{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "7a3837ac-cced-4e01-bf57-265e40729692",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import re\n",
    "import numpy as np\n",
    "import thefuzz\n",
    "import tqdm\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "import json\n",
    "\n",
    "pd.set_option('display.max_colwidth', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "29ca0dc8-cae7-4f12-bd60-fd74ea6ae5ac",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "BE_df = pd.read_excel('../Daten/Vorhersagen/Katalogauszug und Vorhersagen.xlsx', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "c1e1c42a-962f-40bc-bb17-b62e8089feb7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "entry_df = pd.read_excel('../Daten/Katalogabgleich/Einträge.xlsx', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "50d15898-4687-46b7-b7e0-528d7cf9aec0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def prepare_string(string):\n",
    "    new = re.sub(r'[àáâãå]', 'a', string)\n",
    "    new = re.sub(r'[èéêë]', 'e', new)\n",
    "    new = re.sub(r'[ìíîï]', 'i', new)\n",
    "    new = re.sub(r'[òóôõ]', 'o', new)\n",
    "    new = re.sub(r'[ùúû]', 'u', new)\n",
    "    new = re.sub(r'æ', 'ae', new)\n",
    "    new = re.sub('[.,:;()¬]|^[CLXVI]+? |^\\d+? |^\\d+?\\.+? |^\\.+ ?|= |# ', '', new)\n",
    "    return new\n",
    "\n",
    "entry_df['cleaned entry'] = entry_df['entry'].apply(lambda x: prepare_string(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "990dfeee-1141-4acb-8a3d-a7af0573f5be",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "BE_early = BE_df[BE_df['Anfang Veröffentlichungsdatum'] < 1736]\n",
    "BE_early_no_dup = BE_early.drop_duplicates('Titel')\n",
    "BE_no_year = BE_df[BE_df['Anfang Veröffentlichungsdatum'].isna()].drop_duplicates('Titel')\n",
    "BE_manual = BE_df.loc[BE_early_no_dup.index.union(BE_no_year.index)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bcd301fe-cb80-4b1c-b65f-465fce5ed915",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([['BE.1.T.33', '+Z167651701',\n",
       "        \"Les deux livres de S. Augustin, de la veritable religion et des moeurs de l'eglise catholique, traduits en francois, sur l'edition latine des Peres Benedictins de la congregation de S. Maur\",\n",
       "        'Augustinus, Aurelius Heiliger 354-430', nan, 1693.0, nan,\n",
       "        '1693', 'Paris', 'Paris', 'French', nan, nan, nan, nan, nan,\n",
       "        'Z167651701', 'Z167651701_00000001.jpg', 'B', 0.0008314285660162,\n",
       "        0.9985696077346802, 0.0003245634725317, 0.0002743884397204,\n",
       "        'blue', 0.9836959838867188, 0.0060312687419354,\n",
       "        0.0102726686745882]], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BE_manual[BE_manual['Signatur'].str.contains('BE.1.T.33')].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "c0f4a42a-7e21-41e8-833c-2dd2f9d1985e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\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>volume</th>\n",
       "      <th>page number</th>\n",
       "      <th>category</th>\n",
       "      <th>subcategory</th>\n",
       "      <th>format</th>\n",
       "      <th>handwritten page number</th>\n",
       "      <th>entry_ID</th>\n",
       "      <th>entry</th>\n",
       "      <th>cleaned entry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3508</th>\n",
       "      <td>14.377</td>\n",
       "      <td>98</td>\n",
       "      <td>Poëtica</td>\n",
       "      <td>Poëtæ Gallici unà cum Dramaticis</td>\n",
       "      <td>Octavo und kleiner</td>\n",
       "      <td>502</td>\n",
       "      <td>14.377_098_09</td>\n",
       "      <td>Poësies de Jacques Poille. Paris. 1623. Th. Blaise n. 1257.</td>\n",
       "      <td>Poesies de Jacques Poille Paris 1623 Th Blaise n 1257</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      volume  page number category                       subcategory   \n",
       "3508  14.377           98  Poëtica  Poëtæ Gallici unà cum Dramaticis  \\\n",
       "\n",
       "                  format handwritten page number       entry_ID   \n",
       "3508  Octavo und kleiner                     502  14.377_098_09  \\\n",
       "\n",
       "                                                            entry   \n",
       "3508  Poësies de Jacques Poille. Paris. 1623. Th. Blaise n. 1257.  \\\n",
       "\n",
       "                                              cleaned entry  \n",
       "3508  Poesies de Jacques Poille Paris 1623 Th Blaise n 1257  "
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def search_in_entry(df, string):\n",
    "    return df[df['cleaned entry'].str.contains(string)]\n",
    "\n",
    "info = search_in_entry(search_in_entry(entry_df, 'Poille'), '')\n",
    "print(len(info))\n",
    "info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "id": "c4394718-cfd3-459e-8923-3ef255a41012",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "volume                                                                                                                                     14.377\n",
       "page number                                                                                                                                    28\n",
       "category                                                                                                                                  Poëtica\n",
       "subcategory                                                                                                                           Poëtæ Græci\n",
       "format                                                                                                                         Octavo und kleiner\n",
       "handwritten page number                                                                                                                       436\n",
       "entry_ID                                                                                                                            14.377_028_02\n",
       "entry                      ..........Le Plutus & Les Nuéces du même trad. du grec par Mad.elle Anne le Fevre. 12.° Paris. 1684. Thierry. n. 1062.\n",
       "cleaned entry                                 Le Plutus & Les Nueces du meme trad du grec par Madelle Anne le Fevre 12° Paris 1684 Thierry n 1062\n",
       "Name: 2857, dtype: object"
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entry_df.loc[2857]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "id": "20facf5d-d609-498e-9907-7ebdffc09e15",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BE.6.S.66\n",
      "+Z201401009\n",
      "Florus Danicus ; Otthiniae Impressus a Christiano Schrödero, Anno 1698\n",
      "Bering, Vitus 1617-1675\n",
      "Tyrnaviae\n",
      "1716\n",
      "N\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Signatur                                                                                        BE.6.S.66\n",
       "Barcode                                                                                       +Z201401009\n",
       "Titel                              Florus Danicus ; Otthiniae Impressus a Christiano Schrödero, Anno 1698\n",
       "Autor                                                                             Bering, Vitus 1617-1675\n",
       "Mitwirkender                                                                                          NaN\n",
       "Anfang Veröffentlichungsdatum                                                                      1716.0\n",
       "Ende Veröffentlichungsdatum                                                                           NaN\n",
       "Veröffentlichungsdatum                                                                               1716\n",
       "Veröffentlichungsort                                                                            Tyrnaviae\n",
       "Veröffentlichungsort (normiert)                                                                    Tyrnau\n",
       "Sprache                                                                                             Latin\n",
       "Schlagwörter                                                                         Dänemark; Geschichte\n",
       "Schlagwörter (mit GND)                        Dänemark$Dg--(DE-588)4010877-6;Geschichte$Az;AT-OBV--ONB-AK\n",
       "Vorbesitzer                                                                                           NaN\n",
       "Typ                                                                                                   NaN\n",
       "Bemerkungen                                                                                           NaN\n",
       "Gültiger Barcode                                                                               Z201401009\n",
       "Dateiname                                                                         Z201401009_00000001.jpg\n",
       "Wappenklassifizierung                                                                                   N\n",
       "p_A                                                                                              0.022146\n",
       "p_B                                                                                              0.008077\n",
       "p_C                                                                                              0.014462\n",
       "p_N                                                                                              0.955316\n",
       "Farbklassifizierung                                                                                   NaN\n",
       "p_blue                                                                                                NaN\n",
       "p_red                                                                                                 NaN\n",
       "p_yellow                                                                                              NaN\n",
       "Name: 15975, dtype: object"
      ]
     },
     "execution_count": 414,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BE_entry = BE_df.loc[15975]\n",
    "print(BE_entry['Signatur'])\n",
    "print(BE_entry['Barcode'])\n",
    "print(BE_entry['Titel'])\n",
    "print(BE_entry['Autor'])\n",
    "print(BE_entry['Veröffentlichungsort'])\n",
    "print(BE_entry['Veröffentlichungsdatum'])\n",
    "print(BE_entry['Wappenklassifizierung'])\n",
    "BE_entry"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a499f1aa-20d8-4e5c-9386-abd2b7023974",
   "metadata": {},
   "source": [
    "# Create Matching data\n",
    "\n",
    "## Match from existing catalogue data for BE signatures. Combine author (+ printer etc), title, year and place and try to match it with an entry in the handwritten catalogue."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5388945-7294-420a-a524-c3372e3c761d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "better_matches = []\n",
    "scorer = thefuzz.fuzz.token_set_ratio\n",
    "\n",
    "for index, row in tqdm.notebook.tqdm(BE_manual.iterrows(), total=len(BE_manual)):\n",
    "    keys = ['Autor', 'Mitwirkender', 'Titel', 'Veröffentlichungsort', 'Anfang Veröffentlichungsdatum']\n",
    "    comb_string = ''\n",
    "    for key in keys:\n",
    "        val = row[key]\n",
    "        if not pd.isna(val):\n",
    "            if key == 'Autor' or key == 'Mitwirkender':\n",
    "                if ',' in val:  # falls name, vorname\n",
    "                    val = val.split(',')[0]\n",
    "                val = val.split(' ')[0]\n",
    "            elif key == 'Titel':\n",
    "                val = prepare_string(val)\n",
    "            elif key == 'Anfang Veröffentlichungsdatum':\n",
    "                val = str(int(val))\n",
    "            else: # key == 'Veröffentlichungsort'\n",
    "                pass\n",
    "            comb_string += val + ' '\n",
    "    \n",
    "    matches_lis = thefuzz.process.extract(comb_string, entry_df['cleaned entry'], scorer=scorer, limit=5)\n",
    "    flat_matches = []\n",
    "    for match in matches_lis:\n",
    "        flat_matches.append(match[0])\n",
    "        flat_matches.append(match[1])\n",
    "        flat_matches.append(match[2])\n",
    "    better_matches.append([comb_string] + flat_matches)\n",
    "\n",
    "matches_df = pd.DataFrame(better_matches, columns=['input', 'match_1', 'score_1', 'id_1', 'match_2', 'score_2', 'id_2', 'match_3', 'score_3', 'id_3', 'match_4', 'score_4', 'id_4', 'match_5', 'score_5', 'id_5'])\n",
    "matches_df['control'] = ''\n",
    "matches_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e0f42259-6df9-4e3b-80e1-1dbe4642545c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "matches_df_no_score = matches_df.drop(['score_1', 'score_2', 'score_3', 'score_4', 'score_5'], axis=1)\n",
    "matches_df_no_score.insert(1, 'input_id', BE_manual.index)\n",
    "matches_df_no_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 749,
   "id": "51aae223-d87e-4fa0-8a97-25c33b7c8d65",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Export in batches of 1000\n",
    "matches_df_no_score[:1000].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_1000.xlsx', index=False)\n",
    "matches_df_no_score[1000:2000].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_2000.xlsx', index=False)\n",
    "matches_df_no_score[2000:3000].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_3000.xlsx', index=False)\n",
    "matches_df_no_score[3000:4000].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_4000.xlsx', index=False)\n",
    "matches_df_no_score[4000:5000].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_5000.xlsx', index=False)\n",
    "matches_df_no_score[5000:6000].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_6000.xlsx', index=False)\n",
    "matches_df_no_score[6000:7000].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_7000.xlsx', index=False)\n",
    "matches_df_no_score[7000:8000].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_8000.xlsx', index=False)\n",
    "matches_df_no_score[8000:].to_excel('../Daten/Katalogabgleich/Kandidaten/Kandidaten_8756.xlsx', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "68eb5b1e-a23b-4014-aa7d-903878c14a3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "non_BE = BE_df[~BE_df['Signatur'].str.contains('BE')]\n",
    "non_BE_wappen = non_BE[~non_BE['Wappenklassifizierung'].isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "d34f7a91-6f09-4c93-8376-105dc804764f",
   "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>Signatur</th>\n",
       "      <th>Wappenklassifizierung</th>\n",
       "      <th>Barcode</th>\n",
       "      <th>Mitwirkender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>22595</th>\n",
       "      <td>Be.10.J.38.(Vol.1,1)</td>\n",
       "      <td>N</td>\n",
       "      <td>+Z17136510X</td>\n",
       "      <td>Cotta; Nees von Esenbeck, Christian Gottfried Daniel 1776-1858; Eschweiler, Franz Gerhard 1796-1831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22599</th>\n",
       "      <td>Be.5.Q.69.(Vol.5)</td>\n",
       "      <td>N</td>\n",
       "      <td>+Z197357203</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22612</th>\n",
       "      <td>22.M.23</td>\n",
       "      <td>B</td>\n",
       "      <td>+Z43165504</td>\n",
       "      <td>Manuzio, Aldo Pio 1450-1515; Philostratus, Flavius 160-245; Eusebius Caesariensis 260-339; Rinuccinus, Alemannus 1426-1504; Acciaiuoli, Zanobi 1461-1519; Ευσεβιος Καισαρειας</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22613</th>\n",
       "      <td>22.N.14</td>\n",
       "      <td>B</td>\n",
       "      <td>+Z221977709</td>\n",
       "      <td>Manuzio, Paolo; Manuzio, Paolo 1512-1574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22614</th>\n",
       "      <td>22.N.27 (Vol.1)</td>\n",
       "      <td>B</td>\n",
       "      <td>+Z43162801</td>\n",
       "      <td>Manuzio, Aldo Pio 1450-1515; Theophanes Confessor 752-817; Cosmas Hierosolymitanus -781; Marcus de Idronto ca. um 770; Johannes Damascenus 675-749; Clarius, Daniel ca. 15./16. Jh.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22615</th>\n",
       "      <td>22.N.67</td>\n",
       "      <td>B</td>\n",
       "      <td>+Z221954400</td>\n",
       "      <td>Manuzio, Paolo 1512-1574; Auria, Andrea &lt;&lt;d'&gt;&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22616</th>\n",
       "      <td>22.Q.37</td>\n",
       "      <td>N</td>\n",
       "      <td>+Z22196790X</td>\n",
       "      <td>Asulanus, Franciscus -1546; Aldo Manuzio Senior Haeredes; Carloni, Antonio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22618</th>\n",
       "      <td>60164-D.1</td>\n",
       "      <td>A</td>\n",
       "      <td>+Z194791901</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22619</th>\n",
       "      <td>60164-D.2</td>\n",
       "      <td>A</td>\n",
       "      <td>+Z254932002</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Signatur Wappenklassifizierung      Barcode  \\\n",
       "22595  Be.10.J.38.(Vol.1,1)                     N  +Z17136510X   \n",
       "22599     Be.5.Q.69.(Vol.5)                     N  +Z197357203   \n",
       "22612               22.M.23                     B   +Z43165504   \n",
       "22613               22.N.14                     B  +Z221977709   \n",
       "22614       22.N.27 (Vol.1)                     B   +Z43162801   \n",
       "22615               22.N.67                     B  +Z221954400   \n",
       "22616               22.Q.37                     N  +Z22196790X   \n",
       "22618             60164-D.1                     A  +Z194791901   \n",
       "22619             60164-D.2                     A  +Z254932002   \n",
       "\n",
       "                                                                                                                                                                              Mitwirkender  \n",
       "22595                                                                                  Cotta; Nees von Esenbeck, Christian Gottfried Daniel 1776-1858; Eschweiler, Franz Gerhard 1796-1831  \n",
       "22599                                                                                                                                                                                  NaN  \n",
       "22612        Manuzio, Aldo Pio 1450-1515; Philostratus, Flavius 160-245; Eusebius Caesariensis 260-339; Rinuccinus, Alemannus 1426-1504; Acciaiuoli, Zanobi 1461-1519; Ευσεβιος Καισαρειας  \n",
       "22613                                                                                                                                             Manuzio, Paolo; Manuzio, Paolo 1512-1574  \n",
       "22614  Manuzio, Aldo Pio 1450-1515; Theophanes Confessor 752-817; Cosmas Hierosolymitanus -781; Marcus de Idronto ca. um 770; Johannes Damascenus 675-749; Clarius, Daniel ca. 15./16. Jh.  \n",
       "22615                                                                                                                                       Manuzio, Paolo 1512-1574; Auria, Andrea <<d'>>  \n",
       "22616                                                                                                           Asulanus, Franciscus -1546; Aldo Manuzio Senior Haeredes; Carloni, Antonio  \n",
       "22618                                                                                                                                                                                  NaN  \n",
       "22619                                                                                                                                                                                  NaN  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "non_BE_wappen[['Signatur', 'Wappenklassifizierung', 'Barcode', 'Mitwirkender']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "512515e9-84a4-4e97-a16d-2f28df90abde",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Signatur', 'Barcode', 'Titel', 'Autor', 'Mitwirkender',\n",
       "       'Anfang Veröffentlichungsdatum', 'Ende Veröffentlichungsdatum',\n",
       "       'Veröffentlichungsdatum', 'Veröffentlichungsort',\n",
       "       'Veröffentlichungsort (normiert)', 'Sprache', 'Schlagwörter',\n",
       "       'Schlagwörter (mit GND)', 'Vorbesitzer', 'Typ', 'Bemerkungen',\n",
       "       'Gültiger Barcode', 'Dateiname', 'Wappenklassifizierung', 'p_A', 'p_B',\n",
       "       'p_C', 'p_N', 'Farbklassifizierung', 'p_blue', 'p_red', 'p_yellow'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "non_BE_wappen.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "b8de2583-c260-46df-ab7c-15b4feff0a33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['filename', 'prediction', 'p_A', 'p_B', 'p_C', 'p_N', 'color', 'p_blue',\n",
       "       'p_red', 'p_yellow', 'man_prediction', 'man_color', 'valid_bc',\n",
       "       'Permanent Call Number', '992', '993', '695', '866',\n",
       "       'Library Code (Active)', 'Location Code', 'Barcode', 'Item Call Number',\n",
       "       'Title', 'Author', 'Author (contributor)', 'Begin Publication Date',\n",
       "       'End Publication Date', 'Publication Date', 'Publication Place',\n",
       "       'Publisher', 'Unnamed: 17', 'MMS Id', '856', 'Subjects',\n",
       "       'Subjects (Names)'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred = pd.read_csv('../Daten/Vorhersagen/catalogue_pred_combined.csv')\n",
    "pred.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "042eb3f3-6d53-4403-a230-513d36ea8b44",
   "metadata": {},
   "outputs": [],
   "source": [
    "no_sign_wappen = pred[pred['Permanent Call Number'].isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "87462bd0-ad17-4ea5-9486-f4b23605d74d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "803"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(no_sign_wappen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "d7326106-193b-4841-ac3c-becae1b27ddf",
   "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>filename</th>\n",
       "      <th>prediction</th>\n",
       "      <th>p_A</th>\n",
       "      <th>p_B</th>\n",
       "      <th>p_C</th>\n",
       "      <th>p_N</th>\n",
       "      <th>color</th>\n",
       "      <th>p_blue</th>\n",
       "      <th>p_red</th>\n",
       "      <th>p_yellow</th>\n",
       "      <th>...</th>\n",
       "      <th>Begin Publication Date</th>\n",
       "      <th>End Publication Date</th>\n",
       "      <th>Publication Date</th>\n",
       "      <th>Publication Place</th>\n",
       "      <th>Publisher</th>\n",
       "      <th>Unnamed: 17</th>\n",
       "      <th>MMS Id</th>\n",
       "      <th>856</th>\n",
       "      <th>Subjects</th>\n",
       "      <th>Subjects (Names)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Z103519105_00000001.jpg</td>\n",
       "      <td>A</td>\n",
       "      <td>0.998598</td>\n",
       "      <td>0.000445</td>\n",
       "      <td>0.000400</td>\n",
       "      <td>0.000558</td>\n",
       "      <td>red</td>\n",
       "      <td>0.000419</td>\n",
       "      <td>0.997730</td>\n",
       "      <td>0.001851</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Z10353460X_00000001.jpg</td>\n",
       "      <td>A</td>\n",
       "      <td>0.994711</td>\n",
       "      <td>0.002387</td>\n",
       "      <td>0.001679</td>\n",
       "      <td>0.001224</td>\n",
       "      <td>red</td>\n",
       "      <td>0.002559</td>\n",
       "      <td>0.982544</td>\n",
       "      <td>0.014897</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Z105561605_00000001.jpg</td>\n",
       "      <td>B</td>\n",
       "      <td>0.000142</td>\n",
       "      <td>0.999590</td>\n",
       "      <td>0.000070</td>\n",
       "      <td>0.000198</td>\n",
       "      <td>red</td>\n",
       "      <td>0.000502</td>\n",
       "      <td>0.995507</td>\n",
       "      <td>0.003991</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Z137115906_00000001.jpg</td>\n",
       "      <td>A</td>\n",
       "      <td>0.997722</td>\n",
       "      <td>0.001312</td>\n",
       "      <td>0.000461</td>\n",
       "      <td>0.000505</td>\n",
       "      <td>blue</td>\n",
       "      <td>0.993158</td>\n",
       "      <td>0.003776</td>\n",
       "      <td>0.003066</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Z13711690X_00000001.jpg</td>\n",
       "      <td>A</td>\n",
       "      <td>0.999452</td>\n",
       "      <td>0.000185</td>\n",
       "      <td>0.000149</td>\n",
       "      <td>0.000213</td>\n",
       "      <td>blue</td>\n",
       "      <td>0.994273</td>\n",
       "      <td>0.005353</td>\n",
       "      <td>0.000374</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6154</th>\n",
       "      <td>Z260077107_00000001.jpg</td>\n",
       "      <td>B</td>\n",
       "      <td>0.000248</td>\n",
       "      <td>0.998484</td>\n",
       "      <td>0.000442</td>\n",
       "      <td>0.000827</td>\n",
       "      <td>red</td>\n",
       "      <td>0.000213</td>\n",
       "      <td>0.994317</td>\n",
       "      <td>0.005469</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6155</th>\n",
       "      <td>Z43162801_00000001.jpg</td>\n",
       "      <td>B</td>\n",
       "      <td>0.000684</td>\n",
       "      <td>0.997634</td>\n",
       "      <td>0.001180</td>\n",
       "      <td>0.000502</td>\n",
       "      <td>red</td>\n",
       "      <td>0.001450</td>\n",
       "      <td>0.997198</td>\n",
       "      <td>0.001353</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6156</th>\n",
       "      <td>Z43163301_00000001.jpg</td>\n",
       "      <td>B</td>\n",
       "      <td>0.000872</td>\n",
       "      <td>0.998139</td>\n",
       "      <td>0.000583</td>\n",
       "      <td>0.000406</td>\n",
       "      <td>red</td>\n",
       "      <td>0.000331</td>\n",
       "      <td>0.998473</td>\n",
       "      <td>0.001197</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6157</th>\n",
       "      <td>Z43165504_00000001.jpg</td>\n",
       "      <td>B</td>\n",
       "      <td>0.000670</td>\n",
       "      <td>0.998324</td>\n",
       "      <td>0.000560</td>\n",
       "      <td>0.000445</td>\n",
       "      <td>red</td>\n",
       "      <td>0.001188</td>\n",
       "      <td>0.996374</td>\n",
       "      <td>0.002438</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6158</th>\n",
       "      <td>Z43169509_00000001.jpg</td>\n",
       "      <td>A</td>\n",
       "      <td>0.995156</td>\n",
       "      <td>0.001711</td>\n",
       "      <td>0.002191</td>\n",
       "      <td>0.000941</td>\n",
       "      <td>red</td>\n",
       "      <td>0.000120</td>\n",
       "      <td>0.999710</td>\n",
       "      <td>0.000170</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>803 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     filename prediction       p_A       p_B       p_C  \\\n",
       "0     Z103519105_00000001.jpg          A  0.998598  0.000445  0.000400   \n",
       "4     Z10353460X_00000001.jpg          A  0.994711  0.002387  0.001679   \n",
       "13    Z105561605_00000001.jpg          B  0.000142  0.999590  0.000070   \n",
       "16    Z137115906_00000001.jpg          A  0.997722  0.001312  0.000461   \n",
       "17    Z13711690X_00000001.jpg          A  0.999452  0.000185  0.000149   \n",
       "...                       ...        ...       ...       ...       ...   \n",
       "6154  Z260077107_00000001.jpg          B  0.000248  0.998484  0.000442   \n",
       "6155   Z43162801_00000001.jpg          B  0.000684  0.997634  0.001180   \n",
       "6156   Z43163301_00000001.jpg          B  0.000872  0.998139  0.000583   \n",
       "6157   Z43165504_00000001.jpg          B  0.000670  0.998324  0.000560   \n",
       "6158   Z43169509_00000001.jpg          A  0.995156  0.001711  0.002191   \n",
       "\n",
       "           p_N color    p_blue     p_red  p_yellow  ...  \\\n",
       "0     0.000558   red  0.000419  0.997730  0.001851  ...   \n",
       "4     0.001224   red  0.002559  0.982544  0.014897  ...   \n",
       "13    0.000198   red  0.000502  0.995507  0.003991  ...   \n",
       "16    0.000505  blue  0.993158  0.003776  0.003066  ...   \n",
       "17    0.000213  blue  0.994273  0.005353  0.000374  ...   \n",
       "...        ...   ...       ...       ...       ...  ...   \n",
       "6154  0.000827   red  0.000213  0.994317  0.005469  ...   \n",
       "6155  0.000502   red  0.001450  0.997198  0.001353  ...   \n",
       "6156  0.000406   red  0.000331  0.998473  0.001197  ...   \n",
       "6157  0.000445   red  0.001188  0.996374  0.002438  ...   \n",
       "6158  0.000941   red  0.000120  0.999710  0.000170  ...   \n",
       "\n",
       "     Begin Publication Date End Publication Date Publication Date  \\\n",
       "0                       NaN                  NaN              NaN   \n",
       "4                       NaN                  NaN              NaN   \n",
       "13                      NaN                  NaN              NaN   \n",
       "16                      NaN                  NaN              NaN   \n",
       "17                      NaN                  NaN              NaN   \n",
       "...                     ...                  ...              ...   \n",
       "6154                    NaN                  NaN              NaN   \n",
       "6155                    NaN                  NaN              NaN   \n",
       "6156                    NaN                  NaN              NaN   \n",
       "6157                    NaN                  NaN              NaN   \n",
       "6158                    NaN                  NaN              NaN   \n",
       "\n",
       "     Publication Place Publisher Unnamed: 17 MMS Id  856 Subjects  \\\n",
       "0                  NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "4                  NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "13                 NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "16                 NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "17                 NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "...                ...       ...         ...    ...  ...      ...   \n",
       "6154               NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "6155               NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "6156               NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "6157               NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "6158               NaN       NaN         NaN    NaN  NaN      NaN   \n",
       "\n",
       "     Subjects (Names)  \n",
       "0                 NaN  \n",
       "4                 NaN  \n",
       "13                NaN  \n",
       "16                NaN  \n",
       "17                NaN  \n",
       "...               ...  \n",
       "6154              NaN  \n",
       "6155              NaN  \n",
       "6156              NaN  \n",
       "6157              NaN  \n",
       "6158              NaN  \n",
       "\n",
       "[803 rows x 35 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "no_sign_wappen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "07da4f64-6dbd-4a57-9122-338a9c66bf5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "nsw = no_sign_wappen.dropna(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "73c74495-9522-427a-88db-d8f1cca96cdd",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_content(url):\n",
    "    retries = 0\n",
    "    while retries < 3:\n",
    "        try:\n",
    "            resp = requests.get(url)\n",
    "            if resp.status_code == 200:\n",
    "                return resp.content\n",
    "            else:\n",
    "                retries += 1\n",
    "        except requests.exceptions.Timeout:\n",
    "            retries += 1\n",
    "        except (requests.exceptions.TooManyRedirects, requests.exceptions.RequestException) as e:\n",
    "            raise SystemExit(e)\n",
    "\n",
    "def extract_signature_from_manifest(bc):\n",
    "    man_url = f'https://iiif.onb.ac.at/presentation/ABO/{bc}/manifest'\n",
    "    metadata = json.loads(get_content(man_url))['metadata']\n",
    "    metadata_str = json.dumps(metadata)\n",
    "    loc_s = re.compile('<a.+?data.onb.ac.at.+?>(.+?)</a>')\n",
    "    ac_s = re.compile('AC[0-9]+')\n",
    "    loc = loc_s.findall(metadata_str)\n",
    "    if len(loc) > 0:\n",
    "        loc = loc[0]\n",
    "    else:\n",
    "        loc = ''\n",
    "    acnr = ac_s.findall(metadata_str)\n",
    "    if len(acnr) > 0:\n",
    "        acnr = acnr[0]\n",
    "    else:\n",
    "        acnr = ''\n",
    "    return (loc, acnr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "f4ef590d-775f-41c6-bd35-384aa9e5dd8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('', 'AC09912489')"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "extract_signature_from_manifest('Z150809200')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "8920d0a5-6ead-4db8-8407-cd6d4c8657e7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_7044/501467936.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  nsw.loc[i, 'Signatur'] = sig\n",
      "/tmp/ipykernel_7044/501467936.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  nsw.loc[i, 'AC-Nummer'] = ac\n"
     ]
    }
   ],
   "source": [
    "for i in nsw.index:\n",
    "    bc = nsw.loc[i, 'valid_bc']\n",
    "    sig, ac = extract_signature_from_manifest(bc)\n",
    "    nsw.loc[i, 'Signatur'] = sig\n",
    "    nsw.loc[i, 'AC-Nummer'] = ac"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "0ae7c215-f811-4b6d-897f-55328337ead4",
   "metadata": {},
   "outputs": [],
   "source": [
    "nsw_no_dup = nsw.drop_duplicates('valid_bc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "e3916d07-7d22-40c3-aff2-eb9823840f96",
   "metadata": {},
   "outputs": [],
   "source": [
    "keine_BE = nsw_no_dup.drop(['filename', 'prediction', 'p_A', 'p_B', 'p_C', 'p_N', 'color', 'p_blue', 'p_red', 'p_yellow'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "62d169f7-2bcb-431b-8f6b-76d37194abc9",
   "metadata": {},
   "outputs": [],
   "source": [
    "keine_BE.rename(columns={'man_prediction': 'Wappen', 'man_color': 'Einbandfarbe', 'valid_bc': 'Barcode'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "3cc27a7c-b960-4360-81c8-6873fc39a95e",
   "metadata": {},
   "outputs": [],
   "source": [
    "keine_BE = keine_BE.reindex(columns=['Barcode', 'Signatur', 'AC-Nummer', 'Wappen', 'Einbandfarbe'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "f2c1a4aa-3312-4353-9767-ef0009bf35da",
   "metadata": {},
   "outputs": [],
   "source": [
    "keine_BE.to_excel('../Daten/Vorhersagen/Eugeniana aber nicht BE.xlsx', index=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "054a6f0d-251d-4cc5-84b9-0d777b7d1f7c",
   "metadata": {},
   "source": [
    "# Analyze manual matching data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "d6efcff5-0393-4835-b673-001e85877f13",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "manual_file_names = [\n",
    "    'Ausgefüllt_1000.xlsx',\n",
    "    'Ausgefüllt_2000.xlsx',\n",
    "    'Ausgefüllt_3000.xlsx',\n",
    "    'Ausgefüllt_4000.xlsx',\n",
    "    'Ausgefüllt_5000.xlsx',\n",
    "    'Ausgefüllt_6000.xlsx',\n",
    "    'Ausgefüllt_7000.xlsx',\n",
    "    'Ausgefüllt_8000.xlsx',\n",
    "    'Ausgefüllt_8756.xlsx',\n",
    "]\n",
    "\n",
    "manual_matches_dfs = []\n",
    "\n",
    "for fname in manual_file_names:\n",
    "    df = pd.read_excel(f'../Daten/Katalogabgleich/Ausgefüllt/{fname}')\n",
    "    manual_matches_dfs.append(df)\n",
    "\n",
    "man_matches = pd.concat(manual_matches_dfs, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "7a39c6a7-d81b-4f79-89a0-bafc96411d93",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "has_hw_catalog = man_matches.dropna(subset=['control'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "881ea2ed-277b-46da-8f23-e3f3f56aae86",
   "metadata": {},
   "source": [
    "## Matching statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "cb7b6815-c782-4e00-bd7f-9abcf7f523f5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "75 <class 'numpy.int64'>\n",
      "75 <class 'int'>\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "def num_in_lis(num, lis_str):\n",
    "    if pd.isna(lis_str):\n",
    "        return False \n",
    "    else:\n",
    "        if isinstance(lis_str, int):\n",
    "            lis = [lis_str]\n",
    "        if isinstance(lis_str, str):\n",
    "            if '?' in lis_str:\n",
    "                return False\n",
    "            lis = lis_str.split(', ')\n",
    "            lis = [int(n) for n in lis]\n",
    "        return num in lis\n",
    "\n",
    "example = man_matches.loc[9]\n",
    "print(example['id_1'], type(example['id_1']))\n",
    "print(example['control'], type(example['control']))\n",
    "print(num_in_lis(example['id_1'], example['control']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "836d1b5e-ef2f-4ff8-9c03-298b029f73b2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5778 out of 8756 BE signatures from the appropriate time period were matched\n",
      "For 4564 matches the first one was correct\n",
      "For 5072 matches one of the five given ones in the table was correct\n",
      "124 matches have two or more mentions in the handrwitten catalog\n"
     ]
    }
   ],
   "source": [
    "BE_signatures_matched = len(man_matches.dropna(subset=['control']))\n",
    "print(BE_signatures_matched, 'out of', len(man_matches), 'BE signatures from the appropriate time period were matched')\n",
    "\n",
    "first_matches = sum(man_matches.apply(lambda x: num_in_lis(x['id_1'], x['control']), axis=1))\n",
    "print('For', first_matches, 'matches the first one was correct')\n",
    "any_matches = sum(man_matches.apply(lambda x: num_in_lis(x['id_1'], x['control']) \n",
    "                                    or num_in_lis(x['id_2'], x['control']) \n",
    "                                    or num_in_lis(x['id_3'], x['control']) \n",
    "                                    or num_in_lis(x['id_4'], x['control']) \n",
    "                                    or num_in_lis(x['id_5'], x['control']), axis=1))\n",
    "print('For', any_matches, 'matches one of the five given ones in the table was correct')\n",
    "\n",
    "double_matches = man_matches['control'].str.contains(',').sum()\n",
    "print(double_matches, 'matches have two or more mentions in the handrwitten catalog')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "9f7bd1bf-a4cd-427a-b65a-5e2fce029212",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "num_re = re.compile('\\d{1,4}(?!\\?)')\n",
    "all_matches = []\n",
    "for row in man_matches['control']:\n",
    "    match = num_re.findall(str(row))\n",
    "    if match:\n",
    "        all_matches.append(match)\n",
    "\n",
    "flat_matches = [el for sublis in all_matches for el in sublis]\n",
    "set_matches = set(flat_matches)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "17434971-7462-4f00-8370-d5573f3ea72c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5086 entries out of 9403 entries from the handwritten catalog were matched (at least once)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[2, 4, 7, 9, 10, 11, 12, 14, 16, 18, 19, 20, 22, 25, 26, 28, 29, 32, 34, 35]"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_matches_int = sorted([int(n) for n in set_matches])\n",
    "\n",
    "print(len(unique_matches_int), 'entries out of', len(entry_df), 'entries from the handwritten catalog were matched (at least once)')\n",
    "unique_matches_int[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "25fcabf9-fb1c-4fe7-838a-8b595f0a2673",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "no_matches_df = entry_df.loc[entry_df.index.difference(unique_matches_int)]\n",
    "matches_df = entry_df.loc[unique_matches_int]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "24bb9a74-0e99-4760-a3d5-05f8df71f85a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Historia Nova Europæ': 0.48382838283828383, 'Poëtica': 0.5410273515677118, 'Paralipomena Historica': 0.5508870214752568, 'Theologia': 0.7555555555555555, 'Philologia': 0.596694214876033, 'Historia Naturalis': 0.6634615384615384, 'Historia Ecclesiastica': 0.689119170984456, 'Artes': 0.5623342175066313, 'Philosophia': 0.6542857142857142, 'Historia Antiqua': 0.3862928348909657, 'Codices Manuscripti': 0.0034129692832764505, 'Imagines Incisæ': 0.04330708661417323, 'Geographia': 0.5317460317460317, 'Iurisprudentia': 0.6715686274509803, 'Historia Nova extra Europam': 0.5577889447236181, 'Rhetorica': 0.5864197530864198, 'Mathematica': 0.7559055118110236, 'Grammatica': 0.5819672131147541, 'Medicina': 0.6330275229357798, 'Chronologia': 0.5612244897959183, 'Miscellanea Historica': 0.3877551020408163, 'Imagines Variæ Incisæ': 0.0851063829787234, 'Effigierum Incisarum Collectio': 0.0, 'Imaginum Delineatarum Collectio': 0.0}\n"
     ]
    }
   ],
   "source": [
    "all_counts = entry_df['category'].value_counts()\n",
    "match_counts = matches_df['category'].value_counts()\n",
    "no_match_counts = no_matches_df['category'].value_counts()\n",
    "\n",
    "ratios = {}\n",
    "for cat, count in all_counts.items():\n",
    "    matched = 0\n",
    "    if cat in match_counts.index:\n",
    "        matched = match_counts[cat]\n",
    "    ratios[cat] = matched / count\n",
    "\n",
    "print(ratios)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "6c952698-2bc7-4511-a688-3bcd30ed8196",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sorted_ratios = sorted(ratios.items(), key=lambda x: x[1], reverse=True)\n",
    "n, r = list(zip(*sorted_ratios))\n",
    "\n",
    "fix, ax = plt.subplots()\n",
    "ax.bar(n, [100 * ratio for ratio in r])\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "ax.set_ylabel('Vollständigkeit [%]')\n",
    "ax.set_title('Verbindung von hs. Katalog und mod. Katalog')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b49f3686-efd3-478b-b493-b69b60ce3ad4",
   "metadata": {},
   "source": [
    "## Add new matching data to existing catalogue data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "c52f2098-221b-4912-841a-d54e25788143",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "BE_df = pd.read_excel('../Daten/Vorhersagen/WIP_complete_BE.xlsx', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "32d281c0-4015-4913-a5ec-da22c6a9c8ad",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Barcode', 'Titel', 'Autor', 'Mitwirkender',\n",
       "       'Anfang Veröffentlichungsdatum', 'Ende Veröffentlichungsdatum',\n",
       "       'Veröffentlichungsdatum', 'Veröffentlichungsort',\n",
       "       'Veröffentlichungsort (normiert)', 'Sprache', 'Schlagwörter',\n",
       "       'Schlagwörter (mit GND)', 'Vorbesitzer', 'Typ', 'Bemerkungen',\n",
       "       'Gültiger Barcode', 'Dateiname', 'Wappenklassifizierung', 'p_A', 'p_B',\n",
       "       'p_C', 'p_N', 'Farbklassifizierung', 'p_blue', 'p_red', 'p_yellow',\n",
       "       'hs. Katalog', 'hs. Katalog Konfidenz', 'hs. Katalogband',\n",
       "       'hs. Katalogseite Digitalisat', 'Wissensklasse', 'Wissensunterklasse',\n",
       "       'Formatangabe', 'hs. Katalogseite Handschrift', 'hs. Katalogeintrag ID',\n",
       "       'hs. Katalogeintrag', 'hs. Katalog Image URL', 'identifier',\n",
       "       'ABO-Barcode'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# volume \tpage number \tcategory \tsubcategory \tformat \thandwritten page number \tentry_ID \tentry \t\n",
    "BE_df['hs. Katalog'] = 0\n",
    "\n",
    "BE_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "0ddd0ffe-3546-43fb-90ff-1d7206af138e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['volume', 'page number', 'category', 'subcategory', 'format',\n",
       "       'handwritten page number', 'entry_ID', 'entry', 'cleaned entry'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entry_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b8d40359-5eba-49e6-b2a6-3bc37786dd4c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "dod_id = {\n",
    "    '14.376': 51202, \n",
    "    '14.377': 51184,\n",
    "    '14.378': 51219\n",
    "}\n",
    "\n",
    "for i, entry in has_hw_catalog.iterrows():\n",
    "    man_match = str(entry['control'])\n",
    "    match_regex = re.compile('\\d{1,4}')\n",
    "    matches = match_regex.findall(man_match)\n",
    "    if matches:\n",
    "        first_match_id = int(matches[0])\n",
    "        corr_entry = entry_df.loc[first_match_id]\n",
    "        BE_id = entry['input_id']\n",
    "        BE_df.at[BE_id, 'hs. Katalog'] = 1\n",
    "        if '?' not in man_match:\n",
    "            BE_df.at[BE_id, 'hs. Katalog Konfidenz'] = 'sicher'\n",
    "        else:\n",
    "            BE_df.at[BE_id, 'hs. Katalog Konfidenz'] = 'unsicher'\n",
    "        BE_df.at[BE_id, 'hs. Katalogband'] = str(corr_entry['volume'])\n",
    "        BE_df.at[BE_id, 'hs. Katalogseite Digitalisat'] = corr_entry['page number']\n",
    "        BE_df.at[BE_id, 'Wissensklasse'] = corr_entry['category']\n",
    "        BE_df.at[BE_id, 'Wissensunterklasse'] = corr_entry['subcategory']\n",
    "        BE_df.at[BE_id, 'Formatangabe'] = corr_entry['format']\n",
    "        BE_df.at[BE_id, 'hs. Katalogseite Handschrift'] = corr_entry['handwritten page number']\n",
    "        BE_df.at[BE_id, 'hs. Katalogeintrag ID'] = corr_entry['entry_ID']\n",
    "        BE_df.at[BE_id, 'hs. Katalogeintrag'] = corr_entry['entry']\n",
    "        BE_df.at[BE_id, 'hs. Katalog Image URL'] = f\"https://iiif.onb.ac.at/images/DOD/{dod_id[str(corr_entry['volume'])]}/{corr_entry['page number']:08}.jp2/full/full/0/native.jpg\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "4ed3c187-ab7a-419a-8530-386a69143b3d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# BE_df.to_excel('../Daten/Vorhersagen/Katalogauszug, Vorhersagen und hs. Katalogverbindungen.xlsx', index=False)\n",
    "BE_df.to_excel('../Daten/Vorhersagen/Complete_BE.xlsx', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "7f5dabc1-49bf-469a-9abe-c15fa20204ce",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Signatur', 'Barcode', 'Titel', 'Autor', 'Mitwirkender',\n",
       "       'Anfang Veröffentlichungsdatum', 'Ende Veröffentlichungsdatum',\n",
       "       'Veröffentlichungsdatum', 'Veröffentlichungsort',\n",
       "       'Veröffentlichungsort (normiert)', 'Sprache', 'Schlagwörter',\n",
       "       'Schlagwörter (mit GND)', 'Vorbesitzer', 'Typ', 'Bemerkungen',\n",
       "       'Gültiger Barcode', 'Dateiname', 'Wappenklassifizierung', 'p_A', 'p_B',\n",
       "       'p_C', 'p_N', 'Farbklassifizierung', 'p_blue', 'p_red', 'p_yellow',\n",
       "       'hs. Katalog', 'hs. Katalog Konfidenz', 'hs. Katalogband',\n",
       "       'hs. Katalogseite Digitalisat', 'Wissensklasse', 'Wissensunterklasse',\n",
       "       'Formatangabe', 'hs. Katalogseite Handschrift', 'hs. Katalogeintrag ID',\n",
       "       'hs. Katalogeintrag', 'hs. Katalog Image URL'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BE_df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88b825b9-8557-441d-b387-697db4ea2a5b",
   "metadata": {},
   "source": [
    "# Eugeniana-Inkunabeln aus dem handschriftlichen Katalog extrahieren"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 513,
   "id": "bc7c8cf5-7afa-43c1-8427-ab7cd58323b3",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1661]\n",
      "[1628]\n",
      "[1703, 5926]\n",
      "[1662]\n"
     ]
    }
   ],
   "source": [
    "def extract_four_digit_number(entry):\n",
    "    four_dig_re = re.compile('(?<! [pPnN] )\\d{4}')\n",
    "    match = four_dig_re.findall(entry)\n",
    "    if match:\n",
    "        return [int(x) for x in match]\n",
    "    else:\n",
    "        return []\n",
    "\n",
    "year_samples = [\n",
    "    'Vossij Isaaci Dissertationes de 70 Interpretum tralatione & Chronologia Hagae Comp 1661 Vlacq p 7145 n 1360',\n",
    "    'Biblia Sacra graece ac latine juxta 70 Interpretes 3 Vol charta magna Paris 1628 Nic Buon N 3743',\n",
    "    'Nummi Antiqui Familiarum Romanar cum Ioannis Vaillant Interpretationibus 2 Vol Amsteln 1703 Gallet n 5925 5926',\n",
    "    'Hulsij antonij Authentia absoluta Seu textus hebraei vindicata contra criminationes Isaaci Vossii in libro recens edito de 70 Interpretum tralatione cum binis epistolis Roterod 1662 arn Leers n 2407 P 1234'\n",
    "]\n",
    "\n",
    "for entry in year_samples:\n",
    "    print(extract_four_digit_number(entry))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 497,
   "id": "42988cd3-f87f-46b4-be10-b5d254c286d0",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "entry_df['years'] = entry_df['cleaned entry'].apply(lambda x: extract_four_digit_number(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 498,
   "id": "46d0487a-096b-4d41-872a-b9668315ee8a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "years_raw = entry_df['years']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 518,
   "id": "0110a88f-8777-4efd-84c7-b74e6fdd740a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             [1515]\n",
       "1             [1572]\n",
       "2       [1637, 1669]\n",
       "3             [1462]\n",
       "4             [1472]\n",
       "            ...     \n",
       "9398              []\n",
       "9399              []\n",
       "9400              []\n",
       "9401              []\n",
       "9402              []\n",
       "Name: years, Length: 9403, dtype: object"
      ]
     },
     "execution_count": 518,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "years_raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 519,
   "id": "8f60804d-17fa-4d3a-9ad2-ec4a549bdf50",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "years_cleaned = years_raw.apply(lambda x: list(filter(lambda y: 1400 < int(y) < 1736, x)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 520,
   "id": "08f2d680-91e7-4fa7-8e58-ae2793ad184b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "years_min = years_cleaned.apply(lambda x: int(min(x)) if len(x) else np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 521,
   "id": "d9d40c18-f7b0-4725-941b-90e1ccf8b974",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "without_years = entry_df.loc[years_raw[years_min.isna()].index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 522,
   "id": "40328321-57d1-4d29-a087-832354f560a8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1515.0\n",
       "1       1572.0\n",
       "2       1637.0\n",
       "3       1462.0\n",
       "4       1472.0\n",
       "         ...  \n",
       "9398       NaN\n",
       "9399       NaN\n",
       "9400       NaN\n",
       "9401       NaN\n",
       "9402       NaN\n",
       "Name: years, Length: 9403, dtype: float64"
      ]
     },
     "execution_count": 522,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "years_min"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 523,
   "id": "7e083bdd-3aa6-40df-b12c-43238aae5355",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "before_1501 = entry_df.loc[years_min < 1501]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 526,
   "id": "321b9d28-7198-49fd-9f56-290dd6c58950",
   "metadata": {
    "tags": []
   },
   "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>volume</th>\n",
       "      <th>page number</th>\n",
       "      <th>category</th>\n",
       "      <th>subcategory</th>\n",
       "      <th>format</th>\n",
       "      <th>handwritten page number</th>\n",
       "      <th>entry_ID</th>\n",
       "      <th>entry</th>\n",
       "      <th>cleaned entry</th>\n",
       "      <th>years</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14.376</td>\n",
       "      <td>25</td>\n",
       "      <td>Theologia</td>\n",
       "      <td>Textus &amp; Versiones Sacræ Scripturæ</td>\n",
       "      <td>Folio</td>\n",
       "      <td>1</td>\n",
       "      <td>14.376_025_03</td>\n",
       "      <td>4 Biblia Sacra Latina Moguntina dicta, prima omnium editio in Membranis. 2 Vol. Moguntiæ. 1462.¬ Ioan. Fust, &amp; Petr. Schoiffer de Gerneshem. n. 2088. II.O.5.</td>\n",
       "      <td>Biblia Sacra Latina Moguntina dicta prima omnium editio in Membranis 2 Vol Moguntiae 1462 Ioan Fust &amp; Petr Schoiffer de Gerneshem n 2088 IIO5</td>\n",
       "      <td>[1462]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>14.376</td>\n",
       "      <td>25</td>\n",
       "      <td>Theologia</td>\n",
       "      <td>Textus &amp; Versiones Sacræ Scripturæ</td>\n",
       "      <td>Folio</td>\n",
       "      <td>1</td>\n",
       "      <td>14.376_025_04</td>\n",
       "      <td>5 Biblia Sacra Latina Moguntina, editio altera 2 Vol. chartâ Magnâ. Moguntiæ. 1472. Petr. Schoiffer. II.O.7. de Gerneshem. n. 2089.</td>\n",
       "      <td>Biblia Sacra Latina Moguntina editio altera 2 Vol charta Magna Moguntiae 1472 Petr Schoiffer IIO7 de Gerneshem n 2089</td>\n",
       "      <td>[1472]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>14.376</td>\n",
       "      <td>25</td>\n",
       "      <td>Theologia</td>\n",
       "      <td>Textus &amp; Versiones Sacræ Scripturæ</td>\n",
       "      <td>Folio</td>\n",
       "      <td>1</td>\n",
       "      <td>14.376_025_06</td>\n",
       "      <td>7 Biblia Sacra latina vulgatæ Editionis. 2 Vol. chartâ III.B.3. Magnâ. 1474. absque loco Editionis n. 2090.</td>\n",
       "      <td>Biblia Sacra latina vulgatae Editionis 2 Vol charta IIIB3 Magna 1474 absque loco Editionis n 2090</td>\n",
       "      <td>[1474]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>14.376</td>\n",
       "      <td>25</td>\n",
       "      <td>Theologia</td>\n",
       "      <td>Textus &amp; Versiones Sacræ Scripturæ</td>\n",
       "      <td>Folio</td>\n",
       "      <td>1</td>\n",
       "      <td>14.376_025_07</td>\n",
       "      <td>8 Biblia Sacra Latina cum Evangelistarum Canonibus III.B.7. &amp; concordantiis. chartâ M. Coloniæ. 1479. de Homborch. n. 2093.</td>\n",
       "      <td>Biblia Sacra Latina cum Evangelistarum Canonibus IIIB7 &amp; concordantiis charta M Coloniae 1479 de Homborch n 2093</td>\n",
       "      <td>[1479]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>14.376</td>\n",
       "      <td>26</td>\n",
       "      <td>Theologia</td>\n",
       "      <td>Textus &amp; Versiones Sacræ Scripturæ</td>\n",
       "      <td>Folio</td>\n",
       "      <td>2</td>\n",
       "      <td>14.376_026_00</td>\n",
       "      <td>9. Biblia Sacra Latina. Venetiis. 1481. Leonard Wild de Ratisbonâ n. 2302. III. D. 11.</td>\n",
       "      <td>Biblia Sacra Latina Venetiis 1481 Leonard Wild de Ratisbona n 2302 III D 11</td>\n",
       "      <td>[1481]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9017</th>\n",
       "      <td>14.378</td>\n",
       "      <td>522</td>\n",
       "      <td>Codices Manuscripti</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quarto</td>\n",
       "      <td>1348</td>\n",
       "      <td>14.378_522_05</td>\n",
       "      <td>53 Tractatus de Matrimonio à Fr. Lùcano Parmensi compilat. anno 1468. Ms. in Membranis. n. CCIX.</td>\n",
       "      <td>Tractatus de Matrimonio a Fr Lucano Parmensi compilat anno 1468 Ms in Membranis n CCIX</td>\n",
       "      <td>[1468]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9033</th>\n",
       "      <td>14.378</td>\n",
       "      <td>523</td>\n",
       "      <td>Codices Manuscripti</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Quarto</td>\n",
       "      <td>1347*</td>\n",
       "      <td>14.378_523_09</td>\n",
       "      <td>68 Monita Agapæti Batilica ad Imper. Iustinian. Ms. græcè  A 1500</td>\n",
       "      <td>Monita Agapaeti Batilica ad Imper Iustinian Ms graece  A 1500</td>\n",
       "      <td>[1500]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9051</th>\n",
       "      <td>14.378</td>\n",
       "      <td>527</td>\n",
       "      <td>Codices Manuscripti</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Octavo und kleiner</td>\n",
       "      <td>1349</td>\n",
       "      <td>14.378_527_05</td>\n",
       "      <td>10 Succineta &amp; accurata de scriptio Civitatis Constantinopol. a Constantino Magno anno 331. ad Sult. Mehemet II. anno 1453. cum descriptione Canalis Maris Nigri.¬ autore Ioan. Adamo Zizla. Ms. in 8.° germanicè.</td>\n",
       "      <td>Succineta &amp; accurata de scriptio Civitatis Constantinopol a Constantino Magno anno 331 ad Sult Mehemet II anno 1453 cum descriptione Canalis Maris Nigri autore Ioan Adamo Zizla Ms in 8° germanice</td>\n",
       "      <td>[1453]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9052</th>\n",
       "      <td>14.378</td>\n",
       "      <td>528</td>\n",
       "      <td>Codices Manuscripti</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Octavo und kleiner</td>\n",
       "      <td>1350</td>\n",
       "      <td>14.378_528_00</td>\n",
       "      <td>84. I.Trionfi di Francesco Petrarca con miniature Ms. 8.° 11. Questo Ms.° è del tempo del medesimo Petrarca n. CCXXXIV. obüt Petrarca an. 1374. &amp; codex in fine habet 1459. p. 519</td>\n",
       "      <td>ITrionfi di Francesco Petrarca con miniature Ms 8° 11 Questo Ms° e del tempo del medesimo Petrarca n CCXXXIV obüt Petrarca an 1374 &amp; codex in fine habet 1459 p 519</td>\n",
       "      <td>[1374, 1459]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9059</th>\n",
       "      <td>14.378</td>\n",
       "      <td>529</td>\n",
       "      <td>Codices Manuscripti</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Octavo und kleiner</td>\n",
       "      <td>1351</td>\n",
       "      <td>14.378_529_03</td>\n",
       "      <td>Descriptio civitatis Constantinopoleos a Constantino M. anno 331. ad Sultanum Mehemet II. anno 1453. cum descriptione Canalis Maris Nigri. autore I. Adamo Zizla. 8.° Ms. germanicè</td>\n",
       "      <td>Descriptio civitatis Constantinopoleos a Constantino M anno 331 ad Sultanum Mehemet II anno 1453 cum descriptione Canalis Maris Nigri autore I Adamo Zizla 8° Ms germanice</td>\n",
       "      <td>[1453]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>366 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      volume  page number             category   \n",
       "3     14.376           25            Theologia  \\\n",
       "4     14.376           25            Theologia   \n",
       "6     14.376           25            Theologia   \n",
       "7     14.376           25            Theologia   \n",
       "8     14.376           26            Theologia   \n",
       "...      ...          ...                  ...   \n",
       "9017  14.378          522  Codices Manuscripti   \n",
       "9033  14.378          523  Codices Manuscripti   \n",
       "9051  14.378          527  Codices Manuscripti   \n",
       "9052  14.378          528  Codices Manuscripti   \n",
       "9059  14.378          529  Codices Manuscripti   \n",
       "\n",
       "                             subcategory              format   \n",
       "3     Textus & Versiones Sacræ Scripturæ               Folio  \\\n",
       "4     Textus & Versiones Sacræ Scripturæ               Folio   \n",
       "6     Textus & Versiones Sacræ Scripturæ               Folio   \n",
       "7     Textus & Versiones Sacræ Scripturæ               Folio   \n",
       "8     Textus & Versiones Sacræ Scripturæ               Folio   \n",
       "...                                  ...                 ...   \n",
       "9017                                 NaN              Quarto   \n",
       "9033                                 NaN              Quarto   \n",
       "9051                                 NaN  Octavo und kleiner   \n",
       "9052                                 NaN  Octavo und kleiner   \n",
       "9059                                 NaN  Octavo und kleiner   \n",
       "\n",
       "     handwritten page number       entry_ID   \n",
       "3                          1  14.376_025_03  \\\n",
       "4                          1  14.376_025_04   \n",
       "6                          1  14.376_025_06   \n",
       "7                          1  14.376_025_07   \n",
       "8                          2  14.376_026_00   \n",
       "...                      ...            ...   \n",
       "9017                    1348  14.378_522_05   \n",
       "9033                   1347*  14.378_523_09   \n",
       "9051                    1349  14.378_527_05   \n",
       "9052                    1350  14.378_528_00   \n",
       "9059                    1351  14.378_529_03   \n",
       "\n",
       "                                                                                                                                                                                                                   entry   \n",
       "3                                                          4 Biblia Sacra Latina Moguntina dicta, prima omnium editio in Membranis. 2 Vol. Moguntiæ. 1462.¬ Ioan. Fust, & Petr. Schoiffer de Gerneshem. n. 2088. II.O.5.  \\\n",
       "4                                                                                    5 Biblia Sacra Latina Moguntina, editio altera 2 Vol. chartâ Magnâ. Moguntiæ. 1472. Petr. Schoiffer. II.O.7. de Gerneshem. n. 2089.   \n",
       "6                                                                                                            7 Biblia Sacra latina vulgatæ Editionis. 2 Vol. chartâ III.B.3. Magnâ. 1474. absque loco Editionis n. 2090.   \n",
       "7                                                                                            8 Biblia Sacra Latina cum Evangelistarum Canonibus III.B.7. & concordantiis. chartâ M. Coloniæ. 1479. de Homborch. n. 2093.   \n",
       "8                                                                                                                                 9. Biblia Sacra Latina. Venetiis. 1481. Leonard Wild de Ratisbonâ n. 2302. III. D. 11.   \n",
       "...                                                                                                                                                                                                                  ...   \n",
       "9017                                                                                                                    53 Tractatus de Matrimonio à Fr. Lùcano Parmensi compilat. anno 1468. Ms. in Membranis. n. CCIX.   \n",
       "9033                                                                                                                                                   68 Monita Agapæti Batilica ad Imper. Iustinian. Ms. græcè  A 1500   \n",
       "9051  10 Succineta & accurata de scriptio Civitatis Constantinopol. a Constantino Magno anno 331. ad Sult. Mehemet II. anno 1453. cum descriptione Canalis Maris Nigri.¬ autore Ioan. Adamo Zizla. Ms. in 8.° germanicè.   \n",
       "9052                                  84. I.Trionfi di Francesco Petrarca con miniature Ms. 8.° 11. Questo Ms.° è del tempo del medesimo Petrarca n. CCXXXIV. obüt Petrarca an. 1374. & codex in fine habet 1459. p. 519   \n",
       "9059                                 Descriptio civitatis Constantinopoleos a Constantino M. anno 331. ad Sultanum Mehemet II. anno 1453. cum descriptione Canalis Maris Nigri. autore I. Adamo Zizla. 8.° Ms. germanicè   \n",
       "\n",
       "                                                                                                                                                                                            cleaned entry   \n",
       "3                                                           Biblia Sacra Latina Moguntina dicta prima omnium editio in Membranis 2 Vol Moguntiae 1462 Ioan Fust & Petr Schoiffer de Gerneshem n 2088 IIO5  \\\n",
       "4                                                                                   Biblia Sacra Latina Moguntina editio altera 2 Vol charta Magna Moguntiae 1472 Petr Schoiffer IIO7 de Gerneshem n 2089   \n",
       "6                                                                                                       Biblia Sacra latina vulgatae Editionis 2 Vol charta IIIB3 Magna 1474 absque loco Editionis n 2090   \n",
       "7                                                                                        Biblia Sacra Latina cum Evangelistarum Canonibus IIIB7 & concordantiis charta M Coloniae 1479 de Homborch n 2093   \n",
       "8                                                                                                                             Biblia Sacra Latina Venetiis 1481 Leonard Wild de Ratisbona n 2302 III D 11   \n",
       "...                                                                                                                                                                                                   ...   \n",
       "9017                                                                                                               Tractatus de Matrimonio a Fr Lucano Parmensi compilat anno 1468 Ms in Membranis n CCIX   \n",
       "9033                                                                                                                                        Monita Agapaeti Batilica ad Imper Iustinian Ms graece  A 1500   \n",
       "9051  Succineta & accurata de scriptio Civitatis Constantinopol a Constantino Magno anno 331 ad Sult Mehemet II anno 1453 cum descriptione Canalis Maris Nigri autore Ioan Adamo Zizla Ms in 8° germanice   \n",
       "9052                                  ITrionfi di Francesco Petrarca con miniature Ms 8° 11 Questo Ms° e del tempo del medesimo Petrarca n CCXXXIV obüt Petrarca an 1374 & codex in fine habet 1459 p 519   \n",
       "9059                           Descriptio civitatis Constantinopoleos a Constantino M anno 331 ad Sultanum Mehemet II anno 1453 cum descriptione Canalis Maris Nigri autore I Adamo Zizla 8° Ms germanice   \n",
       "\n",
       "             years  \n",
       "3           [1462]  \n",
       "4           [1472]  \n",
       "6           [1474]  \n",
       "7           [1479]  \n",
       "8           [1481]  \n",
       "...            ...  \n",
       "9017        [1468]  \n",
       "9033        [1500]  \n",
       "9051        [1453]  \n",
       "9052  [1374, 1459]  \n",
       "9059        [1453]  \n",
       "\n",
       "[366 rows x 10 columns]"
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       "      <td>14.376_025_05</td>\n",
       "      <td>6 Biblia Sacra Latina cum glossa &amp; Comment. 4 Vol. chartâ Magnâ. Editio perantiqua sine loco &amp; II.O.1. anno n. 2086.</td>\n",
       "      <td>Biblia Sacra Latina cum glossa &amp; Comment 4 Vol charta Magna Editio perantiqua sine loco &amp; IIO1 anno n 2086</td>\n",
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       "      <td>14.376_027_02</td>\n",
       "      <td>18 La S.e Bible historiée dite d'Escholatre avec des fig. gravées en bois. 2 Vol. sans datte. Barthel. Verard. n. 165.</td>\n",
       "      <td>La Se Bible historiee dite d'Escholatre avec des fig gravees en bois 2 Vol sans datte Barthel Verard n 165</td>\n",
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       "      <td>3</td>\n",
       "      <td>14.376_027_06</td>\n",
       "      <td>22 Biblia Sacra germanicè Mss. in Membranis cum figuris pictis. n. II.</td>\n",
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       "      <td>14.376_027_07</td>\n",
       "      <td>23 Biblia Sacra Hollandicé Mss. in Membranis cum fig. pictis. 2 Vol. n. III.</td>\n",
       "      <td>Biblia Sacra Hollandice Mss in Membranis cum fig pictis 2 Vol n III</td>\n",
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       "      <td>Folio</td>\n",
       "      <td>3</td>\n",
       "      <td>14.376_027_09</td>\n",
       "      <td>25 Historia Veteris ac Novi Testamenti MS. in Membranis cum innumeris ferè Imaginibus miniatè depictis. n. 1.</td>\n",
       "      <td>Historia Veteris ac Novi Testamenti MS in Membranis cum innumeris fere Imaginibus miniate depictis n 1</td>\n",
       "      <td>[]</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <th>9398</th>\n",
       "      <td>14.378</td>\n",
       "      <td>582</td>\n",
       "      <td>Imaginum Delineatarum Collectio</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1402</td>\n",
       "      <td>14.378_582_00</td>\n",
       "      <td>CCCXXXI Vn Portefeüilles contenant des Desseins de plusieurs Villes d'Espagne par Ant. Van-den-Wingarde. dont il n'y a pas de Catalogue. n. 990.</td>\n",
       "      <td>Vn Portefeüilles contenant des Desseins de plusieurs Villes d'Espagne par Ant Van-den-Wingarde dont il n'y a pas de Catalogue n 990</td>\n",
       "      <td>[]</td>\n",
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       "      <th>9399</th>\n",
       "      <td>14.378</td>\n",
       "      <td>582</td>\n",
       "      <td>Imaginum Delineatarum Collectio</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1402</td>\n",
       "      <td>14.378_582_01</td>\n",
       "      <td>CCCXXXII  Vn Recueil des Portraits peints en miniature sur velain au nombre de 34. dont le Premier est celuy de Philippe le Hardy. n. CCIV.</td>\n",
       "      <td>Vn Recueil des Portraits peints en miniature sur velain au nombre de 34 dont le Premier est celuy de Philippe le Hardy n CCIV</td>\n",
       "      <td>[]</td>\n",
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       "      <th>9400</th>\n",
       "      <td>14.378</td>\n",
       "      <td>582</td>\n",
       "      <td>Imaginum Delineatarum Collectio</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1402</td>\n",
       "      <td>14.378_582_02</td>\n",
       "      <td>CCCXXXIII  Dix Vol. de Plantes peintes en miniature par Nicol. Robert. vide. Hist. Plantarum</td>\n",
       "      <td>Dix Vol de Plantes peintes en miniature par Nicol Robert vide Hist Plantarum</td>\n",
       "      <td>[]</td>\n",
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       "      <td>CCCXXXIV  Cinq Vol. d'Oiseaux peints en Miniature par Nic. Robert. vide. Histor. Animalium.</td>\n",
       "      <td>Cinq Vol d'Oiseaux peints en Miniature par Nic Robert vide Histor Animalium</td>\n",
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       "      <td>14.378_582_04</td>\n",
       "      <td>CCCXXXV Divers Portraits, Ceremonies, Marches &amp;c. des Turcs &amp; d'autres nations du Levant, peints en miniature n. CCLXX.</td>\n",
       "      <td>Divers Portraits Ceremonies Marches &amp;c des Turcs &amp; d'autres nations du Levant peints en miniature n CCLXX</td>\n",
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       "      volume  page number                         category   \n",
       "5     14.376           25                        Theologia  \\\n",
       "17    14.376           27                        Theologia   \n",
       "21    14.376           27                        Theologia   \n",
       "22    14.376           27                        Theologia   \n",
       "24    14.376           27                        Theologia   \n",
       "...      ...          ...                              ...   \n",
       "9398  14.378          582  Imaginum Delineatarum Collectio   \n",
       "9399  14.378          582  Imaginum Delineatarum Collectio   \n",
       "9400  14.378          582  Imaginum Delineatarum Collectio   \n",
       "9401  14.378          582  Imaginum Delineatarum Collectio   \n",
       "9402  14.378          582  Imaginum Delineatarum Collectio   \n",
       "\n",
       "                             subcategory format handwritten page number   \n",
       "5     Textus & Versiones Sacræ Scripturæ  Folio                       1  \\\n",
       "17    Textus & Versiones Sacræ Scripturæ  Folio                       3   \n",
       "21    Textus & Versiones Sacræ Scripturæ  Folio                       3   \n",
       "22    Textus & Versiones Sacræ Scripturæ  Folio                       3   \n",
       "24    Textus & Versiones Sacræ Scripturæ  Folio                       3   \n",
       "...                                  ...    ...                     ...   \n",
       "9398                                 NaN    NaN                    1402   \n",
       "9399                                 NaN    NaN                    1402   \n",
       "9400                                 NaN    NaN                    1402   \n",
       "9401                                 NaN    NaN                    1402   \n",
       "9402                                 NaN    NaN                    1402   \n",
       "\n",
       "           entry_ID   \n",
       "5     14.376_025_05  \\\n",
       "17    14.376_027_02   \n",
       "21    14.376_027_06   \n",
       "22    14.376_027_07   \n",
       "24    14.376_027_09   \n",
       "...             ...   \n",
       "9398  14.378_582_00   \n",
       "9399  14.378_582_01   \n",
       "9400  14.378_582_02   \n",
       "9401  14.378_582_03   \n",
       "9402  14.378_582_04   \n",
       "\n",
       "                                                                                                                                                 entry   \n",
       "5                                 6 Biblia Sacra Latina cum glossa & Comment. 4 Vol. chartâ Magnâ. Editio perantiqua sine loco & II.O.1. anno n. 2086.  \\\n",
       "17                              18 La S.e Bible historiée dite d'Escholatre avec des fig. gravées en bois. 2 Vol. sans datte. Barthel. Verard. n. 165.   \n",
       "21                                                                              22 Biblia Sacra germanicè Mss. in Membranis cum figuris pictis. n. II.   \n",
       "22                                                                        23 Biblia Sacra Hollandicé Mss. in Membranis cum fig. pictis. 2 Vol. n. III.   \n",
       "24                                       25 Historia Veteris ac Novi Testamenti MS. in Membranis cum innumeris ferè Imaginibus miniatè depictis. n. 1.   \n",
       "...                                                                                                                                                ...   \n",
       "9398  CCCXXXI Vn Portefeüilles contenant des Desseins de plusieurs Villes d'Espagne par Ant. Van-den-Wingarde. dont il n'y a pas de Catalogue. n. 990.   \n",
       "9399       CCCXXXII  Vn Recueil des Portraits peints en miniature sur velain au nombre de 34. dont le Premier est celuy de Philippe le Hardy. n. CCIV.   \n",
       "9400                                                      CCCXXXIII  Dix Vol. de Plantes peintes en miniature par Nicol. Robert. vide. Hist. Plantarum   \n",
       "9401                                                       CCCXXXIV  Cinq Vol. d'Oiseaux peints en Miniature par Nic. Robert. vide. Histor. Animalium.   \n",
       "9402                           CCCXXXV Divers Portraits, Ceremonies, Marches &c. des Turcs & d'autres nations du Levant, peints en miniature n. CCLXX.   \n",
       "\n",
       "                                                                                                                            cleaned entry   \n",
       "5                              Biblia Sacra Latina cum glossa & Comment 4 Vol charta Magna Editio perantiqua sine loco & IIO1 anno n 2086  \\\n",
       "17                             La Se Bible historiee dite d'Escholatre avec des fig gravees en bois 2 Vol sans datte Barthel Verard n 165   \n",
       "21                                                                        Biblia Sacra germanice Mss in Membranis cum figuris pictis n II   \n",
       "22                                                                    Biblia Sacra Hollandice Mss in Membranis cum fig pictis 2 Vol n III   \n",
       "24                                 Historia Veteris ac Novi Testamenti MS in Membranis cum innumeris fere Imaginibus miniate depictis n 1   \n",
       "...                                                                                                                                   ...   \n",
       "9398  Vn Portefeüilles contenant des Desseins de plusieurs Villes d'Espagne par Ant Van-den-Wingarde dont il n'y a pas de Catalogue n 990   \n",
       "9399        Vn Recueil des Portraits peints en miniature sur velain au nombre de 34 dont le Premier est celuy de Philippe le Hardy n CCIV   \n",
       "9400                                                         Dix Vol de Plantes peintes en miniature par Nicol Robert vide Hist Plantarum   \n",
       "9401                                                          Cinq Vol d'Oiseaux peints en Miniature par Nic Robert vide Histor Animalium   \n",
       "9402                            Divers Portraits Ceremonies Marches &c des Turcs & d'autres nations du Levant peints en miniature n CCLXX   \n",
       "\n",
       "     years  \n",
       "5       []  \n",
       "17      []  \n",
       "21      []  \n",
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       "24      []  \n",
       "...    ...  \n",
       "9398    []  \n",
       "9399    []  \n",
       "9400    []  \n",
       "9401    []  \n",
       "9402    []  \n",
       "\n",
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