split_inflection_csv.ipynb

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     "text": [
      "csv 0 done!\n",
      "csv 1 done!\n",
      "csv 2 done!\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "import pandas as pd\n",
    "\n",
    "lst = dict()\n",
    "lst[0] = []\n",
    "lst[1] = []\n",
    "lst[2] = []\n",
    "\n",
    "with open('/Users/paigelee/Desktop/clancy/vis-rus/rnc_form_scrape/inflection.csv','r') as infile: \n",
    "    reader = csv.reader(infile, delimiter=\"\\t\")\n",
    "    for i, row in enumerate(reader):\n",
    "        if i < 221552:\n",
    "            lst[0].append(row)\n",
    "        elif i >= 221552 and i < 443104:\n",
    "            lst[1].append(row)\n",
    "        else:\n",
    "            lst[2].append(row)\n",
    "\n",
    "# remove first row with header names\n",
    "lst[0] = lst[0][1:]\n",
    "\n",
    "col_header = ['id',\n",
    " 'lemma_id',\n",
    " 'form',\n",
    " 'stressed',\n",
    " 'type',\n",
    " 'frequency',\n",
    " 'sharoff_freq',\n",
    " 'sharoff_rank']\n",
    "\n",
    "for index in [0,1,2]:\n",
    "    df = pd.DataFrame(lst[index]) \n",
    "    df.to_csv(f'inflection_split_{index}.csv', index=False, \n",
    "              header=col_header, sep='\\t')\n",
    "    print('csv', index, 'done!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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