9-4f61-a496-13ec201d2a10",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 72 clients whose posts do not have any alt text.\n"
     ]
    }
   ],
   "source": [
    "print(f'There are {len(no_atxt_cl_more)} clients whose posts do not have any alt text.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4ac7fc4-0eb1-45e0-a3c9-e984df873a5a",
   "metadata": {},
   "source": [
    "We arbitrarily choose to set 60% of alt text use as a threshold to investigate current data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4b1ca61c-522b-4d35-87b2-cf68d6dbcdcb",
   "metadata": {},
   "outputs": [
    {
     "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>client</th>\n",
       "      <th>posts</th>\n",
       "      <th>atxt_yes</th>\n",
       "      <th>atxt_yes_pct</th>\n",
       "      <th>atxt_no</th>\n",
       "      <th>atxt_no_pct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>KUVO Playlist Bot</td>\n",
       "      <td>365</td>\n",
       "      <td>365</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Indie 102.3 Playlist Bot</td>\n",
       "      <td>571</td>\n",
       "      <td>571</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>The Colorado Sound Playlist Bot</td>\n",
       "      <td>361</td>\n",
       "      <td>361</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>BirdBuddy</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>Bohn Temps Hourly Poster</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>ActivityPub.jl</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>TheInsiderByNB</td>\n",
       "      <td>44</td>\n",
       "      <td>44</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Pokémon Facts</td>\n",
       "      <td>41</td>\n",
       "      <td>41</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>EveryPkmnCard</td>\n",
       "      <td>41</td>\n",
       "      <td>41</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>My User Count</td>\n",
       "      <td>41</td>\n",
       "      <td>41</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Posting the people that do not exist</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Anthologia Graeca</td>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>ICM</td>\n",
       "      <td>36</td>\n",
       "      <td>36</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Bot</td>\n",
       "      <td>38</td>\n",
       "      <td>38</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>NoSoloBot</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>pytooterapp</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Flame Reactor</td>\n",
       "      <td>55</td>\n",
       "      <td>55</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>startrekscreens</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>fediverse</td>\n",
       "      <td>78</td>\n",
       "      <td>78</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>livelakemichigan</td>\n",
       "      <td>80</td>\n",
       "      <td>80</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>python bot</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>TheMoscowTimesByNB</td>\n",
       "      <td>114</td>\n",
       "      <td>114</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>retroVideoGameAdPublisher</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>WikiUntamedPoster</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>FediPlan</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>upcomingtrader blog</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>whatscoolwithu</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>antitrust_bot</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>bot</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>CracktroBotPublisher</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>s2coastalbotapp</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>Anarchist Art</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>StorePageTooter</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>Bots.law</td>\n",
       "      <td>12</td>\n",
       "      <td>12</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>GRP Server</td>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>rtoot package</td>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>PilgrimsOnline</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>Random mars photo</td>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Toot schedule</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>Grass Posting Bot</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>Tweepsmap</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>83.3</td>\n",
       "      <td>1</td>\n",
       "      <td>16.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>EchoFeed</td>\n",
       "      <td>22</td>\n",
       "      <td>17</td>\n",
       "      <td>73.9</td>\n",
       "      <td>5</td>\n",
       "      <td>21.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>Mona for Mac</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>64.3</td>\n",
       "      <td>4</td>\n",
       "      <td>28.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>Phanpy</td>\n",
       "      <td>22</td>\n",
       "      <td>14</td>\n",
       "      <td>63.6</td>\n",
       "      <td>8</td>\n",
       "      <td>36.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   client  posts  atxt_yes  atxt_yes_pct  \\\n",
       "9                       KUVO Playlist Bot    365       365         100.0   \n",
       "7                Indie 102.3 Playlist Bot    571       571         100.0   \n",
       "10        The Colorado Sound Playlist Bot    361       361         100.0   \n",
       "129                             BirdBuddy      9         9         100.0   \n",
       "121              Bohn Temps Hourly Poster      9         9         100.0   \n",
       "118                        ActivityPub.jl     10        10         100.0   \n",
       "55                         TheInsiderByNB     44        44         100.0   \n",
       "63                          Pokémon Facts     41        41         100.0   \n",
       "61                          EveryPkmnCard     41        41         100.0   \n",
       "60                          My User Count     41        41         100.0   \n",
       "66   Posting the people that do not exist     40        40         100.0   \n",
       "75                      Anthologia Graeca     29        29         100.0   \n",
       "72                                    ICM     36        36         100.0   \n",
       "70                                    Bot     38        38         100.0   \n",
       "82                              NoSoloBot     23        23         100.0   \n",
       "85                            pytooterapp     22        22         100.0   \n",
       "52                          Flame Reactor     55        55         100.0   \n",
       "54                        startrekscreens     45        45         100.0   \n",
       "42                              fediverse     78        78         100.0   \n",
       "38                       livelakemichigan     80        80         100.0   \n",
       "35                             python bot     82        82         100.0   \n",
       "28                     TheMoscowTimesByNB    114       114         100.0   \n",
       "136             retroVideoGameAdPublisher      7         7         100.0   \n",
       "137                     WikiUntamedPoster      7         7         100.0   \n",
       "149                              FediPlan      5         5         100.0   \n",
       "138                   upcomingtrader blog      7         7         100.0   \n",
       "150                        whatscoolwithu      5         5         100.0   \n",
       "130                         antitrust_bot      8         8         100.0   \n",
       "133                                   bot      8         8         100.0   \n",
       "124                  CracktroBotPublisher      9         9         100.0   \n",
       "140                       s2coastalbotapp      6         6         100.0   \n",
       "116                         Anarchist Art     11        11         100.0   \n",
       "110                       StorePageTooter     12        12         100.0   \n",
       "111                              Bots.law     12        12         100.0   \n",
       "115                            GRP Server     11        11         100.0   \n",
       "102                         rtoot package     14        14         100.0   \n",
       "91                         PilgrimsOnline     19        19         100.0   \n",
       "92                      Random mars photo     19        19         100.0   \n",
       "132                         Toot schedule      8         8         100.0   \n",
       "126                     Grass Posting Bot      9         9         100.0   \n",
       "139                             Tweepsmap      6         5          83.3   \n",
       "80                               EchoFeed     22        17          73.9   \n",
       "100                          Mona for Mac     13         9          64.3   \n",
       "83                                 Phanpy     22        14          63.6   \n",
       "\n",
       "     atxt_no  atxt_no_pct  \n",
       "9          0          0.0  \n",
       "7          0          0.0  \n",
       "10         0          0.0  \n",
       "129        0          0.0  \n",
       "121        0          0.0  \n",
       "118        0          0.0  \n",
       "55         0          0.0  \n",
       "63         0          0.0  \n",
       "61         0          0.0  \n",
       "60         0          0.0  \n",
       "66         0          0.0  \n",
       "75         0          0.0  \n",
       "72         0          0.0  \n",
       "70         0          0.0  \n",
       "82         0          0.0  \n",
       "85         0          0.0  \n",
       "52         0          0.0  \n",
       "54         0          0.0  \n",
       "42         0          0.0  \n",
       "38         0          0.0  \n",
       "35         0          0.0  \n",
       "28         0          0.0  \n",
       "136        0          0.0  \n",
       "137        0          0.0  \n",
       "149        0          0.0  \n",
       "138        0          0.0  \n",
       "150        0          0.0  \n",
       "130        0          0.0  \n",
       "133        0          0.0  \n",
       "124        0          0.0  \n",
       "140        0          0.0  \n",
       "116        0          0.0  \n",
       "110        0          0.0  \n",
       "111        0          0.0  \n",
       "115        0          0.0  \n",
       "102        0          0.0  \n",
       "91         0          0.0  \n",
       "92         0          0.0  \n",
       "132        0          0.0  \n",
       "126        0          0.0  \n",
       "139        1         16.7  \n",
       "80         5         21.7  \n",
       "100        4         28.6  \n",
       "83         8         36.4  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cl_more_post_pct = cl_more_post[cl_more_post['atxt_yes_pct'] >= 60]\n",
    "cl_more_post_pct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "5469141b-b6e0-41ad-9e51-5973ad3b4847",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "44 clients have more 60% than of the posts with image description.\n"
     ]
    }
   ],
   "source": [
    "print(f'{len(cl_more_post_pct)} clients have more 60% than of the posts with image description.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "1859c761-8b79-41e0-9d20-953f59e50ccb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from '/home/tommi/dev/mastodon-alt-text/.venv/lib64/python3.13/site-packages/matplotlib/pyplot.py'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a bar plot\n",
    "plt.figure(figsize=(20, 20))\n",
    "plt.bar(cl_more_post_pct['client'],cl_more_post_pct['atxt_yes_pct'],color = 'skyblue')\n",
    "\n",
    "# Add percentage values inside the bars\n",
    "for i in range(len(cl_more_post_pct)):\n",
    "    x = cl_more_post_pct['client'].iloc[i]  # Get the x position for the bar\n",
    "    bar_height = cl_more_post_pct['atxt_yes_pct'].iloc[i]  # Get the height of the bar\n",
    "    \n",
    "    # Annotate the percentage value\n",
    "    plt.text(x, bar_height, f'{bar_height:.1f}%', ha='center', va='bottom', color='black', fontsize=10, rotation=90)\n",
    "\n",
    "    \n",
    "plt.xticks(rotation=90)\n",
    "plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "169cb74c-cbcb-4b6a-9318-147a7c8fa6c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_58376/2347707260.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  cl_more_post_pct['label'] = cl_more_post_pct.apply(lambda row: f'{row['client']}\\n{row['atxt_yes']} posts\\n({row['atxt_yes_pct']:.1f}%)', axis=1)\n"
     ]
    },
    {
     "data": {
      "image/png": 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IiIiIiIiIiIiIiIjIW6WmJREREREREREREREREREREREReavUtCQiIiIiIiIiIiIiIiIiIiIiIm+VeWoXICIiIiIiIiIiIiIiIiKv5tT542zasYFLwRe5FxnB0K6jKZqvhOF+YmIin361nEMnfyPszi3sbOwIyp6PVnXbk845farVfeLcMQZP6cOGOVuwt7VPtTpEREQk9WmnJREREREREREREREREZF3TGx8LH6e/nRu1uOZ9+PiY7l8/SKNP27O7BELGdJ1FCFhNxg9Z+hbr1VERETkWbTTkoiIiIiIiIiIiIiIiMg7pkCuwhTIVfi59+1s7RnXd4rRWOemPeg9tgu3I8LJkM71mXmDJvfGx8MXgJ/2/4i5mRlVS9egWa3WmJiYABD1OIrF6+by2/H9JCYmkDMgDx2bdMPD1ROA23fDWLB2NqcvniIxMRHX9K60qd8Rb3dfBk/pA0DD7jUAKFesEn3aDmTPoV9Yu+VTbt0OxcrSmkzemRnefQzWVjavacVE5L/skb9tapfwxpTNdjK1SxB5C/L+oyw1LYmIiIiIiIiIiIikstNHDjKyeztWfrcbOwfH1C7nnTSiW1t8M2elda8BqV2KiMh/1uOYx5iYmPztsWw7935PxZJVmDF0HheDLzBn1XRc0magcqnqAMxYPomb4aEM7z4WWxs7VnyxmJEzB7NgzArMzc2Zv2Y2iYkJTB44Eysra27cvIaNlQ3p07rwSZeRjJ8/ksXjVmFjY4eVhSX3HkQwefFYWtfrQLF8JYmJjebUhZOkpLylhREREZFUoaYlERERERERERERkTeofvE8L77fphM58hZ4Lc/qUrcKd8Ju0mvURIqXr2J0r3fT2oQEX6HLJ6MpU63ma3ne23D7Vihd61V9YUyXT0bTb/x0zM1S91vec8cO45ftWwzX9o5p8M+Wg+ZdeuOTOeCl5xnRrS1njh566uu4bcNqtm1cw/xN2wHYtW0z88cPN9y3srHB3duXui3aUbh0+df2XiLyfohPiGfFF4spVagstjZ2L4xNnzYD7Rt1xcTEBM+M3gSHXOHrHzZRuVR1QsND+O3YPqYMnk32zDkB6N/+E1r1b8T+o3soWbA0d+7dpni+kvh6ZgLAzcXdMLeD3ZPm3DSOzobmqVt3bpKUlETxfCXJkD4jgCFXRERE3l9qWhIRERERERERERF5gxZv2Wn4fN/OHWxYOp9Z6zYbxqxtbLly7vRre14614zs2rbZqNnlwqkTPLgXgZXNu3fETroMGY3W8Jt1qzh2YC/DZi02jNna22NlZZ1KFRoLKlKcLp+MBuBBxF3WL5nLhAHdWfjljleax8LSinWL51G4dHnMzS2eG2djZ2/48xQb/Zhd2zYzffgApn/2JR4+vv/ybUTkfZGYmMiEBaMgJYWuzXv9bXxgpmyGo+AAAv1z8NX3n5OUnMSNW9cwMzMja6ZshvuO9mnwcPXixq3rANQoV5t5q2dy5MwhgrLlp3j+kvh5+T/3eX5e/uTJlo8uI9qRL0cB8uUoQPECpXCwc/jX7y4iIiL/XaapXYCIiIiIiIiIiIjI+8w5XXrDh62dPSYmJkZjNra2htgr588ysE1jmpYtzJCOLQi9Fmw018HduxjQuiFNyhSka/2qfL58IUmJiUYxJStU5cyxw9wNDzOM/bTta0pWrIrZ/9uJ6E7YLSYN7Emz8kVoUaEY04f158G9CMP94IvnGdmtLc3LF6VFhWIMaNOIy2f/bLA6d+IoI7q1pWnZwrSqXIKxvTvx6OFDABLi41k+YyJtq5WmSZmCDO3ckktnTxlyB7ZpzJa1qwzXkwf1otFH+YmJjgYg4nY49Yvn4fatUKP1sraxxdTM3GjMysqaEd3asmLmZMN8XepWYdPKxcwZM4Rm5YvQuU5lDu7+mcj79wzv3LdFPaP3ATh7/AjDOreiSZlCdKpdkeUzJhIbE224v+PLDXRv+DFNyhSkXfUyTB3S1yjfwsLSUJdfQCC1mrUhIjyMyPv3ABjZvR1Lp403yom8f49GpfJz8tBvhrESFSoT/SiKnVu+5EX++ufJzcuHRh26YWJiwvXLF16YJyIfjsTERCYuHMWdiHDG9p3yt7ssvQ6VPqrGsolrKFu0AsGhV+g1pjNbdj7/7zMzUzPG9Z3C6F4T8Xb35ZufvqbjkJaE3bn1xmsVERGR1KOmJREREREREZH30KARHVm8YlpqlyEiIq9o3aI5tOjel4nL1mJmZsaCCSMM984eO8KcMUOpWr8pM1Z/RYf+w9j17Wa+/HSp0RxOadORp1AxwzFlcbEx7Nu5gzLVahnFJScnM3lQTx49jGTU3OUMm7mQ8NAQZgwfYIiZPWowaTO4MnHZWiYtX0ftZm0wM3/S+HT1wjlG9+yAp28mxi36lDHzV5K/eCmSk5MA+Gz+DA78/CPdho5l0vL1ZPTwZmzvzkQ9jAQge978nD56EICUlBTOHj+CrYMD504cBeDM0UOkdcmAm6f3P17PrRtWE5griCkrNpCvWEnmjBnC3LFD+ahSNSYvX4+rhydzxg4lJSUFgLCQG4zr24Uipcsz7dPP6T16MudOHGXZ9AkAXD57muUzJ9GwXRdmrdvMkOnzyR6U77nPj4mOZveObWT09MYhjRMA5T6uw54ftpMQH2+I271jG2ldMpAzfyHDmI2tPXVatOPzFYuMmqZeJCkpyfB19wvI9rfxIvL++1/D0s3wUMb1m4qjfZqXyjt/9azx9ZUzuGfwxMzUDC83H5KSkjh/5c+Yh48iCQ2/gbe7j2HMJW0GqpauwdCuo6ldqT47fv0WAPM//j/yv/9f/I+JiQnZs+SkWa1WzB6xCHNzc/Yf2fOv3l9ERET+29S0JCIiIiIiIvIOmj53JNXqF3zq4+atG6ld2t8aNKKjod5aTYrTvkddNn61wvAD47ch/PZNqtUvyOWr59/aM0VEXkbjjt3JkbcAXn7+1GrWhvMnjxEfFwfA5ysWUrtZG0pXrYGrhyd5ChWlUfuu/PD1F0/NU7Z6LXZ9u4WUlBQO7PqRjB6e+AUEGsWcPPQb169coufIifgHZidLjtx0GzaWM0cPGXZEuhseRu4CRfDw8cPNy4eiZSvimyUrAJvXriRTYHba9xuCb5aseGXKTJV6jXF0ciY2Jprvv9pI8659yFu0BF5+/nQaNBxLKyt++uYrAHLkLcC5E8dISkri2qULmFtYULJCVUMj0+mjh8geVOBfrWfeoiWoUKs+bl4+1GvdkZjHj/APzEHRshVx9/alVtM2hAZfMewu9dVnyyhZsSrVGjbDzcuHrLmCaN1rIL98t5X4uDjuht/CytqG/MU+wiWjO34B2ahav6nRMw/v+5Vm5Yv8sXtVUQ7t+YXeoydjavrk2/GFS5WDP3bN+p+ft2+hTNWaRkcxAVSq0xBLSyu2rv/sue8Y/SjK8LzGpQuwZOo4Og4YTkZPr3+1diLy3xcTG8Pl65e4fP0SAGF3b3H5+iVuR4TDHw1L4xeM5GLwBfp1GEJScjL3Iu9xL/IeCYkJL5z7TsRtlqyfT0jYdX7+bSff7PyKmuXrAODh6kmRoOLMWTWN0xdPcuXGZaYumUA6p/QUCSoOwOJ1czl86iBhd25x6doFTpw7hpfbkybUDOlcMTEx4ffjB4iMekBMbAznrpxlw7Y1XAw+z+2IcPYd3k1kVCRe7v+8cVVERET++8xfIkZERERERERE/oPyBxWlV5fhRmNpHJ1TrZ5XUalcLZo17EhiYgLHTx1kzqLx2Nk6UK1SvdQu7ZUlJiYafltcROTf8vbPYvjcOX16+OPoMJeMbgRfusC5E8fY9OkSQ0xyUjIJ8XHExcZgZW1jGM9XtCSLJo/hzLHD/LTt66d2WQIIvXaFdBlcSe+a0TDm5eePnYMDocFXyZwtJ9UbNWfhxFH8umMruQoUpmiZioZmmOCL5ylapsIz3yM8NISkxEQCcwcZxszNLcicPSeh164AkC1PPmKiHxN84RznTx0je1B+cuQrwNefLQfgzLFD1GjS6l+tp49/gOFzp7Tp/hj7c43TpE0LwMP793BOl55rly5w7fIFdn//7Z+TpKSQkpzM7Vuh5C5YFJeMbnRtUI2gwsXIW7g4hUqVNVr7HHkL0r7/EAAeRz1kx5cbGN+3CxOWrsElozuWVlZ8VLk6P237mmLlKnHl/FmuX7nEwEmznqrfwtKShu26sGzGRCrWbvDMd7SxtWPSivUAxMfGcuLQAZZMHYtDmjQUKFH6X62fiPy3XQw+z+ApfQzXSzcsAKBcsUr0aTuQiAd3+e3YPgC6j2xvlDuh/3RyBwbxPGWLVSQ+IY7eY7tiamJKjfJ1qVyquuF+rzYDWLxuLqNmfUJiUiI5AnIzstcEw7+Lk5KTWbBmFnfv3cHWxo78OQvSvlEXANI7u9C0ZitWblrCzBWTKVu0IvWqNOLUhRNs/mET0TGPyZDOlXYNOlEgV+HXvGoiIiLyX6LvqImIiIiIiIi8oywsLEnrnP6lYn/65Vs2f7ue0JvXsLKyJk/OgnRo3QenNE9+WHvi9GEGj+zE6CGzWblmLiGh1wgMyMXA3uO4dOUsS1bNJOLeHQrlK0GPzkOxtrKGP44W+mLzKr774WvuP4jAw92bRnXbUqJouRfWY21lbai9QpkafLP9c46e+M3QtJSQEM+qdfP5dc/3PIqOwsfLn9bNupM7R34AHkY9YMGyKZw+c5RHjx+S0dWTBnVaU7pEJcMzkpOT+fKb1Xz3w1fciQjHOU1aKleoQ6O6bWjTtSYAPQY0AyBX9nxMHLWI5ORk1m9axnc/fk3kw/t4efjSqmk3CuQtBn/s0NSma00G9hrHth1fcP7Sabq2H0SFMh+/8tdPRORZjJsgn+y6k5KSDEBsdDQN23WmUKmn/461sLQyujYzN+ejStXZuGwBF0+fpP/4Gf+ongZtO1OiQhWO7NvN0QN72LhsAb1GTaJwqXJYWlm9xAzPZ+fgiG/mAE4fPcSFU8fJXbAI2YLyM2P4AG5eD+bWjetkD8r/r57x1/X83y5GZs8YS07+Y41joqlQsx5V6jd5aq70rm5YWFgwefl6Th89xPHf97Nh6Xw2Ll/IxKVrsHNwBMDaxsboSDu/QdloWak4P275ksYdusEfR8T1b9WAiNvh7Nr2NTnzFcIlo/sz36FkpWpsWbeKTSuXkMHt6RgTU1Oj5/lkDuD47/v5es0KNS2JvOdyBwaxbdlPz73vmj7jC++/iLmZGR0a96Rr897PvO9g50DfdoOfm9+5aY8Xzt/44+Y0/ri50diY3pP+Ua0iIiLy7lLTkoiIiIiIiMgHIDEpkeaNOuLh7kNk5H2WrJrBjHmjGPWJ8a4OazcuoXPbAVhZWTNx+mAmTh+MhYUlA3qOJSY2mnFT+vPN9g3Ur9USgI1frWTX7u107TAIdzcvTp05ytQ5w0nj6ESuHH//g+aUlBROnztGyM1gPNz+PMZmwbLJXA+5yoDe40jn7MK+33cxfFwP5k1bh4ebN/Hx8WTOFEi9mi2wtbXj4JG9TJszAjdXT7JmyQHAyrXz2PHj17Rv1ZscgUHcu3+XkJvBAMyYsJLeg1sxbvg8vD0zYWFuAcDmb9fz1Tdr6NbxE/x9A/h+1zeMmdSX+TM24OH25w+EV66ZR9uWPfH3zYql5b/7ob2IyMvKlDUbodeDjRpUXqRs9Vp8s24VxcpVwt7R8an7Hj6ZiLgdzt3wMMNuSzeuXuZxVBSevpkMce7evrh7+1K9UXNmjhjIrm2bKVyqHD7+WTh5+Dcatuvy1NyuHp6YW1hw7sQxQzNOYmICl8+eplqDZoa47EEFOHXkIJfOnqJxx+44OKbBwycTX65ainM6F9y9ff/RWv1TfgHZCAm+8sI1NjM3J3fBIuQuWIT6bTrSqlJJTh3+ncKlyz8z3sTEBFMTU+LjYg1jPv5Z8A/Mzo9bNrHnh+207fP8H/ybmprSpFMPpn7Sh4q1nr3b0tM5ZoZjBUVERERERP6r1LQkIiIiIiIi8o76/fAe6jb7yHCdP28xPuk78ZmxFcvWMHzu5upJpzb96DWoJTEx0djY2BruNW/cieyBeQCoULYGq9bOY+ncr3Bz9QSgeJFynDh1iPq1WpKQEM/Gr1Ywbtg8smXNbZj7zLnjbP/hqxc2LW3b8QU7dm4mMTGBxKRELC2s+LhqQwBu3wnjh11bWbngG9KldQGgbo3mHD62nx93fUPLJl1Jny4DdWv8+ZvZNao05MixA+ze/wNZs+QgOuYxW75dT+e2/Slf+skxFm4ZPcmR7ckRGP87Rs/BPo3RblVfbVlNvVotKVW8IgBtmnXn5KlDbN62ji7tBhrialZrRPHCZV/q6yQi8rrUa92Bif174OLqRpHS5TExNeXapfNcv3LZsIPPX3n6ZmL5t79gaW39zPlyFyyCd6bMzB41mFY9B5CUlMjSqePJnrcA/tlyEBcXy2dzp1O0TAUyuHsQcTucS2dPU6T0k52eajdvS98W9VgydRwVa9XH3MKCU0cOUrRMBRydnKlYqwGfzZuOvWMa0rtmZPOalcTFxlK2em1DDTnyFWD7pnU4Ojnj4eP3ZCxvAb77cv1zj557k2o1a80nHZqzdNp4yn1cB2sbG0KCr3D89/206/sJh/f+QvjNELLlyY+9oyNH9u8hOSXZqLkqISGe+xF34Y/j4b7btJ7YmGgKFC9l9KxyH9dh2fQJWFnbUOijF/8/JX+xj8iSPRc/bP7CcMzd/6SkpBieFx8Xy4mDBzj++z7qterwGldGRERERETk9VPTkoiIiIiIiMg7KneO/HRtP8hwbW1t89zYi5fPsvbzxVwNvsijx1Ek/3HU0J27YXh7/bmbhp93FsPnzk5psbKyNjQsATilScuFS6cBuBl2g7i4WIaOMf5BeWJiApn8sr6w9tIlK9OwThsePX7Imo2LyZY1N9mzPmmWCr5+ieTkJDr0qGuUk5AYj6N9GgCSkpLY+NUKdu/7kYh7d0hMTCAhMR6rP46tuxESTEJCPHlyFnxhHX8VHf2IiPt3yP5HA9b/ZAvMw9Xgi0ZjWfyzv/S8IiKvS1Dh4gyaMpsvVizm69UrMDM3x8PHl3If13lujkMap+feMzExYcDEWSyfMZHhXVtjamJKUJHitOn95P8tpqZmPHoYyZyxQ4m8F4FDGicKlypHg7ZPdlZy9/Zl6IyFrFs0h8Htm2JpZUXm7LkoUb4yAE079yQlJZk5Y4YQG/2YTIHZGTpjgdGuT4F58pGSnGx0DFyOfAX49vM15Mhb4LWs26vwyRzAqHnLWLdoDsO7tCaFFDJ6eFGs7JPjR23tHfjtl5/YuGwhCfHxuHl502vkRLwyZTbMcezAXjrUeNLYZWNrh7uPL33GTCVHPuP/JxUvX4WVsyZTokKVlzpqr2mXXgzt2OKp8ZjHjwzPs7C0JL2rGw3bdqFms9b/ej1E5MM0ccA/O1JURERE5FWpaUlERERERETkHWVtbYP7X45Ue57Y2BiGj+tOvjxF6NdzDGkcnblzN4xhY7uTkJhgFGtm/tdvFZhgbmb8rQMTExOSk580PMXExgAwcvAM0qXNYBRnYWHxwprsbO0NtQ/qPYF23WuTNUtO8uYuTGxsNKamZsya9CmmpmZPvTPApi2fseXb9bRv1Qdf78xYW9mweOV0Ev94H6s3fGTb/5qjREReVZlqNSlTreZT4znyFeTzvceNxvwCAp8aCypcnKDCxZ87//xN21/4/FU79hhdu2R0Y+CkWc+MtbCwoNeoSS+cL0feAoxduOqZ9yytrGjTe5ChCepZHBzTsHHPMaOxQh+Vfeq9/6pB2840aNv5qfFRc5cZXT9rLf7/vBncPJ4ay5wtJ8NmLnrms7PlyffUc/6q29AxdBs65rn3/yoq8j7x8fFGO0/9z7OekTVnnqdqfd6fJxERERERkXeBaWoXICIiIiIiIiJv1o3QYB5GRdKqaTdyZsuLl4cvDyLv/et5vT39sLCw5M7dcNzdvIw+XNJnfOl5bGxsqVmtEcs+nUVKSgr+fllJTk7iwcP7T837v6Pczp4/TuECpSj7UVUy+QaQ0dWD0FvXDXO6u3lhZWnF8VMHn/lMc/MnTVX/a8ACsLW1J52zC2fOnzCKPXvuON6efq+8PiIiIs+SmJjA/Yi7rF88l4AcucmUNVtqlyQi76CHjyJp0qsO4XfDUruUN2LFF4tZsGZ2apchIiIib5h2WhIRERERERF5z2VInxFzcwu+2b6RKhXrcO36ZdZ/8fxdIl6WrY0ddT5uxpJV00lOSSZHYBCPox9x5vxxbG3sKF+6+kvPVaV8HdZ/sYy9B36iRNFylC5ZmelzRtK2ZU/8fbMS+fABx0/9jq93FgrlL4F7Rm/2HtjJmfPHsbdz5Outa3jwIMLQXGRpaUW9Wi1Z/tkczM0tyJ41D5EP73PtxhUqlauJUxpnrCytOHxsP+nTZcDSwgo7O3vq1GzGmg2LcXP1IJNvAD/s+oYrwRfo1/Plds0QERH5O+dPHGNk93a4efnQd9y01C5HRN5RG7auoUhQMVz/+GWBhWvncObSKa6FBuPl5s3ckUueyrl64zIL1szmwtVzpHFw4uNytalXpZFRzO6DP7P66xWE3w3D3dWT1vXaUzB3kRfWcuLcMZZumM+1m9dwSetCw2rNqFCisuH+rgM/svKLJcTExVCheGXaN+piuBd+N4yh0wcwa9gCbG3sDON1KjWk7aCm1KpYDzcX93+1ViIiIvLfpaYlERERERERkfdcmjTO9O46gk/XzmfL9g34+2WlbYuejJ7U91/P3bxRJ9I4OvH5VyuZEx6KnZ0D/n5ZaVin9SvN4+CQhrKlqrH288UUK1yG3l1GsH7TMpatmkXEvds4OjqRNUtOCuUrCUCjum0Iux3K8LE9sLKypnL5WhQtVJrH0Y8Mczaq2xZTUzNWb1jEvXt3cHZOT9WKdQAwMzOnY5t+rPt8KWs2LCJHtiAmjlpEjSqNiI5+zNJPZxEZeQ8vTz+GDZyGh5v3v14rERERnnMUoIjIq4iNi+X7PdsZ09v4CM+KJapw/spZroZceSonOuYxQ6cPICh7fro270VwyFVmrZyCna09VUo9+WWDM5dOMXnxWFrVbUfB3EX55bedjJ07nFnDF+H7nJ1Hw+7cYuSsT6ha+mP6tR/C8bNHmL1qKmmd0pE/Z0EioyKZvXIqvdsMJKOLGyNnfUKebHkplKcoAPNXz6RV3XZGDUsAaRzSkC9HAb7dtYW2DTq9xtUTERGR/xKTlJSUlJcJDI3a8OarERERERERkQ/O8R3+qV2CiLxl0e6WqV2CiIiIvKdsz0Wkdglv3J5DvzB/9SzWzvzyqXtrNq9k/9G9T+20tG3XZj79cjmrZ3yBxR9HJa/4YjEHju5l0bhVAExcOJrYuFhG9hxvyOszriuZvDLTrUXvZ9ay/PPFHDpxgPljlhvGJi0cw6OYR4zpPYnzV84yes5Q1szYZHhGFt8A6lZuxM+/7eTX33cxvPvYZ869c9/3fPrlMlZN/TB+RplUyTq1SxBJVTE37V4i6t1UNtvJ1C5B5I1Lb9/0H+WZvvZKREREREREREREREREROSNOH3hJJl9Al4p59zlM+QMyG1oWALIl7MgIWE3iHocZYgJyp7PKC9fjoKcu3z6BfOefjonZwHOXT4DgLurJ3HxcVy+dpGoRw+5cPU8vp7+RD2OYvXXK+jctMdz5w7wC+Tu/TuE3w17pXcVERGRd4ealkRERERERERERETkmc4cO8zEAd3pUKM89Yvn4fdff3oq5reff2RMr460rvIR9Yvn4eqFc8+dLyUlhXF9uzx3rrdp17bNtKxUIlVrEBH5J25HhJPWKd0r5dyPvIdTGmejMWdHZ8M9Q4yjcYyTozP3H95//rwP7+PkmPapnOiYx8TFx+Fg50CftgOZtmwivcd1oVyxCuTPWZBlGxdSvWwtwu/covvIDnQZ1oY9h34xmifdH+94OyL8ld5VRERE3h3mqV2AiIiIiIiIiIiIiPw3xcXE4JM5K2Wq1WLqJ32eGRMbG0Ng7rwUK1uJhZNGvXC+bRtWY4LJG6pWROTDEJ8Qh6XFu3PcbrF8JSmWr6Th+uT54wSHXKFTk+60H9ycAR2H4pzGmd5ju5IzILehccrSwgqAuPjYVKtdRERE3iw1LYmIiIiIiIiIiIjIM+UtWoK8RV+8G1Gpyh8DcPtW6Avjrl44xzfrP2XisnV0qFHub5/dpW4VylavRUjwFQ7t+RlbewfqtGhH5bqNDDF3wm6xfMZETh7+DVMTU4KKFKdN70E4pX2yO0fwxfOsnDWZy+fOYGJiQkYvbzr2H0ZsTDTzxw8HoH7xPE/+26YTDdp2ZseXG9i6YTURt8OwtbMnME8++o2b9hKrJSLydjjap+FRdNQr5TinScuDSOMdk/63g5JzmrR/xvy/XZUePLxv2JHpmfM6OvPg4b2ncmxt7LCytHoqPiEhnvmrZ9K33WBu3Q4lKTmJXFmf/D3s4erJ+StnKRxUDICoxw8BSOPg9ErvKiIiIu8OHQ8nIiIiIiIiIiIiIm9UXGwMs0YNpl3fT3BOl/6l87asXYVP5gAmr9hA7WZtWDFrMsd/3w9AcnIykwf15NHDSEbNXc6wmQsJDw1hxvABhvzZowaTNoMrE5etZdLyddRu1gYzc3MCcgXRqucAbOzsWbxlJ4u37OTjxi25fPY0y2dOomG7Lsxat5kh0+eTPSjfG1kTEZF/KpN3Zq7fvPZKOYH+2Tl14QSJiYmGsWOnD+OZ0QsHOwdDzPGzR4zyjp45RKB/jhfMm4NjZ4/+v5zDBPpnf2b8+q2ryZ+zEJl9AkhOTiYpKclwLzEpkeTkZMP1tdBgzM3M8Xb3faV3FRERkXeHdloSEREREREREQDWbFzM2s+XGI15uvuwaNYXhutBIzpy8ozxDzKqVKhDtw6D31qd/98Pu75hycrpbFy1K9VqEBGRF1s5ewpZc+ahYMkyr5SXNXcQtZu3BcDd25dzJ4+xbcNq8hQqyslDv3H9yiXmff4t6V0zAtBt2Fj6NKvDpbOnyJwtJ3fDw6jRpBUePn4AuHn5GOa2tbPHxMTEqInqbvgtrKxtyF/sI2zs7HDJ6I5fQLbXtAoiIq9H/pwFWfXlUqIeRxkajm6GhxITF8P9yPvEx8dx+folALzdfbAwt6B04XKs3fIps1ZOoV6VRlwLDWbzj1/SvlEXw7w1ytdh0OTefLljIwVzF+HX33/iUvAFurfoa4hZuWkJEffv0rfdk3//Vy39MVt/+prlny+iQokqHD97lN0Hf2ZkzwlP1X39ZjC/HvyZOSMWAeDp5o2pqQk7dn+Ls2NaQm5dJ4tfVkP86YsnyJEl1zN3bBIREZH3g5qWRERERERERMTAxysTY4fNM1ybmT39rYNK5WrRrGFHw7W1lfVbq09ERN49B3f/zKnDB5m8YsMr5wbkyG18nTMP2zauBiD02hXSZXA1NCwBePn5Y+fgQGjwVTJny0n1Rs1ZOHEUv+7YSq4ChSlapiIZPb2e+7zcBYviktGNrg2qEVS4GHkLF6dQqbJYWdu8cu0iIm+Kr2cm/L2zsOfgz1Qp/eSIztmrpnLy/HFDTI9RHQBYPmktrukzYmdrz9g+k1mwZjY9R3fC0SENjT9uTpVS1Q052TPnpH/7IXz21XJWfbkMjwweDO02Gl9PP0PMvQf3uHPvtuE6o4sbI3uOZ8n6+Wz+8UvSO6enR8t+5M9Z0KjmlJQU5qyaTvuGnbG2evJ3qpWlFb3bDGT+6lkkJCbQuWkP0ju7GHJ+/X0XTWq0fCNrKCIiIv8NaloSEREREREREQNTUzPSOr/42B5rK+u/jfmr1l1qULFsDa6HXOW3Q79ib+tAgzqtqF65gSHm9p0wFi6fwvGTBzExNSV/UFE6temHs1M6AK4EX2DxyulcunwWTExwz+hF946DiYmNYeb80QBUq//kByNN6renaYMObN3xOZu3ruNORDh2tvbkCAzik36T/uHKiIjIP3Xq8O+Eh96gVeUSRuNTh/QlW558jJq77I09u0HbzpSoUIUj+3Zz9MAeNi5bQK9Rkyhcqtwz423s7Ji8fD2njx7i+O/72bB0PhuXL2Ti0jXYOTi+sTpFRF5V449bsPzzRVT6qBqmpqZMHDDjb3P8vPyZPGjWC2NKFixNyYKln3u/T9uBT43lDgxizsjFL5zXxMSEKYNnPzVeKE9RCuUp+tT4oZO/YWJiSokCpV44r4iIiLzb1LQkIiIiIiIiIgY3w27QvEMVLCwsyRaQi5ZNupHBJaNRzK7d37Fr93acndJRKH9JGtVr97e7LW3aspoGtVvRrEEHDh8/wKIV0/Fw8yFvnsIkJyczZnJfbKxtmThqEUnJSSxYOplJMz5h4qgnR0dMnT2MTL5Z6dp+EKamplwJvoCZmTnZAnLToVUfVm9YZDjGzsbalouXz7Bo+TT6dh9F9qy5iXr0kNNnj77BlRMRkeep1bwN5WrUNhrr27werXr0I3/xF/8w+uLpk//v+gSePpkA8PDJRMTtcO6Ghxl2W7px9TKPo6Lw9M1kyHH39sXd25fqjZozc8RAdm3bTOFS5TC3sCA5KempZ5qZm5O7YBFyFyxC/TYdaVWpJKcO/07h0uX/1TqIiLxOhfIU4ebtECIe3MUlbYbULue1i42LpVebAZiZmaV2KSIiIvIGqWlJRERERERERADImiUHvbuOwNPdh3v377L28yUMGN6e+dPXY2tjB0CpEpXI4OJGOmcXrl6/yIrVcwm5eY2h/ae8cO7sWXPToHYrADzcfTh77jhfb1tL3jyFOX7yIMHXL7N83te4pH/yQ+e+3UbSuU9DLlw6TUDmHNy+G06dGs3x8vB9Moebt2FuW1t7TExMjHZ/un03DGsrawrlL4GtjR0ZXNzw98v6RtZNROR9FhMdTVjIdcP17ZuhXL1wDnvHNLhkdAMg6mEkd8Nucf/uHQBuXg8GwCldepz/8vH/pXd1w9Xd84XPP3fyGJvXrKBgyTKcOHiA/bt+YPCUOQDkLlgE70yZmT1qMK16DiApKZGlU8eTPW8B/LPlIC4uls/mTqdomQpkcPcg4nY4l86epkjpJ7ssZXBzJzYmmpOHfsMncwBW1tZPdoW6GUK2PPmxd3TkyP49JKck4+7t+xpXVUTk9ahVoV5ql/DGaIclERGRD4OalkREREREREQEgAJ5ixs+9/PJQtYsOWnd+WN27/uRSuVqAlClQh1DjK9PZtI6peeT0V24FRaCW8bn/+A5MCDXU9ebt60H4EboVVzSuRoalgC8vTJhZ+fAjdBgAjLnoHb1JsxeOJaffv2WoFyFKFm0/Auflzd3YTK4uNG2ay3yBxUlf96iFC1U5m93hBIREWNXzp1mZPd2hutVc6YCUKpKDboNHQPAod0/M3/8cEPMzBFPjg6q36YTDdp2/lfP/7hRcy6fO8PnyxdiY2dPy+59CSr85P9XJiYmDJg4i+UzJjK8a2tMTUwJKlKcNr0HwR9Hnj56GMmcsUOJvBeBQxonCpcqR4O2XQDImiuICrXqM2P4AKIiH1C/TSdyFSjMb7/8xMZlC0mIj8fNy5teIyfilSnzv3oPEREREREReZqalkRERERERETkmeztHPBw9+ZW2I3nxmTNkhP+OFbuRU1E/1bTBh0oXaISvx/Zy+Gj+1izcTEDe42jWOEyz4y3tbFj9uTPOHH6MEeP/8bqDYtYu3EJMyauwt7O4Y3VKSLyvsmRryCf7z3+wpgy1WpSplrNV5r37+b8H1s7e/qMef5ufi4Z3Rg4adYz71lYWNBr1KQXzt+h/1A69B9qNDZq7rKXqk1ERERERET+HdPULkBERERERERE/ptiYqK5FRZqdOza/3cl+ALAC2MAzl88ZXR97uIpvDyfHLXj5eHHnYhw7twNM9y/fuMKjx9H4e3pZxjzcPehdvUmjB02l2KFy/DDrm8AsDC3IDk5+alnmpmZkzd3Ydo078G8qesIv3OT46cOvvT7i4iIiIiIiIiIyJujnZZEREREREREBICln86kcP6SZHBxI+L+HdZsWIypqSmlilcC4FZYCD/v+Y4CeYvj6JCGq9cusmTVDHJmy4ufT5YXzn3m3HG+2PwpRQuW4uiJ39izfycjB88AICh3IXy9/ZkyezgdWvUhKSmJ+UsnkSt7PrL4ZycuLpbln82meNFyZMzgzt2I21y8dIZiRcoCkCGDGzGx0Rw7+Tt+PgFYWVlz4tRBwsJDyZEtLw72jhw8speU5BQ83X3ewkqKiIiIiIiIiIjI31HTkoiIiIiIiIgAEBFxm8mzhvIwKpI0js7kCMzD9PErSJPGGQBzc3OOnfidzdvWExsXg0s6V4oXLkujum3+du7aHzfl4uWzrP18CbY2drRv2Yv8QUUBMDExYdiAaSxcPoWBwztgYmpK/qCidGrTDwBTUzMePopk+pwR3I+8RxoHJ4oWLkOzBh0AyJ41D1Ur1GXSjE94GBVJk/rtCcpViH2/7WLNxiUkJMTh7ubNgF5j8fHyf6NrKCIir8/8TdtTuwQRERERERF5g0xSUlJSXiYwNGrDm69GREREREREPjjHd6iJ5H3XuksNalZrRK1qTVK7FPmPiHa3TO0SRERE5D1ley4itUsQ+UeSKlmndgkiqSrmpl1ql/DGlM12MrVLEHnj0ts3/Ud5pq+9EhERERERERERERERERERERERkRdQ05KIiIiIiIiIiIiIvJSoyAe0rVaa27dCU7uUN2L1gpksmz4htcsQERERERH5IKhpSURERERERETeqBXzt+hoOBGR98SmVUsoWLIMGdw8AFg+YyID2jSicekC9GvZ4Jk51y5dYFjnVjQpU5BOtSuyec2Kp2L2//Q9PRvXpEmZgvRpXpcj+3b/bS2njxxkQOuGNC5dgG4NqrNr22aj+7t3bKNT7Yq0qlyClbOnGN27fSuUHo0+JvrxI6PxGo1b8sv2bwgPDXmp9RAREREREZF/Tk1LIiIiIiIiIiIiIvK34mJj+Gnr15StXttovGy1WhQrV+mZOdGPHzGmdydcMroxadk6mnftzcZlC/lh8xeGmPMnjzFz5CDKVq/N5BUbKFSyDJMH9+L6lYvPrSX8ZggT+ncjR76CTFm5kWoNmrJw0iiO/bYXgIcP7rNg4iiad+3D0BkL2b1jG4f3/mLIXzp1PE079cTWzt5oXkcnZ/IULsaOrzb+43USERERERGRl6OmJRERERERERERERH5W0f278HCwoKAnLkNY216D6Jy3Ua4uns+M2f399+SmJBA509G45UpM8XLV6FK/cZsXf+ZIWbbxjUEFS5Gzaat8PTNRKMO3cgUkI3vvlj/3Fp++PpzMrh50LJ7Pzx9M1GlXmOKlC7P1g2r4Y+mJlt7e4qXr0zmbDnJka8gIcFXAdjzw3bMzM0pXLr8M+cuULwU+3Z+94/XSURERERERF6OmpZEREREREREhIdRD2jStiLht2+mdilvxIrVc1iwbMpLRIqIyPOcPX6ETIHZXynnwqnjZA/Kj4WFhWEsqFAxbl4P5tHDh09iTp8gd4EiRnl5ChfjwukTL5j3BLn+X05Q4WJcOPUkx83Th/jYWK5eOEvUw0gunzuNT+YsPHr4kPVL5tG2z+Dnzp05e04ibodz+1boK72riIiIiIiIvBo1LYmIiIiIiIgIGzatoEjBj3DN4A7AwuVT6TGgOTUbF6NbvybPzLl67SIDhrWnVpPitOxUjS82f/pUzO79P9KxZz1qNSlOlz6NOHhk79/WcuL0YXoMaEbNxsVo1602P+z6xuj+rt3badmpGg1alWXJyhlG98Jv36R9j7pERz8yGq9Tozk7f9nGrfCQl1oPERF52t2wWzind3mlnAcRd0mTNq3RWJq06Z7cu3f3LzHpjGKc0qbjQcTd58977y5O/y8njXM6Yh4/Ii4uFntHR7oOHcOcMUMZ3K4ppSp/TFDh4nw6bxpV6jbi9q1Q+rdqQJ9mddi/6wejef73jnfCbr3Su4qIiIiIiMirUdOSiIiIiIiIyAcuNi6W73/aTMWyNY3GK5b9mI+KVXhmTnT0I4aO6YaLS0ZmTfqUNs17snbjYrb/8KUh5sz540yeOZSKZWsye/JqihYqxdjJ/Qi+fum5tYSFhzJyQi9y58jPnClrqFmtMbMXjuPwsf0ARD58wOwF42jbvCdjh85h1+7t/H54tyF//tJJtGraFVtbe6N50zg6kS9PEb7dsekfr5OIyIcuPi4WS0ur1C7jpRUuVY7pn21i7satNGjbmdNHD3H90kXK16zLzOEDadVzAH3HTWfBhJFE3o8w5FlaPXnH+NjYVKxeRERERETk/aemJREREREREZEP3KEje7GwsCQwIJdhrFObflSv3ICMrh7PzNm1+zsSExPp1Xk4Pl7+lCpekY+rNOTrrWsNMVu2rSd/UFHq1myOt6cfzRt1xj9TIFu/+/y5tXz7w5dkzOBOu5a98fb04+MqDShRpKxh3rDwUGxt7fioeEUCMucgd4783AgJBuDnPTswMzOneOGyz5y7cIGS/Lrv+3+8TiIiHzqHNM48inr4SjlO6dITee+e0VjkvScNQk5p0/8lJsIo5sG9CJzSpX/+vGnT8+D/5UTej8DGzh4rK+un4hPi41k6dRwdBgwjLOQGSUmJ5MhbAA8fX9y9fLh4+qQh9n/H1jk6Ob/Su4qIiIiIiMirUdOSiIiIiIiIyAfu9NmjZM4U+Eo55y6cJGf2vFhYWBjG8gUVJeTmNaIePTTEBOUuaJSXL08Rzl04+dR8f503KFch45ygP3Pc3byIi4/j8tXzREVFcuHyGXx9MhP16CGr1y+kc9v+z507IHMO7kbcJvz2zVd6VxERecIvIJCQq1deKScgZx7OHDtMYmKCYezEwQO4e/ti7+j4JCZHbk4e/s0o78TBAwTkyP2CeZ/OOX7wAAE5n52zaeVigooUJ1PWbCQnJ5GUlGS4l5iYSHJysuH6xpVLmJmb45nJ/5XeVURERERERF6NmpZEREREREREPnC374aR1tnllXLuP4jAKU1aozHnP67vP4j4S0w6oxgnp7SG+8+d18l4Xqc06YiOeUxcXCwO9o706TqCaXNG0HtwK8qVqkb+oKIs+3QW1avUJ/z2Tbr3b0qXPg3Zs3+n0TzpnJ/s2HH7zq1XelcREXkiT+FihFy9bNiJCOBWyHWuXjjHg4i7xMfFcvXCOa5eOEdCwpMmpRIVqmBuYcGCCSO5ceUSe3/8jm8/X0P1Rs0Nc1Rr0JRjB/bxzbpVhF67ysZlC7h87jSV6zUyxKxZMIs5Y4YYrivUqs/tmyF8Nm8GodeusuPLDez/6XuqN2z2VN03rl5m3087aNiuCwDuPn6Ympqy85svObzvV25ev4p/thyG+LPHj5AtT75n7tgkIiIiIiIir495ahcgIiIiIiIiIqkrPj4OS0vL1C7jpRUrXIZihcsYrk+ePkzw9Yt0atuf9t1rM6DnWJyd0tF7cCtyZs9raK6ytHzyw+e4+NhUq11E5F3m458Fv6yB7P9pBxVq1Qdg4cRRnDl6yBAzoHVDAOZ98S0Z3Dyws3dg2IyFLJ02noFtG+OQxol6rTtSoWY9Q07WXEH0HDmBdYvnsnbRHNw8vRkwYSbembIYYu5H3OVueJjh2tXdk8FT5rJy9hS+/XwN6Vxc6TRwBEGFixvVnJKSwqLJo2nZvR/WNrYAWFlZ03XIaJZOm0BCQjxtew8mnYurIWfvj9/RoG2nN7KGIiIiIiIi8ic1LYmIiIiIiIh84Bwd0vDoUdQr5Tg7peNB5D2jsft/XDs7pftLjPGuSg8e3DPcf+68D4znfRAZga2N3TN3vEhIiGf+0kn07T6aW2E3SEpKIleO/AB4uHtz/uIpChf4CICoR5EApHF0fqV3FRGRP9Vr3ZHP5s2gXI26mJqaMmrusr/N8ckcwJgFK18YU7RsRYqWrfjc+92GjnlqLEe+gkxZufGF85qYmDB2waqnxvMXL0X+4qWeGj+6fw8mpqYUKV3hhfOKiIiIiIjIv6fj4UREREREREQ+cJn8snI95Mor5QQG5OLUmaMkJiYaxo6d+A1Pdx8c7B0NMcdPHjTKO3riNwIDcr1w3mP/P+f478/NWb9pGfmDipI5UyDJyckkJSUZ7iUmJpKcnGy4vnbjMuZm5nh7ZnqldxURkT/lL/YRFWrU5d6d26ldyhsRGxtD109GYWau3/cVERERERF509S0JCIiIiIiIvKBy5+nKNdDrhD16KFh7OatG1y+ep77DyKIj4/j8tXzXL56noSEBABKl6iMubk5sxaM4dqNy/y693s2f7ueWtWbGOaoUa0Rh4/t58tvVnMjNJg1Gxdz6fJZqleub4hZuWYu0+aMMFxXrVCHsNuhLP9sNjdCg9m643N27//RaN7/uX7jCr/u+5FmDZ8c4ePp7oOpqQk7dm7m98N7CLl5jSz+2Q3xp88eI0e2oGfu2CQiIi+vWsNmpHfNmNplvBFFy1QgS47cqV2GiIiIiIjIB0G/LiIiIiIiIiLygfP1yYy/XyB79v9IlQp1AJi9cCwnzxwxxPQY0AyA5fM245rBHTs7e8YOm8uCpZPpObAFjg5ONK7XzpAPkD1rHvr3HMtn6xawau18PNy8GDpgKr7emQ0x9+7f5c7dMMN1RlcPRg6eyZKV09n87XrSp8tAj05DyB9U1KjmlJQU5iwaT/uWvbC2tgHAysqa3l1HMH/pZBIS4unctj/p02Uw5Py693uaNOjwRtZQREREREREREREXo1JSkpKyssEhkZtePPViIiIiIiIyAfn+A7/1C5BgN8P72H5Z7OZP309pqbv38bMh47uZemqWcybthYzM/0OV2qLdrdM7RJERETkPWV7LiK1SxD5R5IqaUdY+bDF3LRL7RLemLLZTqZ2CSJvXHr7pv8oT9+lExEREREREREK5S/BzbDrRNy7jUv69+/In9jYWHp1Ha6GJRERERERERERkf8IfadORERERERERACoVa1JapfwxpQoWi61SxAREREREREREZG/eP/2excRERERERERERERERERERERkf80NS2JiIiIiIiIiIiIiIiIiIiIiMhbpaYlERERERERERERERERERERERF5q9S0JCIiIiIiIiIiIiIiIiIiIiIib5WalkRERERERERERERERERERERE5K1S05KIiIiIiIiIiIiIiIiIiIiIiLxValoSEREREREREREREREREREREZG3Sk1LIiIiIiIiIiIiIiIiIiIiIiLyVqlpSURERERERERERERERERERERE3io1LYmIiIiIiIiIiIiIiIiIiIiIyFulpiUREREREREREREREREREREREXmr1LQkIiIiIiIiIiIiIiIiIiIiIiJvlZqWRERERERERERERERERERERETkrVLTkoiIiIiIiIiIiIiIiIiIiIiIvFVqWhIRERERERERERERERERERERkbdKTUsiIiIiIiIiIiIiIiIiIiIiIvJWqWlJRERERERERERERERERERERETeKjUtiYiIiIiIiIiIiIiIiIiIiIjIW6WmJREREREREREREREREREREREReavUtCQiIiIiIiIiIiIiIiIiIiIiIm+VmpZEREREREREREREREREROStqOFZjAPf/ZLaZbxz1k5bSs+KLVO7DBGR10pNSyIiIiIiIiIiIiIiIiIiH4iZvcdSw7MYNTyLUdu3JO2K1mXF2HnEx8aldmnyhp3cd4QansV4FBmV2qWIiABgntoFiIiIiIiIiIiIiIiIiIjI25OvdBF6Th9CYmIil0+cY2bvsZiYQKshXVO7tHdeQnwCFpYWqV2GiMg7QU1LIiIiIiIiIiIiIiIiIiIfEAsrC5wzpAPAxd2VPJt2cGz3QcP9h/cjWTR0GqcPHONRZBRuPh7U696CUrUqGmI+qdcV32z+WFhZ8cO6LZhbWlC5WS2a9G1niLl55Qaz+4/n4rGzZPR2p92oXk/VEnz2MktGzOD84VNY2VhTtGpp2o7ogY2dLfyxM9Tjh1FkCcrON8s2khifQM32jajfvQWfTljID+u/wcrGmqb921O+YfXnvvMn9briE+iPqZkpP32xHXMLc5r170Cp2hVZNHQa+7b9TJr0znQc04f8ZYsCkJSUxLwBkzix7zAPbkfg4pGRKi1qU6NdQ8O8hvryZOPbVV9ibmnB0v2b+HbVJjYv2cDdW7exdbAjR6E8DFo8/pm17dy4jaUjZ9Fz+hBWjJ3H3Vu3yVkkiG5TBuPi7moUu+uL7ayZuoRHkVHkL1OErpMHYWtvB0BCXDwrxs5l95YfiX4UTebcgbQb0YMsQdkJv3GLIQ26AdAkRyUAytavSq8ZQ1+YJyLyJul4OBERERERERERERERERGRD9S1c5c5d/gk5hZ/7g6UEBtP5lyBDP90KnN3rqZS05rM6DmGC0fPGOX+9MV2rG2tmfrNUloN6cqGmSs4+uvvACQnJzOh/WAsLCyY+s0SOk/oz6rx843yY6NjGNmsN/ZpHJm2bRkDFo3l+J5DLBo63SjuxN7D3Au7y4RN82kzvAdrpy1ldMv+2Dk5MPWbpVRuXov5gyZz9+btF77rT198i2PaNEz7ZinVW9djwSdTmdRxKIH5czFj+wrylirE9J6jiYuJBSAlOYX0bhkYuHAsc3etpWGv1nw2aRF7vtlpXN+ew4Revs7otTMZvnIKF4+fZfHwmTTp144Fv6xj5Orp5Cgc9MLa4mJi2ThnFb1nDWPSVwt5HPmIKV2GG8WEXQvlwI7dDFs5hWErp3DqwDE2zfvMcH/luHns+/Znes0YxoztK3Dz9WRE095E3X9IevcMhqapBb+uZ9WRb2j/RxPZi/JERN4kNS2JiIiIiIiIiIiIiIiIiHxADv64jwYB5ajrX5ru5ZsTefc+dTo1MdxP5+ZC7U5NyJQjgIw+HlRvU598pQuzZ6txs45vtsw07tMW90xelK1Xhcy5Azmx5xAAx3cfJOTyNXrNHIZf9izkLJKX5gM7GeX/8tX3xMfG0XvWMHwC/clTvAAdx/Th503fcf/OPUOcg5MjHcb0xtPfhwqNquPh701cbCwNurfEPZMX9bq1wNzCgjMHj7/wvf2yZ6Fhz9aGHEsrSxzTpqFS05q4Z/KiUa82RN2P5OqZSwCYW5jTpF87suTJRkZvd0rXqUS5BtWealqysrWm25TBeGfNhHfWTNwJDcfa1pqC5YuTwdMN/5xZ+bhtgxfWlpiQSMcxfQnMn4vMuQPpNXMo5w6dNGoUS05OpueMIfgE+pOjcBCl61Tm+J7D8EcD2PbPvqL10G7kL1sU7wA/uk0ehKW1FT+s/wYzMzMcnBwBSJPOGecM6bBztP/bPBGRN0nHw4mIiIiIiIiIiIiIiIiIfEByFctH5/H9iYuJYfOSDZiZmVGsWhnD/aSkJD6f8yl7v9lJRNgdEhMSSYiPx8rG2mge32z+RtfOrul4EHEfgBsXg0nv7kq6jC6G+4H5cxrFh1wKxi97FqxtbQxj2QrmJjk5mdDL13B2SQuAd4AfpqZ/7sfhlD4tPoGZDNdmZmY4ODsSeff+C9/7r/X+L8cn8M8xpz+eFxnx5zzbVm7ixw1buRMaTnxsHIkJCfhlz2I0r0+gPxaWf+5UFfRRQVw8MtKh2JNmr3yli1C0Sqmn1u+vzMzNyBKUzXDtmdkXuzQO3LgUTEDeJ8e0ZfByMxwFB5DWNZ2h1lvBoSQmJJKtYC7DfXMLcwKCsnPjUvBzn/tP80REXgfttCQiIiIiIiIiIiIiIiIi8gGxtrXG3c8Tv+xZ6DHtEy4cPc336/7cVeerBWv4ZtlG6nRpxrjP5zJzxyrylipMYkKC0Txm5sZ7ZJiYmJCSnPLa6zWzePo5z3p2csqLn/2snL/ObWJiAkBKcjIAv27+gRVj5lChUXVGrZ3BzB2rKNegGokJiUbzWNsaNyPZ2tsx87sV9Js3CucM6Vk7bQk9KrTgUWTUK733/2f+/+rHxMRQq4jIu0hNSyIiIiIiIiIiIiIiIiIiHyhTU1PqdW/BmimLiYuJA+DsoZMUrliSMnUr45c9Cxl93Ll55cYrzeuVxZe7N8O5F37XMHb+yCmjGM/Mvlw9c5HY6BjD2NmDJzA1NcXD3+dfv9u/dfbgSQIL5KJqy7r458yKu58nYddCXyrXzNycoJIFaT20K7N/+IzbIbc4sffwc+OTEpO4dPyc4Trk8jUeR0bhldn3pZ7n5uuBuaUFZw+eNIwlJiRy8fhZvLP4AWD+x25QyX9pdHqZPBGRN0XHw4mIiIiIiIiIiIiIiMh7ISp3utQuQeQfseVxqj6/RPWyrBw7j29XbaJ2pya4+3myd9vPnD10Evs0DmxevI4Hd+/hFfByDTQAeUoWxD2TNzN7j6H10G5ERz1m9eTFRjGl61Ri3fRlzOw1hsZ92hIZ8YDFw6dTum5lw9Fwqcndz5Ndm7Zz5OcDuHq7s2vTd1w8fhZXL/cX5h38cS9h10LJUSQI+zQOHPppPynJKXj6ez83x9zCnMXDptN+dG/MzM1YNHQaWfPlMBwN93esbW2o0rw2K8bOxd7JERcPV75csIa4mFgqNKoOQAaPjJiYmHDwx70UKFsUS2srbOxs/zZP5G1at/pXhg5azeWQxS8R/d+SL0cvOnSpTKeulVO7lHeGmpZERERERERERERERERERD5gZubmVGtVly8XrKZKi9o06NGasOs3Gdm0N5Y2VlRqWpPClT4iOurRS89pamrKJ0snMKffBPpWb4erpxvtR/diZLM+hhgrG2tGrp7BkhEz6FutLVY21hStWpq2I3q8oTd9NZWb1eLK6QtM6TIcTEz4qGZ5qrSow5FdB16YZ+doz/7tv7Bu+jLi4+Jx9/Oi37xReGfN9NwcKxtr6nRpxrTuI4gIu0v2QnnoMXXwK9XbcnBnUpKTmdFzNDGPo8mcO5BRa2Zg7+QIQDo3Fxr3bcenExYwu884ytSrQq8ZQ/8271XV8Cz2wvuNerehSd92/2hueTd067iIDWt3PzVepnwuNn418K3U4OLQ7KmxQkUC2PbD8LfyfHk5Jikpf3Ow5x9Coza8+WpERERERETkg3N8h39qlyAib1m0u2VqlyAiIiLvqST9M0PeUbZuqbvTkqSunRu3sXTkLNad+T61S3kt7t+OMHy+e8uPrJ22lAW/rDeMWdvZYGNna5QTc9Purdb4NpXNdvIlot4v3Tou4s6dSGYv6GA0bmVpgZPzi7/Wr2unJReHZsxe0IGyFXIbxiwtzHFOa/+v5n2RD3mnpfT2Tf9Rnulrr0REREREREREREREREREREQ+SM4Z0hk+7BztMTExwTlDOiytrWhdoCYhl64BkJycTJMclej3cXtD7u7tW+lSvaLh+m54GDMG96d12RK0KV+SKf16cvtmqNHzdn79Jb0b1KJZiYL0rl+THV/8uSHL7ZuhNCyUh73fb2dY2xY0K1GQvo3qcObIIUPMo4cPmT1sMO0qlqZZyUL0rPsxu7752ih//w87GNG+Fc1KFmJwyybcvBbMpTOnGNyiMS1KFWFCzy48vH/PMOelM6cY260j7SqUIpNHe2pUHsvxY1eN6nZxaMaKpT/SsM5kvFxaUyBXb7Z8/ftr/VqkJitLC1xdnYw+/tewFPngMX17LCN7pi54pm9NyUKD+H77UaP8n348QbH8A/DJ2JYGtScRFnbfcC85OZmpE78id9bueKRrRelin7Dzh+NP1ZAmja3R8//XsBQXl8CIT9aSK6A7Pq5tqVRmBHt3nzHKPbDvPNUrjsbLpTV5AnswuP+nPH4ca7h/504kTetPw8ulNflz9uaLDXtf+xp+CNS0JCIiIiIiIiIiIiIiIiIiIm+UnaM9fjmycGr/k+aUa+cuY2JiwpXTF4iNjgbgzJHDZMuXH4DExATG9+iMja0toxavYPSSVVjZ2DKhZxcSExIA2P3dNj5fPJ9GnbsxfcNXNOrSnY0L5/HL1i1Gz14zewbVm7Zg4mcbCMiVh8l9exD14AEAGxfNJfTqZQbPnMf0DV/RduAQHJ2cjPI3LllA7TbtmfjpeszMzJgzbDBr5sygZd8BjFq8grCQG2xcNN8QH/v4MaWqfcyoJSv5budIMvm70rjuVB5FxRjNO3HMF1SvUZCf942nboNidGg1lwvnjJuy3jfJyck0qjOF3w9cZP7Szuw5OIlhoxpiavZn+0pMdBzzZ3/L/CWd2PLdUEJvRDByyDrD/cXzdzB/zreMGteEX/aPp2y53DRvOJ3Ll8JeqoZBfVdx8PeLLF7RlZ/3j6dGrUI0rD3FkH/1SjgN60ymes1C/Lx/AktWduO3/ecZ1HeVYY7unRYTGhrBV9uGsPyzHixf8iN37zx8rWv1IVDTkoiIiIiIiIiIiIiIiIiISCop16Dae3M03N/JWTQvJ/cfAeDkviMEfVQQr8y+nDv+pJHpzJFDZM9XAID9P+wgJTmZjkNH4p05C55+megyfDR3w8I4ffggAJ8vXkDznn0pXKY8GTw8KVymPFUbN+PHr74wem6l+o0oXLY8nn6ZaDdwCLZ29vy05SsA7oaF4Zs1EP/sOcjg7kHuQkXIX7K0Uf7HTVsQVLQ4nn6ZqNKoCVfOnaFumw4E5smLX9ZslKlRy1ATQM6ChSlZpToevn4EBHowfU5bYmLi2LfnnNG8NWoXpnmrMvhncWPwsPoE5fVj6aL348/C998dxSdjW6OPGVM288uu0xw5fJmVa3pSumwufP0yULFKXspXzGPITUhIYsrM1gTly0SeID/adqzArz+fNtyfN/tbuveqTu16Rckc4M7wMY3ImduHRfO/M6qhY5t5Rs//9ptDhNy4y7rVv7L8sx4ULR6IXyZXuvasRuGiAaxb/QsAs6ZtoV6DYnTqWhn/zBkpVCSA8ZNbsHHdHmJj47l88RY7vz/OjDltKVAoM3ny+jFrXntiYuLf4gq/H8xTuwARERERERERERERERERERF5/+Uskpcf128lKSmJUweOkbdUIZxc0nHm8EG8M2ch7MZ1Q9PStYsXCAu5QcvSRY3mSIiPIzwkhNiYaMJDbrBw7EgWjR9luJ+clIStvb1RTpZcfzbEmJmbkylbdkKDrwBQoW4Dpg/sy9Vz58hduCgFS5cha+4go3zvLAGGz9OkTfdkLHMWo7HIvxwP9yAigg0L53LmyCEeR94hKSmZmOh4QkLuGs1boFBm4+vCWTh14torrel/VYmPsjN5RiujMWdne1av+hl3j7T4Z3F7bq6trRV+mVwN166uToZdjKIeRhN26z6FigYY5RQqEsDpk9eNxsZMbMZHpXP8OU9GJ/buPktSUjKF8/Yzio2PSzQcH3f61HXOnLrBFxv3/RmQAsnJKVwPvsPlS2GYm5uRJ6+f4XaWrO6kcbJ92eWRP6hpSURERERERERERERERERERN64HIWDiHkUzZWT5zn92zFaDOqIs0taNs5ci0+WrDi7uODm7QNAbHQ0mQKz0X30hKfmcXR2Jjb6yVFrHYYMJ0uOXEb3TU1f/tCpvMVKMG/Ldo7u3cOJ3/czpmsHKtVrSPOefQ0x5uZ/tlaYmJjAH81Pfx1LSU4xXM8fNZSoyEha9RlAteKPsLQ0p2q5UcTHJ710Xe86W1srMvlnfGrc2sbyb3PNLcyMrk1MTEhJSXlu/PNkyJDmqRoeP47DzMyUnb+OMTqSDsDO3vpJzKM4WrQpS/tOFZ+a09Mr/UsfQyd/T8fDiYiIiIiIiIiIiIiIiIiIyBtnn8YBn2z+bF25CXMLczwz+5KjcF6Cz5/j8J5fyZ63gCHWLzAbt25cx9E5LRm9vI0+bO0dcEqXDmcXF26Hhjx1P4OHp9FzL546Yfg8KTGRK+fO4uGbyTDm6JyWUtVr0H30BFr27s/Orzf9q/c8f+IYVRo2Jm/xkgRm88TKyoKIiKin4g4fvGR8/fslArK6/6tn/9dlz+nFzdB7XL546x/lOzjaktHNmd/3XzAa//3ABQICPf42P3duH5KSkrlz5yGZ/DMafbi6Oj2JCfLlwrnQp+5n8s+IpaU5WQLcSExM4vjRq4Z5L124SeSD6H/0Th8yNS2JiIiIiIiIiIiIiIiIiMh/xqkDRxnTqj+t8teghmcxDnz3y1Mx9+/cY2bvsbTKX4N6mcswomlvbl65kSr1/k/4jVvU8CzGldMXXiL6w5WraD5++ep7chZ5cgSbg7MjHr6Z2P/jDrLly2+IK1G5Ko5pnJjSvydnjx7hdmgIpw8fZMXUiUSEhwNQv30Xvl65nO0b1nDzWjDXL11k1zdfs3XNp0bP/P6LDfy+ayehwVdZNmU8j6MeUqZGLQA2LprHwV92EXbjOjcuX+LInl/x8PXj38jo5c3u7VsJuXqFwwcv0antfGyescPQlq9+Z82nv3D54i0mjdvEkcOXadvx6d193kVx8QmEhz8w+oi4G0XxEtkoWjyQ1s1m8fNPJ7kWfJsfvz/Ozh+Ov/TcXXtWY87MrXy16QCXLtxk9PD1nDpxjQ6dK/1trn8WN+o1LEa3jovYuvkg14Jvc+TQZWZO3cL33x0FoHvv6hz87SID+67i5IlrXL4UxvathxnYdxUAmQPcKVshN317LufwwUscP3qVXt2WPvNrLC+m4+FEREREREREREREREREROQ/Iy46Fr/smSnfsDoT2g9+6n5KSgrj2w7EzMKcIcsmYuNgx+bF6xnWuAfzdq3F2tYmVeqWl5OzSBBblm4gZ9F8hrHs+Qtw7eJ5cuQvaBizsrZh5KIVrJk7k2kD+xAb/Zi0LhnIWbAwNnZ2AJSrVQcra2u+Wb2S1bNnYGVjg7d/Fqo2amr0zCZde7L50+UEXzhPRk8v+k+dhaOTMwBm5hasmz+bOzdvYmllRWBQPnqOnfSv3rHT0JEsHj+GQS0a4eXpzJCRDRg5ZO1TcQOG1OHrTfsZ2GclrhmdWLSiK1lfYregd8FPP5wgZ+ZuRmOZs7ix/8gUVqzuyYgha+nYeh7R0XH4ZXJl6KiGLz13h84ViXoYzYhP1nD3zkMCAj34bEMf/DM/fRzds8xe0IHpkzczYshabt28R9p0DhQomJmKVfICkCOnN5u3D2H86M/5uNIYUlJS8PNzpWadwkZz9O66lJpVxuGSwZHBw+ozcewXL/0O8oRJykse/BcateHNVyMiIiIiIiIfnOM7/FO7BBF5y6Ld9ZuHIiIi8mYk6Z8Z8o6ydXuc2iX8Z9XwLMYnSydQpHIpw1jolet0/qgRc3euxjvrkyO+kpOTaZm3Os0HdqJikxrPnGtm77E8fhhFphwBbFu5iYT4eErVqkj70b2xsLQAICEunhVj57J7y49EP4omc+5A2o3oQZag7AA8evCQRUOnc/TX34l9HE06twzU796C8g2rU8OzmNHzchbJy/gv5nFy3xFWjpvH9QtXMbcwxyvAj35zR5LB0+0Nrty7Jeam3RuZ9/bNULrXqsqk1RvwDQh8I8/4O2WznXzmuItDM1at7UXVjws8877IuyS9fdOXiHqadloSEREREREREREREREREZF3RkJcAgAWVn92KpqammJhacmZgyee27QEcGLPYSytLBn/+VzCQ24xu884HJwdaT6wEwArx81j37c/02vGMFw8M/LlgjWMaNqbRXs+x8HZkdVTlnD94lVGfDYNx7RO3AoOIT42DoBpW5fSt3o7xqyfjXeAH+YWFiQlJjK+3SAqNq5Bv3mjSExI5MKxM5iYmLzxdRIR+a8zTe0CREREREREREREREREREREXpZnZh9cPFz5dOJCHj14SEJ8ApvmfcbdW7e5f/vuC3PNLczpMW0I3lkzUbBccZr0a8/W5V+QnJxMbHQM2z/7itZDu5G/bFG8A/zoNnkQltZW/LD+GwDu3gwnU84AsuTJhquXG0ElC1KoQgkAHNM9OW7MwdkR5wzpcHB2JDoqmscPH1GwfHHcfD3xyuJLufpVcfF4uWOsRETeZ9ppSURERERERERERERERERE3hnmFuYMXjKBOf0m0CRnZUzNzMhTogD5yxQlJSXlhbm+2TNjZWNtuA7Mn5OYx9HcvRnO44ePSUxIJFvBXEbPCgjKzo1LwQBUaV6bCR0+4crJCwR9VIgilT8iW4Fcz3wWfzQwlWtQlRHNehNUsiB5ShSgxMflSOua/rWshbxYBncPNvx+PLXLeKY7UatTuwSRVKedlkRERERERERERERERERE5J2SOXcgs75fxboz37PqyBZGrZlB1P1IMvq4v9Hn5i9blGW/fUmN9g25F36HYQ27s3zMnBfm9Jw+lMmbFxFYIBd7vtlJ548ace7wqTdap4jIu0BNSyIiIiIiIiIiIiIiIiIi8k6yc7QnTTpnbl65waUT5yhcseQL44PPXCIuJs5wff7IaWzsbEnv7oqbrwfmlhacPXjScD8xIZGLx8/incXPMJYmnTPl6lel75yRtBvVix1rNsMfuzIBJCclP/Vc/5xZqd+tBZM3L8Y7qx+/fv39a3l/EZF3mY6HExERERERERERERERERGR/4yYx9HcCg4xXIffuMWV0xdwcHLExSMjAHu2/kSatE64eLgSfO4yS0fMpHClj8hbqvAL505MSGROv/E06NmK2zdusXbaUqq2qoupqSnWtjZUaV6bFWPnYu/kiIuHK18uWENcTCwVGlUHYM2UJfjnzop3QCYS4+M5+ONevDL7AuCU3hlLayuO/HyAdG4ZsLSyJOrBQ3as2UzhiiVI65qe0MvXuXk1hDL1qrzRNXyXfb54AV8sXWg05u7jy4zPN6daTbdvhtK9VlUmrd6Ab0BgqtXxLtq35xzzZm3j+LGrhIc9YNXaXlT9uIBRjItDs2fmjhjTiG69qr+lSo3t3X2GWlXHc+nGItI42aVKDR8CNS2JiIiIiIiIiIiIiIiIiMh/xqXj5xjSoJvhetmo2QCUrV+VXjOGAnA//C7LR83mwd17OGdIR5l6VWjYs/Xfzp27RH7c/bwYXLcLifEJlKxZniZ92hrutxzcmZTkZGb0HE3M42gy5w5k1JoZ2Ds5AmBuac5nExcSfuMWVtZWZC+ch37zRwNgZm5Oh9G9WT9zBWunLiV7oTz0XzCG0EvXmPjFdh7ejyRthnRUa1mXys1qvfZ1e594ZvJn2NzFhmtTc7NUrUf+uejoOHLk8qZJ849o1XTWM2NOXZprdL3z++P06rqU6jULvaUqJbWYpKSkpLxMYGjUhjdfjYiIiIiIiHxwju/wT+0SROQti3a3TO0SRERE5D2VpH9myDvK1u1xapfwQZjZeyyPH0YxZNmk1C5F/p+Ym3/uZPP54gUc/GUXk9dsfOn8+aOG8TgqCt+sgez4fD2JCfEUr1iF1v0GYW5hAUBCfDyrZ09n3w/fEfP4MZmyZadF7/5kzp4TgEcPH7J8ygRO/Laf2Jho0mVwpVartpT5uBYNC+Uxel72fAUYsXAZpw8fZM2cGYRcuYyZuQWemfzpMWYCLm7uhtiy2U4iT7g4NHvmTkv/X4tGM3j0KIYvt37y3JiaVcYSmN0LgM/X78HC3IxW7coxaGg9TExMAHhw/zFDBn7Gju1HiI9LpGiJQMZPboF/5ic7tt24fpdBfVfx24HzJMQn4eWdnhFjG5M10IP8OXsbPa9hk5LMXdSRLV//ztQJX3L1Sjg2NlbkyuPDp+t7Y2dn/RpW6N2V3r7pP8rTTksiIiIiIiIiIiIiIiIiIiLynxF24xqdqpbHwtKSLLny0KRrD9JndHthzqlDv2FhZcmIBUu5c+smC8YMxyGNE426dAdgzZwZ/LbrR7qMGItLRje2fLaS8T06M3vTVuzTpGHjormEXr3M4JnzcHByIizkBglxsQCMW7mGIa2aMnTuYrwy+WNuYUFSYiJT+/emXK069Bg7icSEBC6fPmVomJF/5vbtSH7YcYy5izr+beyGtbtp2qIU3+8axbGjV+nbYzmenulp3roMAN07LeLK5TA+W98HB0cbRg9fT+N6U9h7cBIWFuYM7LOShIREtnw3DFtbKy6cC8XOzhoPz3SsWN2T1s1mceDIFOwdbbCxtiQs7D4dW89jxJhGVP24AI8exXJg3zlebqsgeRY1LYmIiIiIiIiIiIiIiIiIiMh/Quacueg8fAzuPr7cv3uHTUsXMaJDa6au24SNnd1z88zNLeg8bBRW1jZ4+WemQYcurJ4zgwaduhIfF8v3mzbSZfgY8hYrAUCHIcM5UXM/P235ihrNW3E3LAzfrIH4Z88BQAZ3D8Pcjk7OADg4pcEpfXoAHkVGEv0oinwlPiKj55Mdfzz9Mr3RtfkQbFizG3sHa6rVePFuTAAeHmkZO7EZJiYmZA5w58zpGyyct53mrctw+VIY3317hG0/DKdQkQAAFi7tQlC2nny79TA1axcmNCSC6jULkj3Hk6+fr18Gw9zOaZ/8WUvv4kgapyefX70aTmJiEtVqFMTL+8mfg//lyj+jpiUREREREREREREREREREXnv9ZoxNLVLkJfwv6YiAJ8sAWTJmYuuNaqw/8cdlK1Z57l5PlkCsLK2MVxnyZWH2OhoIsLDiH70iKTERLLmCTLcNze3IHP2nIQGXwGgQt0GTB/Yl6vnzpG7cFEKli5D1txBz3wWgH2aNJSqXoPxPTqTq1ARchUqQtHyFXFO7/IaVuHDtfazX6jboBjW1n9/5mv+gpmNdrYqWCgLC+ZsJykpmYvnQzE3NyN/wcyG+2nTOeCfxY2L528C0K5TRQb0XsmunScpVSYn1WsWJEdO7+c+L2cuHz4qnYOPigyiTLnclCmbi49rFcLJ+fnNdPJipqldgIiIiIiIiIiIiIiIiIiIiMiz2Dk44ubtQ1jIjTf6nLzFSjBvy3aqNW7G/bu3GdO1A5/NmvbCnC7DxzBm2acE5A5i/w876FWvBhdOnnijdb7P9u89x6WLt2jWsvRbeV7zVmU4dHI6DRqX4OzpG1T4aBhLFn7/3HgzM1O+2DKI9ZsGkDXQg6WLvqdovv5cC779Vup9H6lpSURERERERERERERERERE/hMe3o+keZ6qhN+4ldqlvBGrxs9n0dDpqV3GOyU2Oprw0Bs4/3Es2/Ncu3iB+NhYw/XFUyewtrUlnWtGXD09Mbew4PzxY4b7iYkJXD57Gk8/f8OYo3NaSlWvQffRE2jZuz87v94EgLmFBQDJSclPPdcvazZqt2rLmGWf4pUpM3t3fPta3vtDtObTX8iT14+cuXxeKv7IoctG14cOXiKTvytmZqZkyepBYmIShw9eMty/FxHF5Yu3CAj88+g/D890tGpbjpVre9G5e1VWr9wFgIXFk4PLkv7f19zExITCRQMYOKQuP+0dh4WlGd9+c+hfvfeHTE1LIiIiIiIiIiIiIiIiIiLyn/D57JUUrlgSVy83ABYPm07vKq2pk6kUPSu2fGbO1TOXGFSnM3X9S9OmYC02zV/9VMyerT/RuVQj6vqXpnu5Zhzaue9vazm57wi9KreiTqZSdChen50btxnd//nLHbQpWIvGOSqxbNQso3vhN27RqWRDoqMeG43X7tSEn774lrBroS+1Hh+iz2ZN48yRQ9y+Gcr5E8eYOqA3pqZmFK9Y5YV5iYkJLBw7kpArlzm6dzefL15ApfqNMDU1xdrGlgp1G7B6znSO7d9LyJXLLB43mrjYWMrUqA3AxkXzOPjLLsJuXOfG5Usc2fMrHr5+AKRxToullTXH9u/lQUQE0Y+iuB0awtp5s7hw4jh3bt3k+IF9hN24jodvpreyTu+KR49iOXniGidPXAPg+rU7nDxxjZAbd43ioh5G883Xv7/SLkshIREMG7SaSxdu8uXn+1i66Hs6dKkEgH/mjFSplp8+3ZdxYN95Tp28Ruf2C8jo7kyVavkAGDLwM3768QTXgm9z/NhV9v56hixZ3QHw8k6PiYkJ3393lLt3HvLoUSyHD15ixpTNHDtyhZAbd9m65SARd6PIktXjhXXK85mndgEiIiIiIiIiIiIiIiIiIiJxMbH8sH4rI1fPMBov37A6F46eJvjs5adyoqMeM6JpL/KUKECXCf0JPneZ2X3HY+doT+VmtQA4e+gkU7uOoMWgThQsX5xfvv6e8e0GMWP7CnwC/Z+aEyDs+k1Gt+xH5ea16DtnJMf3HGJO/4k4Z0hHvtJFeHjvAXP7T6DnjKFk9HZndMt+5C5egILliwOw8JOptBjcGVsHO6N5HdM6kbdUYbZ/+hWth3V7jav3/oi4Hc7soYOIinyAo7MzWfPkZezyz3B0TvvCvJwFCpPR25uRHduQkBBP8YpVqN++s+F+k649SUlOZu6IIcRGPyZTtux8MnsB9o6OAJiZW7Bu/mzu3LyJpZUVgUH56Dl20h/3zGnVdyCbli1i4+L5ZAvKR89xk7kZfJXp274hKvIBzuldqFi/IeXr1HvDK/RuOX70CrWqjjdcDxu8BoCGTUoyd1FHw/hXXxwgJSWFOvWKvvTcDRqXIDY2gYplRmBmZkqHzpVo0bqs4f7sBR0YMvAzmjaYRkJ8IkWKZ2XdF/2NdlEa2Hclt0Lv4+BgQ9kKuRkzoSkAbu5pGTikDmNGbKBH5yU0aFyCHr2rs3/fORbP30FUVAyeXukYNb4J5SvmeS1r9SEySUlJSXmZwNCoDW++GhEREREREfngHN/x7G8Oisj7K9rdMrVLEBERkfdUkv6ZIe8oW7fHLxH1/tu79ScWDpnKZ8efPl5r7bSl/LZjN7O+X2U0/u2nX7J60iJWHd2KheWTI7xWjZ/PgR2/suCX9QBM7jyM2OgYhq+aasjr93F7MuXIQpeJA55Zy8px8zj00z7m7lxjGJvSZRiPIh8xas0MLhw9w9g2A/j06FbDMzLnDqRO56b88vX37N7yI0OXT37m3D99sZ3Vkxax/ODX/2id3kcxN+1eIur55o8axuOoKPpPnfnaanpdymY7mdolvJdqVhlLztw+jJvUPLVLESC9fdN/lKfj4UREREREREREREREREREJNWd+f04/rkCXynn/OFT5CgSZGhYAshbqjChl6/z6MFDAM4dPkWekgWN8vKVKsy5w6eeO++5I6fIU8I4J2+pwpw/8iTH3c+TuJhYLp86T9T9h1w8fhbfbP48evCQNVOW0HFs3+fOHRCUjbu3bhN+49YrvauIyPtGx8OJiIiIiIiIiIiIiIiIiEiqux0aRlrX9K+Uc/9OBK5e7kZjTi5p/7h3D3snRx7cicApvfP/i3Hm/p2I58774PY9wzyGnPRpiY56TFxMHPZOjvSaMYyZPccQFxtHmbqVyVe6CLP7jqda63qEX7/J2NYDSEpMpHHvthSv/ueRVWldXQC4ExKGq5fbK72viMj7RE1LIiIiIiIiIiIiIiIiIiKS6uJj47C0fnfOeSxapRRFq5QyXJ/af5Tgc5foOLYPHUs0oN/cUThlSEu/6u3IUSQIp/RPmqAsra0AiIuJTbXa3zddRoxJ7RLkLdu8fWhqlyCvgY6HExERERERERERERERERGRVOfo7MSjB1GvlOPsko4Hd+8ZjT24c++Pe0+ahJxc0vHg7v3/F3MfZ5d0z53XKUNawzyGnLv3sHWww8rG6qn4hLh4FgyZSteJA7l5NYSkxERyFs2Lp78P7pm8uHD0jCE26o9j6xzTOb3Su4qIvG/UtCQiIiIiIiIiIiIiIiIiIqkuU84AblwMfqWcrPlzcvrAMRITEg1jx3YfxMPfG3snRwAC8+fkxJ5DRnnHdv9OYP6cz503MN8zcn49SNZ8z87ZMHsl+UoXxj9XVpKTk0hKTDLcS0pIIjnpz+vr569gbmGOd0CmV3pXEZH3jZqWREREREREREREREREREQk1eUtVZjrF67w6I+diABuXg3hyukLPLhzj/jYOK6cvsCV0xdIiE8AoFStiphbWjCn33iun7/C7i0/8s2yjdRs38gwx8dtG3Dk5wN8tWgtIZeCWTttKZdOnKNaq7qGmFUTFjCj52jDdeXmtQm7fpMVY+cRcimYb1dtYs/Wn6jZvuFTdV+/cJU9W3bStF97ADz9fTExNeX7dd9wcOdeQi5fI0ue7Ib4078dI3uhPM/cselDF/XgAe0rleb2zdDULuWVHdu/lwFNG5CcnJzapfyn3YuIIptfF65fu5PapbyynT8cp3SxT/Q1fo3UtCQiIiIiIiIiIiIiIiIiIqnON5s//jmzsmfrT4axuf0n0KtSK75b/TWhV67Tq1IrelVqxb3wuwDYOdozas1Mwm/confVNiwfPYdGvVpTuVktwxzZCuSi79xRfL9mCz0qtmTft7v4ZOlEfAL9DTH3b0dwJzTccJ3R253hq6ZybPfv9KjYkq8Xr6P7lEHkK13EqOaUlBTmDZxE2xE9sLa1AcDKxopeM4ayYeZy5vSbQMcxfUjn5mLI2b3lRyo2qfGGVvHd9tWKJRT4qAwZ3D0AuHTmFGO6tKd12RK0KVeCcd07EXzhvCH+5rVgRnVuS4fKZWhWoiDda1Vl/YK5JCYmPPcZUQ8eML5HZzpVLU/T4gXoUr0iy6eMJ/rRI0PM1fNnGdisAS1KFWFSn+48iow03EtKTGRQi0ZcOn3SaN6gosUxMzdnz3fbXvOqvF9mTNlM5Wr58PZxYd3qX3FxaPbMjzt3nqz5gX3nqVp+FAHenfByaU3RfP1ZOHf73z7n6y8PULrYJ3hnaEPe7D2ZO3Or0f0Tx4MpU3wIPhnb0rT+NO7f+/Prn5iYRLmSQzly6LJRTrkKebCwMOOLDfte23p86ExSUlJSXiYwNGrDm69GREREREREPjjHd/i/RJSIvE+i3S1TuwQRERF5TyXpnxnyjrJ1e5zaJfxnHNy5l5Vj5zFn52pMTd+/PTgO/7Sf5WPmMPuHTzEzN0/tcv4zYm7aERcbQ8cq5flk9gICcuUmNjqarjUqk/+jUtRq2ZakxEQ+X7KAc8eOMn/rDszNLQgPDeHMkUP4Zc2GnYMD1y5eYPH4UZSpUZvGXXo881mPHj5k3/ff4Z89B47OzoTduMHyKePxy5qNHmMnAjCoRSOy5ytA+dr1WDRuFJlz5KR5z74AbF61nHt3btO636Cn5t7x+Xp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      "text/plain": [
       "<Figure size 3000x3000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## visualization to see the proportions of clients on their contribution on the alt text images\n",
    "\n",
    "#confirm percentages of alttext_all_percent\n",
    "#labels\n",
    "cl_more_post_pct['label'] = cl_more_post_pct.apply(lambda row: f'{row['client']}\\n{row['atxt_yes']} posts\\n({row['atxt_yes_pct']:.1f}%)', axis=1)\n",
    "    \n",
    "# Treemap plotting\n",
    "plt.figure(figsize=(30, 30))\n",
    "sq.plot(sizes=cl_more_post_pct['atxt_yes'], label=cl_more_post_pct['label'], alpha=0.4)\n",
    "plt.title('Proportion of clients with all of their attachd media with alt text description', fontsize=10)\n",
    "plt.axis('off')  # No axes for treemap\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b12a504-4286-48bf-9892-c3e20d58a1e8",
   "metadata": {},
   "source": [
    "The tree map provides a clear visual representation of the proportion of alt text usage among clients, based on their total number of posts. It highlights that KUVO Playlist Bot, Indie 102.3 Playlist Bot, and The Colorado Sound Playlist Bot not only have the highest total post counts but also demonstrate exemplary performance with 100% of their images containing alt text. This indicates that these three clients are among the best performers in utilizing alt text effectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "88286862-93a2-43bf-ba7b-431a69a3b769",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LdrtdycnJysrKUlRUlE9rA+BdDodDVqtVmZmZCg0N9XU5ALyo/QrKl/FqgElISJAk1dXVKTEx0d1eV1enoUOHusfU19d7rHfhwgWdOXPGvX5CQoLq6uo8xrQvt4/5rPDwcIWHh1/UHhoayg8cEKDYv4HA09F92qvzwKSkpCghIUFbtmxxt9ntdu3atUtpaWmSpLS0NJ09e1bV1dXuMVu3bpXL5dKIESPcY8rLyz2ug1mtVg0YMOCSl48AAEDXctkBprGxUTU1NaqpqZH+feNuTU2NTpw4IYvFonnz5umxxx7TX//6Vx04cED33nuvkpKSlJubK0kaNGiQJk6cqNmzZ2v37t3asWOHCgoKNG3aNCUlJUmSvvvd7yosLEyzZs3SoUOH9PLLL+upp57yuEQEAAC6rsu+hLR3716NHz/evdweKmbMmKG1a9fqZz/7mZqamjRnzhydPXtWo0eP1ubNmxUREeFeZ926dSooKNCECRMUFBSkqVOnauXKle7+6OholZaWau7cuRo2bJj69OmjRYsWecwVAwAAui6L8f/P5xJw7Ha7oqOj1dDQwE28QIBxOBzauHGjcnJyuAcGCDAdPX7zLiQAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6BBgAAGA6Xg8wTqdTDz/8sFJSUtStWzf9x3/8h371q1/JMAz3GMMwtGjRIiUmJqpbt27KyMjQ0aNHPbZz5swZ5efnKyoqSjExMZo1a5YaGxu9XS4AADAhrweYpUuXatWqVfrd736nw4cPa+nSpVq2bJmefvpp95hly5Zp5cqVWr16tXbt2qXu3bsrOztbLS0t7jH5+fk6dOiQrFarSkpKVF5erjlz5ni7XAAAYEIW49OnRrzgjjvuUHx8vP74xz+626ZOnapu3brphRdekGEYSkpK0vz587VgwQJJUkNDg+Lj47V27VpNmzZNhw8f1uDBg7Vnzx4NHz5ckrR582bl5OTogw8+UFJS0pfWYbfbFR0drYaGBkVFRXnzKwLwMYfDoY0bNyonJ0ehoaG+LgeAF3X0+O31MzCjRo3Sli1b9K9//UuS9Oabb+qNN97QpEmTJEm1tbWy2WzKyMhwrxMdHa0RI0aosrJSklRZWamYmBh3eJGkjIwMBQUFadeuXd4uGQAAmEyItzf40EMPyW63a+DAgQoODpbT6dSvf/1r5efnS5JsNpskKT4+3mO9+Ph4d5/NZlNcXJxnoSEh6t27t3vMZ7W2tqq1tdW9bLfbpX//n5rD4fDytwTgS+37NPs2EHg6ul97PcD83//9n9atW6cXX3xRN9xwg2pqajRv3jwlJSVpxowZ3v44t6KiIi1evPii9tLSUkVGRnba5wLwHavV6usSAHhZc3Nzh8Z5PcA88MADeuihhzRt2jRJUmpqqo4fP66ioiLNmDFDCQkJkqS6ujolJia616urq9PQoUMlSQkJCaqvr/fY7oULF3TmzBn3+p+1cOFCFRYWupftdruSk5OVlZXFPTBAgHE4HLJarcrMzOQeGCDAtF9B+TJeDzDNzc0KCvK8tSY4OFgul0uSlJKSooSEBG3ZssUdWOx2u3bt2qX77rtPkpSWlqazZ8+qurpaw4YNkyRt3bpVLpdLI0aMuOTnhoeHKzw8/KL20NBQfuCAAMX+DQSeju7TXg8wkydP1q9//Wv17dtXN9xwg/75z39qxYoV+sEPfiBJslgsmjdvnh577DFdf/31SklJ0cMPP6ykpCTl5uZKkgYNGqSJEydq9uzZWr16tRwOhwoKCjRt2rQOPYEEAAACm9cDzNNPP62HH35YP/7xj1VfX6+kpCT913/9lxYtWuQe87Of/UxNTU2aM2eOzp49q9GjR2vz5s2KiIhwj1m3bp0KCgo0YcIEBQUFaerUqVq5cqW3ywUAACbk9Xlg/AXzwACBi3lggMDls3lgAAAAOhsBBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmA4BBgAAmE6nBJgPP/xQ3/ve9xQbG6tu3bopNTVVe/fudfcbhqFFixYpMTFR3bp1U0ZGho4ePeqxjTNnzig/P19RUVGKiYnRrFmz1NjY2BnlAgAAk/F6gPnkk0902223KTQ0VJs2bdJbb72lJ554Qr169XKPWbZsmVauXKnVq1dr165d6t69u7Kzs9XS0uIek5+fr0OHDslqtaqkpETl5eWaM2eOt8sFAAAmZDEMw/DmBh966CHt2LFDFRUVl+w3DENJSUmaP3++FixYIElqaGhQfHy81q5dq2nTpunw4cMaPHiw9uzZo+HDh0uSNm/erJycHH3wwQdKSkr60jrsdruio6PV0NCgqKgob35FAD7mcDi0ceNG5eTkKDQ01NflAPCijh6/Q7z9wX/961+VnZ2tb3/72yorK9PXvvY1/fjHP9bs2bMlSbW1tbLZbMrIyHCvEx0drREjRqiyslLTpk1TZWWlYmJi3OFFkjIyMhQUFKRdu3bprrvuuuhzW1tb1dra6l622+3Sv3/oHA6Ht78mAB9q36fZt4HA09H92usB5r333tOqVatUWFion//859qzZ4/uv/9+hYWFacaMGbLZbJKk+Ph4j/Xi4+PdfTabTXFxcZ6FhoSod+/e7jGfVVRUpMWLF1/UXlpaqsjISC9+QwD+wmq1+roEAF7W3NzcoXFeDzAul0vDhw/XkiVLJEk33XSTDh48qNWrV2vGjBne/ji3hQsXqrCw0L1st9uVnJysrKwsLiEBAcbhcMhqtSozM5NLSECAab+C8mW8HmASExM1ePBgj7ZBgwbp1VdflSQlJCRIkurq6pSYmOgeU1dXp6FDh7rH1NfXe2zjwoULOnPmjHv9zwoPD1d4ePhF7aGhofzAAQHE6XRq586dKi8vV/fu3TV+/HgFBwf7uiwAXtLRY7bXn0K67bbbdOTIEY+2f/3rX+rXr58kKSUlRQkJCdqyZYu73263a9euXUpLS5MkpaWl6ezZs6qurnaP2bp1q1wul0aMGOHtkgGYRHFxsfr376/MzEytWLFCmZmZ6t+/v4qLi31dGoCrzOsB5qc//amqqqq0ZMkSvfPOO3rxxRe1Zs0azZ07V5JksVg0b948PfbYY/rrX/+qAwcO6N5771VSUpJyc3Olf5+xmThxombPnq3du3drx44dKigo0LRp0zr0BBKAwFNcXKy8vDylpqaqoqJCL730kioqKpSamqq8vDxCDNDVGJ3gb3/7mzFkyBAjPDzcGDhwoLFmzRqPfpfLZTz88MNGfHy8ER4ebkyYMME4cuSIx5iPP/7YuOeee4wePXoYUVFRxsyZM41z5851uIaGhgZDktHQ0OC17wXANy5cuGBcd911xuTJkw2n02m0tbUZGzZsMNra2gyn02lMnjzZSElJMS5cuODrUgFcoY4ev70+D4y/YB4YIHBs375d48ePV2VlpUaOHHnRPDCVlZUaNWqUtm3bpnHjxvm6XABXoKPHb96FBMDvnTp1SpI0ZMiQS/a3t7ePAxD4CDAA/F77E4sHDx68ZH97+6efbAQQ2AgwAPzemDFjdN1112nJkiVyuVwefS6XS0VFRUpJSdGYMWN8ViOAq4sAA8DvBQcH64knnlBJSYlyc3NVVVWl8+fPq6qqSrm5uSopKdHy5cuZDwboQrw+kR0AdIYpU6Zo/fr1mj9/vtLT093tKSkpWr9+vaZMmeLT+gBcXTyFBMBUnE6ntm3bpk2bNmnSpEnMxAsEGJ+9jRoAOlNwcLDGjh2rpqYmjR07lvACdFHcAwMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyHAAMAAEyn0wPMb37zG1ksFs2bN8/d1tLSorlz5yo2NlY9evTQ1KlTVVdX57HeiRMndPvttysyMlJxcXF64IEHdOHChc4uFwAAmECnBpg9e/boD3/4g77xjW94tP/0pz/V3/72N73yyisqKyvTyZMnNWXKFHe/0+nU7bffrra2Nu3cuVN/+tOftHbtWi1atKgzywUAACbRaQGmsbFR+fn5evbZZ9WrVy93e0NDg/74xz9qxYoV+uY3v6lhw4bp+eef186dO1VVVSVJKi0t1VtvvaUXXnhBQ4cO1aRJk/SrX/1KzzzzjNra2jqrZAAAYBIhnbXhuXPn6vbbb1dGRoYee+wxd3t1dbUcDocyMjLcbQMHDlTfvn1VWVmpkSNHqrKyUqmpqYqPj3ePyc7O1n333adDhw7ppptuuujzWltb1dra6l622+2SJIfDIYfD0VlfE4APtO/T7NtA4Onoft0pAebPf/6z9u3bpz179lzUZ7PZFBYWppiYGI/2+Ph42Ww295hPh5f2/va+SykqKtLixYsvai8tLVVkZOQVfR8A/slqtfq6BABe1tzc3KFxXg8w77//vv77v/9bVqtVERER3t7851q4cKEKCwvdy3a7XcnJycrKylJUVNRVqwNA53M4HLJarcrMzFRoaKivywHgRe1XUL6M1wNMdXW16uvrdfPNN7vbnE6nysvL9bvf/U6vv/662tradPbsWY+zMHV1dUpISJAkJSQkaPfu3R7bbX9KqX3MZ4WHhys8PPyi9tDQUH7ggADF/g0Eno7u016/iXfChAk6cOCAampq3P+GDx+u/Px893+HhoZqy5Yt7nWOHDmiEydOKC0tTZKUlpamAwcOqL6+3j3GarUqKipKgwcP9nbJAEzE6XSqrKxM5eXlKisrk9Pp9HVJAHzA62dgevbsqSFDhni0de/eXbGxse72WbNmqbCwUL1791ZUVJR+8pOfKC0tTSNHjpQkZWVlafDgwZo+fbqWLVsmm82mX/ziF5o7d+4lz7IA6BqKi4tVWFio48ePS5JWrFihfv36acWKFR5TMQAIfD6Zife3v/2t7rjjDk2dOlXp6elKSEhQcXGxuz84OFglJSUKDg5WWlqavve97+nee+/VL3/5S1+UC8APFBcXa+rUqR5nZiWpvr5eU6dO9fgNARD4LIZhGL4uojPY7XZFR0eroaGBm3gBk3M6nUpMTNTp06d1xx136MEHH9QHH3yga6+9VkuXLlVJSYni4uJ08uRJBQcH+7pcAFego8dv3oUEwO9t375dp0+f1ujRo/WXv/xFI0aMULdu3TRixAj95S9/0ejRo1VfX6/t27f7ulQAVwkBBoDfaw8mixcvVlCQ589WUFCQHnnkEY9xAAIfAQYAAJgOAQaA3xs3bpwk6ZFHHpHL5fLoc7lcevTRRz3GAQh8BBgAfm/cuHGKi4vTG2+8oW9961uqqqrS+fPnVVVVpW9961vasWOH4uLiCDBAF9JpL3MEAG8JDg7WqlWrlJeXpy1btqikpMTdFxkZKYvFolWrVvEEEtCFcAYGgClMmTJF69evv+SLXtevX89EdkAXwzwwAEzF6XRq27Zt2rRpkyZNmqTx48dz5gUIIB09fnMJCYCpBAcHa+zYsWpqatLYsWMJL0AXxSUkAABgOgQYAABgOgQYAABgOgQYAABgOgQYAABgOgQYAABgOgQYAABgOgQYAABgOgQYAABgOgQYAKbidDpVVlam8vJylZWVyel0+rokAD5AgAFgGsXFxerfv78yMzO1YsUKZWZmqn///iouLvZ1aQCuMgIMAFMoLi5WXl6eUlNTVVFRoZdeekkVFRVKTU1VXl4eIQboYngbNQC/53Q61b9/f6WmpmrDhg1yOp3auHGjcnJyFBwcrNzcXB08eFBHjx7l5Y6AyXX0+M0ZGAB+r6KiQseOHdPPf/5zBQV5/mwFBQVp4cKFqq2tVUVFhc9qBHB1EWAA+L1Tp05JkoYMGXLJ/vb29nEAAh8BBoDfS0xMlCQdPHjwkv3t7e3jAAQ+AgwAvzdmzBhdd911WrJkiVwul0efy+VSUVGRUlJSNGbMGJ/VCODqIsAA8HvBwcF64oknVFJSotzcXFVVVen8+fOqqqpSbm6uSkpKtHz5cm7gBbqQEF8XAAAdMWXKFK1fv17z589Xenq6uz0lJUXr16/XlClTfFofgKuLx6gBmEpbW5uefvppbd26Vd/85jf1k5/8RGFhYb4uC4CX8Bg1gIBTXFysAQMGaMGCBdq4caMWLFigAQMGMIkd0AURYACYAjPxAvg0LiEB8HvMxAt0HVxCAhAwmIkXwGcRYAD4PWbiBfBZBBgAfo+ZeAF8FgEGgN9jJl4An+X1AFNUVKRbbrlFPXv2VFxcnHJzc3XkyBGPMS0tLZo7d65iY2PVo0cPTZ06VXV1dR5jTpw4odtvv12RkZGKi4vTAw88oAsXLni7XAAmwEy8AD7L6wGmrKxMc+fOVVVVlaxWqxwOh7KystTU1OQe89Of/lR/+9vf9Morr6isrEwnT570mEXT6XTq9ttvV1tbm3bu3Kk//elPWrt2rRYtWuTtcgGYRPtMvAcOHFB6erruuecepaen6+DBg8zEC3RBnf4Y9enTpxUXF6eysjKlp6eroaFB11xzjV588UXl5eVJkt5++20NGjRIlZWVGjlypDZt2qQ77rhDJ0+eVHx8vCRp9erVevDBB3X69OkOzbrJY9RAYHI6ndq2bZs2bdqkSZMmafz48Zx5AQJIR4/fnf4upIaGBklS7969JUnV1dVyOBzKyMhwjxk4cKD69u3rDjCVlZVKTU11hxdJys7O1n333adDhw7ppptuuuhzWltb1dra6l622+2SJIfDIYfD0anfEcDVNWrUKDU1NWnUqFFyuVwX3RcDwLw6eszu1ADjcrk0b9483Xbbbe7HHG02m8LCwhQTE+MxNj4+XjabzT3m0+Glvb+971KKioq0ePHii9pLS0sVGRnpte8EwH9YrVZflwDAy5qbmzs0rlMDzNy5c3Xw4EG98cYbnfkxkqSFCxeqsLDQvWy325WcnKysrCwuIQEBxuFwyGq1KjMzU6Ghob4uB4AXtV9B+TKdFmAKCgpUUlKi8vJyXXvtte72hIQEtbW16ezZsx5nYerq6pSQkOAes3v3bo/ttT+l1D7ms8LDwxUeHn5Re2hoKD9wQABxOp3auXOnysvL1b17d+6BAQJMR4/ZXn8KyTAMFRQU6LXXXtPWrVuVkpLi0T9s2DCFhoZqy5Yt7rYjR47oxIkTSktLkySlpaXpwIEDqq+vd4+xWq2KiorS4MGDvV0yAJMoLi5W//79lZmZqRUrVigzM1P9+/fnRY5AF+T1ADN37ly98MILevHFF9WzZ0/ZbDbZbDadP39ekhQdHa1Zs2apsLBQ27ZtU3V1tWbOnKm0tDSNHDlSkpSVlaXBgwdr+vTpevPNN/X666/rF7/4hebOnXvJsywAAh9vowbwaV5/jNpisVyy/fnnn9f3v/996d8T2c2fP18vvfSSWltblZ2drd///vcel4eOHz+u++67T9u3b1f37t01Y8YM/eY3v1FISMeuevEYNRA4eBs10HV09Pjd6fPA+AoBBggc27dv1/jx491TLTgcDneACQ0NVWVlpUaNGqVt27Zp3Lhxvi4XwBXo6PGbdyEB8Hu8jRrAZxFgAPi9T7+N2ul0qqysTOXl5SorK5PT6eRt1EAXxCUkAH6v/R6YPn366PTp0zp+/Li7r1+/frrmmmv08ccfcw8MEAC4hAQgYAQHB+vb3/629u7dq5aWFq1atUrPPfecVq1apZaWFu3du1d5eXmEF6AL4QwMAL/36TMwH330kY4dO+buS0lJUWxsLGdggADBGRgAAaOiokLHjh3T008/rSNHjmj58uXKycnR8uXL9fbbb2vlypWqra1VRUWFr0sFcJUQYAD4vfani959910NGDBACxYs0MaNG7VgwQINGDBA7733nsc4AIGPAAPA77U/XTR9+vRLzsQ7ffp0j3EAAh8BBoDfGzVqlEJCQhQXF6dXXnlFLS0t2rNnj1paWvTKK68oLi5OISEhGjVqlK9LBXCVdNrbqAHAW3bu3KkLFy6orq5OvXr1cr9bbcWKFerWrZt7eefOnczEC3QRnIEB4Pe+6N6WT79/jXtggK6DAAPA78XFxUmSRo8erYaGBlmtVhUWFspqters2bO67bbbPMYBCHxcQgJgKsHBwRo7dqyampo0duxYBQcHe5yFAdA1cAYGgN+rr6+XJO3YsUO5ubmqqqrS+fPnVVVVpdzcXO3YscNjHIDAR4AB4PfaH49esmSJDhw4oPT0dN1zzz1KT0/XwYMH9etf/9pjHIDAx6sEAPi9T79KoL6+XidOnHD39e3bV3FxcbxKAAgQvEoAQMD49MscPx1eJOnEiRO8zBHogjgDA8DvOZ1OxcbGqqGh4XPHREdH6+OPPybEACbX0eM3TyEB8Htbt251h5c+ffpo+vTpam5uVmRkpP73f/9XH330kRoaGrR161ZlZmb6ulwAVwGXkAD4vbVr10qSevTooVOnTmnp0qWaNGmSli5dqlOnTqlHjx4e4wAEPgIMAL+3f/9+SdLMmTMVEuJ54jgkJET33nuvxzgAgY8AA8DvtV8H37Jli1wul0efy+XStm3bPMYBCHzcAwPA7911113auXOn3nrrLd15553KysrS0aNHdfz4cZWWlurw4cPucQC6Bp5CAuD32traFBERoS/6ubJYLGppaVFYWNhVrQ2AdzEPDICAERYWpjvvvPMLx9x5552EF6ALIcAA8HtOp1Nvvvnm5waUsLAw7d+/X06n86rXBsA3CDAA/F5FRYWOHTumtrY2WSwW3XzzzRo9erRuvvlmWSwWtbW1qba2VhUVFb4uFcBVwk28APxebW2t9O/7XJqbmxUcHKyNGzcqJydHTqdTkZGRMgxDtbW1GjdunK/LBXAVcAYGgN/74x//KEnKzs5WRESER19ERIR79t32cQACH2dgAFwVzc3Nevvtt7/SujabTZJUX1+vvXv3qrnVoZ0H3lWvPnsVGR6q06dPu8ft27fvsrc/cOBARUZGfqXaAPgGj1EDuCr27dunYcOG+bqMS6qurtbNN9/s6zIA8DJHAP5m4MCBqq6u/krrNjY2auzYsZKk+Ph41dXVufs+vVxWVuZ+L9Ll1gbAXAgwAK6KyMjIKzrLccstt2jPnj2qr6/XiNvG6m1LXw00Tmj3znJ3f3p6uhcrBuDPuIQEwDRuvfVW7dmz56L2W265Rbt37/ZJTQC8i5l4AQSc3bt369y5cxqXOUmhffppXOYknTt3jvACdEF+fQnpmWee0eOPPy6bzaYbb7xRTz/9tG699VZflwV0ObUfNamp9YKvy3ArWLJatesPqCAvVccanFJDg69LkiR1Dw9RSp/uvi4D6BL8NsC8/PLLKiws1OrVqzVixAg9+eSTys7O1pEjRxQXF+fr8oAuo/ajJo1fvt3XZVzS/PUHfF3CRbYtGEeIAa4Cvw0wK1as0OzZszVz5kxJ0urVq/X3v/9dzz33nB566CFflwd0Ge1nXp68e6j6x13+Ez6doel8q0q2V+qOcWnq3i3c1+VIkt6pb9S8l2v86kwVEMj8MsC0tbWpurpaCxcudLcFBQUpIyNDlZWVl1yntbVVra2t7mW73S5JcjgccjgcV6FqIDCdO98qS4hd7549LIV+9TMLLa0tOvXBCa/U5Lzg0umPj6rizTMKDrnyW/kSr+2riPCIDoz8fO83npclxK4LFy7wmwNcgY7uP34ZYD766CM5nU7Fx8d7tMfHx3/uTJ5FRUVavHjxRe2lpaXMsAlcgco6i0JjdmntiS2Sd/KHdyRIOxq9tK2z3tlMaMwE7amM1PFu3tke0BU1Nzd3aJxfBpivYuHChSosLHQv2+12JScnKysri8eogSswsqlNKQe+puieeYoICf7K2/H2GZh33jmq/v2v95szMJKU2PMa3ZzU74q3A3Rl7VdQvoxfBpg+ffooODjYY7ZNSaqrq1NCQsIl1wkPD1d4+MXXwkNDQxUaGtpptQKBLj4mVP81xkuvAPDSZhwOh/tt1OzfQGDp6D7tl/PAhIWFadiwYdqyZYu7zeVyacuWLUpLS/NpbQAAwPf88gyMJBUWFmrGjBkaPny4br31Vj355JNqampyP5UEAAC6Lr8NMHfffbdOnz6tRYsWyWazaejQodq8efNFN/YCAICux28DjCQVFBSooKDA12UAAAA/45f3wAAAAHwRAgwAADAdAgwAADAdAgwAADAdAgwAADAdAgwAADAdAgwAADAdAgwAADAdAgwAADAdv56J90oYhiFdxmu5AZiHw+FQc3Oz7HY7b6MGAkz7cbv9OP55AjbAnDt3TpKUnJzs61IAAMBlOnfunKKjoz+332J8WcQxKZfLpZMnT6pnz56yWCy+LgeAF9ntdiUnJ+v9999XVFSUr8sB4EWGYejcuXNKSkpSUNDn3+kSsAEGQOCy2+2Kjo5WQ0MDAQbooriJFwAAmA4BBgAAmA4BBoDphIeH65FHHlF4eLivSwHgI9wDAwAATIczMAAAwHQIMAAAwHQIMAAAwHQIMAAAwHQIMAA63bFjx2SxWFRTU3NZ661du1YxMTGdVhcA8yLAAAAA0yHAAPCKzZs3a/To0YqJiVFsbKzuuOMOvfvuu5KklJQUSdJNN90ki8WicePGqaWlRTfccIPmzJnj3sa7776rnj176rnnntP27ds1c+ZMNTQ0yGKxyGKx6NFHH/3CGn75y19qyJAhF7UPHTpUDz/8sHv5f/7nfzRo0CBFRERo4MCB+v3vf+/ua2trU0FBgRITExUREaF+/fqpqKjIK38jAF5kAIAXrF+/3nj11VeNo0ePGv/85z+NyZMnG6mpqYbT6TR2795tSDL+8Y9/GKdOnTI+/vhjwzAM45///KcRFhZmbNiwwbhw4YIxcuRI46677jIMwzBaW1uNJ5980oiKijJOnTplnDp1yjh37twX1vD+++8bQUFBxu7du91t+/btMywWi/Huu+8ahmEYL7zwgpGYmGi8+uqrxnvvvWe8+uqrRu/evY21a9cahmEYjz/+uJGcnGyUl5cbx44dMyoqKowXX3yxE/9yAL6KEF8HKACBYerUqR7Lzz33nK655hq99dZbuuaaayRJsbGxSkhIcI8ZOnSoHnvsMf3whz/UtGnTdPz4cZWUlEiSwsLCFB0dLYvF4rHOF7n22muVnZ2t559/Xrfccosk6fnnn9fYsWP19a9/XZL0yCOP6IknntCUKVOkf58deuutt/SHP/xBM2bM0IkTJ3T99ddr9OjRslgs6tevn5f+QgC8iUtIALzi6NGjuueee/T1r39dUVFRuu666yRJJ06c+ML15s+fr//8z//U7373Oz333HOKjY29ojpmz56tl156SS0tLWpra9OLL76oH/zgB5KkpqYmvfvuu5o1a5Z69Ojh/vfYY4+5L3d9//vfV01NjQYMGKD7779fpaWlV1QPgM7BGRgAXjF58mT169dPzz77rJKSkuRyuTRkyBC1tbV94Xr19fX617/+peDgYB09elQTJ0684jrCw8P12muvKSwsTA6HQ3l5eZKkxsZGSdKzzz6rESNGeKwXHBwsSbr55ptVW1urTZs26R//+Ie+853vKCMjQ+vXr7+iugB4FwEGwBX7+OOPdeTIET377LMaM2aMJOmNN95w94eFhUmSnE7nRev+4Ac/UGpqqmbNmqXZs2crIyNDgwYNcq93qXW+SEhIiGbMmKHnn39eYWFhmjZtmrp16yZJio+PV1JSkt577z3l5+d/7jaioqJ099136+6771ZeXp4mTpyoM2fOqHfv3pdVC4DOQ4ABcMV69eql2NhYrVmzRomJiTpx4oQeeughd39cXJy6deumzZs369prr1VERISio6P1zDPPqLKyUvv371dycrL+/ve/Kz8/X1VVVQoLC9N1112nxsZGbdmyRTfeeKMiIyMVGRn5pfX88Ic/dIegHTt2ePQtXrxY999/v6KjozVx4kS1trZq7969+uSTT1RYWKgVK1YoMTFRN910k4KCgvTKK68oISGB+WgAf+Pru4gBBAar1WoMGjTICA8PN77xjW8Y27dvNyQZr732mmEYhvHss88aycnJRlBQkDF27Fjj8OHDRrdu3Tye8Pnkk0+M5ORk42c/+5m77Uc/+pERGxtrSDIeeeSRDtczZswY44Ybbrhk37p164yhQ4caYWFhRq9evYz09HSjuLjYMAzDWLNmjTF06FCje/fuRlRUlDFhwgRj3759V/CXAdAZLIZhGL4OUQDgTYZh6Prrr9ePf/xjFRYW+rocAJ2AS0gAAsrp06f15z//WTabTTNnzvR1OQA6CQEGgGlUVFRo0qRJn9vf2NiouLg49enTR2vWrFGvXr2uan0Arh4uIQEwjfPnz+vDDz/83P7+/ftf1XoA+A4BBgAAmA4z8QIAANMhwAAAANMhwAAAANMhwAAAANMhwAAAANMhwAAAANMhwAAAANMhwAAAANP5/wAKHzQNX1jIXAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cl_more_post[['atxt_yes']].boxplot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c4f9a447-59b2-4832-8503-9f58a0d13cb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Count'>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(cl_more_post[['atxt_yes']], bins=50, kde=False, color='skyblue', edgecolor='black')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebbb7eb5-214b-479c-8858-195a2a3e5a8c",
   "metadata": {},
   "source": [
    "## Conclusion and future development\n",
    "\n",
    "Even though the Fediverse and alternative social networks supposedly are more sensitive to ethical issues, this analysis showed without any doubt that the use of image descriptions is still too limited.\n",
    "\n",
    "Our analysis proved to be extremely informative concerning some aspects in particular. Despite what we were expecting, we discovered that a great number of clients was used to published only very few posts, and we facced the chellenge of deciding how to treat this surprising knowledge.\n",
    "\n",
    "We believe that there is a great room for expansion and deepening of this analysis, not merely in terms of development, but chiefly in relation to the expansion of the dataset, in particular:\n",
    "\n",
    "- by updating the dataset to a more recent date\n",
    "- by including more posts in the dataset\n",
    "- by gathering information from other servers outside of mastodon.social\n",
    "- by cross-referencing alt text use among different servers, not only among different clients\n",
    "\n",
    "Lastly, we believe it would be very interesting, also using skills and tools learned from other courses, to investigate the qualities and the design on the most popular clients, pinpointing best practices to incentivize users to add image descriptions."
   ]
  }
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