Contabiliza títulos citados não resolvidos por StatBiblio e NewBiblio

count-unmatches.ipynb

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   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "### 1. Configurações"
   ]
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  {
   "cell_type": "code",
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   "source": [
    "import json\n",
    "import pandas\n",
    "import os\n",
    "\n",
    "# Diretórios\n",
    "DIR_DATA = '/home/rafaeljpd/Data/'\n",
    "\n",
    "# Caminho de arquivo de citações enriquecidas\n",
    "FILE_CITED_REFS_ENRICHED = os.path.join(DIR_DATA, 'scielo/refs/via-rm/gold/regsc_rafael_v0.6c.txt')"
   ]
  },
  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "### 2. Leitura de referências citadas"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "id": "768eebfb",
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   "outputs": [],
   "source": [
    "titles = {}\n",
    "\n",
    "counter = 1\n",
    "\n",
    "with open(FILE_CITED_REFS_ENRICHED) as fin:\n",
    "    for line in fin:\n",
    "        if counter % 250000 == 0:\n",
    "            print(counter)\n",
    "        json_line = json.loads(line)\n",
    "\n",
    "        if 'sb_cited_issn' not in json_line and 'cited_issnl' not in json_line:\n",
    "            t = json_line['cited_journal']\n",
    "\n",
    "            if t:\n",
    "                if t not in titles:\n",
    "                    titles[t] = 0\n",
    "                titles[t] += 1        \n",
    "        counter += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c04e15e",
   "metadata": {},
   "source": [
    "### 3. Geração de tabela de frequência de títulos não resolvidos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "416b5773",
   "metadata": {},
   "outputs": [],
   "source": [
    "dftf = pandas.DataFrame({'Frequência': titles})\n",
    "dftf.sort_values('Frequência', ascending=False, inplace=True)\n",
    "dftf.to_csv(os.path.join(DIR_DATA_RESULTS, 'unmatches_freq.csv'), sep='|', index_label='Título citado')"
   ]
  }
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