{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparing Textual Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```{note}\n",
    "Install ekorpkit package first.\n",
    "Set logging level to Warning, if you don't want to see verbose logging,\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.base:IPython version: (6, 9, 0), client: jupyter_client\n",
      "INFO:ekorpkit.base:Google Colab not detected.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "version: 0.1.35+0.g69734d6.dirty\n",
      "is notebook? True\n",
      "is colab? False\n",
      "evironment varialbles:\n",
      "{'CUDA_DEVICE_ORDER': None,\n",
      " 'CUDA_VISIBLE_DEVICES': None,\n",
      " 'EKORPKIT_CONFIG_DIR': '/workspace/projects/ekorpkit-book/config',\n",
      " 'EKORPKIT_DATA_DIR': None,\n",
      " 'EKORPKIT_LOG_LEVEL': 'WARNING',\n",
      " 'EKORPKIT_PROJECT': 'ekorpkit-book',\n",
      " 'EKORPKIT_WORKSPACE_ROOT': '/workspace',\n",
      " 'KMP_DUPLICATE_LIB_OK': 'TRUE',\n",
      " 'NUM_WORKERS': 230}\n"
     ]
    }
   ],
   "source": [
    "%config InlineBackend.figure_format='retina'\n",
    "from ekorpkit import eKonf\n",
    "\n",
    "eKonf.setLogger(\"WARNING\")\n",
    "print(\"version:\", eKonf.__version__)\n",
    "print(\"is notebook?\", eKonf.is_notebook())\n",
    "print(\"is colab?\", eKonf.is_colab())\n",
    "print(\"evironment varialbles:\")\n",
    "eKonf.print(eKonf.env().dict())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir = \"../data/fomc\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load FOMC corpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.base:IPython version: (6, 9, 0), client: jupyter_client\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Corpus : fomc\n"
     ]
    }
   ],
   "source": [
    "cfg = eKonf.compose('corpus')\n",
    "cfg.name = 'fomc'\n",
    "cfg.path.cache.uri = 'https://github.com/entelecheia/ekorpkit-book/raw/main/assets/data/fomc.zip'\n",
    "cfg.data_dir = cfg.path.cached_path\n",
    "cfg.auto.merge = True\n",
    "fomc_corpus = eKonf.instantiate(cfg)\n",
    "print(fomc_corpus)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load FOMC class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cfg = eKonf.compose(\"io/fetcher/fomc\")\n",
    "cfg.output_dir = data_dir\n",
    "fomc = eKonf.instantiate(cfg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>unscheduled</th>\n",
       "      <th>forecast</th>\n",
       "      <th>confcall</th>\n",
       "      <th>speaker</th>\n",
       "      <th>rate</th>\n",
       "      <th>rate_change</th>\n",
       "      <th>rate_decision</th>\n",
       "      <th>rate_changed</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1982-10-05</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Paul Volcker</td>\n",
       "      <td>9.50</td>\n",
       "      <td>-0.50</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-11-16</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Paul Volcker</td>\n",
       "      <td>9.00</td>\n",
       "      <td>-0.50</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-12-21</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Paul Volcker</td>\n",
       "      <td>8.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-01-14</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>Paul Volcker</td>\n",
       "      <td>8.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-01-21</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>Paul Volcker</td>\n",
       "      <td>8.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-11-03</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Jerome Powell</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-15</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>Jerome Powell</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-26</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Jerome Powell</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-16</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>Jerome Powell</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-04</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>Jerome Powell</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.50</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>415 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            unscheduled  forecast  confcall        speaker  rate  rate_change  \\\n",
       "date                                                                            \n",
       "1982-10-05        False     False     False   Paul Volcker  9.50        -0.50   \n",
       "1982-11-16        False     False     False   Paul Volcker  9.00        -0.50   \n",
       "1982-12-21        False     False     False   Paul Volcker  8.50         0.00   \n",
       "1983-01-14        False     False      True   Paul Volcker  8.50         0.00   \n",
       "1983-01-21        False     False      True   Paul Volcker  8.50         0.00   \n",
       "...                 ...       ...       ...            ...   ...          ...   \n",
       "2021-11-03        False     False     False  Jerome Powell  0.25         0.00   \n",
       "2021-12-15        False      True     False  Jerome Powell  0.25         0.00   \n",
       "2022-01-26        False     False     False  Jerome Powell  0.25         0.00   \n",
       "2022-03-16        False      True     False  Jerome Powell  0.50         0.25   \n",
       "2022-05-04        False     False     False  Jerome Powell  1.00         0.50   \n",
       "\n",
       "            rate_decision  rate_changed  \n",
       "date                                     \n",
       "1982-10-05           -1.0             1  \n",
       "1982-11-16           -1.0             1  \n",
       "1982-12-21            0.0             0  \n",
       "1983-01-14            0.0             0  \n",
       "1983-01-21            0.0             0  \n",
       "...                   ...           ...  \n",
       "2021-11-03            0.0             0  \n",
       "2021-12-15            0.0             0  \n",
       "2022-01-26            0.0             0  \n",
       "2022-03-16            1.0             1  \n",
       "2022-05-04            1.0             1  \n",
       "\n",
       "[415 rows x 8 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fomc.load_calendar(from_year=1982, force_download=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Postprocess metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>id</th>\n",
       "      <th>text</th>\n",
       "      <th>split</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>content_type</th>\n",
       "      <th>date</th>\n",
       "      <th>speaker</th>\n",
       "      <th>title</th>\n",
       "      <th>decision</th>\n",
       "      <th>rate</th>\n",
       "      <th>recent_meeting</th>\n",
       "      <th>recent_decision</th>\n",
       "      <th>recent_rate</th>\n",
       "      <th>next_meeting</th>\n",
       "      <th>next_decision</th>\n",
       "      <th>next_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2817</th>\n",
       "      <td>2850</td>\n",
       "      <td>CHAIR  YELLEN.  I’d like to begin by welcoming...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-06-18</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-06-18</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-06-18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818</th>\n",
       "      <td>2851</td>\n",
       "      <td>CHAIR YELLEN.  Good morning, everybody.  I wou...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2819</th>\n",
       "      <td>2852</td>\n",
       "      <td>CHAIR YELLEN.  Good morning, everybody. Our fi...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2820</th>\n",
       "      <td>2853</td>\n",
       "      <td>CHAIR YELLEN.  I’d like to call this meeting t...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2821</th>\n",
       "      <td>2854</td>\n",
       "      <td>CHAIR YELLEN.  Good afternoon, everyone.  I th...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id                                               text  split  \\\n",
       "2817  2850  CHAIR  YELLEN.  I’d like to begin by welcoming...  train   \n",
       "2818  2851  CHAIR YELLEN.  Good morning, everybody.  I wou...  train   \n",
       "2819  2852  CHAIR YELLEN.  Good morning, everybody. Our fi...  train   \n",
       "2820  2853  CHAIR YELLEN.  I’d like to call this meeting t...  train   \n",
       "2821  2854  CHAIR YELLEN.  Good afternoon, everyone.  I th...  train   \n",
       "\n",
       "      timestamp         content_type        date       speaker  \\\n",
       "2817 2014-06-18  fomc_meeting_script  2014-06-18  Janet Yellen   \n",
       "2818 2014-07-30  fomc_meeting_script  2014-07-30  Janet Yellen   \n",
       "2819 2014-09-17  fomc_meeting_script  2014-09-17  Janet Yellen   \n",
       "2820 2014-10-29  fomc_meeting_script  2014-10-29  Janet Yellen   \n",
       "2821 2014-12-17  fomc_meeting_script  2014-12-17  Janet Yellen   \n",
       "\n",
       "                        title  decision  rate recent_meeting  recent_decision  \\\n",
       "2817  FOMC Meeting Transcript       0.0  0.25     2014-06-18              0.0   \n",
       "2818  FOMC Meeting Transcript       0.0  0.25     2014-07-30              0.0   \n",
       "2819  FOMC Meeting Transcript       0.0  0.25     2014-09-17              0.0   \n",
       "2820  FOMC Meeting Transcript       2.0  0.25     2014-10-29              2.0   \n",
       "2821  FOMC Meeting Transcript       0.0  0.25     2014-12-17              0.0   \n",
       "\n",
       "      recent_rate next_meeting  next_decision  next_rate  \n",
       "2817         0.25   2014-07-30            0.0       0.25  \n",
       "2818         0.25   2014-09-17            0.0       0.25  \n",
       "2819         0.25   2014-10-29            2.0       0.25  \n",
       "2820         0.25   2014-12-17            0.0       0.25  \n",
       "2821         0.25   2015-01-28            0.0       0.25  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Postprocessing\n",
    "fomc_data = fomc.postprocess_metadata(fomc_corpus.data)\n",
    "fomc_data.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Postprocess FOMC corpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.pipelines.pipe:Applying pipeline: OrderedDict([('filter_length', 'filter_length'), ('save_dataframe', 'save_dataframe')])\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function filter_length at 0x7fc2a666cf70>, len_bytes={'_partial_': True, '_target_': 'ekorpkit.utils.func.len_bytes'}, len_words={'_partial_': True, '_target_': 'ekorpkit.utils.func.len_words'})\n",
      "INFO:ekorpkit.base:Using batcher with minibatch size: 13\n",
      "INFO:ekorpkit.utils.batch.batcher: backend: joblib  minibatch_size: 13  procs: 230  input_split: False  merge_output: True  len(data): 2802 len(args): 5\n",
      "Calculating length: 100%|██████████| 216/216 [00:04<00:00, 53.65it/s] \n",
      "INFO:ekorpkit.pipelines.pipe:removed 0 of 2802 documents with length < 50\n",
      "INFO:ekorpkit.pipelines.pipe: >> elapsed time to filter length: 0:00:04.039304\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function save_dataframe at 0x7fc2a666d550>)\n",
      "INFO:ekorpkit.io.file:Saving dataframe to ../data/fomc/fomc_corpus.parquet\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\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>id</th>\n",
       "      <th>text</th>\n",
       "      <th>split</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>content_type</th>\n",
       "      <th>date</th>\n",
       "      <th>speaker</th>\n",
       "      <th>title</th>\n",
       "      <th>decision</th>\n",
       "      <th>rate</th>\n",
       "      <th>recent_meeting</th>\n",
       "      <th>recent_decision</th>\n",
       "      <th>recent_rate</th>\n",
       "      <th>next_meeting</th>\n",
       "      <th>next_decision</th>\n",
       "      <th>next_rate</th>\n",
       "      <th>text_num_words</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2817</th>\n",
       "      <td>2850</td>\n",
       "      <td>CHAIR  YELLEN.  I’d like to begin by welcoming...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-06-18</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-06-18</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-06-18</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>86489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818</th>\n",
       "      <td>2851</td>\n",
       "      <td>CHAIR YELLEN.  Good morning, everybody.  I wou...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>88197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2819</th>\n",
       "      <td>2852</td>\n",
       "      <td>CHAIR YELLEN.  Good morning, everybody. Our fi...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>61211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2820</th>\n",
       "      <td>2853</td>\n",
       "      <td>CHAIR YELLEN.  I’d like to call this meeting t...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>72240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2821</th>\n",
       "      <td>2854</td>\n",
       "      <td>CHAIR YELLEN.  Good afternoon, everyone.  I th...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>58709</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id                                               text  split  \\\n",
       "2817  2850  CHAIR  YELLEN.  I’d like to begin by welcoming...  train   \n",
       "2818  2851  CHAIR YELLEN.  Good morning, everybody.  I wou...  train   \n",
       "2819  2852  CHAIR YELLEN.  Good morning, everybody. Our fi...  train   \n",
       "2820  2853  CHAIR YELLEN.  I’d like to call this meeting t...  train   \n",
       "2821  2854  CHAIR YELLEN.  Good afternoon, everyone.  I th...  train   \n",
       "\n",
       "      timestamp         content_type        date       speaker  \\\n",
       "2817 2014-06-18  fomc_meeting_script  2014-06-18  Janet Yellen   \n",
       "2818 2014-07-30  fomc_meeting_script  2014-07-30  Janet Yellen   \n",
       "2819 2014-09-17  fomc_meeting_script  2014-09-17  Janet Yellen   \n",
       "2820 2014-10-29  fomc_meeting_script  2014-10-29  Janet Yellen   \n",
       "2821 2014-12-17  fomc_meeting_script  2014-12-17  Janet Yellen   \n",
       "\n",
       "                        title  decision  rate recent_meeting  recent_decision  \\\n",
       "2817  FOMC Meeting Transcript       0.0  0.25     2014-06-18              0.0   \n",
       "2818  FOMC Meeting Transcript       0.0  0.25     2014-07-30              0.0   \n",
       "2819  FOMC Meeting Transcript       0.0  0.25     2014-09-17              0.0   \n",
       "2820  FOMC Meeting Transcript       2.0  0.25     2014-10-29              2.0   \n",
       "2821  FOMC Meeting Transcript       0.0  0.25     2014-12-17              0.0   \n",
       "\n",
       "      recent_rate next_meeting  next_decision  next_rate  text_num_words  \n",
       "2817         0.25   2014-07-30            0.0       0.25           86489  \n",
       "2818         0.25   2014-09-17            0.0       0.25           88197  \n",
       "2819         0.25   2014-10-29            2.0       0.25           61211  \n",
       "2820         0.25   2014-12-17            0.0       0.25           72240  \n",
       "2821         0.25   2015-01-28            0.0       0.25           58709  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove sections having less than 50 words because those are unlikely to contain meaningful sentences.\n",
    "overrides=[\n",
    "    '+pipeline=default',\n",
    "    'pipeline/filter_length=words',\n",
    "]\n",
    "cfg = eKonf.compose(\"pipeline\", overrides)\n",
    "cfg._pipeline_ = [\"filter_length\", \"save_dataframe\"]\n",
    "cfg.num_workers = 10\n",
    "cfg.filter_length.min_length = 50\n",
    "cfg.save_dataframe.output_dir = data_dir\n",
    "cfg.save_dataframe.output_file = \"fomc_corpus.parquet\"\n",
    "fomc_data = eKonf.instantiate(cfg, data=fomc_data)\n",
    "fomc_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.io.file:Processing [1] files from ['fomc_corpus.parquet']\n",
      "INFO:ekorpkit.io.file:Loading 1 dataframes from ['../data/fomc/fomc_corpus.parquet']\n",
      "INFO:ekorpkit.io.file:Loading data from ../data/fomc/fomc_corpus.parquet\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>text</th>\n",
       "      <th>split</th>\n",
       "      <th>timestamp</th>\n",
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       "      <th>date</th>\n",
       "      <th>speaker</th>\n",
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       "      <th>recent_meeting</th>\n",
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       "      <th>next_meeting</th>\n",
       "      <th>next_decision</th>\n",
       "      <th>next_rate</th>\n",
       "      <th>text_num_words</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2817</th>\n",
       "      <td>2850</td>\n",
       "      <td>CHAIR  YELLEN.  I’d like to begin by welcoming...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-06-18</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-06-18</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
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       "      <td>0.25</td>\n",
       "      <td>86489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818</th>\n",
       "      <td>2851</td>\n",
       "      <td>CHAIR YELLEN.  Good morning, everybody.  I wou...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-07-30</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>88197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2819</th>\n",
       "      <td>2852</td>\n",
       "      <td>CHAIR YELLEN.  Good morning, everybody. Our fi...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>61211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2820</th>\n",
       "      <td>2853</td>\n",
       "      <td>CHAIR YELLEN.  I’d like to call this meeting t...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>72240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2821</th>\n",
       "      <td>2854</td>\n",
       "      <td>CHAIR YELLEN.  Good afternoon, everyone.  I th...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>58709</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id                                               text  split  \\\n",
       "2817  2850  CHAIR  YELLEN.  I’d like to begin by welcoming...  train   \n",
       "2818  2851  CHAIR YELLEN.  Good morning, everybody.  I wou...  train   \n",
       "2819  2852  CHAIR YELLEN.  Good morning, everybody. Our fi...  train   \n",
       "2820  2853  CHAIR YELLEN.  I’d like to call this meeting t...  train   \n",
       "2821  2854  CHAIR YELLEN.  Good afternoon, everyone.  I th...  train   \n",
       "\n",
       "      timestamp         content_type        date       speaker  \\\n",
       "2817 2014-06-18  fomc_meeting_script  2014-06-18  Janet Yellen   \n",
       "2818 2014-07-30  fomc_meeting_script  2014-07-30  Janet Yellen   \n",
       "2819 2014-09-17  fomc_meeting_script  2014-09-17  Janet Yellen   \n",
       "2820 2014-10-29  fomc_meeting_script  2014-10-29  Janet Yellen   \n",
       "2821 2014-12-17  fomc_meeting_script  2014-12-17  Janet Yellen   \n",
       "\n",
       "                        title  decision  rate recent_meeting  recent_decision  \\\n",
       "2817  FOMC Meeting Transcript       0.0  0.25     2014-06-18              0.0   \n",
       "2818  FOMC Meeting Transcript       0.0  0.25     2014-07-30              0.0   \n",
       "2819  FOMC Meeting Transcript       0.0  0.25     2014-09-17              0.0   \n",
       "2820  FOMC Meeting Transcript       2.0  0.25     2014-10-29              2.0   \n",
       "2821  FOMC Meeting Transcript       0.0  0.25     2014-12-17              0.0   \n",
       "\n",
       "      recent_rate next_meeting  next_decision  next_rate  text_num_words  \n",
       "2817         0.25   2014-07-30            0.0       0.25           86489  \n",
       "2818         0.25   2014-09-17            0.0       0.25           88197  \n",
       "2819         0.25   2014-10-29            2.0       0.25           61211  \n",
       "2820         0.25   2014-12-17            0.0       0.25           72240  \n",
       "2821         0.25   2015-01-28            0.0       0.25           58709  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fomc_data = eKonf.load_data(\"fomc_corpus.parquet\", data_dir)\n",
    "fomc_data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting countplot with {'x': 'content_type', 'hue': None}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/CountPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 331,
       "width": 701
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cfg = eKonf.compose(\"visualize/plot=countplot\")\n",
    "cfg.countplot.x = \"content_type\"\n",
    "cfg.figure.figsize = (10, 5)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.ax.title = \"Number of documents per content type\"\n",
    "eKonf.instantiate(cfg, data=fomc_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of corpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/HistPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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uhQ4ry/zC7tObIzrqsRp9780WtcXNLFQIAAAAAACAdDVGkjp/br1WtaS+QdNlk/4xq0xTy109UBkAAED3K3DadMFIj84b4ZE3w+4WK5sTOvOZen1xcZOaosxxYf/yOmVlmqY2bdqkkSNH9nYp2Ms79TFd81KTTCv12N8eW6Kx3J0FAAAOYHKZSwvOqdAPjwyowJHZCVHMlH7xXrumPlKj+5a3K5ZM4+AEAAAAAAAA3aopauqCeQ36oCl12M9hSH85sVQnDHb3QGUAAADZYxiGJpQ4dd0Eny4a6c349Q+uDunI/9bo3+tCsizmuLCvvA78/fznP1dra6tmz57d26Vgly3tCV02v0GhROo3m1sOLdB5VZm/qQEAgP7FYTN086GFev3CSs2u8mT8+vqIqa+/3qLpj9Xo0fUhmZwUAQAAAAAA9Ij6SFLnPlevZQ3xlGNthvSnE0p19gjmjgAAQN/hc9h0/4ml+vvJpar0ZhbTqo+Y+tzLTTp/boPWtqQ+nkL/kReBvyuvvFIPPfSQXn/9db311lt65JFHdMEFF+jOO+/U3XffreHDh/d2iZDUEjN16fMNqgmnbil6xjCPvnN4oAeqAgAAfcUQv10PnFSmR04tU1WhPePXb2xL6tqFTTrpyTq9uC3C3VAAAAAAAABZVBtO6rxn6/V+Y+rJaUPS748r0fld6H4DAACQD84Z4dXrF1TqmnH+jF+7cEdURz9eqx+81aJgnGV+ITl6u4B0lJaW6ic/+Ym2b98u0zRVWVmpo48+WvPnz9fUqVN7uzxICsZNXT6/QSuaU7djn1Lm1P0nlMhuy2xZPgAAAEk6ZahHr51fqZ+/16ZfvtemaDKz1y9riOuCeQ2aWenSN6cU6vhBbhkGxyUAAAAAAADdZWcoqfOeq9fqltTzRpL0y2OKddloX5arAgAA6F3FbpvuObpYl4326suvNmt5Ghmb3WKm9LN32/XPtSH94MgiXTjSy/xWP5YXgb9f//rXvV0COhFJWLryhUa9VhNLOXao365/nVImvzMvmksCAIAc5XUY+r+pAV0xxqfvvtmiORsjGW/jtZqYZs9t0IwBLn1zaqFOIPgHAAAAAABw0LYFkzrvuTqta03vLs27ZxTpqrGZd7oBAADIV0dVurVw9gD97oN2/Whpm8LJ9Fel2h4yde3CJv1pZVA/mVGsSaXOLFaKXEXqCgcllrR01YsNeml7NOXYgNPQf04t00Bf5kvwAQAA7E9VoUMPnFSmJ88o18SSrt3LsqQ2pvPnNujMZ+o1d0tEJkv9AgAAAAAAdMmmtoTOfjb9sN8d04t03YSCLFcFAACQe5w2Q7dMKtRrFwzQaUPdGb/+tZqYTniiVl99rVmNkQyXw0LeI/CHLoublq55qVHztqYO+zkM6W8nl2pCCcliAADQ/Y4b5NbL5w3Qz2cWq8zdtUPcJbUxXTa/QUc/Xqu/rwkqmsHdVAAAAAAAAP3diqa4znimThvb0g/7fX4iYT8AANC/VRU69O9TyvTASaUa6M1sjsu0pPtXBjXt0Rr9aUW7kiZzW/0FgT90SdK0dMPLTXpqc3rL5/3ymGKdMNiT5aoAAEB/ZrcZunq8X29fXKmvHVYon6Nry/OubE7o5kXNOuw/O/WLd9vUHDW7uVIAAAAAAIC+5Y3amM58pk47QuldR/nJUYT9AAAAdjMMQ7OrvHr9wkpdP96vTGe4mmOWvrakRSc8WafFO1M37UL+I/CHjCVNSzcvbtajG8Jpjb9taqGurPZnuSoAAPJfgrtuuuVnUOSy6fZpAb19UaWuHe+XvWu5P+0Mm/reW6065OGd+tLiJr3XGD/o2tLR1Z9BdXW1qquru327AAAAAAAAnVmwLaLZc+vVHEvv2sPPZxbrs4cQ9gMAAPioIpdNP51ZrPnnVGhSaeYraL7fGNfZz9brmpcatbEtkYUKkSscvV0A8ks0aen6hY16YlN6nf1uObRAXz+sMMtVAQDQNzhshu5a2tqt27xtaqBbt5dt3f0zKPfYdM04v2ojSc3ZmN7xy0eFEpb+ujqkv64OacYAl64d79d5VV65u5okTKGrP4PGhkZJUmlZ6X6fz7ffBQAAAAAAkPv+uz6kz73SpHgajf0MSb86plifGkuTCAAAgM4cXuHSi+dW6K+rgvrh261p31ix2383hPXkprCun+DX1yYXqtRjz1Kl6C10+EPa2uOmLpvfkHbY73MT/PreEQEZRnYmwwEAANJR6rHpgZPK9PJ5FTpnuOegtrWkNqbrX27SxId36v/+16wPeqjrHwAAAAAAQK7504p2XbswvbCfzZB+f1wJYT8AAIA0OWyGrptQsGdFK1uG0Zu4Kf3ug6CmPFqjX7zbpnCClaD6EgJ/SEtjJKnz59brpe3prfX9mbE+/eioIsJ+AAAgZ0wuc+nvs7on+FcfMfW7D4I6Zk6tTniiVvcub1dDJNlNlQIAAAAAAOQu07L07Tda9LUlLUpn2thhSH86vkSXj/FlvTYAAIC+ptRj189mFuulcys0s9KV8etbY5a+91arjni0Rg+tCSppEvzrCwj8IaXtwaTOerZeb9al18Hm8tFe3XN0MWE/AACQk3YH/16ZPUDnjvDoYI9YljXE9Y3XWzT+3zt1+fwGPbwupLZ0bm0HAAAAAADIM+GEpatfatSv329Pa7zPYehfp5TpwlGE/QAAAA7G5DKXnjmzXPefUKLBvszjXttCSd20qFnHP1GrBdsisiyCf/mMwB86tbo5rjOeqdPK5kRa4y8c6dVvji2RjbAfAADIcZNKnfrbyWV648IBunqcT277wW0vbkrPbYnosy83acw/d+iTCxr03/UhBQn/AQAAAACAPqA+ktTs5+o1Z2MkrfHFLkOPn16mU4Ye3EoLAAAA6GAYhi4a5dMbF1bqa5ML5epC6uuDpoQumtegC+Y1aFlDrPuLRI8g8IcDWrAtolOertPm9vSWp7twpFf3Hl8iR6YLhwMAAPSiMUVO/fzoEr1/yUDdelihStwHfywTTUpPbY7omoVNGv3PHbpsfoMeWBXUzhDL/gIAAAAAgPyztiWuU5+q0//q0psUHui16ZmzKjR9gDvLlQEAAPQ/fqdNtx8e0OsXVOqs4V27ueKl7VGd8ESdrl/YqLUt6a34idxB4A8fY1mWfv9Buy55vkGtsfRaeF4zzq8/Hl8iJ2E/AACQpyq8dn1rWkDvXzJQP59ZrENKHN2y3UhSmrsloltebdb4f+/UrCdrdfeyNr1TH5NJu3QAAAAAAJDjFm6P6tSn67ShLb0bGUcW2vXc2RU6pMSZ5coAAAD6t5EBhx6aVab/nlbW5Xmt/6wPa/pjtbrh5Uatb01v9U/0vu6ZxUSfkTQtPb8tqmUN6ad3vza5UN+aViiDZXwBAEAf4HfadPV4vz4zzqcltTH9aUVQT2wKq7tW5n2rPq636uP64dtSmdumk4a4dfJgt04a4tEg30GuKwwAAAAAANBNLMvSvSuC+tb/WpRM857FyaVO/efUMlVyjQMAAKDHnDzEo1cGufWvdSHd+XabtmW44pRpSf9aF9Z/1od12WifCp2Git30kMtlBP6wRzhh6bENYW0Jpr/j//DIgG4+tDCLVQEAAPQOwzA0s9KtmZVu1YSSenB1UH9fE9Km9u5blrchauqR9WE9sj4sSRpX5NDRA12qj5ga6rcr4OJkCgAAAAAA9Lxo0tJXXmvWP9aE0n7N6UPduv/EUhU4uZ4BAADQ0+w2Q1dW+3XhSJ/uXd6ue95tU2s8s5Wmkpb00NqQDEmTSp06utKlIoJ/OYnAHyRJW4NJPbExrLY0d3abIf3qmGJ9stqf5coAAAB6X6XPrlunBPTVwwr1Wk1MD60N6fENYQUT3bsk76qWhFa1fNguvchlaJjfrqEFdg0rcKjEZdBVGQAAAAAAZNWOUFKfeqFBb9alvxrUteP9+vFRRXLYuG4BAADQm7wOQ1+aXKhPjfXp7mVt+tPKYMarWFmS3m2M6/3GuCaVOTWz0qUimlTkFAJ//ZxlWfpfXVwLt0eV7nS1127ovhNKdO4Ib1ZrAwAAyDU2w9AxA906ZqBbPz6qSE9sDOtf68JatDMqs3uzf5KklpilllhC7zclJEXldxgaVmDXUL9dQ/x2VXhtshMABAAAAAAA3eR/tVFd9UKjdobTnxX+wZEB3TyxgJsUAQAAckiZx667jirW5w4p0A/eatWjG8IZb8OUtKwhrvca45pc2hH8Y3Wq3EDgrx8LJUw9vTmi9a3pL0s32GfTQ7PKNKXclcXKAAAAcl+B06Yrqv26otqvmlBST2wK678bwlpSE0v7RopMBROWVjYntLK5owugw5AqfTYN8tkVMA1VuCyVWBYX2AEAAAAAQEYsy9JvP2jX995sVboLGnjs0r3Hl2p2FQ0iAAAAclVVoUP3n1iqz0+M6dtvtmjxzljG2zAt6Z2GuN5tiOuQEoemD3CpwmvPQrVIF4G/fmpre0JzNkXUnsF63YeXO/WPWWUa6GOnBQAA2Fulz67rJxTo+gkF2h5Mas7GsJ7aHNZrNbGsdP7bLWFJ24KmtgVN7T6099UFNWhXCHCQz67BPrs8DgKAAAAAAABg/5qjpm5a1KRnNkfSfk2l16a/n1ymIwfQIAIAACAfTKtw6akzyjVva1R3vN2qdxvjGW/DlPR+U8fKVKMDdh01wKWhfjuNKHoBgb9+JmFaWrQzpv/VZtZ55pJRXv3qmBJ5mSwGAADYI2Factj2PT4a7LfrxokFunFigRojST2/LapnN0c0f2tE7eneIn8QQglL61qTWrdXF+cSl6G1LQlNLXdqWrlLk8ucKnB2T8v1/f0Mcnm7AAAAAADgQ2/XxfSZlxq1uT391aCmlTv195PLNNhPgwgAAIB8YhiGTh/m0WlD3Xp6c0R3LW3VB02JLm2rYy4qrME+m44a4FJ1kYPgXw8i8NeP7Agl9fTmiBoiZkav+/a0gL4yuYAdEwAA4CMcNkN3LW1NOW5csUOjA35taU9qQ1tCG9qSqs/wmOxgNMUsPbohrEc3hCVJNkMaV+TQlHKXppU7NbXcpUNLnF3qBJjuzyBTt00NdPs2AQAAAABAB8uydO+KoL79RoviGVyiuHy0V784uoTVBAAAAPKYYRg6Z4RXZw336MlNEf14aauWN3ct+Lc9ZOqxjRGVum2aPsCpiSVOGjr0AAJ//UDStLS4JqYlNZl19St2Gfr9cSU6c7g3a7UBAAD0Fw6boZEBh0YGOg7B22KmNrQltbEtoU3tSYV6oPvfbqYlrWhOaEVzQv9cu6s+QzqkxLknADi13KkJJU45OSkDAAAAAKBP2RFK6uZFTVqwLZr2a2yG9MMji3TjIX4aRAAAAPQRNsPQ7Cqvzh3h0ZyNYf34nTat7GLwrzFq6rktUS3aEdMRFU5NKXfJbee4MVsI/PVxO0JJPbc5otoMO8gcWeHUn08s1bACfkUAAACyodBl0+QymyaXOWVZlhqjpra0J1XktunZzRG1xXsuAChJCUt6tzGudxvj+uvqkCTJY5cmlTp3dQLsCAFWBxyyEwIEAAAAACAvzdkY1pdebVJTNP3rDsUuQ385sVQnDfFksTIAAAD0Fpth6IKRPp03wqvHN4Z165IWNUa7tlJVe8LSSztierUmpkNLnTq83KVSj62bKwZprj4qkrD08o6oljbEM37t9AFOPX1mBd1cAAAAeohhGCrz2FXmseu2qQHdtbRVLbGOAOCW9qS2BhNqzOBCfHeJJKU36uJ6oy4uKShJKnAYmlzm3BMAnFbukmVZ3N0PAAAAAEAOa42Z+ubrLXpobSij1x1e3tEgYkQhU4oAAAB9nd1m6KJRPq1sjmtFU0Kv1kS7PD8VM6W36+N6uz6uUYV2HVnh0slD3LIxn9QtODrvYyzL0vKmhF7YHs14WTiPXTpnuFejixyE/QAAAHpZkcumolKbDi11SpLa46a2BpPa2p7UjlBSNWFTyZ7PAKo9YenVmo47s3bz2KWBPrsGeu0a5LNpiN8uv5O7tQAAAAAAyAULt0f1xcVN2tSezOh1Nxzi1/ePKJKLpdgAAAD6FZthaGKpUxNKHFrVnNDrtTHVhLvW8U+S1rcldfHzDfr1McX61Fh/N1bafxH460PqI0k9vzWqzRmesEnS8AK7zh7uUcDFxCwAAEAuKnDaNL7YpvHFHQHApGmpNmJqRyipHcGktrbF1ZzonQvwkaS0sS2pjW0fHocWuQwN8ds12GfXYL9dA7w22blrCwAAAACAHtMcNfWdN1v04OrMuvoFnIZ+fWyJZld5s1QZAAAA8oHNMDShxKnxxQ5tak/q9drYPnNBmSh0GhxfdiMCf31AMG5q8c6Y3mmIK9MmL06bdOIgt6aWO1mGDQAAII/YbYYG+ewa5LNL5VJjQ1hRU4p4AtoRTGpHqCMMGMyw63N3aYlZaokltLwpIUlyGB1dADtCgHQBBAAAAAAgm57aFNbXXmvWzgw7sRxW5tRfTyzVyABTiAAAAOhgGIaqCh2qKnSoJtQR/FvZnMgoo3TFGB9NyLoRR+t5LJKw9Ifl7bpvRVCxLnTOHOq366zhHpW42aEAAAD6ArdNGlTo0MjCjsN8y7LUFre0M5TUqIBDS+vjers+puZYz4cAE5Y6liQO0gUQAAAAAIBsqQkl9Y3XW/T4xnDGr715YoFunxaQx8G5OQAAAPav0mfXeVVeHR819UZdTO82xJVO74nPHVKQ/eL6EQJ/eWr+1oi+/FqztnRh+V6HIR0/yK3DK5yyMaEKAADQZxmGoYDLUMBl021TA5I6QoCb2pN6uy6mpQ0dAcBl9XG190InwAN1ARzqt+uIioimD3CpiLu9AAAAAABIKW5a+uOKoH60tFWt8czO8Yf47PrdcSU6YbA7S9UBAACgryl223TqUI+OGejSW3Ud802RA0SYRgfsGkUH6W7FTzNP2Qx1Kew3osCuU4d6VOZh4hQAAKA/2rvt+oWjOh4zLUtrWhJ7OgC+Ux/Xu40HPjHLlr27AF7yfIMMSRNLnZpZ6dLMAS7NHOjuWMIYAAAAAADs8cqOqL6+pFkrmhMZv/biUV7dPaNYxawGBQAAgC7wOWw6bpBbRw1w6YOmuN6si6sxuu8ypYdXuHqpur6LwF+eOnmIR6cMcWv+tmha4/0OQycPcWtCsUMGXf0AAACwF5thaFyxU+OKnbp8jE9SR2eAlc0JLa2P7foT1wdNccXNFBvrRpak9xvjer8xrj+uCErquIFlZqVLRw90a8YAl6qLOL4FAAAAAPRP24JJfeeNFj26IfPlewMuQz+bUaxLRvuyUBkAAAD6G5fd0NRyl6aUObWhLam36mNa35pUmdumqgKaOXQ3An957AdHFumF7bUyU3Rmn1bu1PGD3HLbmQgFAABAepw2Q5NKnZpU6tRVY/2SpEjC0vKmji6ASxviWloX08qWRMrj0e60qT2pTe1h/Wtdx2RGmdumGZWujhBgpVuTypxy2jjuBQAAAAD0Xa0xU796r12/W96uUCLzk/Izh3n0s5nFGuxn4hUAAADdyzAMjQo4NCrgUGPEVChh0rghCwj85bEJJU59eqxPf1kV2u/zg3w2nTbUo4EsewYAAIBu4HEYmlbh0rS9Wq8H46a+vqRZO0KmtoeS2hZMqi3ecwnAhqippzdH9PTmiKSOztZHVLg0o9KloytdOqLCJb+TZYkAAAAAAPkvlrT051VB/fSdNjVEM2/BX+6x6aczinR+lZdJVwAAAGRdqcemUjFHkw0E/vLcbVMD+seakGJ7ndcFnIZOGJyby/cmTEsOOq4AAIAexjFI9n4GfqdNQwscGlrw4WNtMVPbQkltD3YEAGvCppI9lAEMJiwt3BHVwh1RSZLdkA4rc2pmpVszKl06otypQX5Og5BfsrX/8t4IAAAA5AfTsvT4hrC+/3arNrYlu7SNy0d7def0IpV6aBIBAAAA5DtmuvLcAK9dMypdenlHTC6bNHNXF5NcnbRx2AzdtbS127d729RAt28TAAD0HRyD9OzPoNBl03iXTeOLnZI6QkU1YVPbg8ke7wKYtKS36+N6uz6u337Q8diYgGPPMsAzK90aWWjPuRtlgL3xHgYAAAD0T6Zl6YmNEf1kWauWNyW6tI3hBXbdM7NYpwz1dHN1AAAAAHoLgb8+4IgKl6JJ6cgKJ8uVAQAAIOc4bIaG+O0a4v+wi0BvdgFc25rQ2taE/r4mJEka4LVpxgCXZlS6NbPSpUmlzpy9gQYAAAAA0PclTUtzNob102VtWtHctaCfxy59eXKhvnhoobwOznEBAACAvoTAXx/gtBk6cbC7t8sAAAAA0ra/LoA7w6a2tie0NZhUfcRUS6xnEoC1YVNPbIroiU0RSZLfYeiIit0dAF06vMKlAm6sAQAAAABkWdy09N8NYd2zrE2rWroW9JOkc4Z7dMf0Io0oZBoQAAAA6Is40gcAAADQ6xw2Q0P9dg3d1QXwG1MK9bXXmrU1mNSW9qS29uAywMGEpYU7olq4IypJshvS5DLnPl0AB3jtKbYCAAAAAEB6mqOmHlgd1L3L27U9ZHZ5O2MCDv14RpFmDWH5XgAAAKAvI/AHAAAAIOfYDEMVXrsqvHZNLe94rCVmauuu8N+WYFINka5PgmQiaUlL6+NaWh/X75cHJUmjCu2aOdCtowa4NH2AS2OLHLIZLJEEAAAAAEjfxraEfv9Bu/6+JqRgous3uZV7bPr6YYX6zDi/XHbOTQEAAIC+jsAfAAAAgLxQ5LKpqNSmiaUdywCHEqa2BTuWAd4STKomZKpnIoDS+rak1reF9I81IUlSwGno8AqXjqjoCAAeUeFSiZtlgAEAAAAA+0qaluZtjegvq4J6fmtUB9PL3ucw9PmJBfrCoQUKuDgHBQAAAPoLAn8AAAAA8pLPYVN1kU3VRR2nNXHT0vZgRwfArcGktgWTivdQArA1bunF7VG9uD2657ExAYeOqHDqyF0BwIklTjlsdFoAAAAAgP5oRyipv60O6sHVIW0NJg9qW3ZDumqsT9+YEtBAn72bKgQAAACQLwj8AQAAAOgTnDZDIwodGlHYcZpjWpZqwqa2BZN7lgI+mCWSMrW2NaG1rQn9a11YkuS1G5pc5tSUMqemlrs0tdypMQGH7IQAAQAAAKBPCicsPbclrH+tC2v+1oiSB3lKajeky8f49NXJhRoVYIoPAAAA6K84GwAAAADQJ9kMQ4N8dg3y2XVEhWRZli4f49drNVEtqYlpSW1Ma1oSPVZPOGnp9dqYXq+NSQpKkvyOjhDg1HKnppZ1hABHBRyyGYQAAQAAACAfmZalV2ti+vfakOZsDKs1fvA3njkM6RNjfPrqYYWqKmRqDwAAAOjvOCsAAAAA0C8YhqFRAYdGBRy6stovSaqPJDvCfzUxLamN6p36uHqwCaCCCUuv1cT0Ws2HIcCA09Chpc49fyaVOjW+2CmvgxAgAAAAAOQi0+q4wWvOxrCe2hQ56CV7d3PZOoJ+X5lcuKebPQAAAABwdgAAAACg3yr32HXOCK/OGeGVJIUSpt6qi2tJTVRLamP6X21Mbd3QjSETrfGObhCv1sT2PGYzpDEBhyaWdIQAJ5Y6dGiJU0P8dhl0AwQAAACAHhc3Lb26M6YnN4X15KawasJmt227xG3o2vEFun68X5U+e7dtFwAAAEDfQOAPAAAAAHbxOWw6bpBbxw1yS5ISpqUPmuJ7ugC+VhPVzm6cxEmXaUmrWxJa3ZLQYxvDex4vdhmaUOLU2CKHqoscGlfsVHWRQ8P8dtltBAEBAAAAoDvVhJJ6fltE87ZE9NL2aLcs17u30QG7bppYoE+M8cnnsHXrtgEAAAD0HQT+AAAAAOAAHDZDh5W5dFiZS587RLIsS5vaO5YBfqMupjdqY/qgKa5kzzYB3KM5tveSwB/y2KXRAYfGFjk1ttixJxA4KuBQgZNJIwAAcsHGtoQao6YMqeOPoY9/b0iGDNmMjo6/dkOy0d0XAHpMKGHqf7Uxvbwjqhe2RfVOQ7zb/w1D0ilD3Lp6vF9nDPPwPg8AAAAgJQJ/2K+EaclBRxAAAAD0MQd7nGsYhqoKHaoqdOjyMT5JUnM0qfebEnqzdlcIsC6m2l7oAri3SFL6oCmhD5oSH3uuzG1TVaFdIwodGlGw79ehfrtc9q79fDiH4GeA7MvW71g2ttvVbVZXV2dlu0AuOu+5em1uT2b8OkO7g3+S3TBkt3X8fXcYcO6WiHwOQz6HIe+urx1/bPI6DPk/9rix13ib/A5DhU5DAZdN7i4eFwBAvgonLC2tj2nRzqgW7ojqjdqYYlk6vRvgtelT1T5dNdavEYVM1wEAAABIH2cQ2C+HzdBdS1u7fbu3TQ10+zYBAACAdGXjOPe2qQG9siMoSTq01KmJJQ61xixtCyW1PZjU9lBStWGz17oAflRD1FRD1NRb9R/vTGFIKnAaKnbZVOjqCAQUOG0qcO7+vuPvLltH+HFvHOun//tlWpYSppTY9TVuSknr478gux+6ZrxfNaF9AyEd4Q5jT8Bj78AHHUH6rnw6V+9qrY0NjZKk0rLS/T7Pew36ErOLxwaWpIS16xtZUnLfZ+sj3ZdMcdmkgMumwK4A4O4g4N7fF33sOUNFLptK3DYVu2xdvpkAAHrCzlBSr9fG9L/amF6vjWpZQ1zxLN6/ZTOkEwe5ddVYv84a7uE9EgAAAECXEPgDAAAAgG5kGIaK3IaK3DYdUuKUJCXNjsn3HeGkakKmdoaSqo2YXZ7ozxZLUlvcUls8KQUPPM5p054woN9pyGs3FEtaKnLZVOy2qcjVERrs+N6m4l0T//Yc7MplWpYiSUuRhKVwUru+djwWTux6btfzm3baFTUNFUbaOsbsHrtnnPReY+xjYb6EaSlpSXHTUsLKPODx19WhjMYbkhy2jslEh2HIaZNcdkMumyHXru+dNkMtMVMFzo6Axu7/P4vdhkp2/X9HUAMAsms/We+cEzOl+oip+oj0kWRh2vwOo+MzxW1TiWvv7zs+a/b83d1xzLD7Mb/D+NgNBgBwMGrDSb1TH9c7DTEtrY9rWUNM20M905390FKnLhvt1SWjfBros/fIvwkAAACg7yLwBwAAAABZZrcZqvTZVemzS2UdjyVMS3WRjvDfzpCpneGk6sOmencx4PTETak5Zqk59uHE/zsNH+8Y+FEFu5YQdNsNeeyG3Hbt+mp85GtHKG3vKf6PTvfvPf9vWh2BhLhpKZa09vk+bkoxc9djyQ8DfLuDepktz+Xu+LK++zusdSdL2tOVJCprr0f39V5j6v/PpI6gRkeA09gnoLF3KLDEbez6+uHjASdBDQDojLmf9+a+KJiwFEwktTWYWWDQadNenzOdBwb3/jzK1ZsMAPScSMLSqpa4PmiMa3lTQsub4lreFNfOcM+ebQ0rsOv8Kq8uG+3ToaXOHv23AQAAAPRtBP4AAAAAoBc4bIYG+ewatFd3h7hpqSFiqjZsakShXe83xvV+Y1zNsb4RCGhPWGpP9I3/lv5kd1BjW2aNBmU3pGKXTaWe3aEMY08YsGQ/QY3dnZ0KXTY5CWoA6AdyrdNvrombUm2447goU0W7g4Ef/axx2VTkNj72ObQ7QOhx8PkD5IukaWlHKKkNbUmtbUloTWtca5oTWtOa0Ob2ZK+9x44qtGt2lVfnVXk1pczJDTAAAAAAsoLAHwAAAADkCKfN0ECfXQN9dt02NSBJsixL20Om3m+M64OmjgDgB41xrWlNEBRATktaUkPUVEM086CG124o4DJU6LSp0GUosGvp4UJXR+fAQlfH332Ojq6Qvl3dI32OjiWmvbv+7t31nHvXMsZOm3Ju0tWyOpZ8TphS0upY9jm5axnohPXhktDJXc/XhTsmsC11hIVMy/rw+11frV2Pm9r9vfb6/uOP//q9tgPXl8Z/g2FIdsOQ3ehYTtpuGLIZHV0kbbuetxkdnTpthmSTIcPY9fiux3a/vj3e8ZgjZsq++3FbR4DUlmP/3wEHi8/x7GmJWWqJJZXpMsReu7EnoP6xsOCux4pchgK7Po8CLtuuP4YKWIIY6FYJ09L2UFKb25Pa3JbQluCH329uT2pbMKlcuZdoWrlTpw716NwRXk0scfBeAAAAACDrCPwBAAAAQA4zDEND/HYN8dt1+jDPnsfDCUtrWxNa0xzX6pbEnj9rW+KKZDa3DeSccNJSOGypJgvLrtmNjmUinTZDjl1fncaH39t3BdF2T9Mae/6n48vuCVxDu0J3uwN5u8J0H/3e3PX3pGXt9/tcCPy8tD3a2yXsZddydzuDH3vGkDRriFvTB7h7tiQgS3Jh/8e+wklL4VDHzRaZshlSobNjSeF9A4GGipwdXzse3/v7D0ODBU5DfochB11u0ceFEuau7p1J1YRN1YVN1YST+3zdEU5qezCpZI6+TwZchk4e7NFpQ906ZahHA7z21C8CAAAAgG6UN4G/lStX6s4779Srr76qcDissWPH6sYbb9Sll17a26UBAAAAQI/zOgxNKnVqUqlzn8dNy9KW9uSeAOCa5rhWtSS0oTWhnVkITwH5JmlJyaQU2TODnKMzyfgYS2K55zzFdb39qyq07+nSaamj8+bHvrckS3sHhnu1ZHTCtLreWXBvHrtU4LTJ7zDkdxoqcNjk3xUG9DuNfZ7zOz78++5Ot7s733r2/n5X91veQ9Fd4qalYNxSW9xUc8xSc9RUc8zs+Lr7+70eb4p2/KkLm2rPlbZ8GXDbpaMGuHX8ILeOH+TS1HIX+xMAAACAXpUXgb/3339fZ511lqZPn6777rtPgUBAzz33nG666SZt2bJFX/3qV3u7RAAAAADICTbD0IhCh0YUOnTq0H2fCycsbWlP6CfL2tQSM9US7ZiIa4mZaomZdAYEkPOYXM8/XNc7sAXnDtBdS1szft2+HUStXUt+f9hB9JPVfgUTlsIJS6GEqVDCUmjX3z983NrrcXOfx9sTltpiplrjFl0Ie0EkKUWSpuqzsG2H0XHTyO4AoNfeEQzcHQp02Q25bJLLttf3dkMumyG3veM92G035Nw1Zvf3HV87xuzz2l3fO/Zaot1hSA7b7mXg910O3rF7CXiWQ03J2vU+kDA79vuEJSXNjq8JU4omLUWSlqK7/kSSHz4WMz98bp/H93pNMGGpPd4R6gsmzF3hvg+/j/Xx+4h8DkOHlzt1VKVbxw10a/oAl7wOfi8BAAAA5I68CPx96Utf0sSJE/Xwww/LZrNJko444ghVVFToW9/6ls477zxVV1f3cpUAAAAAkNu8DkNji50aHdj/qWA02dGFoy1uqT3e0X0jGN812Zcw90z69fH5vR7h2DW57bAZeya+9zeFaEga4LOrNvRhGtPSh0vGdkzu7gp80PkJ/YDL1tsVIFNc1+t+NsPQh9nXj396HF7h6pZ/x7I6Qj9tcUutMVOtMUutcVNtu762xMx9n9v19903EjRFTbXELPqo5pCEJbXtCm7lMoehXeFA48OvewcDbZLdkAwZMgzJJskwOvaG3V9tRsexVSzqkWFY8q6s7QgTquN1HcHC/b9m723u/vrRDpzS/jpyfrxj524f7dq5+/ukpX3Ceh9+/TDIlzA/PM5L7HqeMG73Gl5g1xEVLh01oOPPoaVOltcGAAAAkNNyPvC3bNkyvfnmm3rsscf2XBTc7ZprrtHdd9+tv//97/p//+//9VKFAAAAANA3uO2GKn12VXYyxrI6uv/s7voRSnR0ATlygEstMVPNUUvNuyb6m3dN9O8OBOQqt73jv91r/7Djzd5fd38fC7bJbbNUWVa8Z6xnr+44XruhpzeH5dg1Eb13mM9hk5x7T1Bn0LnmtqmBtDtAWVZHIHN3t6eE2dGBJWZaiic//D6WtHTsILfadwU62+MdYY2O5dc6QhrNBDWQg1x2Jt/zCdf18pthGCpwGipwSoN89i5tI2laao133FDQFDXVtNfSns17/m7t+fvuz6DGqKk4dxj0WwlLSiSl6J6jkIM5Gtn13tMeP9iy0EcMK7BraplTU8pdmlLm1JQyp0o9XXuPAwAAAIDeYjQ3N+f0tftf/epXuvPOO7V582a5XB+/O/Xaa6/V+vXr9eKLL/ZCdQAAAAAAAAD2h+t6AAAAAAAAQPfL+YVQVq5cqaqqqv1eFJSk6upqrV69uoerAgAAAAAAANAZrusBAAAAAAAA3S/nA3/19fUqKys74PMVFRUKBoNqb2/vwaoAAAAAAAAAdIbregAAAAAAAED3y/nAXyQSOeBdwJL2PBeJRHqqJAAAAAAAAAApcF0PAAAAAAAA6H45H/jzeDyKxWIHfH73cx6Pp6dKAgAAAAAAAJAC1/UAAAAAAACA7pfzgb+SkhI1NDQc8Pm6ujq53W75/f4erAoAAAAAAABAZ7iuBwAAAAAAAHS/nA/8VVdXa8OGDQe8G3j16tUaPXq0DMPo4coAAAAAAAAAHAjX9QAAAAAAAIDul/OBv2OPPVbRaFSLFi362HPxeFwvv/yyjj322F6oDAAAAAAAAMCBcF0PAAAAAAAA6H45H/ibPn26JkyYoJ/+9KcyTXOf5/785z+roaFBn/zkJ3upOgAAAAAAAAD7w3U9AAAAAAAAoPsZzc3NVm8Xkcrrr7+u8847T8cdd5w+//nPq7CwUHPnztXPf/5z3XDDDfrhD3/Y2yUCAAAAAAAA+Aiu6wEAAAAAAADdKy8Cf5K0bNky3XXXXVqyZIkikYiqq6t13XXX6dOf/nRvlwYAAAAAAADgALiuBwAAAAAAAHSfnF/Sd7fDDjtM//rXv7Rx40bt3LlTr7zySp++KLhy5UpdddVVGjNmjIYMGaKTTjpJDz/8cG+XBfQqy7L07LPP6uqrr9a0adM0cOBATZ48WZ/73Oe0cePG/b5m27ZtuummmzR+/HgNGjRIM2fO1B/+8AdZ1v6zzs3NzfrGN76hQw89VAMHDtS0adP0ox/9SLFYbL/jo9Go7rjjDk2dOlUDBw7UoYceqttuu02tra3d9Z8N9LqWlhZNmjRJxcXF+t///vex59nPgK7btGmTbrvtNs2YMUP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\n",
      "text/plain": [
       "<Figure size 1296x1152 with 8 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1123,
       "width": 1278
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "content_types = fomc_data.content_type.unique()\n",
    "\n",
    "cfg = eKonf.compose(\"visualize/plot=histplot\")\n",
    "cfg.figure.figsize = (18, 16)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.subplots.ncols = 2\n",
    "cfg.subplots.nrows = 4\n",
    "ax = cfg.ax.copy()\n",
    "histplot = cfg.histplot.copy()\n",
    "histplot.x = \"text_num_words\"\n",
    "histplot.bins = 50\n",
    "histplot.kde = True\n",
    "cfg.plots = [histplot.copy() for _ in range(len(content_types))]\n",
    "cfg.axes = [ax.copy() for _ in range(len(content_types))]\n",
    "for i, ctype in enumerate(content_types):\n",
    "    plot = cfg.plots[i]\n",
    "    plot.query = f\"content_type == '{ctype}'\"\n",
    "    plot.axno = i\n",
    "    ax = cfg.axes[i]\n",
    "    ax.title =  f\"Distribution of number of words in [{ctype}]\"\n",
    "    ax.axno = i\n",
    "\n",
    "eKonf.instantiate(cfg, data=fomc_data)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split corpus into sections"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.pipelines.pipe:Applying pipeline: OrderedDict([('explode_splits', 'explode_splits'), ('filter_length', 'filter_length'), ('reset_index', 'reset_index'), ('save_dataframe', 'save_dataframe')])\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function explode_splits at 0x7fc2a666c820>)\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function filter_length at 0x7fc2a666cf70>, len_bytes={'_partial_': True, '_target_': 'ekorpkit.utils.func.len_bytes'}, len_words={'_partial_': True, '_target_': 'ekorpkit.utils.func.len_words'})\n",
      "INFO:ekorpkit.base:Using batcher with minibatch size: 923\n",
      "INFO:ekorpkit.utils.batch.batcher: backend: joblib  minibatch_size: 923  procs: 230  input_split: False  merge_output: True  len(data): 212170 len(args): 5\n",
      "Calculating length: 100%|██████████| 230/230 [00:00<00:00, 431.45it/s]\n",
      "INFO:ekorpkit.pipelines.pipe:removed 120119 of 212170 documents with length < 50\n",
      "INFO:ekorpkit.pipelines.pipe: >> elapsed time to filter length: 0:00:00.560365\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function reset_index at 0x7fc2a666c940>)\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function save_dataframe at 0x7fc2a666d550>)\n",
      "INFO:ekorpkit.io.file:Saving dataframe to ../data/fomc/fomc_sections.parquet\n"
     ]
    },
    {
     "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>id</th>\n",
       "      <th>text</th>\n",
       "      <th>split</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>content_type</th>\n",
       "      <th>date</th>\n",
       "      <th>speaker</th>\n",
       "      <th>title</th>\n",
       "      <th>decision</th>\n",
       "      <th>rate</th>\n",
       "      <th>recent_meeting</th>\n",
       "      <th>recent_decision</th>\n",
       "      <th>recent_rate</th>\n",
       "      <th>next_meeting</th>\n",
       "      <th>next_decision</th>\n",
       "      <th>next_rate</th>\n",
       "      <th>text_num_words</th>\n",
       "      <th>section_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>92046</th>\n",
       "      <td>2854</td>\n",
       "      <td>MS. BRAINARD.  Thank you.  Since we last met, ...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>506</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92047</th>\n",
       "      <td>2854</td>\n",
       "      <td>VICE CHAIRMAN DUDLEY.  No worries.  It happene...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1446</td>\n",
       "      <td>285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92048</th>\n",
       "      <td>2854</td>\n",
       "      <td>CHAIR YELLEN.  Thank you.  Okay.  I think the ...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>83</td>\n",
       "      <td>286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92049</th>\n",
       "      <td>2854</td>\n",
       "      <td>MR. LUECKE.  This vote, as Chair Yellen indica...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>73</td>\n",
       "      <td>287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92050</th>\n",
       "      <td>2854</td>\n",
       "      <td>CHAIR YELLEN.  Okay.  Thank you very much.  An...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>Janet Yellen</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>77</td>\n",
       "      <td>288</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id                                               text  split  \\\n",
       "92046  2854  MS. BRAINARD.  Thank you.  Since we last met, ...  train   \n",
       "92047  2854  VICE CHAIRMAN DUDLEY.  No worries.  It happene...  train   \n",
       "92048  2854  CHAIR YELLEN.  Thank you.  Okay.  I think the ...  train   \n",
       "92049  2854  MR. LUECKE.  This vote, as Chair Yellen indica...  train   \n",
       "92050  2854  CHAIR YELLEN.  Okay.  Thank you very much.  An...  train   \n",
       "\n",
       "       timestamp         content_type        date       speaker  \\\n",
       "92046 2014-12-17  fomc_meeting_script  2014-12-17  Janet Yellen   \n",
       "92047 2014-12-17  fomc_meeting_script  2014-12-17  Janet Yellen   \n",
       "92048 2014-12-17  fomc_meeting_script  2014-12-17  Janet Yellen   \n",
       "92049 2014-12-17  fomc_meeting_script  2014-12-17  Janet Yellen   \n",
       "92050 2014-12-17  fomc_meeting_script  2014-12-17  Janet Yellen   \n",
       "\n",
       "                         title  decision  rate recent_meeting  \\\n",
       "92046  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "92047  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "92048  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "92049  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "92050  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "\n",
       "       recent_decision  recent_rate next_meeting  next_decision  next_rate  \\\n",
       "92046              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "92047              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "92048              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "92049              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "92050              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "\n",
       "       text_num_words  section_id  \n",
       "92046             506         281  \n",
       "92047            1446         285  \n",
       "92048              83         286  \n",
       "92049              73         287  \n",
       "92050              77         288  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cfg = eKonf.compose(\"pipeline\")\n",
    "cfg._pipeline_ = [\"explode_splits\", \"filter_length\", \"reset_index\", \"save_dataframe\"]\n",
    "cfg.num_workers = 100\n",
    "cfg.explode_splits.id_key = \"id\"\n",
    "cfg.explode_splits.split_key = \"section_id\"\n",
    "cfg.explode_splits.separator = \"\\n\\n\"\n",
    "cfg.filter_length.min_length = 50\n",
    "cfg.filter_length.len_func = \"len_words\"\n",
    "cfg.filter_length.len_column = \"num_words\"\n",
    "cfg.reset_index.drop_index = True\n",
    "cfg.save_dataframe.output_dir = data_dir\n",
    "cfg.save_dataframe.output_file = \"fomc_sections.parquet\"\n",
    "fomc_sections = eKonf.instantiate(cfg, data=fomc_data)\n",
    "fomc_sections.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.io.file:Saving dataframe to ../data/fomc/fomc_sections.parquet\n"
     ]
    }
   ],
   "source": [
    "fomc_sections = fomc.find_speaker_of_sections(fomc_sections)\n",
    "eKonf.save_data(fomc_sections, \"fomc_sections.parquet\", data_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.io.file:Processing [1] files from ['fomc_sections.parquet']\n",
      "INFO:ekorpkit.io.file:Loading 1 dataframes from ['../data/fomc/fomc_sections.parquet']\n",
      "INFO:ekorpkit.io.file:Loading data from ../data/fomc/fomc_sections.parquet\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>text</th>\n",
       "      <th>split</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>content_type</th>\n",
       "      <th>date</th>\n",
       "      <th>speaker</th>\n",
       "      <th>title</th>\n",
       "      <th>decision</th>\n",
       "      <th>rate</th>\n",
       "      <th>recent_meeting</th>\n",
       "      <th>recent_decision</th>\n",
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       "      <th>next_decision</th>\n",
       "      <th>next_rate</th>\n",
       "      <th>text_num_words</th>\n",
       "      <th>section_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>92046</th>\n",
       "      <td>2854</td>\n",
       "      <td>MS. BRAINARD.  Thank you.  Since we last met, ...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>MS. BRAINARD</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
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       "      <td>506</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92047</th>\n",
       "      <td>2854</td>\n",
       "      <td>VICE CHAIRMAN DUDLEY.  No worries.  It happene...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>VICE CHAIRMAN DUDLEY</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
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       "      <td>0.25</td>\n",
       "      <td>1446</td>\n",
       "      <td>285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92048</th>\n",
       "      <td>2854</td>\n",
       "      <td>CHAIR YELLEN.  Thank you.  Okay.  I think the ...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>CHAIR YELLEN</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>83</td>\n",
       "      <td>286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92049</th>\n",
       "      <td>2854</td>\n",
       "      <td>MR. LUECKE.  This vote, as Chair Yellen indica...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>MR. LUECKE</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>73</td>\n",
       "      <td>287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92050</th>\n",
       "      <td>2854</td>\n",
       "      <td>CHAIR YELLEN.  Okay.  Thank you very much.  An...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>CHAIR YELLEN</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>77</td>\n",
       "      <td>288</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         id                                               text  split  \\\n",
       "92046  2854  MS. BRAINARD.  Thank you.  Since we last met, ...  train   \n",
       "92047  2854  VICE CHAIRMAN DUDLEY.  No worries.  It happene...  train   \n",
       "92048  2854  CHAIR YELLEN.  Thank you.  Okay.  I think the ...  train   \n",
       "92049  2854  MR. LUECKE.  This vote, as Chair Yellen indica...  train   \n",
       "92050  2854  CHAIR YELLEN.  Okay.  Thank you very much.  An...  train   \n",
       "\n",
       "       timestamp         content_type        date               speaker  \\\n",
       "92046 2014-12-17  fomc_meeting_script  2014-12-17          MS. BRAINARD   \n",
       "92047 2014-12-17  fomc_meeting_script  2014-12-17  VICE CHAIRMAN DUDLEY   \n",
       "92048 2014-12-17  fomc_meeting_script  2014-12-17          CHAIR YELLEN   \n",
       "92049 2014-12-17  fomc_meeting_script  2014-12-17            MR. LUECKE   \n",
       "92050 2014-12-17  fomc_meeting_script  2014-12-17          CHAIR YELLEN   \n",
       "\n",
       "                         title  decision  rate recent_meeting  \\\n",
       "92046  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "92047  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "92048  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "92049  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "92050  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "\n",
       "       recent_decision  recent_rate next_meeting  next_decision  next_rate  \\\n",
       "92046              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "92047              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "92048              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "92049              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "92050              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "\n",
       "       text_num_words  section_id  \n",
       "92046             506         281  \n",
       "92047            1446         285  \n",
       "92048              83         286  \n",
       "92049              73         287  \n",
       "92050              77         288  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fomc_sections = eKonf.load_data(\"fomc_sections.parquet\", data_dir)\n",
    "fomc_sections.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting countplot with {'x': 'content_type', 'hue': None}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/CountPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 331,
       "width": 701
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cfg = eKonf.compose(\"visualize/plot=countplot\")\n",
    "cfg.countplot.x = \"content_type\"\n",
    "cfg.figure.figsize = (10, 5)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.ax.title = \"Number of sections per content type\"\n",
    "eKonf.instantiate(cfg, data=fomc_sections)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of sectons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/HistPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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xMgAAAAAABqdFixZp3rx5Ov/885OOC4VCcjqdnR4/eCwU6lq3uf66ArsrDnYQKCjsPAyZrrd2h2QpmnTMqeU+FeYc2bRxT9TaW9fNxD2Sqeff1VoP3jsHz3tmQkKXrmjQq/s6nxs7aFvAlN3p1Lmj3bJ1Y1eXwfBvb6j61/sGSAf3DbqD+wbdxb2D7uC+QXdw36C/IqWFlBpTbOOb7+Q2wsBgGIb+68Rc2VLMT97zfqt2tcZ6pygAAAAAAAap3/72t3r//fd15513phzrdrsViUQ6PX7wmNvt7rH6hpq2aELvNyQP+pV6TI3LTr3VKwYmn8PUn+cV6tPDXWmN39QU01M7QorR4g8AAAAAgH6DlBZSakoR9qOzHwaSSXkOXTXJl3RMOC79xz+ae6kiAAAAAAAGnz179ujWW2/Vf//3fys/Pz/l+Pz8fDU0NHR6vLa2VpKSbvWL5N6tiyqeIrN1cqlTRje6uGHg8NgNPVJZqDPL0wv8bWmJ6YmdQQJ/AAAAAAD0E6S0kBLb+GKw+feZOcp3JZ+4fnpXSH/dHuiligAAAAAAGFw2bdqktrY2XXbZZcrLyzvk1/Tp0yVJ5557rvLy8nTXXXepoqJCfr9fu3fvPuz1Nm/erOzsbJWVlfXm0xg0InFLa+o675woSUVuUxW5R7Z9LwYGt93Q7z5dqHNGpdcpc3tLXI/tCCpK4A8AAAAAgD7H7A2SagonFIp3ftyQlOtgtS8GlnyXqVtm5ug7bybv3vetN5p0YolTI7P4VgkAAAAAQFecfPLJeu2112RZnwwH7d+/XxdffLF+8YtfaMaMGSovL1coFJIkrVixQl/+8pc/cc6KFSs0Z86cTJc9aL3fGE06xydJJ5XQ1W8ocdoMPfCpAp36VI02NsVSjt/ZGtdftwd10ViPnDbuEwAAAAAA+goJFiS1qy35RE+2w5DNZHIHA8+Xj/Lptxv92pBkMrMlYulrrzVq6VlFMpnsBgAAAAAgbR6PR1OnTj3ssdzcXEnS2LFjNW3atI7H58+fr3vuuUcXX3yxvF5vx+PLli3T+vXrtXjx4swWPUglLEtv1yTv6pftMDQpn6ni/iyWsGTv4jxsRUVF0uMO09C5o92yGSF90Jg68PdRW1yPbg/qc+M8chH463XduQf64poAAAAAgMxiBgdJ7WpNvuSXLXwxUNlNQ0tOzNX5y+uTjlu1P6L/eb9Ni6Zm91JlAAAAAAAMTbfffrsqKyt13nnn6dvf/rbKysq0evVqLVmyROeff77OPvvsvi5xQNraHFNjJPn2q8cWO2VjoWO/ZjcNLVnT0qVzGuobJEkFhQWHPb54Zo5Mw9DZo9wyjZDWN6QO/FX54/rztoAuHueV284905u6cw+ksnhmTo9eDwAAAACQeSS1kNSu1uQTPLlObiEMXKcNd+uyCd6U4370bovWN0R7oSIAAAAAAAY/h8MhwzDkdDoPeXzcuHFauXKlxowZo0WLFumss87SQw89pJtuukm/+c1v+qjage8ftcnnNJymNL3A0UvVoD8yDUMLRro1ozC9+2BfIKE/bwsoGEseIgUAAAAAAD2Pzn5Ialdbis5+TlZvYmD76Ym5Wr0/nPRejySkr77SoJXnlrBiGQAAAACAIzR8+HA1NjYe9tiYMWN0//3393JFg9e+QFx7/Mnn96YWOJjvgAzD0BnlLtkM6Z261Ite9wcT+uPWgD4/wSOvnQXhAAAAAAD0Fl6FI6mdKTr7sY0vBrocp6lfz82XmWJO+8OmmP7znebeKQoAAAAAAKAHvFUTSXrcNKTjip1Jx2DoMAxDlSNcOqE4vQ5/taGEHtkaVFs0keHKAAAAAADAQSS1kFSqzn5s44vB4KRSl741LTvluF9t8OupncFeqAgAAAAAAODINEcS2tSUfCHvuaPdLObFIQzD0OnDXZpdml4ItD7U3uGvNULgDwAAAACA3sBMDjqVsCztStXZj218MUjcPCNbM4tSr1q+9tVGralLvioeAAAAAACgr71TG5GVYsz1R6de/IihxzAMzR3m0ill6QX+GsKWHtkaUDOBPwAZFEuk+qnWP64JAAAAZJq9rwtA/7U/kFCy+RmHKXnthP0wODhMQ/fNzdfcp2oVjHf+Aj8Yt3TZinqtOKdEw322XqwQAAAAAAAgPeG4pbX10aRjRvhMHV/i1ItVoV6qCgPNnDKXbIb0yr7UC1+bIpZ+vyWgS8Z7eqEyAEOR3TS0ZE1Lj15z8cycHr0eAAAA0Bvo7IdO7UzR1S/XacowCPth8KjIdegnJ+SmHLcvkNClK+rlj7JaGQAAAAAA9D/r6qNJF/FK0vHF6XVtw9B2UqlLnx7uSmtsW9TSH7YE9E4tu2IAAAAAAJAphP3QqV1t8aTHc9nCF4PQFUd5dWZ56gnMtfVRXftaoxIWbf4BAAAAAED/YVmW1tQlD1vlOg1V5LLpC9JzfIlT80ekF/gLxaXznqvTy3vpGAkAAAAAQCYQ9kOnUnX2y3Ny+2DwMQxDvzo1X+OyU2/R+/SukH7ybs9uGwAAAAAAAHAkdrTG1RhJvjjxuGKnTHbsQBfMKnbqzJHpBf78MUsXv1Cvp3YGM1wVAAAAAABDD2ktdGpXGtv4AoNRgdumP80rVE4a3SvvWtemhzb5e6EqAAAAAACA1N5N0dXPaUrTChy9VA0GkxmFTp09yq10YqKRhHTFyw3MmwEAAAAA0MNIa6FTqbbxzXNx+6D/iCV6djvdiXkOPfypAtnSmL284fUm/XV7oEe/PgAAAAAAQFc1hRPa1pJ8Tm9qgUPOdCY8gMOYWuDQOaPdab2xkLCkb77epJ+ta5Vl9ezcHQAAAAAAQ5W9rwtA/5Wqs19eGl3PgN5iNw0tWdPzW+r+v5Ny9e03mpOOsSRd82qjPDZDnxnt6fEaAAAAAAAA0rEmRVc/SZpV5OyFSjCYTcl3yGUz9OSOoGJpZPh++E6L6sMJ3XZcjgy2jwYAAAAA4IjQmg2HFYpZ2htIJB3DNr4YCq6clKWvTvalHBe32rcmeakq1AtVAQAAAAAAHCqasLSuIZp0zNhsmwrczOnhyI3PseuS8R65bOmNv+f9Nl2/uqnHd+cAAAAAAGCoYWYHh7Xbn7yrn9dusN0Hhoz/OiFXlSNcKcdFEtIXVjTo9f3hXqgKAAAAAADgnzY0RhVKvoMvXf3Qo8qz7Lpsglc+e3rzxH/YEtC/rWxQKJ12gAAAAAAA4LAI++GwdrYmnxnMZQtfDCF209BvTy/QlLzUO58H45YuebFe79Sm3jYHAAAAAACgJ1iWpXfrknf1y3UaGpeTZhs2IE0lHpu+UOFVXprzxc9+FNJnX6hTcyT5rjIAAAAAAODwCPvhsHa1Ju/sl8cWvhhicp2mHj+zSOOyU0+Kt0YtXfh8ndbUEfgDAAAAAACZV+WPqyaYPDw1s8gp02ABL3pevsvUFyq8Kk5zi+hV+yNa8LdaVflTtKIEAAAAAACfQGILh5W6sx+3DoaeMq9NT51VpHJf6sBfS8TS+csJ/AEAAAAAgMxL1dXPbkjTChy9VA2GoiyHqcsmeDUijXkzSdrQGNMZz9RqQ2PyexcAAAAAAByKxBYOa1dbis5+LlYBY2gamWXXU2cWqdST+tsngT8AAAAAAJBpbdGENjUln8ubku+Qx858HjLLbTd0yXiP5o9wpTW+KhDXWX+r1Wv7whmuDAAAAACAwYOwHw6Lzn5A58bn2vXEmUUqcBH4AwAAAAAAfWttfVTJN/CVZhXR1Q+9w2EaemReoT43zpPW+JaIpYuer9Nj2wMZrgwAAAAAgMGBxBY+wbIs7WpN0dmPsB+GuCn5Dj1+RqFyHKlXxRP4AwAAAAAAmZCwLL1Xn3wb1BE+U6Xe9LZWBXqCwzT067n5unqyL63xkYR05SuN+tm6VlmWleHqAAAAAAAY2Ehs4ROaIpZaop1PqhiScpxs+wHMKHLq0fmFykpjG5yDgb/3CPwBAAAAAIAesq0lprYk83iSNKvI2UvVAP9kGob+34m5WjwzO+1zfvhOi76xuknRBIE/AAAAAAA6Q9gPn5Cqq1+O05BpEPYDJOmkUpf+ckb6gb8Ln6/TBw3JV9wDAAAAAACk47265HMMPruho3LtvVQNcCjDMHTzjBzdMydPtjSnk3+3JaCLnq9XUzjV5tQAAAAAAAxNhP3wCTtb40mPs4UvhpJYGiuJZ3ch8NcYbu/wt6mJwB8AAAAAAOi+5nBC21PM400rdMhmsmgXfetLE33607xC+dKYO5OkV/eFdcaztdqZYlE6AAAAAABDEcs68Qm72pJPouQS9sMQYjcNLVnTktbY88e49ZftQUVSLDyuCyV0/nN1enZBscazuh4AAAAAAHTD2jR2Dphe6OiFSoDU5pe79cyCIl38Qr1qQ6m79m1ujqny6Vo9UlmgE0tdvVAhAAAAAAADA6ktfEKqFZN5LlYDA4dTnmXX58Z5lE4edn8wofOeq2OFMgAAAAAA6LK4ZWldffKw37gcG4t20a/MLHLqhXOKNT7Hltb4+nBC5z5Xpz9s8We4MgAAAAAABg5me/AJu1Js/8EkIdC5g4E/Rxr/TKoCcZ33XJ32pOimCQAAAAAA8HFbm2Pyx6ykY2YUOnupGiB9Y7Ltev4zxZpdmt79GUlIX1/VpO+91aRYIvk9DwAAAADAUDAgU1vNzc2aOnWq8vLy9NZbb33ieFVVla677jpNmjRJw4YN0+zZs3XvvffKsg4/GdDU1KSbb75ZxxxzjMrKyjRr1iz99Kc/VSQSyfRT6ZdSdvYj7AckdTDwZ0+jCeZHbXFd9Hy9GsOpty8BAAAAAACQpPdSdPXLchhpd08Deluh26YnzyzS58Z50j7nfz/w6+IX6tXEHBoAAAAAYIgbkKmtm2++WQUFBZKkcDh8yLF9+/apsrJSmzdv1t13361nn31Wl112mW677TbdcMMNn7iW3+/XWWedpZdeekm33Xabli1bpm9+85u6//77demll3YaEBys4glLu/3JO/uxjS+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rr3Xq1ClVVFQoPDxc3bt317hx49SvXz+vxxQVFelPf/qTEhISdPfdd/s9/8svv6x9+/bpZz/7mbp16+bx/NX23Xff6bvvvpMkGY1G/fa3v1VUVJQk6fjx43rmmWfUuXNn3XXXXT7va9++ffruu+907NgxFRcXy2QyqUOHDurbt6/Gjx+vjh07+jz2j3/8o4xGo+677z5lZWVp48aNOnjwoHva/Li4OA0aNEhTp05VWFiY38ccjIb09cMPP1RqaqrHtrVr12rt2rWSakb7LVmyJOg+fPPNN3r33Xf14x//WKNGjdLWrVuVlpam7OxsVVRUKDQ0VMnJyZo0aZL69+/v8zxPP/20cnJy9Jvf/EbR0dE+27l+72fHtSR9+umnWrdunW666Sb16NFDGzZs0M6dO5Wfn6/Q0FB17txZU6dOVZ8+fdzHnD59WuvXr9eRI0dUXFysqKgoDR06VNOnT1d4eHhQz0FD4r+2PXv2aOvWrcrMzFR5ebkiIiLUo0cPTZgwQb179/b7PFx77bUaMWKEtm3bpvXr1ys3N1eRkZG66aablJiYGFT/XQoKCpSamqp9+/apoKBAVVVVioiIUHJyskaMGKFhw4bVOcb1uqqdnCwoKPC4Bl1//fVej63N4XDof/7nf+R0OvX//t//8xsDH3zwgbZs2aKoqCj9v//3//wudfLiiy/qwIEDuu++++oss2O32/Xdd99p586dOn36tMrKyhQaGqq4uDgNGDBAkyZN8vk6dV17+/Tpo5tvvllZWVlatWqVDh8+LIPBoGnTpmnatGkex5w6dUqbNm3SoUOHVFxcLIvFovj4eI0YMULjx4/3+/xINXGyZcsWd5yYTCbFxMSoe/fumj59uhISEgKe4+z+h4SE6OGHH/bYd+DAAb344ouaMWOGZs6cqbS0NH3zzTc6c+aMysrKZLVa1aVLF40dO1YjRowI+j7rqyHvby6lpaVKTU3V3r17lZ+f735dJiUladiwYUpJSZHJZPJ6v19//bXee+89zZs3T6NHj9bmzZu1bds25ebmymw2q1OnTpo0aZKGDh3qPiYvL08bNmzQ/v37VVhYqPDwcA0YMEAzZsxQhw4dAj7W/Px8bd26Vfv27VN+fr4qKytlsVgUGxur7t27a968ecE+bQFVVlZq48aN2r17t3JycmS32xUSEqJOnTqpd+/euvjiiz3av/zyyzp06JD++7//W3a7Xd988437+aiqqlJ0dLT69++vKVOmKC4uLuD9Hz58WF999ZWOHDmisrIyhYWFqWvXrho7dqyGDBni91i73a4tW7Zo+/btys7Olt1uV3R0tPr27aupU6cGdf8ZGRnavn27jh49qpKSEjmdToWGhioxMVETJkzQ8OHDvR537NgxffXVVx7HdejQQQMHDtS0adPcf2sAAACgYcijkUcjj0YejTxaDfJoNcij1Q95tObJo9VWVVWlLVu2KC0tzZ1Ti46OVp8+fTRlypSA15CG5rVefvllZWRkaNGiRRo0aJDXNgcPHtTWrVt19OhRlZaWymq1KikpSaNHj9aoUaN05swZ/d///Z/Gjx+vuXPnej1HZWWlNm3apF27dik3N1dSzTLQAwcO1AUXXKDIyMiAz1FZWZm++uor7dq1S3l5ee5z9O/fXxdccIHfa5VUUwC9c+dOpaWlKTMzU6WlpbJYLO5zTJw4MagYacj1OViFhYX697//raysLF1zzTUaOXJkg88FAL5Q7AcALWzixIn6/PPPlZWVpRMnTriTay6uqdRdP13sdrteeuklHTx4UAaDQTExMerYsaOqq6uVnZ2tEydOaNKkSYqNjZXZbFaPHj3cH+KOHj0qSerRo4f7fDExMXXut6qqSjabTf/+97914sQJJSYmKjo6WoWFhQH7V1t1dbWWLVumPXv2yGKxKCEhQeHh4crNzdWuXbu0a9cuTZgwQXPmzKmTpLXb7XI4HH7PX7svTqdTVVVVHo/L9ThLSkrcyZn4+HhJNUnK2ssgVFVV1TnH2ffx5ptvas+ePZJqlpTp2LGj7Ha7cnJylJWVpS1btujiiy+uk3yorbKyUvv27dOrr77q/hDh+v1lZWXpzJkz2rFjh26//fagPpg0dV8TEhLqPG8dOnRwx4m/hI83ruRUeXm5li5dqn379sloNCo+Pl6xsbHKz89XRkaGMjIyNGvWLE2fPt3nY3I4HLLb7QEfe+2f3vqSn5+vjz/+WFlZWe7nv7CwUPv27dO+ffs0d+5cTZgwQTt37tSbb74pu92u+Ph4xcfHKycnRxs2bNCePXu0ePFivwUcjYl/qeY18PbbbystLU1STUx37txZRUVF2rlzp3bu3KmpU6fqsssu8/s8bNiwQZ988okiIiLUqVMnlZaWqry83O/zeLatW7fqo48+UlVVlQwGgxISEmS1WpWfn6/du3dr9+7d6tWrl2644QaPxF1oaKh69Ojhfu6PHj0qs9msrl27SpIMBoMiIiIC3r/RaFSvXr2UkZGh9PR0n0m76upqbd++XVJNEuvAgQMaPHiw17ZFRUU6ePCgOxZry8nJ0bJly5SVlSVJioqKUufOnVVWVqbjx4/r+PHj2rx5s6699lqviebq6mr39Ss7O1vPPfecbDabO6lTVFTk0X7Lli368MMP5XQ63c+vxWJRdna2Pv74Y3399dc+Ey2S9Nlnn+nzzz+XJEVGRqpz587u+/n222/Vq1eveiUpXf33dT2UamLrvffe09dffy2DwaC4uDh16NDB/bwePHhQhw4darYE2tnvb5mZmaqurvb7/iZJ6enpevvtt92vAdfvv7CwUPv379f+/fu1adMm3XjjjV6Pd8VySUmJXnjhBR05ckQhISFKTExUSUmJDh8+rMOHD7tfm4cPH9bSpUtVWVmpmJgYJSYmKicnR19//bX27Nmj2267TZ06dfL5OL/88kutWbNG1dXV7uc5Pj5eNptNubm5ysvLa7LnuKKiQs8++6zOnDkjo9GomJgYRUREqKqqSpmZmTp27JhmzJgho/GHSeJdfzMUFRVp2bJlOnnypDuZX1VVpZycHH311Vf65ptvdO211/p8PUrSJ598og0bNkj64TVXWlrqfo8YMWKErr76ao/7dykqKtJLL72k06dPy2AwKDExURaLRbm5udqyZYu+/fZbXXvttT4LBktLS/Wf//xHBw4ckFTzvhkfHy+TyaSysjIdOXJEnTp18lrs9+WXX2rLli2S5H5PsdvtysrK0qZNm7Rz507dcccdda4zAAAAqB/yaOTRyKORRyOPRh5NIo/WEOTRmj6PVlteXp6WLl2qrKwshYeHKz4+XuXl5crNzVVubq6+/fZb/ehHP9KoUaO8Ht+YvFagvy9WrFihzZs3S6qJg4SEBBkMBh07dkyHDh3Stm3bNG3aNDmdTp/nOHPmjF5++WUVFBTIZDIpMTFRRqNROTk5Wr9+vbZu3aobb7zRI57OlpmZqWXLlqmwsFBRUVHuGMjKylJWVpa2bt2qRYsWeRSQ11ZSUqJXX33V/bdZeHi4OnXqJJvNptOnT+vUqVP66quvNHfuXKWkpPjsR0Ovz8Gw2Wx65ZVXlJWVpQsuuIBCPwDNhmI/AGhhFotFvXv3Vnp6uo4ePVonSenLN998o4MHD6pjx45auHChx6hSh8OhrKws9wfusLAw3X777e79rpFad9xxR8D7Wb9+vUpLS3XXXXepS5cu9XlobitXrtSZM2c0Y8YMXXDBBQoJCZFU86X6Z599pi1btig1NVWJiYmaNGlSg+7Dl+HDh7u/lP/222/1zjvvqH///lqwYEG9z+VwOLR06VIdOnRIkZGRuvzyyzVs2DD3iLWKigpt3rxZn3/+uVatWiWTyaQpU6bUOY/BYFBVVZX+85//KDo6WvPmzVPv3r3dCar8/Hy98cYbOn78uD788EMtWrTonPd18uTJmjx5ssfzNmbMGM2cObPefZHkLsrYsGGDiouLdcEFF3iM5nU4HPr666+1fPlyffrpp+rTp0/Qr4X6cj0Hq1evlsPh0PXXX6+hQ4e6n/99+/bpP//5jz766CN169ZNb775phISEnTNNde4kz6VlZV67733tGPHDr3//vt+f0eNjf/3339faWlp6tatm6666iqP1+HBgwf15ptvav369YqPj9e4ceO89iE3N1cbN27UFVdcoYkTJ3otkgnkm2++0fvvvy+p5suVCy+80J2cdTgc2r9/v1asWKHDhw/rxRdf1B133OH+AiAxMVGLFy92n+v+++9XZGRkUNegsw0ZMiRgkvLgwYOqrKxU3759deDAAaWnp/tMUqanp8vpdHqMHJVqRt89//zzKi4uVpcuXXTllVeqZ8+e7v35+flavXq10tLS9Morr+jWW2/1m8h4//331bVrVy1YsMBrUvvIkSPuBOXgwYN15ZVXupNj1dXVSk1N1apVq/T22297PX9WVpbWrVsni8WihQsXasCAAR77XV/QNBVXDKWlpamoqEgpKSm65JJLPL5U2b17t9566y1t3bpV/fr1q/McN4Wz39/+9Kc/qaCgwG9s7du3T6+99prsdruGDx+uWbNmeYyKPXr0qFasWKHMzEw9//zz+sUvflFn5gHXdWTjxo2y2WyaM2eOxo0b595+4sQJvfbaa1q/fr0GDx6s1157TaGhoVq0aJF7BoHq6mqtXLlSmzdv1ptvvqm77rrL6xcVruI3q9WqSy+9VGPGjPFI6tvtdvco2KbwxRdf6MyZM+rVq5euvvpqjyRtdXW1cnNzfV5D3n33XWVnZ+uqq67S6NGj3deAgoICLV++XOnp6XrjjTd01113eZ0NY+3atdqwYYMSEhLc740umZmZevPNN5WWlqbY2FjNmjXL49iqqiq9+OKLysrKUkpKii699FL3a81ut7uTeK77PzspXF5ermeeeUa5ubnq3LmzZs2apb59+3qMSi8tLfW5xM2WLVuUnJysK6+8Ut27d3dvLyws1Ouvv65jx45pxYoVDXpPBwAAwA/Io5FHI49GHo08WvDIo5FHq408WtPn0WpbtmyZiouLde2112rYsGHu33tWVpbef/99HTlyRO+8846SkpLc10eXxua1/ElNTdXmzZtlMBjc11ZXEXpFRYXWrl2rjRs3ugt1vXEVapaUlGjq1Km68MILFRoa6u77F198oc8//1xLly7V3Xff7fV1W1lZqVdeeUUGg0E33XSTx8y0x44d03vvvaczZ85o2bJluueee+rM8FdZWal//etfysrKUlxcnK688kr179/f/TyXlJRo3bp12rx5s9555x1ZrVavr6PGXJ8DcTqdeuutt3Ty5EkNHTrUa2E5ADSV+v+FCgBocq5ReWfOnAn6mH379kmSZs+eXecLc6PRqKSkpCbp21dffaWf/OQnDU5QSjVLN8ycOVMzZ850J2ikmplvrrrqKo0dO1ZSzZf81dXVje5zc/nqq6906NAhhYeHa/HixRo5cqRHEUBoaKguuugiXXfddZJqkmDZ2dlez1VVVSWj0ajFixerT58+Hh9MY2Nj9ZOf/EQmk0l79+5t0IfPpuxrUyoqKtKFF16o2bNne3zoNxqNGj9+vMaPHy+n01ln6ZPmUF5eruuuu07Dhg3zeP779++vCy+8UHa7XS+//LLCw8N16623enwADwkJ0Y9+9CNFRkYqPT3dY5T+2RoT/wcPHtS3336ruLg43XrrrXVeh3369NENN9wgg8GgTz/91Ofr56uvvtKkSZM0efLkBiUoCwsLtWLFCknS5Zdfrjlz5nh8YDcajRowYIDuuOMOxcXFKTMzU1988UW97ycYgwYNksFg0MGDB32OMnSNwr/ssssUFhamjIwMj6VPvLU9e0Tk8uXLVVxcrO7du2vx4sUeCUqp5nV67bXXatKkSaqurtbbb7/tc6T8qVOnlJ+fr5/85Cc+R69/9tlncjqd6tevnxYuXOhRYGU2mzVlyhTNmTNHBQUFXo/fv3+/nE6nJk6cWCdBKdWMuK0df02lqKhIo0aN0oIFC+rMnjBkyBD3FxuukaMtzWaz6d1335XdbtekSZN03XXX1Vn+okePHrr99tvVvXt35efn65NPPvF5vvLycl155ZWaOHGixzU2OTnZvWTYq6++KpvNpltuucWjeM1sNuuKK65QUlKSTp065R6RWtvevXvdCcrbbrtN06ZNqzN63zWStqm4/r646qqr6ozGdi2t4suBAwe0YMECjR8/3iMJFhMTo4ULF6pXr16qrq7Wp59+WufY7Oxsff755woNDdXtt99eZ1mlrl276uabb5bVatWGDRtUUlLisf+LL75QVlaWhg8fXufLAJPJpIkTJ+rSSy+V3W73ev/vv/++cnNz1bt3b91xxx0aMGBAneVnIiIifL6GO3bsqNtuu82j0E+SOnTooGuvvVZGo1F79+51LzUGAACAhiOPRh6NPBp5NPJowSGPVuD1ePJowSGPVj9nzpzRDTfcoBEjRnhcOzp27Kibb75ZSUlJcjgc+uyzz+oc29i8li92u929pPzMmTM1Y8YMj9lmQ0NDdfnll2vy5Ml1Zs+s7ZNPPlFJSYmmTZumyy67zF3oJ9UMxLj44os1ceJElZeX+7yelZeXq7y8XLfcckudJei7d++uW2+9VdHR0aqsrPR6js8++0xZWVmKj4/Xz372Mw0cONDjeY6MjNSVV16pyy+/XE6nU++//77Kyso8ztHc1+fPPvtMu3fvVvfu3XX11Vd7LUgFgKZCsR8AtAKuDxxn/+Hpj+sDt79lD5pC165dG5WglKTo6GhNnTrV5/5Zs2bJYrGorKzMvXRea+NwOLRx40ZJNR+K/E3hP2TIEA0ZMkTV1dXatGmTz3aTJk3y+fuLjo5W79695XQ6vX5wPdd9bSohISF+l2UZMWKEpJrRmc2ta9euXpM5Uk0iTKoZDTZ9+nSvIzmtVqt7OvkTJ074vJ/GxL8rsTN79myfS75069ZNvXr1UmlpqQ4ePOi1jc1mc48wb4gtW7bIZrMpOTnZ73lco99dffe3bEVDRUZGqkePHqqurtb+/fvr7Hc6nUpPT1dcXJy6dOmi/v37q7i42OvvqLKyUgcPHlSHDh2UnJzs3p6dna309HQZDAbNnz/f73I7l156qaKjo5Wbm6vdu3d7bWOz2TR27Fif5ykuLtbhw4cl1fyufSWSx44dW2fUp4trtrHmfk84m8Fg0CWXXOJzv+s1ffz48YDLBp0LrhHUHTp00KWXXuqzndVq1VVXXSVJ2rZtm88vIiIjIzVmzBiv+wYOHCiDwaCSkhJNmDDBayLRYDBo4MCBkrxfR1zJv1mzZnnEaHNqzN8XvXr10rBhw7zuM5lMmj17tqSa5GtFRYXH/tTUVDkcDs2YMcPnfcfExGjYsGGy2+3atWuXe7vdbteWLVtkNpvd1yBvJkyYIIvFUuf+T506pZ07d8pisejaa6+t9xJbkjRt2jSfx8XGxrqXYDp27Fi9zw0AAABP5NHIo52NPNqRZu8LebTgkUcjj+YLebTzL49W25AhQ9SrVy+v+ywWi/s5zMjI8FgWvLF5LX8OHTqkkpIShYWF+b22XnLJJT6Xqy0pKdGOHTsUFRWliy66yOc5XOffsWOH38fgq9gyMjLSff6zz1FRUaGtW7dKkq644gq/M29OnjxZXbp0UVlZmb7++muPfc15fd6+fbvWrVun+Ph4LVq0SBaLJeAxANAYFPsBQCvg+uDqa3SdN64PNStXrgz6D/uG8DVlf30MGTLE7zTXERER6tu3ryT/yZ6WdOrUKRUUFMhqtWr06NEB27uWgXCNdvTGleDyxfWhx9+IKm+ao69NpVu3bn4TPq7R9edi5iN/S0XUHg3qb8kEVzt/r8GGxr/D4dCBAwdksVjcr3dfXDNt+Xr9dO3atc5o0fpIT0+XVDOtfaDRaAMHDlR0dLTKy8vdibem5rou7d27t86+48ePq7i42N3GlXD21jYjI0N2u12DBw/2eFx79+6V0+lUr169Ai6JYLFYlJKSIkk+k5S1++xNZmamnE6n4uLi/M4mYTAYNHLkSK/7BgwYIIPBoE2bNvldcqGpxcXF1Zn9rbbo6GiFhoaqurraI4nVUlyxPHbs2IAJl86dO6t79+5yOBxe40equaadPfubi9lsdieezh7xXpuv60hOTo5Onjwpq9XqnrngXHBdb5YvX17vWUJcSWlfkpOT1aFDB9ntdmVmZnrsc33p4FoyzBdv17vMzEyVlpaqV69edZb4qM1isSg+Pl4Oh0OnTp1yb3clEEeMGNHgRL9rdplA/c7Pz2/Q+QEAAPAD8mjk0bwhj9a8yKMFjzyab+TRyKOdb3m02gLlxfr166ewsLA6eanG5rX8cQ067d+/v99rq9Vq9fm8Hzx4UHa7XYMGDfL7nhQTE6OQkBCVlJT4nFUz0HPkWia+tLTUI4d24MABVVVVKS4uzmfhuYvBYHAvW372daa5rs/Hjh3Tu+++q/DwcN144411ZpQEgOYQ3ALjAIBm5frgVp8/AMeMGaOjR4/qu+++05///GdNnTpV48ePb/Lp5c9e2qQhghlF1bVrV6WnpzdoqY1z4eTJk5JqHkswM/707NlTRqNRxcXFKioq8vohzd/oI0nuqdDrO6qzOfraVAI9Zlf8NsdI1rPVnmr+bK4PvqGhoX6fD38fkF0aGv95eXmy2WwymUz617/+5fd412jJs5e1dGnM0gTV1dXupZHOXlbTG6PRqF69eiktLU0nT56sMyV/UxgyZIg++eQTdzKx9gdzV7LdlRTs37+/jEaj0tPTdfHFF3ucx/Vh/+xEhus1FMzjlWpmM/viiy/cx53NYDD4/R24fu9nL4Phja946tixo+bOnasVK1bo//7v/zR27FhNnTpVsbGxQTyChgumMCokJEQVFRXn5HUdSH1/t71799axY8d8/m79XUckuROY/pLdvq4jrmRct27dzulI0IsuukiZmZnavn27jhw5ogsvvFApKSlBXe98jZivLS4uToWFhcrNzXV/WVddXa2cnBxJ0uuvv+73+NLSUkme17vTp09Lqvn9Pvvss36PdyUbax/veq6DjQtvAr3fukZHV1ZWNvg+AAAAUIM8Gnk0b8ijNS/yaMEhjxYYeTT/yKO1rTxabYGuX0ajUZ07d9ahQ4eUl5fnfl4bm9fyx5Vv81cY65KcnKxvvvmmznZX/zIyMgL2zzUjZXFxcZ3CVpPJFLAfERERiomJUX5+vvLy8tyvSVdM9erVK6ilcV0zLNYuimyu63NhYaFeffVVSdKiRYv8zhAMAE2JYj8AaAVcI04DJXBqMxqNWrBggYYNG6Y1a9Zo5cqVWrdunSZOnKjJkyc32ciRpjhPMI/L9UG3OUdXN4ZraRh/I+9qs1qtCg8PV0lJiUpLS70munwtMeASzIcWb5qjr00l0GMOtL8pBfP8BkpABKOh8e/6Pdrt9novQXO2xryOy8vL3YnAYGPDNfo52KRDfcXFxalz5846deqUjh8/ru7du7v37dmzRxEREe4R52FhYerZs6cOHTqkwsJCd9/sdrv27duniIiIOssr1Pc15Grn6/GGhob6HLUq/VD8E0zCz1+b8ePHq2fPnlqzZo22bNmirVu3asSIEZo+fXqTfOHkTTCvo4Zey5qDq1As2N9toFgO9rE15AtE18wMjZlNoCEsFotuuukm99IT77//vtasWaMLLrhA48eP9/vlV3h4eMDzu2K4dtGb6zojqUHXO9drtrS01P07rg/X77c5n2vX+5vrcQIAAKDhyKORR/OGPFrzIo8WHPJogZFHa3ybc4U8Wv009vrV0LyWP64BEsH0zdc1y9W/wsJCn0s0ByM8PNzva9slKipK+fn5Xp+j+l5nqqurVVFRodDQ0Ga5PldVVemVV15xFzcGmt0UAJoSxX4A0Aq4poDu1q1bvY8dOHCgBg4cqL1792rt2rVat26dNm3apDlz5gS19EQgTZGkCeaLbVebxnyYPRdfoNfnPpriMTVGW+prU3M4HC3dBbfGxn9MTIx+85vfNKoPjXkdNyYmmjOeBg8erFOnTik9Pd2dpMzKylJ2drbGjBnjkfAeOHCgDh06pL1797qn8D948KAqKio0evRon8nxYF9DgV4/gRJUruOCSXYEiu1OnTpp4cKFOn36tD7//HNt375d27dv14QJE3TFFVec0y8CWiPXc91Uv9v63m9DtERxmMFg0KhRozRixAilpaXpiy++0CeffKL169frxz/+sc/lMoK59rraeBuJbTAY9MgjjzQ4TlNSUrRgwYIGHStRiAcAANBWkEcjj9Yc2lJfmxp5NE/k0cijkUerQR6t6e/b33PU2LyWN66Z9oJ5vQSaEXHGjBmaOXNmg/vSFHFU33PUPk9zXJ83b96s6upqdezYUVlZWXrvvfd0/fXXN/h+AKA+2vdfKQDQCuTl5SkzM1Mmk8nnl+fBGDhwoH7+859r/vz5qq6u1rvvvqt9+/Y1YU8bLj8/P2Ab18irYGYF8qWpRz3V5hr55Bo9HkhVVVW9Rk01pbbU14YK9KHONdKrNWho/LuWfCwrK2vRJEVYWJiMRqOcTmfQMeUa4dec8eRaMmTv3r3ubWcvPeIycOBASVJ6enqdtmcvPSL9MMIy2JGKrnbBjCj2xvW7DuYaFkw8STVLM1x//fW64447FBkZqa+++kpr1qxpUP/OJ66YDPZ325AZQ5qKK55aclkuo9GoUaNG6Ze//KVmzpypkpISvfrqq+7lO87mupb542pT+zl1fZHidDobdP12vYYaOguCqy+5ubkNOh4AAADnDnm0GuTRmk5b6mtDkUc7d8ijBUYere0gj1Y/wcSbK3fliuPa/2+O2T1dOTfX+1YwfTtbU/WvtLRUNpst6H7Ufo7q+17tilmLxeIuIG6O63N1dbXGjRunn//85+rYsaN27typLVu2BHVuAGgsiv0AoIWtWbNGDodDI0eObJLRv2PHjtUll1wip9OpL7/8sgl62HgHDx4M2CYzM1OS6kyR7xpxFGhZksrKymb9kj45OVmSdPz4cVVVVQVsf+TIETkcDsXGxp7zD7dtqa/15ZoJqvbyj9644qk1aGj8x8bGymQyyWaz6cyZM83Wv0BMJpO6dOkiSTp06FDA9g6HQ0eOHJEkj2VBmlrnzp0VGxur06dPuxMpe/bskdVqVd++fT3aJiYmKiEhQQcPHpTNZpPT6VR6erpCQkLUr1+/Oufu2rWrpB9miwikMbNKSD/83oP5PQfbJ5fu3bvrJz/5iSRp06ZNQSVUzmeu62MwsSz98Hw3Zyz74oqnEydONOuXcMEwGo2aMWOGxo8fr+rqam3cuNFru5MnT/o9T3V1tU6dOiWp5jXsYrFY3MtrHD9+vN79S0xMlFRzLW3IjBSu329GRka9jwUAAMC5RR6tBnm0ptOW+lpf5NHOPfJogZFHazvIo9VPoOuXw+Fw585qL/fa2LyWP67XS6CcnSQdO3bM63ZX/06cONGovjidzoCxVFpaqoKCAkme1/iGxmLt60xzXJ/79OmjuXPnymq16rrrrpPFYtHHH3/sc6A0ADQliv0AoAVt2bJF27ZtU0hIiGbNmtVk53WNvnN9oX62+k6/3ljp6el+R3+VlZW5Pwj16dPHY194eLiMRqMqKir8jrbZsWNHwA9CjXncnTp1UseOHWWz2fTNN98EbJ+amipJGjZsWL3vq7HaUl/ry5VE9ZfMycnJaVVJyobGv9lsdn+I/fbbb5u3kwEMHTpUkvTVV18FfP3s3btXhYWFio6ObvbEjmvkcXp6uoqKinTixAn179/f65IDgwYNUnV1tQ4cOKDjx4+rqKhIAwYM8LqU6ODBg2U0GnXo0KGAH8yrqqr03XffSfrheaqv5ORkhYSEKC8vz+d1W5JsNpu2bdtW7/N3795dERERstlsLTq6tTVw/Y6+/vrrgF/inDx5UkePHpXFYmnUjCENlZiYqKSkJNntdq1fv/6c3783gf6+2Llzp9/j9+7dK5vNpri4OCUkJHjs69mzp6SGXe+6du0qs9ms0tLSBhXsueJi7969JOMAAABaMfJoNcijNa221Nf6Io/WMsij+UYerW0hj1Y/W7du9fveun//flVUVCgiIkJJSUnu7Y3Na/nTv39/SdLu3bv9Fn5XVlZq+/btXvf16NFDUk0xor/XXDBc76G+7Nq1S06nU507d1ZERIR7e58+fRQWFqa8vDyPGUq9cTqd7tn1zr7ONPX1uWfPnu7lvpOSknTFFVeoqqpKb7zxRrsvFgbQ/Cj2A4AWUF1drZUrV+rDDz+U0WjUggULGjxtvTeuUTq+Rji7tjfHtODe2O12ffDBBz4/6KxevVpVVVXq2rWre2SNi9lsdn/w8fXhvLS0VGvWrHGPXvalsY976tSpkqTPPvtM2dnZPtulpaVpz549slgsmjhxYoPuq7HaUl/rw5W08xULDodDK1ascH/Aag0aE/9jx46VVPPh09fIunNh7NixCgsL04kTJ/wmS4qKivTRRx9JkqZMmRLwNdlYrqVD0tPTlZ6eLqfTWWfpERfXlzd79+71u/SIJHXo0EEjR46U0+nUu+++6zcR8vHHH6uoqEidO3ducCLLYrFo5MiR7vP5i5Vglkk9W0FBgXtJnqaY+aItGzJkiOLj41VYWKhPPvnEZ7vKykq9//77kqQxY8Z4JJfOpYsuukiStHHjxoCJrHPBldDzFUfHjx/3mRisrKzUp59+KumHa1ttrm27d+/W7t2769WvkJAQDR8+XJL00Ucf1XsEd9euXTVgwAA5HA795z//afGZFAEAAOCJPJon8mhNry31tT7Io7UM8mjk0c4X5NHq5/Tp0z5Xw6iqqtLq1aslSSkpKR6v98bmtfzp0aOHkpOTVVFRoVWrVvlst2LFCvdSv2e/JyQkJKhXr16SpPfffz+oWXB9ycjI8DlYuLS0VOvWrZNUE0e1WSwWTZo0SZK0fPlyv6/tL7/8UidPnlRUVJRGjx7tsa+5r8/jxo3TsGHDlJWVpRUrVgR1DAA0VOv5Cx4AznNVVVU6duyYPv30Uz3++ONav369rFarrrnmGp8flP3Zvn27Dh065PFh1ul0aufOne4/Qn2NMI2Li5Mkbd682b3NZrPJbrfXux/BGD58uPbu3avXX3/d44/wsrIyLV++XFu3bpXJZNKVV17p9XjXH/aff/659u3b57EvKytLL774ohwOh/sDkS+ux332KEPXh5hAUlJS1L9/f5WXl+u5557Ttm3bPJ6z8vJyffrpp3rrrbckSbNnz3YvS3iutaW+1sfo0aNlMBi0b98+ffHFFx7xX15erjfffFP79+93f/BrDRoT/6NGjVL37t1lt9v173//W1u2bKnzYbq0tFSbN2/Wrl27mu0xhIeHa86cOTIYDFq1apU+/PBDj8ficDi0Z88ePfPMM8rPz1ePHj3Oye+gR48eioiI0OHDh7Vt2zaZTCZ3MtJb27CwMHeS0mw2+00qXnbZZerQoYNOnDih5557zj1lv0tubq5effVVbdmyRVarVfPnz3fPetAQM2fOVEREhA4ePKjXXnvNYxR7RUWFli9frs2bN2vEiBFejz98+LB27dpVZ8TgiRMntGzZMjmdTiUnJ7eJ13lzMplMmj9/vsxms1JTU/X666/XGaV9+PBhPfvsszpx4oQSEhJ0ySWXtFBva97HR40aJYfDoVdffVWfffZZnYSfw+FwL8HTFLZu3arjx497jG612+3aunWrPv/8c3e/vOnUqZPeffddbdmyxeM9Jzs7W//+97+VnZ2t+Ph4TZ48uc6xvXv3dp/3jTfe0Lp16+osPVZRUaHvvvvOPTq3tksuucQ9wveZZ57Rvn376ozQzcnJ0cqVK71+eTd//nxFRUXpzJkz+uc//6k9e/bU+buosrLynH3BCwAA0N6RRyOPdi61pb7WB3k08mi1kUf7AXm04JBHq5/hw4dr1apVWrNmjce1Jzs7Wy+99JJOnTqlDh066MILL6xzbGPzWv7MmzfP/Tv84IMPPN7Hi4uL9eabb+rbb791Ly0cEhJS5xxXXHGFTCaTjh8/rueee85rQfWpU6f0wQcf1MnnuXTo0EE9evTQW2+9pdTUVI/32czMTL3wwgsqLCxUly5dNH78+DrHT5s2TZ07d1Z+fr6eeeYZ7d271+N9raioSO+//75Wr14to9GoefPmyWq1epzjXFyf58+fr9jYWH3zzTfasWNHvY4FgPqoO98yAKDRCgoK9Oyzz0qqSf65ls5w/fFqtVo1ZswYXXzxxYqOjm7QfXz++efKzs6W1WpVhw4dZLValZ+f7x511qtXL82YMcPrscOGDVNmZqa++OIL7dixQyEhIcrKytLNN9+s3r17N6g//owfP16hoaHaunWr9u7dq8TERDmdTuXk5Mhut8tisWjBggXu6cC9HZ+RkaGMjAy99NJLSkpKUmxsrIqLi5WZmSmLxaIbbrgh4ExArmU5srKy9Pe//10dO3Z0f/C47777Aj4Og8GgG264Qe+99562bdumt956S8uXL1dcXJzsdrvH45k7d67GjRtX/yeribSlvtZHUlKSLrnkEq1evVqrV69WamqqOnfuLJvNpmPHjqm6ulqzZs1SfHx8S3fVrTHxbzQadcMNN+jVV1/V0aNH9cEHH+jjjz92L39ZXFys0tJSOZ1OXXrppc36OEaOHCmDwaAPPvhAqamp2rJlixITE2WxWDyuPYMHD9bVV1/d7KORpZrnZ9CgQfrmm2909OhR9e3bV2FhYV7bmkwm9e/fX2lpaSouLtbAgQO9Ji5cIiMjdccdd+jVV19VZmamnnvuOUVFRalDhw4qLy9Xbm6upJokxXXXXeceLd9QkZGRuvHGG/Xyyy9rz5492rt3r+Lj42U2m5WTk6OqqioNGjRIM2bMUFpaWp3j09LStGXLFplMJkVHRys8PFwlJSXuZGeHDh109dVXN6qP54vevXvrxhtv1JtvvqmdO3dq586dio+PV1hYmAoLC90Jnh49emjhwoUtPor7xz/+sUJDQ5WamqrPP/9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\n",
      "text/plain": [
       "<Figure size 1296x1152 with 8 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1123,
       "width": 1277
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cfg = eKonf.compose(\"visualize/plot=histplot\")\n",
    "cfg.figure.figsize = (18, 16)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.subplots.ncols = 2\n",
    "cfg.subplots.nrows = 4\n",
    "ax = cfg.ax.copy()\n",
    "histplot = cfg.histplot.copy()\n",
    "histplot.x = \"text_num_words\"\n",
    "histplot.bins = 50\n",
    "histplot.kde = True\n",
    "cfg.plots = [histplot.copy() for _ in range(len(content_types))]\n",
    "cfg.axes = [ax.copy() for _ in range(len(content_types))]\n",
    "for i, ctype in enumerate(content_types):\n",
    "    plot = cfg.plots[i]\n",
    "    plot.query = f\"content_type == '{ctype}'\"\n",
    "    plot.axno = i\n",
    "    ax = cfg.axes[i]\n",
    "    ax.title =  f\"Distribution of number of words in [{ctype}]\"\n",
    "    ax.axno = i\n",
    "\n",
    "eKonf.instantiate(cfg, data=fomc_sections)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split sections into sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.io.file:Processing [1] files from ['fomc_sections.parquet']\n",
      "INFO:ekorpkit.io.file:Loading 1 dataframes from ['../data/fomc/fomc_sections.parquet']\n",
      "INFO:ekorpkit.io.file:Loading data from ../data/fomc/fomc_sections.parquet\n",
      "INFO:ekorpkit.pipelines.pipe:Applying pipeline: OrderedDict([('segment', 'segment'), ('explode_splits', 'explode_splits'), ('filter_length', 'filter_length'), ('reset_index', 'reset_index'), ('save_dataframe', 'save_dataframe')])\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function segment at 0x7fc2a666cb80>)\n",
      "INFO:ekorpkit.pipelines.pipe:instantiating segmenter\n",
      "INFO:ekorpkit.base:instantiating ekorpkit.preprocessors.segmenter.PySBDSegmenter...\n",
      "INFO:ekorpkit.base:Using batcher with minibatch size: 921\n",
      "INFO:ekorpkit.utils.batch.batcher: backend: joblib  minibatch_size: 921  procs: 100  input_split: False  merge_output: True  len(data): 92051 len(args): 5\n",
      "Splitting column: text: 100%|██████████| 100/100 [00:56<00:00,  1.76it/s]\n",
      "INFO:ekorpkit.pipelines.pipe: >> elapsed time to segment: 0:00:56.907007\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function explode_splits at 0x7fc2a666c820>)\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function filter_length at 0x7fc2a666cf70>, len_bytes={'_partial_': True, '_target_': 'ekorpkit.utils.func.len_bytes'}, len_words={'_partial_': True, '_target_': 'ekorpkit.utils.func.len_words'})\n",
      "INFO:ekorpkit.base:Using batcher with minibatch size: 1000\n",
      "INFO:ekorpkit.utils.batch.batcher: backend: joblib  minibatch_size: 1000  procs: 100  input_split: False  merge_output: True  len(data): 757506 len(args): 5\n",
      "Calculating length: 100%|██████████| 758/758 [00:01<00:00, 727.49it/s]\n",
      "INFO:ekorpkit.pipelines.pipe:removed 104004 of 757506 documents with length < 10\n",
      "INFO:ekorpkit.pipelines.pipe:removed 34 of 653502 documents with length > 350\n",
      "INFO:ekorpkit.pipelines.pipe: >> elapsed time to filter length: 0:00:01.235069\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function reset_index at 0x7fc2a666c940>)\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function save_dataframe at 0x7fc2a666d550>)\n",
      "INFO:ekorpkit.io.file:Saving dataframe to ../data/fomc/fomc_sents.parquet\n"
     ]
    },
    {
     "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",
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       "      <th>recent_rate</th>\n",
       "      <th>next_meeting</th>\n",
       "      <th>next_decision</th>\n",
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       "      <th>section_id</th>\n",
       "      <th>sent_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>653463</th>\n",
       "      <td>2854</td>\n",
       "      <td>It will not have the word “somewhat” on line 3.</td>\n",
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       "      <td>fomc_meeting_script</td>\n",
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       "      <td>MR. LUECKE</td>\n",
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       "      <td>0.25</td>\n",
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       "      <td>10</td>\n",
       "      <td>287</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653464</th>\n",
       "      <td>2854</td>\n",
       "      <td>Chair Yellen      Yes Vice Chairman Dudley    ...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>MR. LUECKE</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>2014-12-17</td>\n",
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       "      <td>2015-01-28</td>\n",
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       "      <td>0.25</td>\n",
       "      <td>31</td>\n",
       "      <td>287</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653465</th>\n",
       "      <td>2854</td>\n",
       "      <td>And let me confirm that the next meeting will ...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>CHAIR YELLEN</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
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       "      <td>2014-12-17</td>\n",
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       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>19</td>\n",
       "      <td>288</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653466</th>\n",
       "      <td>2854</td>\n",
       "      <td>I believe box lunches are now available for pe...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>CHAIR YELLEN</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>33</td>\n",
       "      <td>288</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>653467</th>\n",
       "      <td>2854</td>\n",
       "      <td>I will do my best, and I will consider at the ...</td>\n",
       "      <td>train</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>fomc_meeting_script</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>CHAIR YELLEN</td>\n",
       "      <td>FOMC Meeting Transcript</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2014-12-17</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2015-01-28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>18</td>\n",
       "      <td>288</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                               text  split  \\\n",
       "653463  2854  It will not have the word “somewhat” on line 3.    train   \n",
       "653464  2854  Chair Yellen      Yes Vice Chairman Dudley    ...  train   \n",
       "653465  2854  And let me confirm that the next meeting will ...  train   \n",
       "653466  2854  I believe box lunches are now available for pe...  train   \n",
       "653467  2854  I will do my best, and I will consider at the ...  train   \n",
       "\n",
       "        timestamp         content_type        date       speaker  \\\n",
       "653463 2014-12-17  fomc_meeting_script  2014-12-17    MR. LUECKE   \n",
       "653464 2014-12-17  fomc_meeting_script  2014-12-17    MR. LUECKE   \n",
       "653465 2014-12-17  fomc_meeting_script  2014-12-17  CHAIR YELLEN   \n",
       "653466 2014-12-17  fomc_meeting_script  2014-12-17  CHAIR YELLEN   \n",
       "653467 2014-12-17  fomc_meeting_script  2014-12-17  CHAIR YELLEN   \n",
       "\n",
       "                          title  decision  rate recent_meeting  \\\n",
       "653463  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "653464  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "653465  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "653466  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "653467  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "\n",
       "        recent_decision  recent_rate next_meeting  next_decision  next_rate  \\\n",
       "653463              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "653464              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "653465              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "653466              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "653467              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "\n",
       "        text_num_words  section_id  sent_id  \n",
       "653463              10         287        2  \n",
       "653464              31         287        4  \n",
       "653465              19         288        3  \n",
       "653466              33         288        4  \n",
       "653467              18         288        5  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seg_cfg = eKonf.compose(\"preprocessor/segmenter=pysbd\")\n",
    "\n",
    "cfg = eKonf.compose(\"pipeline\")\n",
    "cfg.data_dir = data_dir\n",
    "cfg.data_file = \"fomc_sections.parquet\"\n",
    "cfg._pipeline_ = [\n",
    "    \"segment\",\n",
    "    \"explode_splits\",\n",
    "    \"filter_length\",\n",
    "    \"reset_index\",\n",
    "    \"save_dataframe\",\n",
    "]\n",
    "cfg.segment.preprocessor.segmenter = seg_cfg\n",
    "cfg.num_workers = 100\n",
    "cfg.explode_splits.id_key = [\"id\", \"section_id\"]\n",
    "cfg.explode_splits.split_key = \"sent_id\"\n",
    "cfg.explode_splits.separator = \"\\n\"\n",
    "cfg.filter_length.min_length = 10\n",
    "cfg.filter_length.max_length = 350\n",
    "cfg.filter_length.len_func = \"len_words\"\n",
    "cfg.filter_length.len_column = \"num_words\"\n",
    "cfg.reset_index.drop_index = True\n",
    "cfg.save_dataframe.output_dir = \"../data/fomc\"\n",
    "cfg.save_dataframe.output_file = \"fomc_sents.parquet\"\n",
    "fomc_sents = eKonf.instantiate(cfg)\n",
    "fomc_sents.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.io.file:Processing [1] files from ['fomc_sents.parquet']\n",
      "INFO:ekorpkit.io.file:Loading 1 dataframes from ['../data/fomc/fomc_sents.parquet']\n",
      "INFO:ekorpkit.io.file:Loading data from ../data/fomc/fomc_sents.parquet\n"
     ]
    },
    {
     "data": {
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       "      <th>653465</th>\n",
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       "      <th>653466</th>\n",
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       "      <td>2854</td>\n",
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       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id                                               text  split  \\\n",
       "653463  2854  It will not have the word “somewhat” on line 3.    train   \n",
       "653464  2854  Chair Yellen      Yes Vice Chairman Dudley    ...  train   \n",
       "653465  2854  And let me confirm that the next meeting will ...  train   \n",
       "653466  2854  I believe box lunches are now available for pe...  train   \n",
       "653467  2854  I will do my best, and I will consider at the ...  train   \n",
       "\n",
       "        timestamp         content_type        date       speaker  \\\n",
       "653463 2014-12-17  fomc_meeting_script  2014-12-17    MR. LUECKE   \n",
       "653464 2014-12-17  fomc_meeting_script  2014-12-17    MR. LUECKE   \n",
       "653465 2014-12-17  fomc_meeting_script  2014-12-17  CHAIR YELLEN   \n",
       "653466 2014-12-17  fomc_meeting_script  2014-12-17  CHAIR YELLEN   \n",
       "653467 2014-12-17  fomc_meeting_script  2014-12-17  CHAIR YELLEN   \n",
       "\n",
       "                          title  decision  rate recent_meeting  \\\n",
       "653463  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "653464  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "653465  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "653466  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "653467  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "\n",
       "        recent_decision  recent_rate next_meeting  next_decision  next_rate  \\\n",
       "653463              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "653464              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "653465              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "653466              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "653467              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "\n",
       "        text_num_words  section_id  sent_id  \n",
       "653463              10         287        2  \n",
       "653464              31         287        4  \n",
       "653465              19         288        3  \n",
       "653466              33         288        4  \n",
       "653467              18         288        5  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fomc_sents = eKonf.load_data(\"fomc_sents.parquet\", data_dir)\n",
    "fomc_sents.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting countplot with {'x': 'content_type', 'hue': None}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/CountPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 331,
       "width": 701
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cfg = eKonf.compose(\"visualize/plot=countplot\")\n",
    "cfg.countplot.x = \"content_type\"\n",
    "cfg.figure.figsize = (10, 5)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.ax.title = \"Number of sentences per content type\"\n",
    "eKonf.instantiate(cfg, data=fomc_sents)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/HistPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x1152 with 8 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1123,
       "width": 1278
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "content_types = fomc_sents.content_type.unique()\n",
    "\n",
    "cfg = eKonf.compose(\"visualize/plot=histplot\")\n",
    "cfg.figure.figsize = (18, 16)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.subplots.ncols = 2\n",
    "cfg.subplots.nrows = 4\n",
    "ax = cfg.ax.copy()\n",
    "histplot = cfg.histplot.copy()\n",
    "histplot.x = \"text_num_words\"\n",
    "histplot.bins = 50\n",
    "histplot.kde = True\n",
    "cfg.plots = [histplot.copy() for _ in range(len(content_types))]\n",
    "cfg.axes = [ax.copy() for _ in range(len(content_types))]\n",
    "for i, ctype in enumerate(content_types):\n",
    "    plot = cfg.plots[i]\n",
    "    plot.query = f\"content_type == '{ctype}'\"\n",
    "    plot.axno = i\n",
    "    ax = cfg.axes[i]\n",
    "    ax.title =  f\"Distribution of number of words in [{ctype}]\"\n",
    "    ax.axno = i\n",
    "\n",
    "eKonf.instantiate(cfg, data=fomc_sents)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Split sections into chunks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.io.file:Processing [1] files from ['fomc_sections.parquet']\n",
      "INFO:ekorpkit.io.file:Loading 1 dataframes from ['../data/fomc/fomc_sections.parquet']\n",
      "INFO:ekorpkit.io.file:Loading data from ../data/fomc/fomc_sections.parquet\n",
      "INFO:ekorpkit.pipelines.pipe:Applying pipeline: OrderedDict([('segment', 'segment'), ('chunk', 'chunk'), ('explode_splits', 'explode_splits'), ('filter_length', 'filter_length'), ('reset_index', 'reset_index'), ('save_dataframe', 'save_dataframe')])\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function segment at 0x7fc2a666cb80>)\n",
      "INFO:ekorpkit.pipelines.pipe:instantiating segmenter\n",
      "INFO:ekorpkit.base:instantiating ekorpkit.preprocessors.segmenter.PySBDSegmenter...\n",
      "INFO:ekorpkit.base:Using batcher with minibatch size: 921\n",
      "INFO:ekorpkit.utils.batch.batcher: backend: joblib  minibatch_size: 921  procs: 100  input_split: False  merge_output: True  len(data): 92051 len(args): 5\n",
      "Splitting column: text: 100%|██████████| 100/100 [00:43<00:00,  2.29it/s]\n",
      "INFO:ekorpkit.pipelines.pipe: >> elapsed time to segment: 0:00:43.723911\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function chunk at 0x7fc2a666cd30>)\n",
      "INFO:ekorpkit.pipelines.pipe:instantiating segmenter\n",
      "INFO:ekorpkit.base:Using batcher with minibatch size: 921\n",
      "INFO:ekorpkit.utils.batch.batcher: backend: joblib  minibatch_size: 921  procs: 100  input_split: False  merge_output: True  len(data): 92051 len(args): 5\n",
      "Chunking column: text: 100%|██████████| 100/100 [00:00<00:00, 182.49it/s]\n",
      "INFO:ekorpkit.pipelines.pipe: >> elapsed time to segment: 0:00:00.574704\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function explode_splits at 0x7fc2a666c820>)\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function filter_length at 0x7fc2a666cf70>, len_bytes={'_partial_': True, '_target_': 'ekorpkit.utils.func.len_bytes'}, len_words={'_partial_': True, '_target_': 'ekorpkit.utils.func.len_words'})\n",
      "INFO:ekorpkit.base:Using batcher with minibatch size: 1000\n",
      "INFO:ekorpkit.utils.batch.batcher: backend: joblib  minibatch_size: 1000  procs: 100  input_split: False  merge_output: True  len(data): 133938 len(args): 5\n",
      "Calculating length: 100%|██████████| 134/134 [00:00<00:00, 341.18it/s]\n",
      "INFO:ekorpkit.pipelines.pipe:removed 4798 of 133938 documents with length < 50\n",
      "INFO:ekorpkit.pipelines.pipe:removed 34 of 129140 documents with length > 350\n",
      "INFO:ekorpkit.pipelines.pipe: >> elapsed time to filter length: 0:00:00.432632\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function reset_index at 0x7fc2a666c940>)\n",
      "INFO:ekorpkit.base:Applying pipe: functools.partial(<function save_dataframe at 0x7fc2a666d550>)\n",
      "INFO:ekorpkit.io.file:Saving dataframe to ../data/fomc/fomc_chunks.parquet\n"
     ]
    },
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      "text/plain": [
       "          id                                               text  split  \\\n",
       "129101  2854  It also might help minimize the risks of the t...  train   \n",
       "129102  2854  Getting the right message on inflation is very...  train   \n",
       "129103  2854  CHAIR YELLEN.  \\nThank you.  \\nOkay.  \\nI thin...  train   \n",
       "129104  2854  MR. LUECKE.  \\nThis vote, as Chair Yellen indi...  train   \n",
       "129105  2854  CHAIR YELLEN.  \\nOkay.  \\nThank you very much....  train   \n",
       "\n",
       "        timestamp         content_type        date               speaker  \\\n",
       "129101 2014-12-17  fomc_meeting_script  2014-12-17  VICE CHAIRMAN DUDLEY   \n",
       "129102 2014-12-17  fomc_meeting_script  2014-12-17  VICE CHAIRMAN DUDLEY   \n",
       "129103 2014-12-17  fomc_meeting_script  2014-12-17          CHAIR YELLEN   \n",
       "129104 2014-12-17  fomc_meeting_script  2014-12-17            MR. LUECKE   \n",
       "129105 2014-12-17  fomc_meeting_script  2014-12-17          CHAIR YELLEN   \n",
       "\n",
       "                          title  decision  rate recent_meeting  \\\n",
       "129101  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "129102  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "129103  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "129104  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "129105  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "\n",
       "        recent_decision  recent_rate next_meeting  next_decision  next_rate  \\\n",
       "129101              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "129102              0.0         0.25   2015-01-28            0.0       0.25   \n",
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       "129105              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "\n",
       "        text_num_words  section_id  chunk_id  \n",
       "129101             172         285         6  \n",
       "129102             158         285         7  \n",
       "129103              83         286         0  \n",
       "129104              73         287         0  \n",
       "129105              77         288         0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "seg_cfg = eKonf.compose(\"preprocessor/segmenter=pysbd\")\n",
    "\n",
    "cfg = eKonf.compose(\"pipeline\")\n",
    "cfg.data_dir = data_dir\n",
    "cfg.data_file = \"fomc_sections.parquet\"\n",
    "cfg._pipeline_ = [\n",
    "    \"segment\",\n",
    "    \"chunk\",\n",
    "    \"explode_splits\",\n",
    "    \"filter_length\",\n",
    "    \"reset_index\",\n",
    "    \"save_dataframe\",\n",
    "]\n",
    "cfg.segment.preprocessor.segmenter = seg_cfg\n",
    "cfg.num_workers = 100\n",
    "cfg.chunk.chunk_size = 200\n",
    "cfg.chunk.len_func = \"len_words\"\n",
    "cfg.explode_splits.id_key = [\"id\", \"section_id\"]\n",
    "cfg.explode_splits.split_key = \"chunk_id\"\n",
    "cfg.explode_splits.separator = \"\\n\\n\"\n",
    "cfg.filter_length.min_length = 50\n",
    "cfg.filter_length.max_length = 350\n",
    "cfg.filter_length.len_func = \"len_words\"\n",
    "cfg.filter_length.len_column = \"num_words\"\n",
    "cfg.reset_index.drop_index = True\n",
    "cfg.save_dataframe.output_dir = \"../data/fomc\"\n",
    "cfg.save_dataframe.output_file = \"fomc_chunks.parquet\"\n",
    "fomc_chunks = eKonf.instantiate(cfg)\n",
    "fomc_chunks.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.io.file:Processing [1] files from ['fomc_chunks.parquet']\n",
      "INFO:ekorpkit.io.file:Loading 1 dataframes from ['../data/fomc/fomc_chunks.parquet']\n",
      "INFO:ekorpkit.io.file:Loading data from ../data/fomc/fomc_chunks.parquet\n"
     ]
    },
    {
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       "</table>\n",
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      ],
      "text/plain": [
       "          id                                               text  split  \\\n",
       "129101  2854  It also might help minimize the risks of the t...  train   \n",
       "129102  2854  Getting the right message on inflation is very...  train   \n",
       "129103  2854  CHAIR YELLEN.  \\nThank you.  \\nOkay.  \\nI thin...  train   \n",
       "129104  2854  MR. LUECKE.  \\nThis vote, as Chair Yellen indi...  train   \n",
       "129105  2854  CHAIR YELLEN.  \\nOkay.  \\nThank you very much....  train   \n",
       "\n",
       "        timestamp         content_type        date               speaker  \\\n",
       "129101 2014-12-17  fomc_meeting_script  2014-12-17  VICE CHAIRMAN DUDLEY   \n",
       "129102 2014-12-17  fomc_meeting_script  2014-12-17  VICE CHAIRMAN DUDLEY   \n",
       "129103 2014-12-17  fomc_meeting_script  2014-12-17          CHAIR YELLEN   \n",
       "129104 2014-12-17  fomc_meeting_script  2014-12-17            MR. LUECKE   \n",
       "129105 2014-12-17  fomc_meeting_script  2014-12-17          CHAIR YELLEN   \n",
       "\n",
       "                          title  decision  rate recent_meeting  \\\n",
       "129101  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "129102  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "129103  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "129104  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "129105  FOMC Meeting Transcript       0.0  0.25     2014-12-17   \n",
       "\n",
       "        recent_decision  recent_rate next_meeting  next_decision  next_rate  \\\n",
       "129101              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "129102              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "129103              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "129104              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "129105              0.0         0.25   2015-01-28            0.0       0.25   \n",
       "\n",
       "        text_num_words  section_id  chunk_id  \n",
       "129101             172         285         6  \n",
       "129102             158         285         7  \n",
       "129103              83         286         0  \n",
       "129104              73         287         0  \n",
       "129105              77         288         0  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fomc_chunks = eKonf.load_data(\"fomc_chunks.parquet\", data_dir)\n",
    "fomc_chunks.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting countplot with {'x': 'content_type', 'hue': None}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/CountPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 331,
       "width": 701
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cfg = eKonf.compose(\"visualize/plot=countplot\")\n",
    "cfg.countplot.x = \"content_type\"\n",
    "cfg.figure.figsize = (10, 5)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.ax.title = \"Number of chunks per content type\"\n",
    "eKonf.instantiate(cfg, data=fomc_chunks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Distribution of chunks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.plot:Plotting histplot with {'x': 'text_num_words', 'bins': 50, 'kde': True}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/HistPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1296x1152 with 8 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1123,
       "width": 1278
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "content_types = fomc_chunks.content_type.unique()\n",
    "\n",
    "cfg = eKonf.compose(\"visualize/plot=histplot\")\n",
    "cfg.figure.figsize = (18, 16)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.subplots.ncols = 2\n",
    "cfg.subplots.nrows = 4\n",
    "ax = cfg.ax.copy()\n",
    "histplot = cfg.histplot.copy()\n",
    "histplot.x = \"text_num_words\"\n",
    "histplot.bins = 50\n",
    "histplot.kde = True\n",
    "cfg.plots = [histplot.copy() for _ in range(len(content_types))]\n",
    "cfg.axes = [ax.copy() for _ in range(len(content_types))]\n",
    "for i, ctype in enumerate(content_types):\n",
    "    plot = cfg.plots[i]\n",
    "    plot.query = f\"content_type == '{ctype}'\"\n",
    "    plot.axno = i\n",
    "    ax = cfg.axes[i]\n",
    "    ax.title =  f\"Distribution of number of words in [{ctype}]\"\n",
    "    ax.axno = i\n",
    "\n",
    "eKonf.instantiate(cfg, data=fomc_chunks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare number of records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:ekorpkit.visualize.plot:Plotting countplot with {'x': 'content_type', 'hue': None}\n",
      "INFO:ekorpkit.visualize.plot:Plotting countplot with {'x': 'content_type', 'hue': None}\n",
      "INFO:ekorpkit.visualize.plot:Plotting countplot with {'x': 'content_type', 'hue': None}\n",
      "INFO:ekorpkit.visualize.plot:Plotting countplot with {'x': 'content_type', 'hue': None}\n",
      "INFO:ekorpkit.visualize.base:Saved figure to /workspace/projects/ekorpkit-book/outputs/figs/CountPlot.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 331,
       "width": 1062
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "titles = ['FOMC Corpus', 'FOMC Sections', 'FOMC Sentences', 'FOMC Chunks']\n",
    "cfg = eKonf.compose(\"visualize/plot=countplot\")\n",
    "cfg.figure.figsize = (15, 5)\n",
    "cfg.figure.fontsize = 10\n",
    "cfg.subplots.ncols = 4\n",
    "cfg.subplots.nrows = 1\n",
    "ax = cfg.ax.copy()\n",
    "plot = cfg.plot.copy()\n",
    "plot.x = \"content_type\"\n",
    "cfg.plots = [plot.copy() for _ in range(4)]\n",
    "cfg.axes = [ax.copy() for _ in range(4)]\n",
    "for i in range(4):\n",
    "    plot = cfg.plots[i]\n",
    "    plot.axno = i\n",
    "    plot.datano = i\n",
    "    ax = cfg.axes[i]\n",
    "    ax.title =  titles[i]\n",
    "    ax.xtick_params = dict(labelrotation=45)\n",
    "    ax.axno = i\n",
    "\n",
    "eKonf.instantiate(cfg, data=[fomc_data, fomc_sections, fomc_sents, fomc_chunks])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "f869af7787e6a1c49e09e367fc6e1b81d93d1c6583b43249c80edc047bd13cb2"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}