08_combine_text.ipynb

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   "source": [
    "import pandas as pd\n",
    "import csv\n",
    "from ast import literal_eval\n",
    "import sys\n",
    "import numpy as np\n",
    "import glob"
   ]
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   "source": [
    "sc = pd.read_csv(\"data/smart_cities20240110.csv\")"
   ]
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   "source": [
    "sc = sc[sc.smart==1]"
   ]
  },
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   "outputs": [],
   "source": [
    "path = \"../hpcc/text/all\"\n",
    "file_names = glob.glob(path+\"/*.csv\")"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "file_list = []\n",
    "for file_name in file_names:\n",
    "    file = pd.read_csv(file_name, names=[\"GISJOIN\",\"text\"])\n",
    "    file_list.append(file)"
   ]
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   "outputs": [],
   "source": [
    "df = pd.concat(file_list, ignore_index=True)"
   ]
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   "outputs": [],
   "source": [
    "df = df.dropna(subset=[\"text\"]) # drop empty text"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "df = df.loc[~df.text.str.contains(\"access denied\", case=False)] # drop \"access denied\""
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "sorter = list(sc.GISJOIN)\n",
    "df.GISJOIN = df.GISJOIN.astype(\"category\")\n",
    "df.GISJOIN = df.GISJOIN.cat.set_categories(sorter)"
   ]
  },
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   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "part1 = df[:2000]\n",
    "part2 = df[2000:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "part1.to_csv(\"data/hpcc_text_part1_20240124.csv\", index=False)\n",
    "part2.to_csv(\"data/hpcc_text_part2_20240124.csv\", index=False)"
   ]
  }
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