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   "execution_count": 1,
   "id": "israeli-perth",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
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   "execution_count": 143,
   "id": "accurate-grill",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.plotting.backend = \"plotly\""
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   "id": "brave-marsh",
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    "vals = range(21, 25)\n",
    "indexes = [0,1,1,1]  # first file has no סמל ועדה column\n",
    "dfs = [pd.read_csv(f\"{e}.csv\", index_col=i, encoding=\"iso-8859-8\") for e, i in zip(vals, indexes)]\n",
    "\n",
    "# cleanup NaN columns\n",
    "del dfs[2][\"Unnamed: 37\"]\n",
    "del dfs[3][\"Unnamed: 46\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "ordered-executive",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['סמל ועדה', 'סמל ישוב', 'בזב', 'מצביעים', 'פסולים', 'כשרים', 'אמת', 'ב',\n",
      "       'ג', 'ודעם', 'ז', 'זץ', 'ט', 'י', 'יז', 'ינ', 'יף', 'יק', 'יר', 'כ',\n",
      "       'כך', 'כן', 'ל', 'מחל', 'מרצ', 'נ', 'ני', 'נר', 'עם', 'פה', 'ףז', 'צי',\n",
      "       'צכ', 'צף', 'ץ', 'ק', 'קי', 'קך', 'קץ', 'ר', 'רנ', 'רף', 'רק', 'שס',\n",
      "       'ת'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(dfs[3].keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "foreign-segment",
   "metadata": {},
   "outputs": [],
   "source": [
    "static_keys = [\"סמל ועדה\", \"שם ישוב\", \"בזב\", \"מצביעים\", \"פסולים\", \"כשרים\"]"
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  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "normal-theology",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "provincial-cookbook",
   "metadata": {},
   "outputs": [],
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    "df2 = dfs[2].sort_values(by=['בזב'], ascending=False)[:50]\n",
    "df3 = dfs[3].sort_values(by=['בזב'], ascending=False)[:50]"
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    "rate3 = df3[\"מצביעים\"] / df3[\"בזב\"]\n",
    "rate2 = df2[\"מצביעים\"] / df2[\"בזב\"]\n",
    "lik3 = df3[\"מחל\"] / rate3\n",
    "lik2 = df2[\"מחל\"] / rate2\n",
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    "    \"rates\": rate3 / rate2,\n",
    "    \"likud\": lik3 / lik2\n",
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    "odf.sort_values(by=\"rates\", ascending=True)[:100]\n",
    "odf.plot.scatter(x=\"rates\", y=\"likud\")"
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     },
     "metadata": {},
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    }
   ],
   "source": [
    "rate3 = df3[\"מצביעים\"] / df3[\"בזב\"]\n",
    "rate2 = df2[\"מצביעים\"] / df2[\"בזב\"]\n",
    "mesh3 = df3[\"ודעם\"] / rate3\n",
    "mesh2 = df2[\"ודעם\"] / rate2\n",
    "odf = pd.DataFrame({\n",
    "    \"rates\": rate3 / rate2,\n",
    "    \"mesh\": lik3 / lik2\n",
    "})\n",
    "odf.sort_values(by=\"rates\", ascending=True)[:100]\n",
    "odf.plot.scatter(x=\"rates\", y=\"mesh\")"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "homeless-geology",
   "metadata": {},
   "outputs": [],
   "source": []
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   "cell_type": "code",
   "execution_count": null,
   "id": "wired-clearing",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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