{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "# Analyzing Text Content of all Ontologies\n",
    "\n"
   ],
   "id": "91379b6d59f5c8ed"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-20T03:24:26.298342Z",
     "start_time": "2024-12-20T03:24:26.266440Z"
    }
   },
   "cell_type": "code",
   "source": "",
   "id": "fbf2be05abef4f73",
   "outputs": [],
   "execution_count": 14
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-19T19:27:33.099743Z",
     "start_time": "2024-12-19T19:27:32.938042Z"
    }
   },
   "cell_type": "code",
   "source": "!mkdir -p output",
   "id": "6a36717659364a16",
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "!python -m oaklib.utilities.metrics.text_content_analysis ~/repos/semantic-sql/db/*.db > output/ontologies-tc.tsv",
   "id": "2edefc15b805bbcc"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-19T19:28:39.154652Z",
     "start_time": "2024-12-19T19:28:38.613182Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('output/ontologies-tc.tsv', sep='\\t')\n",
    "df"
   ],
   "id": "4fd30caaf6c167cd",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                                              ontology  text_content\n",
       "0              /Users/cjm/repos/semantic-sql/db/aao.db           NaN\n",
       "1              /Users/cjm/repos/semantic-sql/db/ado.db      0.945262\n",
       "2              /Users/cjm/repos/semantic-sql/db/adw.db           NaN\n",
       "3              /Users/cjm/repos/semantic-sql/db/aeo.db      0.879694\n",
       "4             /Users/cjm/repos/semantic-sql/db/aero.db           NaN\n",
       "..                                                 ...           ...\n",
       "145        /Users/cjm/repos/semantic-sql/db/go-lego.db      0.589013\n",
       "146     /Users/cjm/repos/semantic-sql/db/go-nucleus.db      0.846068\n",
       "147        /Users/cjm/repos/semantic-sql/db/go-plus.db      0.500000\n",
       "148             /Users/cjm/repos/semantic-sql/db/go.db      0.604229\n",
       "149  /Users/cjm/repos/semantic-sql/db/goa_uniprot_a...           NaN\n",
       "\n",
       "[150 rows x 2 columns]"
      ],
      "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>ontology</th>\n",
       "      <th>text_content</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/aao.db</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/ado.db</td>\n",
       "      <td>0.945262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/adw.db</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/aeo.db</td>\n",
       "      <td>0.879694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/aero.db</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/go-lego.db</td>\n",
       "      <td>0.589013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/go-nucleus.db</td>\n",
       "      <td>0.846068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/go-plus.db</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/go.db</td>\n",
       "      <td>0.604229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>/Users/cjm/repos/semantic-sql/db/goa_uniprot_a...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 2 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-19T19:29:17.374285Z",
     "start_time": "2024-12-19T19:29:17.362340Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# replace ontology column (which is currently file path) with ontology name (stemmed file name)\n",
    "import os\n",
    "df['ontology'] = df['ontology'].apply(lambda x: os.path.basename(x).replace('.db',''))\n",
    "df"
   ],
   "id": "62c117e15dca07f0",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            ontology  text_content\n",
       "0                aao           NaN\n",
       "1                ado      0.945262\n",
       "2                adw           NaN\n",
       "3                aeo      0.879694\n",
       "4               aero           NaN\n",
       "..               ...           ...\n",
       "145          go-lego      0.589013\n",
       "146       go-nucleus      0.846068\n",
       "147          go-plus      0.500000\n",
       "148               go      0.604229\n",
       "149  goa_uniprot_all           NaN\n",
       "\n",
       "[150 rows x 2 columns]"
      ],
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ontology</th>\n",
       "      <th>text_content</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aao</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ado</td>\n",
       "      <td>0.945262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>adw</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>aeo</td>\n",
       "      <td>0.879694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>aero</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>go-lego</td>\n",
       "      <td>0.589013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>go-nucleus</td>\n",
       "      <td>0.846068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>go-plus</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>go</td>\n",
       "      <td>0.604229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>goa_uniprot_all</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 2 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-19T19:29:53.375367Z",
     "start_time": "2024-12-19T19:29:53.367730Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# drop columns with all text_content values as NaN\n",
    "df = df.dropna()\n",
    "df"
   ],
   "id": "e57b6ab1fc047d35",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "       ontology  text_content\n",
       "1           ado      0.945262\n",
       "3           aeo      0.879694\n",
       "5          agro      0.801219\n",
       "6           aio      0.940620\n",
       "7          aism      0.684825\n",
       "..          ...           ...\n",
       "144    go-amigo      0.592075\n",
       "145     go-lego      0.589013\n",
       "146  go-nucleus      0.846068\n",
       "147     go-plus      0.500000\n",
       "148          go      0.604229\n",
       "\n",
       "[126 rows x 2 columns]"
      ],
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ontology</th>\n",
       "      <th>text_content</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ado</td>\n",
       "      <td>0.945262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>aeo</td>\n",
       "      <td>0.879694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>agro</td>\n",
       "      <td>0.801219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>aio</td>\n",
       "      <td>0.940620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>aism</td>\n",
       "      <td>0.684825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>go-amigo</td>\n",
       "      <td>0.592075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>go-lego</td>\n",
       "      <td>0.589013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>go-nucleus</td>\n",
       "      <td>0.846068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>go-plus</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>go</td>\n",
       "      <td>0.604229</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>126 rows × 2 columns</p>\n",
       "</div>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "## Plot Results\n",
    "\n",
    "use matplotlib to plot the results as a bar chart, ordered by the text_content value"
   ],
   "id": "4a2e2181dfcd02a1"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-19T19:36:22.404326Z",
     "start_time": "2024-12-19T19:36:21.100168Z"
    }
   },
   "cell_type": "code",
   "source": [
    "# use matplotlib to plot df as a bar chart\n",
    "# x-axis: ontology\n",
    "# y-axis: text_content\n",
    "# order by text_content\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "df = df.sort_values('text_content', ascending=False)\n",
    "plt.figure(figsize=(24, 12))\n",
    "sns.barplot(x='ontology', y='text_content', data=df)\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Ontology')\n",
    "plt.ylabel('Text Content')\n",
    "plt.title('Text Content of Ontologies')\n",
    "plt.savefig('output/text_content.png')\n",
    "plt.savefig('output/text_content.svg')\n",
    "plt.show()"
   ],
   "id": "156350a01ac80cdb",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 2400x1200 with 1 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 13
  },
  {
   "metadata": {},
   "cell_type": "code",
   "outputs": [],
   "execution_count": null,
   "source": "",
   "id": "b784c514b296ba0d"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}