Svenskt Kvinnobiografiskt lexikon part 3.ipynb

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    "# Svenskt Kvinnobiografiskt lexikon - SKBL part 3\n",
    "    version part 3 - 2.7\n",
    " \n",
    " This [notebook](https://tinyurl.com/SKBLWDsynch) - latest run [diff WD / SKBL](https://github.com/salgo60/open-data-examples/blob/master/SKBL_new.csv)\n",
    "  \n",
    "  \n",
    "  * SKBL see https://skbl.se/en  \n",
    "    * example structured data from SKBL [GretaGarbo JSON](https://skbl.se/en/article/GretaGarbo.json)\n",
    "    * video \n",
    "      * in [Swedish what we do today](https://youtu.be/LBx7XowzrJ0)\n",
    "      * the vision with [Wikidata <-> SKBL](https://www.youtube.com/watch?v=HIHO-szkD1A)\n",
    "    * [presentation](https://docs.google.com/presentation/d/1EvQHdzPsIA4hr2WuNXnbpsLHec2GS89b_pHvilO6xhQ/edit?usp=sharing) about start using Linked data at SKBL and have same as Wikidata \n",
    "  * [Wikidata:WikiProject_Sweden/Svenskt_kvinnobiografiskt_lexikon](https://www.wikidata.org/wiki/Wikidata:WikiProject_Sweden/Svenskt_kvinnobiografiskt_lexikon)\n",
    "    \n",
    "  \n",
    "### Purpose\n",
    "  * gets statistics about SKBL and compare number of articles produced with what The Swedish National archives [SBL biographies](https://sok.riksarkivet.se/sbl/Start.aspx?lang=en) has produced since 1918\n",
    "  * check if SKBL has new articles created not added to [Wikidata](https://www.youtube.com/watch?v=m_9_23jXPoE)"
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     "text": [
      "Last run:  2022-02-09 16:59:04.288368\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "start_time  = datetime.now()\n",
    "print(\"Last run: \", start_time)"
   ]
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    "#### Other sources we sync\n",
    "* [Arken](https://github.com/salgo60/open-data-examples/blob/master/Arken.ipynb) \n",
    "  * WD [Property:P8899](https://www.wikidata.org/wiki/Property:P8899) \n",
    "* [Kulturpersoner Uppsalakyrkogård](https://github.com/salgo60/open-data-examples/blob/master/Check%20WD%20kulturpersoner%20uppsalakyrkogardar.ipynb)\n",
    "* [Litteraturbanken](https://github.com/salgo60/open-data-examples/blob/master/Litteraturbanken%20Author.ipynb) \n",
    "  * WD property [P5101](https://www.wikidata.org/wiki/Property_talk:P5101) [P5123](https://www.wikidata.org/wiki/Property_talk:P5123)\n",
    "* [Nobelprize.org](https://github.com/salgo60/open-data-examples/blob/master/Nobel%20API.ipynb)\n",
    "  * WD [property 8024](https://www.wikidata.org/wiki/Property:P8024)\n",
    "* [SBL](https://github.com/salgo60/open-data-examples/blob/master/SBL.ipynb) \n",
    "  * WD [property 3217](https://www.wikidata.org/wiki/Property:P3217) \n",
    "* [SKBL](https://github.com/salgo60/open-data-examples/blob/master/Svenskt%20Kvinnobiografiskt%20lexikon%20part%203.ipynb)\n",
    "  * WD [property 4963](https://www.wikidata.org/wiki/Property:P4963)\n",
    "* [Svenska Akademien](https://github.com/salgo60/open-data-examples/blob/master/Svenska%20Akademien.ipynb) \n",
    "  * WD [property 5325](https://www.wikidata.org/wiki/Property:P5325) \n"
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    "### Links\n",
    "* [video](https://www.youtube.com/watch?v=6jxH8MBIhvg) in Swedish about how SKBL deliver and work with Wikidata\n",
    "  * Example how project Women in Red at en:Wikipedia automatic [creates dynamic lists of \"missing\" articles](https://en.wikipedia.org/wiki/Wikipedia:WikiProject_Women_in_Red/Missing_articles_by_dictionary/BDSW) that shows what in SKBL has an english article about a women but not have an english article in en:Wikipedia\n",
    "    * see [version history](https://en.wikipedia.org/w/index.php?title=Wikipedia:WikiProject_Women_in_Red/Missing_articles_by_dictionary/BDSW&action=history) of list created\n",
    "    * see en:Wikipedia articles [with a link to SKBL](https://en.wikipedia.org/wiki/Category:SKBL_template_using_Wikidata_property_P4963) > 680 articles using the [SKBL template](https://en.wikipedia.org/wiki/Template:SKBL)"
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    "Below we also use Wikidata to compare number of female articles produced\n",
    "* [SKBL started 2018](https://skbl.se/en/about-skbl)\n",
    "  * use a data driven approach with structured data\n",
    "  * has swedish/english articles see [MassView tool](https://pageviews.toolforge.org/massviews/?platform=all-access&agent=user&source=category&range=this-year&subjectpage=0&subcategories=0&sort=views&direction=1&view=list&target=https://en.wikipedia.org/wiki/Category:SKBL_template_using_Wikidata_property_P4963)\n",
    "     * page views in different languages for [Ingrid Bergman](https://pageviews.toolforge.org/langviews/?project=en.wikipedia.org&platform=all-access&agent=user&range=latest-20&sort=views&direction=1&view=list&page=Ingrid%20Bergman)\n",
    "* [SBL started 1917](https://sok.riksarkivet.se/sbl/Start.aspx?lang=en)\n",
    "  * publish on paper and then scan the paper and creates a webpage with no machinereadable structured data  \n",
    "\n",
    "**See also**\n",
    "* video [Introduction to Wikidata](https://www.youtube.com/watch?v=m_9_23jXPoE)"
   ]
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       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">0</h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">SBLmalefemale.png</h4><img src=\"SBLmalefemale.png\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-bGCu5SJqgfdREMeAFZJWKh\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "        <div id=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-2fj8WogfAAMnPHuUT2zQ3J\" class=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">1</h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">SKBLSBLfemale.png</h4><img src=\"SKBLSBLfemale.png\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-2fj8WogfAAMnPHuUT2zQ3J\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "        <div id=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-dBWD4kjPbmS2BrC77Tydqr\" class=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">2</h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">SKBLPiepublished.png</h4><img src=\"SKBLPiepublished.png\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-dBWD4kjPbmS2BrC77Tydqr\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "        <div id=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-cexewfvqGxiQsB5ynuK7Rk\" class=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">3</h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">SKBLBarpublished.png</h4><img src=\"SKBLBarpublished.png\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-cexewfvqGxiQsB5ynuK7Rk\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "        <div id=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-fT8XeLTgTesDR7PSebR9Xs\" class=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">4</h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">en_Wikipedia_SKBL_views-20200101-20200919.png</h4><img src=\"en_Wikipedia_SKBL_views-20200101-20200919.png\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-fT8XeLTgTesDR7PSebR9Xs\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "        <div id=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-b3zyJ9MFymjibKFbbUyRWM\" class=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">5</h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">SBL_published_articles_1918-2018.png</h4><img src=\"SBL_published_articles_1918-2018.png\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-b3zyJ9MFymjibKFbbUyRWM\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"ipyplot-placeholder-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "        <div id=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-2AnpWcbsFchFpW67Bvy4rU\" class=\"ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo\">\n",
       "            <h4 style=\"font-size: 12px; word-wrap: break-word;\">6</h4>\n",
       "            <h4 style=\"font-size: 9px; padding-left: 10px; padding-right: 10px; width: 95%; word-wrap: break-word; white-space: normal;\">SBL_published_articles_women_1918-2018.png</h4><img src=\"SBL_published_articles_women_1918-2018.png\"/>\n",
       "            <a href=\"#!\">\n",
       "                <span class=\"ipyplot-img-close\"/>\n",
       "            </a>\n",
       "            <a href=\"#ipyplot-content-div-f2hsZk8qjuuWPk82NDnKfo-2AnpWcbsFchFpW67Bvy4rU\">\n",
       "                <span class=\"ipyplot-img-expand\"/>\n",
       "            </a>\n",
       "        </div>\n",
       "    </div>\n",
       "    </div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ipyplot\n",
    "listOfImageNames = ['SBLmalefemale.png','SKBLSBLfemale.png','SKBLPiepublished.png',\n",
    "                   'SKBLBarpublished.png','en_Wikipedia_SKBL_views-20200101-20200919.png',\n",
    "                    'SBL_published_articles_1918-2018.png','SBL_published_articles_women_1918-2018.png']\n",
    "\n",
    "ipyplot.plot_images(listOfImageNames,img_width=700)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Map with [SKBL ladies](https://w.wiki/cyv) born,died,buried...\n",
    "* [Other external properties](https://w.wiki/czi) in WD on records that has the SKBL property "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import IPython \n",
    "#iframe = '<iframe width=\"900\" height=\"800\" frameborder=\"0\" scrolling=\"no\" src=\"https://w.wiki/cyv\"></iframe>'\n",
    "#IPython.display.IFrame(src=\"https://w.wiki/cyv\",width=900,height=800)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wikidata - WDSKBLtot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pip install sparqlwrapper\n",
    "# https://rdflib.github.io/sparqlwrapper/\n",
    "\n",
    "import sys,json\n",
    "import pandas as pd \n",
    "\n",
    "from SPARQLWrapper import SPARQLWrapper, JSON\n",
    "\n",
    "endpoint_url = \"https://query.wikidata.org/sparql\"\n",
    "\n",
    "querySKBL = \"\"\"SELECT (REPLACE(STR(?item), \".*Q\", \"Q\") AS ?WikidataID)  ?skblid ?en ?sv WHERE {\n",
    "?item wdt:P31 wd:Q5.\n",
    "?item wdt:P4963 ?skblid\n",
    "OPTIONAL {?en schema:about ?item;\n",
    "         schema:inLanguage \"en\";\n",
    "         schema:isPartOf <https://en.wikipedia.org/> . }\n",
    "OPTIONAL {?sv schema:about ?item;\n",
    "         schema:inLanguage \"sv\";\n",
    "         schema:isPartOf <https://sv.wikipedia.org/> . }\n",
    "} order by ?skbl\"\"\"\n",
    "\n",
    "def get_sparql_dataframe(endpoint_url, query):\n",
    "    \"\"\"\n",
    "    Helper function to convert SPARQL results into a Pandas data frame.\n",
    "    \"\"\"\n",
    "    user_agent = \"salgo60/%s.%s\" % (sys.version_info[0], sys.version_info[1])\n",
    " \n",
    "    sparql = SPARQLWrapper(endpoint_url, agent=user_agent)\n",
    "    sparql.setQuery(query)\n",
    "    sparql.setReturnFormat(JSON)\n",
    "    result = sparql.query()\n",
    "\n",
    "    processed_results = json.load(result.response)\n",
    "    cols = processed_results['head']['vars']\n",
    "\n",
    "    out = []\n",
    "    for row in processed_results['results']['bindings']:\n",
    "        item = []\n",
    "        for c in cols:\n",
    "            item.append(row.get(c, {}).get('value'))\n",
    "        out.append(item)\n",
    "\n",
    "    return pd.DataFrame(out, columns=cols)\n",
    "\n",
    "WDSKBLtot = get_sparql_dataframe(endpoint_url, querySKBL)\n",
    "WDSKBLtot[\"Source\"] = \"SKBL\" \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "WDSKBLtot.sort_index(inplace=True)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2057 entries, 0 to 2056\n",
      "Data columns (total 5 columns):\n",
      " #   Column      Non-Null Count  Dtype \n",
      "---  ------      --------------  ----- \n",
      " 0   WikidataID  2057 non-null   object\n",
      " 1   skblid      2057 non-null   object\n",
      " 2   en          1006 non-null   object\n",
      " 3   sv          1851 non-null   object\n",
      " 4   Source      2057 non-null   object\n",
      "dtypes: object(5)\n",
      "memory usage: 80.5+ KB\n"
     ]
    }
   ],
   "source": [
    "WDSKBLtot.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get SKBL records - SKBLtot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2059  antal poster\n"
     ]
    }
   ],
   "source": [
    "import urllib3, json\n",
    "import pandas as pd \n",
    "http = urllib3.PoolManager() \n",
    "\n",
    "\n",
    "  \n",
    "#Ny bättre URL    \n",
    "url = \"https://ws.spraakbanken.gu.se/ws/karp/v5/query?mode=skbl&q=extended%7C%7Cand%7Cskblstatus%7Cequals%7Cok&size=10000\"\n",
    "#r = http.request('GET', url, verify=False) \n",
    "r = http.request('GET', url) \n",
    "data = json.loads(r.data.decode('utf-8')) \n",
    "#print(type(data))\n",
    "#print(r.info())  \n",
    "\n",
    "listSKBL = []\n",
    "i = 0 \n",
    "for row in (data[\"hits\"][\"hits\"]):\n",
    "    #print (row[\"_source\"][\"url\"])\n",
    "    new_item = dict()\n",
    "    new_item['skblid'] = row[\"_source\"][\"url\"]\n",
    "   \n",
    "    try:\n",
    "        publishedDate = row[\"_source\"]['publication_date']        \n",
    "    except:\n",
    "        publishedDate =\"\"\n",
    "    new_item['publishedDate'] = publishedDate\n",
    "    try:\n",
    "        article_author_firstname = row[\"_source\"][\"article_author\"][0]['firstname']\n",
    "    except:\n",
    "        article_author_firstname =\"\"\n",
    "    new_item['article_author_firstname'] = article_author_firstname\n",
    "    try:\n",
    "        article_author_lastname = row[\"_source\"][\"article_author\"][0]['lastname']\n",
    "    except:\n",
    "        article_author_lastname =\"\"\n",
    "    new_item['article_author_lastname'] = article_author_lastname\n",
    "    try:\n",
    "        subtitle_sv = row[\"_source\"]['subtitle']\n",
    "    except:\n",
    "        subtitle_sv =\"\"\n",
    "    new_item['subtitle_sv'] = subtitle_sv\n",
    "    try:\n",
    "        name_lastname = row[\"_source\"]['name']['lastname']\n",
    "    except:\n",
    "        name_lastname = \"\"\n",
    "    new_item['name_lastname'] = name_lastname\n",
    "    try:\n",
    "        name_firstname = row[\"_source\"]['name']['firstname']\n",
    "    except:\n",
    "        name_firstname = \"\"\n",
    "    new_item['name_firstname'] = name_firstname\n",
    "    try:\n",
    "        born = row[\"_source\"][\"lifespan\"]['from']['date']['date']\n",
    "#        born = row[\"_source\"][\"name\"]\n",
    "    except:\n",
    "        born = \"\"\n",
    "    new_item['born'] = born\n",
    "    try:\n",
    "        death = row[\"_source\"][\"lifespan\"]['to']['date']['date']\n",
    "    except:\n",
    "        death = \"\"\n",
    "    new_item['death'] = death\n",
    "    try:\n",
    "        longname = row[\"_source\"][\"lifespan\"]['to']['date']['date']\n",
    "    except:\n",
    "        death = \"\"\n",
    "    new_item['death'] = death\n",
    "    try:\n",
    "        internal_comment = row[\"_source\"][\"internal_comment\"]\n",
    "    except:\n",
    "        internal_comment = \"\"\n",
    "    new_item['internal_comment'] = internal_comment\n",
    "    try:\n",
    "        civil_status = row[\"_source\"][\"civil_status\"]\n",
    "    except:\n",
    "        civil_status = \"\"\n",
    "    new_item['civil_status'] = civil_status\n",
    "\n",
    "    listSKBL.append(new_item)\n",
    "    i = i + 1 \n",
    "    #print (i)\n",
    "print (len(listSKBL) ,\" antal poster\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(type(data)) \n",
    "#print(r.info()) \n",
    "#print(data)\n",
    "#for row in (data[\"hits\"][\"hits\"]):\n",
    "    #print(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "SKBLtot = pd.DataFrame(listSKBL,\n",
    "                  columns=['skblid','publishedDate','article_author_firstname','article_author_lastname',\n",
    "                          'subtitle_sv','name_lastname','name_firstname','born','death','internal_comment','civil_status'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2059 entries, 0 to 2058\n",
      "Data columns (total 11 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   skblid                    2059 non-null   object\n",
      " 1   publishedDate             2059 non-null   object\n",
      " 2   article_author_firstname  2059 non-null   object\n",
      " 3   article_author_lastname   2059 non-null   object\n",
      " 4   subtitle_sv               2059 non-null   object\n",
      " 5   name_lastname             2059 non-null   object\n",
      " 6   name_firstname            2059 non-null   object\n",
      " 7   born                      2059 non-null   object\n",
      " 8   death                     2059 non-null   object\n",
      " 9   internal_comment          2059 non-null   object\n",
      " 10  civil_status              2059 non-null   object\n",
      "dtypes: object(11)\n",
      "memory usage: 177.1+ KB\n"
     ]
    }
   ],
   "source": [
    "SKBLtot.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#SKBLtot.sample(10) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Änka         782\n",
       "Ogift        652\n",
       "Gift         334\n",
       "Frånskild    286\n",
       "               4\n",
       "Trolovad       1\n",
       "Name: civil_status, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SKBLtot[\"civil_status\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "SKBLtot[\"publishedDate\"] = SKBLtot[\"publishedDate\"].astype(\"datetime64\")\n",
    "SKBLtot[\"Source\"] = \"SKBL\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline    \n",
    "import matplotlib.pyplot as plt   \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotPublishedAuthor = SKBLtot  \n",
    "  \n",
    "plotPublishedAuthor[\"Author\"] = plotPublishedAuthor[\"article_author_firstname\"] + \" \" + plotPublishedAuthor[\"article_author_lastname\"]   \n",
    "plotAuthor = plotPublishedAuthor[\"Author\"].value_counts()[:20]\n",
    "plotAuthor.plot( kind = 'pie') \n",
    "plt.title(\"SKBL authors -20\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotAuthor = plotPublishedAuthor[\"Author\"].value_counts()[20:50]\n",
    "plotAuthor.plot( kind = 'pie') \n",
    "plt.title(\"SKBL authors 20-50\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x2400 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.pyplot import figure\n",
    "#plotPublishedperMonth = dfSKBLAuthorcsv['publishedDate'].groupby(df['last_payout'].dt.to_period('M')).sum().plot(kind='bar')\n",
    "#plotPublishedperMonth = dfSKBLAuthorcsv['publishedDate'].groupby([dfSKBLAuthorcsv.publishedDate.year,dfSKBLAuthorcsv.publishedDate.month].agg('count'))\n",
    "plotPublishedperMonth = SKBLtot['publishedDate'].groupby(SKBLtot.publishedDate.dt.to_period(\"M\")).agg('count')\n",
    "plotPublishedperMonth.plot( kind = 'bar') \n",
    "plt.title(\"SKBL articles published per month - \")\n",
    "plt.savefig('SKBLBarpublished.png') \n",
    "figure(num=None, figsize=(20, 30), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "publishedDate\n",
       "2018-03    1008\n",
       "2020-03     254\n",
       "2020-04      47\n",
       "2020-05      71\n",
       "2020-06      51\n",
       "2020-07      11\n",
       "2020-08      22\n",
       "2020-09      67\n",
       "2020-10      70\n",
       "2020-11      89\n",
       "2020-12      60\n",
       "2021-01      82\n",
       "2021-02     112\n",
       "2021-03      93\n",
       "2021-04       5\n",
       "2021-05      11\n",
       "2021-06       2\n",
       "2021-09       1\n",
       "2021-11       2\n",
       "2022-01       1\n",
       "Freq: M, Name: publishedDate, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotPublishedperMonth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "publishedDate\n",
       "2018-03    1008\n",
       "2020-03     254\n",
       "2020-04      47\n",
       "2020-05      71\n",
       "2020-06      51\n",
       "2020-07      11\n",
       "2020-08      22\n",
       "2020-09      67\n",
       "2020-10      70\n",
       "2020-11      89\n",
       "2020-12      60\n",
       "2021-01      82\n",
       "2021-02     112\n",
       "2021-03      93\n",
       "2021-04       5\n",
       "2021-05      11\n",
       "2021-06       2\n",
       "2021-09       1\n",
       "2021-11       2\n",
       "2022-01       1\n",
       "Freq: M, Name: publishedDate, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotPublishedperMonth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1600x2400 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotPublishedperMonth2020 = SKBLtot['publishedDate'].groupby(SKBLtot.publishedDate.dt.to_period(\"M\")).agg('count')\n",
    "\n",
    "plotPublishedperMonth2020.plot( kind = 'bar') \n",
    "plt.title(\"SKBL articles published 2021 per month - \")\n",
    "plt.savefig('SKBL2020Barpublished.png') \n",
    "figure(num=None, figsize=(20, 30), dpi=80, facecolor='w', edgecolor='k')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2059"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotPublishedperMonth.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nr articles left to the goal 2000 =  -59\n"
     ]
    }
   ],
   "source": [
    "print(\"Nr articles left to the goal 2000 = \",2000- plotPublishedperMonth.sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#plotPublishedAccumalted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotPublishedperMonth.plot( kind = 'pie') \n",
    "plt.title(\"SKBL articles published per month\") \n",
    "plt.savefig('SKBLPiepublished.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_rows', None) \n",
    "# Sort latest first \n",
    "#dfSKBLAuthorcsv.sort_values(by=['publishedDate'], ascending=[False])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "both         2057\n",
       "SKBL_only       3\n",
       "Name: WD_SKBL, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import display, HTML  \n",
    "\n",
    "plotPublishedAuthor[\"Link\"] = \"<a href='https://skbl.se/sv/artikel/\" + plotPublishedAuthor['skblid'].astype(str) + \"'>SKBL web</a>\"\n",
    "plotPublishedAuthor[\"Linkjson\"] = \"<a href='https://skbl.se/sv/artikel/\" + plotPublishedAuthor['skblid'].astype(str) + \".json'>SKBL Json</a>\"\n",
    "\n",
    "# Merge plotPublishedAuthor WDSKBLtot  \n",
    "mergeSKBLWD = pd.merge(WDSKBLtot, plotPublishedAuthor,how='outer', on='skblid',indicator=True)   \n",
    "mergeSKBLWD.rename(columns={\"_merge\": \"WD_SKBL\"},inplace = True)\n",
    "mergeSKBLWD['WD_SKBL'] = mergeSKBLWD['WD_SKBL'].str.replace('left_only','WD_only').str.replace('right_only','SKBL_only')\n",
    "mergeSKBLWD[\"WD_SKBL\"].value_counts()  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2060 entries, 0 to 2059\n",
      "Data columns (total 20 columns):\n",
      " #   Column                    Non-Null Count  Dtype         \n",
      "---  ------                    --------------  -----         \n",
      " 0   WikidataID                2057 non-null   object        \n",
      " 1   skblid                    2060 non-null   object        \n",
      " 2   en                        1006 non-null   object        \n",
      " 3   sv                        1851 non-null   object        \n",
      " 4   Source_x                  2057 non-null   object        \n",
      " 5   publishedDate             2060 non-null   datetime64[ns]\n",
      " 6   article_author_firstname  2060 non-null   object        \n",
      " 7   article_author_lastname   2060 non-null   object        \n",
      " 8   subtitle_sv               2060 non-null   object        \n",
      " 9   name_lastname             2060 non-null   object        \n",
      " 10  name_firstname            2060 non-null   object        \n",
      " 11  born                      2060 non-null   object        \n",
      " 12  death                     2060 non-null   object        \n",
      " 13  internal_comment          2060 non-null   object        \n",
      " 14  civil_status              2060 non-null   object        \n",
      " 15  Source_y                  2060 non-null   object        \n",
      " 16  Author                    2060 non-null   object        \n",
      " 17  Link                      2060 non-null   object        \n",
      " 18  Linkjson                  2060 non-null   object        \n",
      " 19  WD_SKBL                   2060 non-null   object        \n",
      "dtypes: datetime64[ns](1), object(19)\n",
      "memory usage: 338.0+ KB\n"
     ]
    }
   ],
   "source": [
    "mergeSKBLWD.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Latest articles published in SKBL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "#mergeSKBLWD.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WikidataID</th>\n",
       "      <th>WD_SKBL</th>\n",
       "      <th>Wikidata</th>\n",
       "      <th>sv</th>\n",
       "      <th>Linkjson</th>\n",
       "      <th>skblid</th>\n",
       "      <th>svWikipedia</th>\n",
       "      <th>internal_comment</th>\n",
       "      <th>publishedDate</th>\n",
       "      <th>subtitle_sv</th>\n",
       "      <th>Link</th>\n",
       "      <th>en</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>SKBL_only</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/nan'>Wikidata</a></td>\n",
       "      <td>NaN</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/LisbethLarsson.json'>SKBL Json</a></td>\n",
       "      <td>LisbethLarsson</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'>svWiki</a></td>\n",
       "      <td>LÅ; ÖVRST 2022-01-24</td>\n",
       "      <td>2022-01-06</td>\n",
       "      <td>Professor, litteraturhistoriker, initiativtagare till SKBL</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/LisbethLarsson'>SKBL web</a></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>SKBL_only</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/nan'>Wikidata</a></td>\n",
       "      <td>NaN</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen.json'>SKBL Json</a></td>\n",
       "      <td>AnnaReinholdsdotterLeuhusen</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'>svWiki</a></td>\n",
       "      <td>Saknar ISNI; Porträtt saknas, LÅ; ÖVRST 2021-12-14</td>\n",
       "      <td>2021-11-14</td>\n",
       "      <td>Abbedissa</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen'>SKBL web</a></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>SKBL_only</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/nan'>Wikidata</a></td>\n",
       "      <td>NaN</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/SigridBotolfsdotter.json'>SKBL Json</a></td>\n",
       "      <td>SigridBotolfsdotter</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'>svWiki</a></td>\n",
       "      <td>Saknar ISNI, porträtt saknas, LÅ; ÖVRST 2021-12-14</td>\n",
       "      <td>2021-11-14</td>\n",
       "      <td>Abbedissa</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/SigridBotolfsdotter'>SKBL web</a></td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Q4975366</td>\n",
       "      <td>both</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q4975366'>Wikidata</a></td>\n",
       "      <td>https://sv.wikipedia.org/wiki/Anna_Roos_(1855%E2%80%931927)</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/AnnaRoos.json'>SKBL Json</a></td>\n",
       "      <td>AnnaRoos</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/Q4975366'>svWiki</a></td>\n",
       "      <td>LÅ; dåligt porträtt; ÖVRST 2021-09-17</td>\n",
       "      <td>2021-09-08</td>\n",
       "      <td>Feminist, socialarbetare, kyrkligt aktiv</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/AnnaRoos'>SKBL web</a></td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Q4954629</td>\n",
       "      <td>both</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q4954629'>Wikidata</a></td>\n",
       "      <td>https://sv.wikipedia.org/wiki/Britta_Holmstr%C3%B6m</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/BrittaHolmstrom0.json'>SKBL Json</a></td>\n",
       "      <td>BrittaHolmstrom0</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/Q4954629'>svWiki</a></td>\n",
       "      <td>LÅ; ÖVRST 2021-08-30</td>\n",
       "      <td>2021-06-30</td>\n",
       "      <td>Biståndsarbetare, filantrop, politiker</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/BrittaHolmstrom0'>SKBL web</a></td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Q107324683</td>\n",
       "      <td>both</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q107324683'>Wikidata</a></td>\n",
       "      <td>None</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/GunvorMargaretaBrinckLindroth.json'>SKBL Json</a></td>\n",
       "      <td>GunvorMargaretaBrinckLindroth</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/Q107324683'>svWiki</a></td>\n",
       "      <td>LÅ; porträtt saknas; ÖVRST 2021-06-29</td>\n",
       "      <td>2021-06-18</td>\n",
       "      <td>Forskare, entomolog</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/GunvorMargaretaBrinckLindroth'>SKBL web</a></td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Q4936740</td>\n",
       "      <td>both</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q4936740'>Wikidata</a></td>\n",
       "      <td>https://sv.wikipedia.org/wiki/Margareta_von_Ascheberg</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/MargaretavonAscheberg0.json'>SKBL Json</a></td>\n",
       "      <td>MargaretavonAscheberg0</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/Q4936740'>svWiki</a></td>\n",
       "      <td>Saknar ISNI; LÅ; ÖVRST 2021-08-05</td>\n",
       "      <td>2021-05-23</td>\n",
       "      <td>Godsägare</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/MargaretavonAscheberg0'>SKBL web</a></td>\n",
       "      <td>https://en.wikipedia.org/wiki/Margareta_von_Ascheberg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Q4945961</td>\n",
       "      <td>both</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q4945961'>Wikidata</a></td>\n",
       "      <td>https://sv.wikipedia.org/wiki/Nina_Einhorn</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/NinaEinhorn0.json'>SKBL Json</a></td>\n",
       "      <td>NinaEinhorn0</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/Q4945961'>svWiki</a></td>\n",
       "      <td>LÅ; ÖVRST 2021-08-10</td>\n",
       "      <td>2021-05-21</td>\n",
       "      <td>Läkare, forskare, Förintelseöverlevare</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/NinaEinhorn0'>SKBL web</a></td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Q20156134</td>\n",
       "      <td>both</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q20156134'>Wikidata</a></td>\n",
       "      <td>https://sv.wikipedia.org/wiki/Lil_Karhola_Wettergren</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/DagmarSigbrittLilKarholaWettergren.json'>SKBL Json</a></td>\n",
       "      <td>DagmarSigbrittLilKarholaWettergren</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/Q20156134'>svWiki</a></td>\n",
       "      <td>LÅ; ÖVRST 2021-08-26</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>Jurist, företagare, pionjär</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/DagmarSigbrittLilKarholaWettergren'>SKBL web</a></td>\n",
       "      <td>https://en.wikipedia.org/wiki/Lil_Karhola_Wettergren</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Q233319</td>\n",
       "      <td>both</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q233319'>Wikidata</a></td>\n",
       "      <td>https://sv.wikipedia.org/wiki/Maria_Eleonora_av_Brandenburg</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/MariaEleonoradrottning.json'>SKBL Json</a></td>\n",
       "      <td>MariaEleonoradrottning</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/Q233319'>svWiki</a></td>\n",
       "      <td>LÅ; ÖVRST 2021-08-11</td>\n",
       "      <td>2021-05-20</td>\n",
       "      <td>Drottning av Sverige, kurprinsessa av Brandenburg</td>\n",
       "      <td><a href='https://skbl.se/sv/artikel/MariaEleonoradrottning'>SKBL web</a></td>\n",
       "      <td>https://en.wikipedia.org/wiki/Maria_Eleonora_of_Brandenburg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# de sista 10 publiserade biografier \n",
    "mergeSKBLWD = mergeSKBLWD.sort_values(by=['publishedDate'], ascending=[False])\n",
    "mergeSKBLWD = mergeSKBLWD.reset_index(drop=True)  \n",
    "mergeSKBLWD[\"Wikidata\"] = \"<a href='https://www.wikidata.org/wiki/\" + mergeSKBLWD['WikidataID'].astype(str) + \"'>Wikidata</a>\"\n",
    "mergeSKBLWD[\"svWikipedia\"] = \"<a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/\" + mergeSKBLWD['WikidataID'].astype(str) + \"'>svWiki</a>\"\n",
    "#mergeSKBLWD[\"enWikipedia\"] = \"<a href='\" + mergeSKBLWD['en'].astype(str) + \"'>enWiki</a>\"\n",
    "\n",
    "HTML(mergeSKBLWD[{'publishedDate','internal_comment','WikidataID','Wikidata','skblid','subtitle_sv','WD_SKBL','Link','Linkjson','svWikipedia','en','sv'}][:10].to_html(escape=False))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#mergeSKBLWDOVRST = mergeSKBLWD[mergeSKBLWD[\"internal_comment\"].str.contains(\"ÖVRST\")].copy() \n",
    "#TBD filter en 20201221\n",
    "#HTML(mergeSKBLWDOVRST[{'publishedDate','internal_comment','skblid','subtitle_sv','WD_SKBL','Link','Linkjson','svWikipedia','en','sv'}][:50].to_html(escape=False))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Get öatest translated add date for ÖVRST\n",
    "#temp = mergeSKBLWD[mergeSKBLWD[\"internal_comment\"].str.contains(\"2021\")].copy() \n",
    "#HTML(temp[{'publishedDate','internal_comment','skblid','subtitle_sv','WD_SKBL','Link','Linkjson','svWikipedia','en'}][:50].to_html(escape=False))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compare SBL\n",
    "SBL started in 1918 and is published by the [National Archives](https://sok.riksarkivet.se/sbl/Start.aspx?lang=en) in Sweden. They have\n",
    "* No API\n",
    "* focus on publish on paper\n",
    "* dont have structured data\n",
    "* no understanding of [Linked data](https://vimeo.com/36752317)\n",
    "* we have before manually been adding links but also tried doing webscrabing to populate [Wikidata P3217](https://www.wikidata.org/wiki/Property_talk:P3217) now I guess we wait on SBL for delivering data as data see question asked [236883](https://phabricator.wikimedia.org/T236883) Oct 30 2019, 11:03 AM - no official answer so far and The Swedish National Archives has no helpdesk system were you get an unique helpdesk number ([some action was promised aug 2018 by Rolf Källman](https://twitter.com/salgo60/status/1030269242296414208?s=20) nothing heard)\n",
    "\n",
    "### Wikidata <-> SBL updated\n",
    "We did a NEW try getting structure from webscrabed data see [Jupyter Notebook](https://github.com/salgo60/open-data-examples/blob/master/SBL.ipynb) as SBL is non structured data we will get errors and also problem understand what is an article about a family and what is about a person.... "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# SPARQL \n",
    "querySBL = \"\"\"SELECT distinct (REPLACE(STR(?item), \".*Q\", \"Q\") AS ?WikidataID)  ?sblid  ?skblid ?genderLabel  WHERE {\n",
    "?item wdt:P31 wd:Q5.\n",
    "OPTIONAL {?item wdt:P21 ?gender}\n",
    "?item wdt:P3217 ?sblid\n",
    "OPTIONAL {?item wdt:P4963 ?skblid}\n",
    "SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\". }\n",
    "} order by ?sblid \"\"\"\n",
    "\n",
    "\n",
    "WDSBLtot = get_sparql_dataframe(endpoint_url, querySBL)\n",
    "WDSBLtot[\"Source\"] = \"SBL\" \n",
    "#WDSBLtot.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotSBLgender = WDSBLtot[\"genderLabel\"].value_counts()\n",
    "plotSBLgender.plot( kind = 'pie') \n",
    "plt.title(\"Riksarkivet SBL male/female\")\n",
    "plot = plotSBLgender.plot.pie( \\\n",
    "                   autopct='%1.0f%%', \\\n",
    "                   shadow=True, startangle=0)\n",
    "plt.title(\"SBL male vs. female articles 1918 - \" + start_time.strftime('%Y %m %d'))\n",
    "plt.savefig('SBLmalefemale.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "male                7093\n",
       "female               534\n",
       "transgender male       1\n",
       "Name: genderLabel, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotSBLgender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7628 entries, 0 to 7627\n",
      "Data columns (total 5 columns):\n",
      " #   Column       Non-Null Count  Dtype \n",
      "---  ------       --------------  ----- \n",
      " 0   WikidataID   7628 non-null   object\n",
      " 1   sblid        7628 non-null   object\n",
      " 2   skblid       392 non-null    object\n",
      " 3   genderLabel  7628 non-null   object\n",
      " 4   Source       7628 non-null   object\n",
      "dtypes: object(5)\n",
      "memory usage: 298.1+ KB\n"
     ]
    }
   ],
   "source": [
    "WDSBLtot.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>WikidataID</th>\n",
       "      <th>sblid</th>\n",
       "      <th>skblid</th>\n",
       "      <th>genderLabel</th>\n",
       "      <th>Source</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [WikidataID, sblid, skblid, genderLabel, Source]\n",
       "Index: []"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "WDSBLtot[WDSBLtot.duplicated(subset=['WikidataID'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "male                7093\n",
       "female               534\n",
       "transgender male       1\n",
       "Name: genderLabel, dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotSBLgender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "plotSBLfemale = WDSBLtot[WDSBLtot[\"genderLabel\"] == \"female\"] \n",
    "#plotSBLfemale[\"birth\"] = plotSBLfemale[\"birth\"].astype(\"datetime64\")\n",
    "#plotSBLfemale.info() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ended:  2022-02-09 16:59:25.743121\n"
     ]
    }
   ],
   "source": [
    "end = datetime.now()\n",
    "print(\"Ended: \", end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfmerge = pd.merge(plotSBLfemale, mergeSKBLWD,how='outer', on='WikidataID',indicator=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dfmerge.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "right_only    1669\n",
       "both           391\n",
       "left_only      143\n",
       "Name: _merge, dtype: int64"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfmerge[\"_merge\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# both is number in bioth SBL and SKBL   \n",
    "# right_only is SBL\n",
    "# left_only is SKBL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "dfmerge['_merge'] = dfmerge['_merge'].str.replace('left_only','SBL_only').str.replace('right_only','SKBL_only')\n",
    "dfmerge.rename(columns={\"_merge\": \"SBL_SKBL\"},inplace = True)\n",
    "\n",
    "#dfmerge[0:10]  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 2203 entries, 0 to 2202\n",
      "Data columns (total 5 columns):\n",
      " #   Column         Non-Null Count  Dtype         \n",
      "---  ------         --------------  -----         \n",
      " 0   WikidataID     2200 non-null   object        \n",
      " 1   sblid          534 non-null    object        \n",
      " 2   skblid_x       391 non-null    object        \n",
      " 3   publishedDate  2060 non-null   datetime64[ns]\n",
      " 4   SBL_SKBL       2203 non-null   object        \n",
      "dtypes: datetime64[ns](1), object(4)\n",
      "memory usage: 103.3+ KB\n"
     ]
    }
   ],
   "source": [
    "mergeCheck = dfmerge[['WikidataID', 'sblid','skblid_x','publishedDate','SBL_SKBL']] \n",
    "mergeCheck.info() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mergeCheckNumber = mergeCheck[\"SBL_SKBL\"].value_counts()\n",
    "mergeCheckNumber.plot( kind = 'pie')  \n",
    "plot = mergeCheckNumber.plot.pie( \\\n",
    "                   autopct='%1.0f%%', \\\n",
    "                   shadow=True, startangle=0)\n",
    "plt.title(\"Wikidata statistics SBL vs SKBL female articles \" + start_time.strftime('%Y %m %d'))\n",
    "plt.savefig('SKBLSBLfemale.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SKBL_only    1669\n",
       "both          391\n",
       "SBL_only      143\n",
       "Name: SBL_SKBL, dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mergeCheckNumber"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Profiles missing in SKBL that SBL has written = left_only \n",
    "WDSBLonly = mergeCheck[mergeCheck[\"SBL_SKBL\"] == \"SBL_only\"].copy() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 143 entries, 7 to 530\n",
      "Data columns (total 5 columns):\n",
      " #   Column         Non-Null Count  Dtype         \n",
      "---  ------         --------------  -----         \n",
      " 0   WikidataID     143 non-null    object        \n",
      " 1   sblid          143 non-null    object        \n",
      " 2   skblid_x       0 non-null      object        \n",
      " 3   publishedDate  0 non-null      datetime64[ns]\n",
      " 4   SBL_SKBL       143 non-null    object        \n",
      "dtypes: datetime64[ns](1), object(4)\n",
      "memory usage: 6.7+ KB\n"
     ]
    }
   ],
   "source": [
    "WDSBLonly.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WikidataID</th>\n",
       "      <th>Wikidata</th>\n",
       "      <th>sbl</th>\n",
       "      <th>sblid</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>486</th>\n",
       "      <td>Q17154110</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q17154110'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=8869'>SBL web</a></td>\n",
       "      <td>8869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>Q3292086</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q3292086'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9073'>SBL web</a></td>\n",
       "      <td>9073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>Q262305</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q262305'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9095'>SBL web</a></td>\n",
       "      <td>9095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>Q1991150</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q1991150'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9096'>SBL web</a></td>\n",
       "      <td>9096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Q4965627</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q4965627'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9101'>SBL web</a></td>\n",
       "      <td>9101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>Q622833</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q622833'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9103'>SBL web</a></td>\n",
       "      <td>9103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>Q61475</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q61475'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9105'>SBL web</a></td>\n",
       "      <td>9105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Q3847259</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q3847259'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9107'>SBL web</a></td>\n",
       "      <td>9107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>Q235438</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q235438'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9109'>SBL web</a></td>\n",
       "      <td>9109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>Q3307503</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q3307503'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9294'>SBL web</a></td>\n",
       "      <td>9294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>Q16595847</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q16595847'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9334'>SBL web</a></td>\n",
       "      <td>9334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>Q13534119</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q13534119'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9352'>SBL web</a></td>\n",
       "      <td>9352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>Q4967436</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q4967436'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9360'>SBL web</a></td>\n",
       "      <td>9360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524</th>\n",
       "      <td>Q232402</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q232402'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9718'>SBL web</a></td>\n",
       "      <td>9718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>Q16602175</td>\n",
       "      <td><a href='https://www.wikidata.org/wiki/Q16602175'>Wikidata</a></td>\n",
       "      <td><a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=9853'>SBL web</a></td>\n",
       "      <td>9853</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "WDSBLonly[\"sbl\"] = \"<a href='https://sok.riksarkivet.se/Sbl/Presentation.aspx?id=\" + WDSBLonly['sblid'].astype(str) + \"'>SBL web</a>\"\n",
    "WDSBLonly[\"Wikidata\"] = \"<a href='https://www.wikidata.org/wiki/\" + WDSBLonly['WikidataID'].astype(str) + \"'>Wikidata</a>\"\n",
    "\n",
    "pd.set_option('column_space', 20)\n",
    "pd.set_option('max_colwidth', 300)\n",
    "#List new SKBL articles not in Wikidata\n",
    "pd.set_option(\"display.max.columns\", None) \n",
    "HTML(WDSBLonly[{'WikidataID','Wikidata','sblid','sbl'}].tail(15).to_html(escape=False))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Same query in Wikidata \n",
    "* Find all women [in SBL but not in SKBL](https://w.wiki/bFw) < 190 women\n",
    "* Find all women [in SBL but not in SKBL and have an en:Wikipedia article](https://w.wiki/bFy) = 123 \n",
    "### Wikipedia articles linking SKBL \n",
    "* sv:Wikipedia [usage template Authority](https://sv.wikipedia.org/wiki/Kategori:Wikipediaartiklar_med_identifierare_fr%C3%A5n_SKBL) > 1460\n",
    "  * **[Issue 23](https://github.com/spraakbanken/skbl-portal/issues/23)** SKBL has no date when the article is  translated maybe bad \"workaround\" is check tag **text_eng** that is missing in a non translated article as [JosephineGabrielleMarcelleMeunierSainteClaire.json](https://skbl.se/sv/artikel/JosephineGabrielleMarcelleMeunierSainteClaire.json) compare translated [article](https://skbl.se/sv/artikel/JennyLind.json) and then check that all articles with **text_eng** has [template SBL](https://en.wikipedia.org/wiki/Category:SKBL_template_using_Wikidata_property_P4963)\n",
    "* en:Wikipedia [usage template SKBL](https://en.wikipedia.org/wiki/Category:SKBL_template_using_Wikidata_property_P4963) > 686 articles\n",
    "\n",
    "### Lists related to SKBL\n",
    "* en:Wikipedia [Women in Red SKBL](https://en.wikipedia.org/wiki/Wikipedia:WikiProject_Women_in_Red/Missing_articles_by_dictionary/BDSW) list with articles \"missing\" in en:Wikipedia but in SKBL\n",
    "* sv:Wikipedia [articles missing](https://w.wiki/Zun) but in SKBL\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 143 entries, 7 to 530\n",
      "Data columns (total 7 columns):\n",
      " #   Column         Non-Null Count  Dtype         \n",
      "---  ------         --------------  -----         \n",
      " 0   WikidataID     143 non-null    object        \n",
      " 1   sblid          143 non-null    object        \n",
      " 2   skblid_x       0 non-null      object        \n",
      " 3   publishedDate  0 non-null      datetime64[ns]\n",
      " 4   SBL_SKBL       143 non-null    object        \n",
      " 5   sbl            143 non-null    object        \n",
      " 6   Wikidata       143 non-null    object        \n",
      "dtypes: datetime64[ns](1), object(6)\n",
      "memory usage: 8.9+ KB\n"
     ]
    }
   ],
   "source": [
    "WDSBLonly.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SKBL_only    1669\n",
       "both          391\n",
       "SBL_only      143\n",
       "Name: SBL_SKBL, dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfmerge[\"SBL_SKBL\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "both         2057\n",
       "SKBL_only       3\n",
       "Name: WD_SKBL, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mergeSKBLWD[\"WD_SKBL\"].value_counts() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "#List new SKBL articles not in Wikidata\n",
    "mergeSKBLWD_WDOnly = mergeSKBLWD[mergeSKBLWD[\"WD_SKBL\"] == \"SKBL_only\"].copy() \n",
    "mergeSKBLWD_WDOnly[\"linkjson\"] = \"<a href='https://www.skbl.se/sv/artikel/\" + mergeSKBLWD_WDOnly[\"skblid\"].astype(str) + \".json'>json</a>\"\n",
    "mergeSKBLWD_WDOnly[\"linkhtml\"] = \"<a href='https://www.skbl.se/sv/artikel/\" + mergeSKBLWD_WDOnly[\"skblid\"].astype(str) + \"'>html</a>\"\n",
    "mergeSKBLWD_WDOnly[\"newWdref\"] = \"<a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22\" + \\\n",
    "                                  mergeSKBLWD_WDOnly[\"skblid\"].astype(str) + \"%22'>QS</a>\"\n",
    "#                                  \"%7CP1343%7C\" + mergeSKBLWD_WDOnly[\"skblid\"].astype(str) +  \"%22'>QS</a>\"\n",
    "                                  \n",
    "pd.set_option(\"display.max.columns\", None) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>WikidataID</th>\n",
       "      <th>skblid</th>\n",
       "      <th>en</th>\n",
       "      <th>sv</th>\n",
       "      <th>Source_x</th>\n",
       "      <th>publishedDate</th>\n",
       "      <th>article_author_firstname</th>\n",
       "      <th>article_author_lastname</th>\n",
       "      <th>subtitle_sv</th>\n",
       "      <th>name_lastname</th>\n",
       "      <th>name_firstname</th>\n",
       "      <th>born</th>\n",
       "      <th>death</th>\n",
       "      <th>internal_comment</th>\n",
       "      <th>civil_status</th>\n",
       "      <th>Source_y</th>\n",
       "      <th>Author</th>\n",
       "      <th>Link</th>\n",
       "      <th>Linkjson</th>\n",
       "      <th>WD_SKBL</th>\n",
       "      <th>Wikidata</th>\n",
       "      <th>svWikipedia</th>\n",
       "      <th>linkjson</th>\n",
       "      <th>linkhtml</th>\n",
       "      <th>newWdref</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>LisbethLarsson</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2022-01-06</td>\n",
       "      <td>Maria</td>\n",
       "      <td>Sjöberg</td>\n",
       "      <td>Professor, litteraturhistoriker, initiativtagare till SKBL</td>\n",
       "      <td>Larsson</td>\n",
       "      <td>/Lisbeth/ Helena</td>\n",
       "      <td>1949-05-11</td>\n",
       "      <td>2021-10-16</td>\n",
       "      <td>LÅ; ÖVRST 2022-01-24</td>\n",
       "      <td>Gift</td>\n",
       "      <td>SKBL</td>\n",
       "      <td>Maria Sjöberg</td>\n",
       "      <td>&lt;a href='https://skbl.se/sv/artikel/LisbethLarsson'&gt;SKBL web&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://skbl.se/sv/artikel/LisbethLarsson.json'&gt;SKBL Json&lt;/a&gt;</td>\n",
       "      <td>SKBL_only</td>\n",
       "      <td>&lt;a href='https://www.wikidata.org/wiki/nan'&gt;Wikidata&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'&gt;svWiki&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.skbl.se/sv/artikel/LisbethLarsson.json'&gt;json&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.skbl.se/sv/artikel/LisbethLarsson'&gt;html&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22LisbethLarsson%22'&gt;QS&lt;/a&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>AnnaReinholdsdotterLeuhusen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-11-14</td>\n",
       "      <td>Martin</td>\n",
       "      <td>Berntson</td>\n",
       "      <td>Abbedissa</td>\n",
       "      <td>Reinholdsdotter (Leuhusen)</td>\n",
       "      <td>/Anna/</td>\n",
       "      <td></td>\n",
       "      <td>1554</td>\n",
       "      <td>Saknar ISNI; Porträtt saknas, LÅ; ÖVRST 2021-12-14</td>\n",
       "      <td>Ogift</td>\n",
       "      <td>SKBL</td>\n",
       "      <td>Martin Berntson</td>\n",
       "      <td>&lt;a href='https://skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen'&gt;SKBL web&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen.json'&gt;SKBL Json&lt;/a&gt;</td>\n",
       "      <td>SKBL_only</td>\n",
       "      <td>&lt;a href='https://www.wikidata.org/wiki/nan'&gt;Wikidata&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'&gt;svWiki&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen.json'&gt;json&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen'&gt;html&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22AnnaReinholdsdotterLeuhusen%22'&gt;QS&lt;/a&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>SigridBotolfsdotter</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2021-11-14</td>\n",
       "      <td>Martin</td>\n",
       "      <td>Berntson</td>\n",
       "      <td>Abbedissa</td>\n",
       "      <td>Botolfsdotter</td>\n",
       "      <td>/Sigrid/</td>\n",
       "      <td></td>\n",
       "      <td>1538</td>\n",
       "      <td>Saknar ISNI, porträtt saknas, LÅ; ÖVRST 2021-12-14</td>\n",
       "      <td>Ogift</td>\n",
       "      <td>SKBL</td>\n",
       "      <td>Martin Berntson</td>\n",
       "      <td>&lt;a href='https://skbl.se/sv/artikel/SigridBotolfsdotter'&gt;SKBL web&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://skbl.se/sv/artikel/SigridBotolfsdotter.json'&gt;SKBL Json&lt;/a&gt;</td>\n",
       "      <td>SKBL_only</td>\n",
       "      <td>&lt;a href='https://www.wikidata.org/wiki/nan'&gt;Wikidata&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'&gt;svWiki&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.skbl.se/sv/artikel/SigridBotolfsdotter.json'&gt;json&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://www.skbl.se/sv/artikel/SigridBotolfsdotter'&gt;html&lt;/a&gt;</td>\n",
       "      <td>&lt;a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22SigridBotolfsdotter%22'&gt;QS&lt;/a&gt;</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  WikidataID                       skblid   en   sv Source_x publishedDate  \\\n",
       "0        NaN               LisbethLarsson  NaN  NaN      NaN    2022-01-06   \n",
       "1        NaN  AnnaReinholdsdotterLeuhusen  NaN  NaN      NaN    2021-11-14   \n",
       "2        NaN          SigridBotolfsdotter  NaN  NaN      NaN    2021-11-14   \n",
       "\n",
       "  article_author_firstname article_author_lastname  \\\n",
       "0                    Maria                 Sjöberg   \n",
       "1                   Martin                Berntson   \n",
       "2                   Martin                Berntson   \n",
       "\n",
       "                                                  subtitle_sv  \\\n",
       "0  Professor, litteraturhistoriker, initiativtagare till SKBL   \n",
       "1                                                   Abbedissa   \n",
       "2                                                   Abbedissa   \n",
       "\n",
       "                name_lastname    name_firstname        born       death  \\\n",
       "0                     Larsson  /Lisbeth/ Helena  1949-05-11  2021-10-16   \n",
       "1  Reinholdsdotter (Leuhusen)            /Anna/                    1554   \n",
       "2               Botolfsdotter          /Sigrid/                    1538   \n",
       "\n",
       "                                     internal_comment civil_status Source_y  \\\n",
       "0                                LÅ; ÖVRST 2022-01-24         Gift     SKBL   \n",
       "1  Saknar ISNI; Porträtt saknas, LÅ; ÖVRST 2021-12-14        Ogift     SKBL   \n",
       "2  Saknar ISNI, porträtt saknas, LÅ; ÖVRST 2021-12-14        Ogift     SKBL   \n",
       "\n",
       "            Author  \\\n",
       "0    Maria Sjöberg   \n",
       "1  Martin Berntson   \n",
       "2  Martin Berntson   \n",
       "\n",
       "                                                                            Link  \\\n",
       "0               <a href='https://skbl.se/sv/artikel/LisbethLarsson'>SKBL web</a>   \n",
       "1  <a href='https://skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen'>SKBL web</a>   \n",
       "2          <a href='https://skbl.se/sv/artikel/SigridBotolfsdotter'>SKBL web</a>   \n",
       "\n",
       "                                                                              Linkjson  \\\n",
       "0               <a href='https://skbl.se/sv/artikel/LisbethLarsson.json'>SKBL Json</a>   \n",
       "1  <a href='https://skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen.json'>SKBL Json</a>   \n",
       "2          <a href='https://skbl.se/sv/artikel/SigridBotolfsdotter.json'>SKBL Json</a>   \n",
       "\n",
       "     WD_SKBL                                                  Wikidata  \\\n",
       "0  SKBL_only  <a href='https://www.wikidata.org/wiki/nan'>Wikidata</a>   \n",
       "1  SKBL_only  <a href='https://www.wikidata.org/wiki/nan'>Wikidata</a>   \n",
       "2  SKBL_only  <a href='https://www.wikidata.org/wiki/nan'>Wikidata</a>   \n",
       "\n",
       "                                                                            svWikipedia  \\\n",
       "0  <a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'>svWiki</a>   \n",
       "1  <a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'>svWiki</a>   \n",
       "2  <a href='https://www.wikidata.org/wiki/Special:GoToLinkedPage/svwiki/nan'>svWiki</a>   \n",
       "\n",
       "                                                                             linkjson  \\\n",
       "0               <a href='https://www.skbl.se/sv/artikel/LisbethLarsson.json'>json</a>   \n",
       "1  <a href='https://www.skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen.json'>json</a>   \n",
       "2          <a href='https://www.skbl.se/sv/artikel/SigridBotolfsdotter.json'>json</a>   \n",
       "\n",
       "                                                                        linkhtml  \\\n",
       "0               <a href='https://www.skbl.se/sv/artikel/LisbethLarsson'>html</a>   \n",
       "1  <a href='https://www.skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen'>html</a>   \n",
       "2          <a href='https://www.skbl.se/sv/artikel/SigridBotolfsdotter'>html</a>   \n",
       "\n",
       "                                                                                                                                                             newWdref  \n",
       "0               <a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22LisbethLarsson%22'>QS</a>  \n",
       "1  <a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22AnnaReinholdsdotterLeuhusen%22'>QS</a>  \n",
       "2          <a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22SigridBotolfsdotter%22'>QS</a>  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mergeSKBLWD_WDOnly"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## New SKBL records\n",
    "missing in Wikidata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 25)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mergeSKBLWD_WDOnly.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WikidataID</th>\n",
       "      <th>linkhtml</th>\n",
       "      <th>linkjson</th>\n",
       "      <th>newWdref</th>\n",
       "      <th>skblid</th>\n",
       "      <th>publishedDate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td><a href='https://www.skbl.se/sv/artikel/LisbethLarsson'>html</a></td>\n",
       "      <td><a href='https://www.skbl.se/sv/artikel/LisbethLarsson.json'>json</a></td>\n",
       "      <td><a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22LisbethLarsson%22'>QS</a></td>\n",
       "      <td>LisbethLarsson</td>\n",
       "      <td>2022-01-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td><a href='https://www.skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen'>html</a></td>\n",
       "      <td><a href='https://www.skbl.se/sv/artikel/AnnaReinholdsdotterLeuhusen.json'>json</a></td>\n",
       "      <td><a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22AnnaReinholdsdotterLeuhusen%22'>QS</a></td>\n",
       "      <td>AnnaReinholdsdotterLeuhusen</td>\n",
       "      <td>2021-11-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td><a href='https://www.skbl.se/sv/artikel/SigridBotolfsdotter'>html</a></td>\n",
       "      <td><a href='https://www.skbl.se/sv/artikel/SigridBotolfsdotter.json'>json</a></td>\n",
       "      <td><a href='https://quickstatements.toolforge.org/#/v1=WDOBJEKT%7CP1343%7CQ50395049%7CP407%7CQ9027%7CP407%7CQ1860%7CS4963%7C%22SigridBotolfsdotter%22'>QS</a></td>\n",
       "      <td>SigridBotolfsdotter</td>\n",
       "      <td>2021-11-14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Display 200\n",
    "HTML(mergeSKBLWD_WDOnly[{'WikidataID','skblid','publishedDate','linkjson','linkhtml','newWdref'}].tail(200).to_html(escape=False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "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>skblid</th>\n",
       "      <th>subtitle_sv</th>\n",
       "      <th>publishedDate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LisbethLarsson</td>\n",
       "      <td>Professor, litteraturhistoriker, initiativtagare till SKBL</td>\n",
       "      <td>2022-01-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AnnaReinholdsdotterLeuhusen</td>\n",
       "      <td>Abbedissa</td>\n",
       "      <td>2021-11-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SigridBotolfsdotter</td>\n",
       "      <td>Abbedissa</td>\n",
       "      <td>2021-11-14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        skblid  \\\n",
       "0               LisbethLarsson   \n",
       "1  AnnaReinholdsdotterLeuhusen   \n",
       "2          SigridBotolfsdotter   \n",
       "\n",
       "                                                  subtitle_sv publishedDate  \n",
       "0  Professor, litteraturhistoriker, initiativtagare till SKBL    2022-01-06  \n",
       "1                                                   Abbedissa    2021-11-14  \n",
       "2                                                   Abbedissa    2021-11-14  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#SKBLtot.info() \n",
    "#SKBLtot[SKBLtot['skblid'].str.contains(\"AlmaIsabelSofiaHedin\")] \n",
    "#df['Position'].str.contains(\"PG\")\n",
    "#Missing in Wikidata    \n",
    "\n",
    "mergeSKBLWD_WDOnly[{\"skblid\",\"publishedDate\",\"subtitle_sv\"}]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "mergeSKBLWD_WDOnly[{\"skblid\",\"publishedDate\",\"subtitle_sv\"}].to_csv(\"SKBL_new.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* See latest checked [SKBL_new.csv in GITHUB](https://github.com/salgo60/open-data-examples/blob/master/SKBL_new.csv)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 25)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mergeSKBLWD_WDOnly.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ended:  2022-02-09 16:59:26.160086\n",
      "Time elapsed (hh:mm:ss.ms) 0:00:21.872048\n"
     ]
    }
   ],
   "source": [
    "end = datetime.now()\n",
    "print(\"Ended: \", end) \n",
    "print('Time elapsed (hh:mm:ss.ms) {}'.format(datetime.now() - start_time))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### more links \n",
    "  * this [Jupyter Notebook](https://github.com/salgo60/open-data-examples/blob/master/Svenskt%20Kvinnobiografiskt%20lexikon%20part%203.ipynb) [tinyurl.com/SKBLSBL](https://tinyurl.com/SKBLSBL)\n",
    "    * [part 1](https://github.com/salgo60/open-data-examples/blob/master/Svenskt%20Kvinnobiografiskt%20lexikon.ipynb) check Wikidata and SKBL - obsolete is done in this Notebook \n",
    "    * [part 2](https://github.com/salgo60/open-data-examples/blob/master/Svenskt%20Kvinnobiografiskt%20lexikon%20part%202.ipynb) more queries etc.\n",
    "    * [part 4](https://github.com/salgo60/open-data-examples/blob/master/Svenskt%20Kvinnobiografiskt%20lexikon%20part%204.ipynb) test extract archives\n",
    "    * [part 5](https://github.com/salgo60/open-data-examples/blob/master/Svenskt%20Kvinnobiografiskt%20lexikon%20part%205.ipynb) check Uppsala University Alvin\n",
    "    * [SKBL issue board](https://github.com/spraakbanken/skbl-portal/issues) on GitHub\n",
    "      * open [SKBL 23](https://github.com/spraakbanken/skbl-portal/issues/23) field when translated\n",
    "      * \n",
    "  * [Möte 2020 dec](https://phabricator.wikimedia.org/T269498)\n",
    "  "
   ]
  }
 ],
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