path: root/stats.py.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 351,
   "id": "israeli-perth",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "viral-evans",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.plotting.backend = \"matplotlib\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "brave-marsh",
   "metadata": {},
   "outputs": [],
   "source": [
    "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\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "id": "ahead-monday",
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = dfs[2].sort_values(by=['בזב'], ascending=False)[:100]\n",
    "df3 = dfs[3].sort_values(by=['בזב'], ascending=False)[:100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "id": "competent-contemporary",
   "metadata": {},
   "outputs": [],
   "source": [
    "def scatter_party(p):\n",
    "    rate3 = df3[\"מצביעים\"] / df3[\"בזב\"]\n",
    "    rate2 = df2[\"מצביעים\"] / df2[\"בזב\"]\n",
    "    p3 = df3[p] / rate3\n",
    "    p2 = df2[p] / rate2\n",
    "    odf = pd.DataFrame({\n",
    "        \"votes\": rate3 / rate2,\n",
    "        \"party\": df2[p] / df2[\"מצביעים\"],\n",
    "        \"name\": df3[p]\n",
    "    })\n",
    "    odf = odf[odf[\"party\"] > 0.05]\n",
    "    g = odf.plot.scatter(y=\"votes\", x=\"party\")\n",
    "    m, c = fit_line(x=odf[\"party\"], y=odf[\"votes\"])\n",
    "    m, b = np.polyfit(odf[\"party\"], odf[\"votes\"], 1)\n",
    "    g.set_xlim(0, 1)\n",
    "    g.set_ylim(0.5, 1)\n",
    "    x = odf[\"party\"].to_numpy()\n",
    "    g.plot(x, m*x+b, color=\"red\")\n",
    "    return g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "id": "warming-afghanistan",
   "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>מחל</th>\n",
       "      <th>שס</th>\n",
       "      <th>ודעם</th>\n",
       "      <th>פה</th>\n",
       "      <th>ל</th>\n",
       "      <th>ג</th>\n",
       "      <th>אמת</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>שם ישוב</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>אום אלפחם</th>\n",
       "      <td>2.687500</td>\n",
       "      <td>1.083333</td>\n",
       "      <td>0.436388</td>\n",
       "      <td>1.200000</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.227273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>אופקים</th>\n",
       "      <td>0.761945</td>\n",
       "      <td>0.932208</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.488142</td>\n",
       "      <td>0.743292</td>\n",
       "      <td>1.028207</td>\n",
       "      <td>0.654321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>אור יהודה</th>\n",
       "      <td>0.829278</td>\n",
       "      <td>0.856481</td>\n",
       "      <td>0.562500</td>\n",
       "      <td>0.422553</td>\n",
       "      <td>0.826331</td>\n",
       "      <td>0.602041</td>\n",
       "      <td>0.824373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>אור עקיבא</th>\n",
       "      <td>0.803556</td>\n",
       "      <td>0.838681</td>\n",
       "      <td>0.083333</td>\n",
       "      <td>0.584626</td>\n",
       "      <td>0.766290</td>\n",
       "      <td>0.678832</td>\n",
       "      <td>0.994872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>אילת</th>\n",
       "      <td>0.788089</td>\n",
       "      <td>0.764416</td>\n",
       "      <td>0.379747</td>\n",
       "      <td>0.460652</td>\n",
       "      <td>0.971963</td>\n",
       "      <td>0.524324</td>\n",
       "      <td>0.984724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>רעננה</th>\n",
       "      <td>0.734019</td>\n",
       "      <td>0.875202</td>\n",
       "      <td>0.369748</td>\n",
       "      <td>0.519085</td>\n",
       "      <td>1.070635</td>\n",
       "      <td>0.661247</td>\n",
       "      <td>1.062368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>שדרות</th>\n",
       "      <td>0.761988</td>\n",
       "      <td>0.922330</td>\n",
       "      <td>0.516129</td>\n",
       "      <td>0.442543</td>\n",
       "      <td>0.695527</td>\n",
       "      <td>0.441441</td>\n",
       "      <td>0.438687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>שוהם</th>\n",
       "      <td>0.748437</td>\n",
       "      <td>0.893004</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>0.518784</td>\n",
       "      <td>1.081560</td>\n",
       "      <td>0.566667</td>\n",
       "      <td>1.092841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>שפרעם</th>\n",
       "      <td>2.181373</td>\n",
       "      <td>1.058824</td>\n",
       "      <td>0.450079</td>\n",
       "      <td>0.379784</td>\n",
       "      <td>0.957500</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.991903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>תל אביב  יפו</th>\n",
       "      <td>0.763720</td>\n",
       "      <td>0.851865</td>\n",
       "      <td>0.443705</td>\n",
       "      <td>0.450189</td>\n",
       "      <td>1.117818</td>\n",
       "      <td>0.734832</td>\n",
       "      <td>0.999278</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>101 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   מחל        שס      ודעם        פה         ל         ג  \\\n",
       "שם ישוב                                                                    \n",
       "אום אלפחם     2.687500  1.083333  0.436388  1.200000  0.750000  1.000000   \n",
       "אופקים        0.761945  0.932208  0.333333  0.488142  0.743292  1.028207   \n",
       "אור יהודה     0.829278  0.856481  0.562500  0.422553  0.826331  0.602041   \n",
       "אור עקיבא     0.803556  0.838681  0.083333  0.584626  0.766290  0.678832   \n",
       "אילת          0.788089  0.764416  0.379747  0.460652  0.971963  0.524324   \n",
       "...                ...       ...       ...       ...       ...       ...   \n",
       "רעננה         0.734019  0.875202  0.369748  0.519085  1.070635  0.661247   \n",
       "שדרות         0.761988  0.922330  0.516129  0.442543  0.695527  0.441441   \n",
       "שוהם          0.748437  0.893004  0.666667  0.518784  1.081560  0.566667   \n",
       "שפרעם         2.181373  1.058824  0.450079  0.379784  0.957500  0.500000   \n",
       "תל אביב  יפו  0.763720  0.851865  0.443705  0.450189  1.117818  0.734832   \n",
       "\n",
       "                   אמת  \n",
       "שם ישוב                 \n",
       "אום אלפחם     0.227273  \n",
       "אופקים        0.654321  \n",
       "אור יהודה     0.824373  \n",
       "אור עקיבא     0.994872  \n",
       "אילת          0.984724  \n",
       "...                ...  \n",
       "רעננה         1.062368  \n",
       "שדרות         0.438687  \n",
       "שוהם          1.092841  \n",
       "שפרעם         0.991903  \n",
       "תל אביב  יפו  0.999278  \n",
       "\n",
       "[101 rows x 7 columns]"
      ]
     },
     "execution_count": 370,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parties = [\"מחל\", \"שס\", \"ודעם\", \"פה\", \"ל\", \"ג\", \"אמת\"]\n",
    "\n",
    "rate3 = df3[\"מצביעים\"] / df3[\"בזב\"]\n",
    "rate2 = df2[\"מצביעים\"] / df2[\"בזב\"]\n",
    "\n",
    "df3[parties] / df2[parties]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "id": "romantic-position",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='party', ylabel='votes'>"
      ]
     },
     "execution_count": 359,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAEKCAYAAAAMzhLIAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8QVMy6AAAACXBIWXMAAAsTAAALEwEAmpwYAAAejUlEQVR4nO3df3xcdZ3v8ddnJmma/qDtthWwaYGFIhSkRQMo9SLgogXd1t2yUJC94lW6Vy17r6vllysIrj8oq3sVqm7hepUF+dVebWHL1ivUy0Mu7bYsbaXlV8SFpuhSQlsotGmS+dw/ziSZTGZOTiZzZk4y7+fjEZ05c+bwndPkvOf785i7IyIiUkyq2gUQEZFkU1CIiEgoBYWIiIRSUIiISCgFhYiIhFJQiIhIqNiCwsx+ZGavmtnTRV43M/uembWY2TYze09cZRERkdLFWaP4MTAv5PXzgZnZn8XAD2Isi4iIlCi2oHD3x4DXQ3ZZANzpgQ3ARDM7Mq7yiIhIaeqq+N+eBuzMed6a3fb7/B3NbDFBrYOxY8e+94QTTqhIAYeDzozz7B/eIHeCvRmccMRh1KWs5GN2dGaor0uVfAwRSZYnn3zyNXefWsp7qxkUkbn7CmAFQHNzs2/evLnKJUqOrTv3ctkdG3mzvbNn2/iGOn7ymTOYPX3ioI+3essurl61jfpUioOZDMsWnsL8OdPKWGIRqQYze6nU91YzKHYB03OeN2W3yQDa9rfTuucAY0el2Xegg0NdmT6vd2QyNE1qLOm4V6/axsGODAcJjnnVqm3MPW4Kk8c1lKXsIjL8VDMo1gBLzOxe4Axgn7v3a3aSvrq/8QMc7MjQkDa63KlPG6Pr0nRkawGlXNi3v7KPTKb/9tY9BxQUIjUstqAws3uAs4EpZtYK3ADUA7j7D4G1wAVAC/A28Km4yjJS5H7j79beFXRONNTB8k+cyknvnFDwot5dC2ma1Njv9bb97dy98WVufeR5OvKC4mBHho7OLrbu3FvwvdUW9rlEpDxiCwp3v2SA1x34fFz//ZGodc+BoO+A/l/7R6XTTGgcVfBimdvv0JHX77B6yy6uWrmV9s7iy81ffPsGxtTX9XtvtYV9LhEpH83MHkaaJjXSUahtiOL9Erm1kDfbOznYkeGqVdto29/e81pYSAB0Zeh579KVW2nb395z7K079/Ycq/txJYR9LhEpr2Ex6kkCk8c1sGzhKVyV10dhKSvaL1GoFlKfStG650DP40I1lGLaO52fbnyZGZPH9I6O6uzC3WmsYK0j7HOpCUqkvBQUw8z8OdOYe9yUnlFPbx3qCm2fL1QLya19FKuhhLltfQvgtHd6nwt19xDdSoyUGuhziUj5qOlpGJo8roHZ0ydy3OHjmT19YugFubsWMro+xfiGOkbXp3pqH/mvNdQZXzzveL7+8ZN7tqULzLdLp4y0Ff/Vya2xxCXsc4lIealGkWCljOgp9J7cWkj+sYq9Nu/kI3pqLR+99de0d/Z+e+/KOFC8XyP3m32co5Lmz5nGOyeM5rEXXuOsmVNoPmZyWY8vIgEFRUKVMqIn7D3dNYhCwl6bNHYUt1wY9IvkHhfo2Vaoj2LyuIY+5TnU1cWSc2Zy6RkzyhYY1//8N9y54WUAvvdoCxc1T2PZhXM0ZFakzMw9fMRL0tTCEh5t+9uZe/OjfeZLjK5P8fjV5xa98JX6nkIX1EKBU6jWkft+oM/rhcoD0FCX4pYLh97Z3fIfb/In//BYv+0LZh/Juh3/oSGzInnM7El3by7lvapRJFApI3oG+55itY9iy3g8fvW5/daOyq+J5D4uNuejvTMYYjtxTH3RyYFRbNm5t+D21VuDyf1agkSkfNSZnUCljOgZzHvC5iB0X+BzldI5HTbno73T+a93/Rtzb36UNVtKW95rTsQFDwdT9rjmglR6jolIudVsUCT5j7eUET3d72moSzFmVJqGuuLvCQuDcg077S1P4WXK3z7U1W+SXKF/k2L/TscdPp75s48YsBxRy756yy7m3vwol92xcUgBVqnjilRSTTY9DYelH8JGKhXj3f/rRtiopLAwyJ3Ul3t+Smm66f4MP934MretbyFtxtsdXX326Q6oX7e81u/fxCH03+nTHziWddtf7TMiqz5tGNAwiAUS41o1V6vxykhRc0ExnP54w0Yj5eu7HEdwMS72uQYKg1JCKuwzXPmhYLTT9lfe4Io7N/e5sHdkMowdle73b7J05TbyJ/Xlf56mSY1YXoUlnTIeWvKBPhMRBxoFFdcsb80el5Gi5oKi+4/3sDd386/f/yQAHak62n95BpxzFsydC+9/P/zRH1W5pIMz2IvSQGEwmJCKYvK4Bs46fmrBobZvHerqV/aUGUHdoLcGkv95Jo9r4Csfm8WND+6gPm10ZZxlC0/huMPH97wnSu0xrlneUY+r4bySdDUXFN1/vN96ZEXPtvpMJ/UbHocNjw/9P1BfDxdfDIsWwYc/HDyvgFIuduUOgygKBVTb/vZ+ZT/Q0dVvVnj+51m9ZRdfe2gH9SmjozPDDX96Up8QKFR7XLpyGxPHjOKkdx7WN3A+OosbH9xOfTpFl3tZZnlHacYbDs2gIjU5j2JNdmntJY/fy9nPPcHJv28pU+nK6KST4GMfg0sugdmzI71lzZZd/S5Kw+Wic/fGl/jyz57us60+baQsWEI9//O07W/nzG890mfl2/x5I4VuEwswpj5NBu85XvfFOm3Goa4MSz/8LhZ/8NiyfbZiNYZS5r6IlErzKAap91vtmRw5qREK3MhnwKaAt9+Ghx+G++6DBx4ofyG3bw9+br458lvmZ396/F32/8eNg2efhWkDh0a1mkFOfueEnkUOu42uS7P8E6cyoXFUv/LcvfHlfsuj5zdNFRui292hftWqbcw68rB+N4P6xsPPMrahjk+876iebUM5L8VqbuXqw2jb3872V/YB1qemJFIuNRkUUPyPN3JTwJgxsHBh8DMUL7wQBM1998G2bUM7VjH790NTU6RdJ2d/Cnrve2HTJvr1IJdB06RGuvJqtx2ZTMFJeW3721m+vn8t8FBXV5+mqe6mn7+5fwudBaZ01KdSbNm5l7pU/89z44PbmXfyEf2WIilnTa0cfSOrt+ziSw9spSN7p8O6FHznojnDpiYpw0PNzqMopCo3w5k5E667DrZuBffSft58E5Ysia+M3Z58ElKpICiG8vOLX/Q79GDmjrTuOUB9gWVtl5wzs9/+c4+bQjpV+Ne8I5NhzvSJHOrq3/xanw6+2cf5OzHUFXDb9rdz1cptPSEB0Jmhz82lRMqhZmsUhQzb4YzjxsGttwY/Jdq6cy//+3Nf5caHvlvGghXxkY8U3Fy06SzPbOBp4Nilq+lKpYFgDalLz5jRb9/WPQcYlU71GZILMCptPSOkbvjTWf36R7rcaZrUWNbmocGs3htF654DpAvUhtI2DH5nZVhRUOSo5ZvhNE1q5L45H+EnJ53Xs62kjtU33oAJE2IoYX+/vWVB3w1f77/PbOA3xQ7wDWDZMuZ99q9pff1t7vj17xhVYNRTOZqHwpquSh191jSpMbvke19dXhu/s1I5NTnqKcxwHjk0VPmf/SsfncXJ0yZUZ3z/ddfBN79Z2f9mqU48EZ56Chr6T+6Le2TTmi27+KL6KCSCoYx6UlAUUMsToLo/+9O79vG1f95RlcAMO//Fli8HGN9Qx12fOaN3ldv2dhg9ugIlLoMZM2DVKmge+O+4UBhp1JMMRMNjy6waE9GSovtzX7ziiaoscxKlmWbZwlNYunJbv36Hfk1CDQ3gXjR4Cs2z6Bc2AP/yL3D++WX/rH28/DKcdlqkXfNHpk0Gzpo2Da69Fs48E979bqjTn7aUj36bpEf3BXXfgUNV6dSPug5X38UGX+gzIS+/fGHBE7lPat48Vj/VGhpgYaHzUttbXLVyK3/+9Hq+sfrvy3Ku+tm1K/rIt+uvhxtvjKccMiIpKASg321L8/tIK9GpP5gRRrmLDYY1U4UFT9SVcqMEWFjozJ4+sWeCZ9tdf1dy2G7duZfP3fpL/mzDai57ai1H7H+9pOOwYoWCQgZFQSEFL4R1qWDI6aj00JYaH4xyr1cVJXiiDE8tduOj/AUKw0KnHM2ZTZMaaWsYy21nLuK2MxcBg+8Y72mG299es82rMngKCil4QW2sr2P5J97DhMb6inXq9/Y/bCVtKbp8aAEVNXgGuoiPHZXu13l+sCNYHh16L75zj5vC41efW7aBEPl9K0O9V4gWIJRSKSik6AW1GiNoghYvAyN7A6bSDfbCWqzT+61DXTSkjfacGdANaeOtQ10FL77dNZTuMpSi2EW91Al6w+k+LJI8Cgop613tcg12mHHvzZd6Q2uoF7OoF9aBOr0tZZATFJaygjdc+sJ9W6hL922yG+y39ih9K4M9H8N21QFJBAWFAOW9qx2U1swR18VsoAtrqZ3ehW641OXQ1ZnpCbtSgi6O81DLqw7I0CkopEe55o+U2sxRrYtZqZ3ebfvbOdTVVeywAHjGB32Bj+M8xFVrlNqgoJCyK/UbcbUuZqV2ek8e18CSc2by7f/zfNFjt3d5T6d3VHGdh3LXGqV2KCik7IbyjbiUi9lQl1wZyoX50jNmcNv6ln6zxLuNrk/1uRlTVOW6qBcaOaWAkMFSUEjZDfUb8WAuZuUa8lnqhXnyuAZuuTD4rGmzgqFQapPRUC/qGg4r5aJFASU2cS+umKR7TvcspvjKPr72UHUWU8wvT1LOjSRDYhcFNLN5wHeBNHCHu38r7/WjgB8BU4HXgcvcvTXOMknlxN3MkaQhn92ftWlSI9MnjQG84G1cKyVJ50aGv9iCwszSwHLgPKAV2GRma9x9R85ufw/c6e4/MbNzgW8CfxlXmWRkSdqQzyQ19STt3MjwFuc9s08HWtz9RXc/BNwL5N2SjFnAo9nH6wu8LhLq82cfR0OdlXTP6XKqyv3WQwz1ftwiueJsepoG7Mx53gqckbfPVuDPCZqn/gwYb2aT3b0tdyczWwwsBpgxo/99kaX25H57B2PxWX/MpWfMUFNPDg2HlXKJs0YRxZeAD5rZU8AHgV1Av2Ej7r7C3ZvdvXnq1KmVLqOUQdv+drbu3FuWb9j5397bOzMs/1VLGUpZuqQ29Uwe18Ds6RMVEjIkcdYodgHTc543Zbf1cPdXCGoUmNk4YKG7742xTFIF5W67T+K3d818lpEszqDYBMw0s2MIAmIRcGnuDmY2BXjd3TPAtQQjoGQEiWPV0qR+e1dTj4xUsTU9uXsnsARYBzwD3O/u283sJjObn93tbOA5M3seOBz4elzlkero/vafq/vbf6mS3FGrph4ZiWKdR+Hua4G1eduuz3m8ElgZZxmkuuL69q9v7yKVU+3ObBnh4vz2X41v7+XslBcZLrTWk8RupHz7T9KEOpFKUlBIRQz3VUt1K1GpZWp6Eokgjk55keFCQSESQVKH5IpUgoJCJIIkD8kViZv6KEQiGimd8iKDpaAQGYTh3ikvUgo1PYmISCgFhYiIhFJQyLCimdEilac+Chk2NDNapDpUo5BhIWm3GhWpJQoKGRY0M1qkehQUMijV6iPQzGiR6lEfhURWzT4C3WpUpHoUFBJJElZP1cxokepQUEgk3X0E3SEBvX0Elbxga2a0SOWpj0IiUR+BSO1SUEgkSVs9VRPvRCpHTU8SWVL6CDTxTqSyFBQyKNXuI0hCp7pIrVHTkwwrmngnUnkKChlW1KkuUnkKChlWktapLlIL1Echw05SOtVFaoWCQoalaneqi9QSNT2JiEgoBYWIiIRSUIiISCgFhYiIhFJQiIhIKAWFiIiEUlCIiEioWIPCzOaZ2XNm1mJm1xR4fYaZrTezp8xsm5ldEGd5RERk8GILCjNLA8uB84FZwCVmNitvt78F7nf3U4FFwPfjKo+IiJQmzhrF6UCLu7/o7oeAe4EFefs4cFj28QTglRjLIyIiJYgzKKYBO3Oet2a35foqcJmZtQJrgSsLHcjMFpvZZjPbvHv37jjKKiIiRVS7M/sS4Mfu3gRcAPyTmfUrk7uvcPdmd2+eOnVqxQspIlLL4gyKXcD0nOdN2W25Pg3cD+DuTwCjgSkxlklERAYpzqDYBMw0s2PMbBRBZ/WavH1eBj4EYGYnEgSF2pZERBIktqBw905gCbAOeIZgdNN2M7vJzOZnd/sicIWZbQXuAS53d4+rTCIiMnix3o/C3dcSdFLnbrs+5/EOYG6cZRARkaGpdme2iIgknIJCRERCKShERCSUgkJEREIpKEREJNSAQWFmc81sbPbxZWb2HTM7Kv6iiYhIEkSpUfwAeNvMZhPMe/gtcGespRIRkcSIEhSd2UlwC4Db3H05MD7eYomISFJEmXD3ppldC/wl8J+yi/bVx1ssERFJiig1iouBduC/uPsfCBb3uyXWUomISGIMGBTZcFgFNGQ3vQb8LM5CiYhIckQZ9XQFsBL4x+ymacDPYyyTiIgkSJSmp88TLNz3BoC7vwC8I85CiYhIckQJivbsPa8BMLM6gntdi4hIDYgSFP/XzK4DGs3sPOAB4MF4iyUiIkkRJSiuIbjr3G+AvwLWuvuXYy2ViIgkRpR5FFe6+3eB27s3mNl/y24TEZERLkqN4pMFtl1e5nKIiEhCFa1RmNklwKXAMWa2Juelw4DX4y6YiIgkQ1jT0/8Dfg9MAb6ds/1NYFuchRIRkeQoGhTu/hLwEvB+MzscOC370jPu3lmJwomISPVFmZn9F8C/An8BXARsNLML4y6YiIgkQ5RRT38LnOburwKY2VTglwTLeoiIyAgXZdRTqjskstoivk9EREaAKDWKh81sHXBP9vnFwNr4iiQiIkkSJSheBe4C5mSfr3B3LTMuIlIjojQhjSVYxuN04HcEw2ZFRKRGRLlx0Y3ufhLBcuNHEiwS+MvYSyYiIokwmE7pV4E/EHRm634UIiI1Iso8is+Z2a+AR4DJwBXufkrcBRMRkWSI0pk9Hfjv7r4l5rJUVNv+dlr3HKBpUiOTxzUM/AYRkRo1YFC4+7WVKEglrd6yi6tXbaM+laIjk2HZwlOYP2datYslIpJINTdxrm1/O1ev2sbBjgxvtndysCPDVau20ba/vdpFExFJpJoLitY9B6hP9f3Y9akUrXsOVKlEIiLJVnNB0TSpkY5Mps+2jkyGpkmNVSqRiEiyxRoUZjbPzJ4zsxYzu6bA6/9gZluyP8+b2d44ywMweVwDyxaewuj6FOMb6hhdn2LZwlPUoS0iUkSUUU8lMbM0sBw4D2gFNpnZGnff0b2Pu38hZ/8rgVPjKk+u+XOmMfe4KRr1JCISQWxBQbDkR4u7vwhgZvcCC4AdRfa/BLghxvL0MXlcgwJCRCSCOJuepgE7c563Zrf1Y2ZHAccAjxZ5fbGZbTazzbt37y57QUVEpLikdGYvAla6e1ehF919hbs3u3vz1KlTK1w0EZHaFmdQ7CKY1d2tKbutkEX03u9CREQSJM6g2ATMNLNjzGwUQRisyd/JzE4AJgFPxFgWEREpUWxB4e6dwBJgHfAMcL+7bzezm8xsfs6ui4B73d3jKouIiJQuzlFPuPta8m6b6u7X5z3/apxlEBGRoUlKZ7aIiCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQsUaFGY2z8yeM7MWM7umyD4XmdkOM9tuZj+NszwiIjJ4dXEd2MzSwHLgPKAV2GRma9x9R84+M4FrgbnuvsfM3hFXeUREpDRx1ihOB1rc/UV3PwTcCyzI2+cKYLm77wFw91djLI+IiJQgzqCYBuzMed6a3ZbreOB4M3vczDaY2bxCBzKzxWa22cw27969O6biiohIIdXuzK4DZgJnA5cAt5vZxPyd3H2Fuze7e/PUqVMrW0IRkRoXZ1DsAqbnPG/KbsvVCqxx9w53/x3wPEFwiIhIQsQZFJuAmWZ2jJmNAhYBa/L2+TlBbQIzm0LQFPVijGUSEZFBii0o3L0TWAKsA54B7nf37WZ2k5nNz+62Dmgzsx3AemCpu7fFVSYRERk8c/dql2FQmpubffPmzdUuhojIsGJmT7p7cynvrXZntoiIJJyCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCSUgkJEREIpKEREJJSCQkREQikoREQklIJCRERCKShERCRUrEFhZvPM7DkzazGzawq8frmZ7TazLdmfz8RZHhERGby6uA5sZmlgOXAe0ApsMrM17r4jb9f73H1JXOUQEZGhibNGcTrQ4u4vuvsh4F5gQYz/PRERiUFsNQpgGrAz53krcEaB/Raa2VnA88AX3H1n/g5mthhYnH3abmZPl7uww9QU4LVqFyIhdC566Vz00rno9a5S3xhnUETxIHCPu7eb2V8BPwHOzd/J3VcAKwDMbLO7N1e2mMmkc9FL56KXzkUvnYteZra51PfG2fS0C5ie87wpu62Hu7e5e3v26R3Ae2Msj4iIlCDOoNgEzDSzY8xsFLAIWJO7g5kdmfN0PvBMjOUREZESxNb05O6dZrYEWAekgR+5+3YzuwnY7O5rgL82s/lAJ/A6cHmEQ6+Iq8zDkM5FL52LXjoXvXQuepV8Lszdy1kQEREZYTQzW0REQikoREQkVGKDIsLyHw1mdl/29Y1mdnQVilkREc7F35jZDjPbZmaPmNlR1ShnJQx0LnL2W2hmbmYjdmhklHNhZhdlfze2m9lPK13GSonwNzLDzNab2VPZv5MLqlHOuJnZj8zs1WJzzSzwvex52mZm74l0YHdP3A9B5/dvgT8GRgFbgVl5+3wO+GH28SKCpUCqXvYqnYtzgDHZx5+t5XOR3W888BiwAWiudrmr+HsxE3gKmJR9/o5ql7uK52IF8Nns41nAv1e73DGdi7OA9wBPF3n9AuBhwID3ARujHDepNYooy38sIJigB7AS+JCZWQXLWCkDngt3X+/ub2efbiCYszISRV0W5mvAzcDBShauwqKciyuA5e6+B8DdX61wGSslyrlw4LDs4wnAKxUsX8W4+2MEI0iLWQDc6YENwMS8aQoFJTUoCi3/Ma3YPu7eCewDJlekdJUV5Vzk+jTBN4aRaMBzka1KT3f3f65kwaogyu/F8cDxZva4mW0ws3kVK11lRTkXXwUuM7NWYC1wZWWKljiDvZ4A1V/CQ8rIzC4DmoEPVrss1WBmKeA7RJuPUwvqCJqfziaoZT5mZu92973VLFSVXAL82N2/bWbvB/7JzE5290y1CzYcJLVGMeDyH7n7mFkdQXWyrSKlq6wo5wIz+xPgy8B8710WZaQZ6FyMB04GfmVm/07QBrtmhHZoR/m9aAXWuHuHu/+OYOHNmRUqXyVFORefBu4HcPcngNEECwbWmkjXk3xJDYoBl//IPv9k9vGFwKOe7a0ZYaIshXIq8I8EITFS26FhgHPh7vvcfYq7H+3uRxP018x395IXQ0uwKH8jPyeoTWBmUwiaol6sYBkrJcq5eBn4EICZnUgQFLsrWspkWAP85+zop/cB+9z99wO9KZFNTx5t+Y//SVB9bCHovFlUvRLHJ+K5uAUYBzyQ7c9/2d3nV63QMYl4LmpCxHOxDviwme0AuoCl7j7iat0Rz8UXgdvN7AsEHduXj8QvlmZ2D8GXgynZ/pgbgHoAd/8hQf/MBUAL8DbwqUjHHYHnSkREyiipTU8iIpIQCgoREQmloBARkVAKChERCaWgEBGRUAoKkZiY2cfNbFa1yyEyVAoKkRhkVwv4OMFKpSLDmoJCpAgzO9rMnjWzu83sGTNbaWZjzOx6M9tkZk+b2YruVYvN7Fdm9j/MbDNwNTAfuMXMtpjZsWb2bznHnpn7XCTJFBQi4d4FfN/dTwTeILgPym3ufpq7nww0Ah/L2X+Uuze7+9cJlktY6u5z3P23wD4zm5Pd71PA/6rYpxAZAgWFSLid7v549vFdwAeAcyy4q+JvgHOBk3L2vy/kWHcAnzKzNHAxMGLvOCcji4JCJFz+GjcOfB+40N3fDdxOsMBct7dCjrUKOJ+gBvLkSFx3SUYmBYVIuBnZ+xcAXAr8Ovv4NTMbR7BycTFvEix9DoC7HyRYuO4HqNlJhhEFhUi454DPm9kzwCSCi/ztwNMEF/1NIe+9F1hqZk+Z2bHZbXcDGeAX8RVZpLy0eqxIEWZ2NPBQttO6XMf8EjDB3b9SrmOKxC2R96MQGYnM7GfAsQQd4CLDhmoUIiISSn0UIiISSkEhIiKhFBQiIhJKQSEiIqEUFCIiEur/A/u+noo8boXNAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_party(\"מחל\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "id": "comparable-width",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='party', ylabel='votes'>"
      ]
     },
     "execution_count": 360,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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z4L21JXUTm54kSYWmDYqIWBMRe1d/PzMi/jYiDiq/NElSJ2jmiuJzwOMRcTSVeQ8/B64otSpJUsdoJihGqpPgTgE+k5mXAvuWW5YkqVM005n9aER8AHgb8B+ri/b1l1uWJKlTNHNF8WZgGPjjzLyfyuJ+nyi1KklSx5g2KKrhcC0wPh7018A3yixKktQ5mhn19G7gGuDvq5tWAteVWJMkqYM00/T0HioL9z0CkJn/BjyrzKIkSZ2jmaAYzsxd4w8ioo/KkuCSpC7QTFD8v4j4C2BJRJwIfB34VrllSZI6RTNBcSGVu879BPgT4PrMvKjUqiRJHaOZeRTnZubfAZeNb4iIP69ukyQtcM1cUfxRg23vmOM6JEkdasoriog4A3gLcEhErK95aj/gN2UXJknqDEVNT/8C/BJYDnyqZvujwKYyi5IkdY4pgyIz7wHuAV4eEc8GXlZ96s7MHGlFcZKk9mtmZvabgH8F3gScBtwaEW8suzBJUmdoZtTTXwIvy8wHACJiBfAdKst6SJIWuGZGPfWMh0TVjiZfJ0laAJq5oviniLgB+Gr18ZuB68srSZLUSZoJigeALwPHVB+vy0yXGZekLtFME9LeVJbxOBb4BZVhs5KkLtHMjYs+kplHUllu/LlUFgn8TumVSZI6wkw6pR8A7qfSme39KCSpSzQzj+LPIuJ7wHeBZcC7M/NFZRcmSeoMzXRmrwb+W2ZuLLkWSVIHmjYoMvMDrShEktSZnDgnSSpkUEiSChkUkqRCpQZFRJwUEXdFxNaIuLDB8/8jIjZWf34WEQ+VWY8kaeaaGfU0KxHRC1wKnAgMARsiYn1mbhnfJzPfW7P/ucCLy6pHkjQ7ZV5RHAtszcy7M3MXcBVwSsH+Z7Bn4UFJUocoMyhWAttqHg9Vt00SEQcBhwA3TvH82RExGBGDDz744JwXKkmaWqd0Zp8OXJOZo42ezMx1mTmQmQMrVqxocWmS1N3KDIrtVGZ1j1tV3dbI6djsJEkdqcyg2AAcFhGHRMQiKmGwvn6niHgBsBT4YYm1SJJmqbSgyMwR4BzgBuBO4OrM3BwRF0fE2ppdTweuyswsqxZJ0uyVNjwWIDOvp+62qZn5wbrHHy6zBknS09MpndmSpA5lUEiSChkUkqRCBoUkqZBBIUkqZFBIkgoZFJKkQgaFJKmQQSFJKmRQSJIKGRSSpEIGhSSpkEEhSSpkUEiSChkUkqRCBoUkqZBBIUkqZFBIkgoZFJKkQgaFJKmQQSFJKmRQSJIKGRSSpEIGhSSpkEEhSSpkUEiSChkUkqRCBoUkqZBBIUkqZFBIkgoZFJKkQgaFJKmQQSFJKmRQSJIKlRoUEXFSRNwVEVsj4sIp9jktIrZExOaI+EqZ9UiSZq6vrDeOiF7gUuBEYAjYEBHrM3NLzT6HAR8A1mTmzoh4Vln1SJJmp8wrimOBrZl5d2buAq4CTqnb593ApZm5EyAzHyixHknSLJQZFCuBbTWPh6rbah0OHB4RN0fELRFxUqM3ioizI2IwIgYffPDBksqVJDXS7s7sPuAw4NXAGcBlEXFA/U6ZuS4zBzJzYMWKFa2tUJK6XJlBsR1YXfN4VXVbrSFgfWbuzsxfAD+jEhySpA5RZlBsAA6LiEMiYhFwOrC+bp/rqFxNEBHLqTRF3V1iTZKkGSotKDJzBDgHuAG4E7g6MzdHxMURsba62w3AjojYAtwEnJeZO8qqSZI0c5GZ7a5hRgYGBnJwcLDdZUjSvBIRt2XmwGxe2+7ObElShzMoJEmFDApJUiGDQpJUyKCQJBUyKCRJhQwKSVIhg0KSVMigkCQVMigkSYUMCklSIYNCklTIoJAkFTIoJEmFDApJUiGDQpJUyKCQJBUyKCRJhQwKSVIhg0KSVMigkCQVMigkSYUMCklSIYNCklTIoJAkFTIoJEmFDApJUiGDQpJUyKCQJBUyKCRJhQwKSVIhg0KSVMigkCQVMigkSYUMCklSoVKDIiJOioi7ImJrRFzY4Pl3RMSDEbGx+vOuMuuRJM1cX1lvHBG9wKXAicAQsCEi1mfmlrpdv5aZ55RVhyTp6SnziuJYYGtm3p2Zu4CrgFNK/DxJUglKu6IAVgLbah4PAcc12O/UiHgl8DPgvZm5rX6HiDgbOLv6cDgi7pjrYuep5cCv211Eh/BY7OGx2MNjscfvzPaFZQZFM74FfDUzhyPiT4AvASfU75SZ64B1ABExmJkDrS2zM3ks9vBY7OGx2MNjsUdEDM72tWU2PW0HVtc8XlXd9pTM3JGZw9WHXwBeWmI9kqRZKDMoNgCHRcQhEbEIOB1YX7tDRDy35uFa4M4S65EkzUJpTU+ZORIR5wA3AL3A5Zm5OSIuBgYzcz3wXyNiLTAC/AZ4RxNvva6smuchj8UeHos9PBZ7eCz2mPWxiMycy0IkSQuMM7MlSYUMCklSoY4NiiaW/1gcEV+rPn9rRBzchjJboolj8d8jYktEbIqI70bEQe2osxWmOxY1+50aERkRC3ZoZDPHIiJOq/7b2BwRX2l1ja3SxP+RAyPipoj4cfX/ycntqLNsEXF5RDww1VyzqPh09ThtioiXNPXGmdlxP1Q6v38O/AdgEXA7cETdPn8GfL76++lUlgJpe+1tOhavAZ5R/f1Pu/lYVPfbF/g+cAsw0O662/jv4jDgx8DS6uNntbvuNh6LdcCfVn8/Avj3dtdd0rF4JfAS4I4pnj8Z+CcggOOBW5t53069omhm+Y9TqEzQA7gGeG1ERAtrbJVpj0Vm3pSZj1cf3kJlzspC1OyyMB8FLgGebGVxLdbMsXg3cGlm7gTIzAdaXGOrNHMsEtiv+vv+wH0trK9lMvP7VEaQTuUU4IqsuAU4oG6aQkOdGhSNlv9YOdU+mTkCPAwsa0l1rdXMsaj1TirfGBaiaY9F9VJ6dWb+YysLa4Nm/l0cDhweETdHxC0RcVLLqmutZo7Fh4EzI2IIuB44tzWldZyZnk+A9i/hoTkUEWcCA8Cr2l1LO0RED/C3NDcfpxv0UWl+ejWVq8zvR8TvZuZD7SyqTc4AvpiZn4qIlwP/EBFHZeZYuwubDzr1imLa5T9q94mIPiqXkztaUl1rNXMsiIjfBy4C1uaeZVEWmumOxb7AUcD3IuLfqbTBrl+gHdrN/LsYAtZn5u7M/AWVhTcPa1F9rdTMsXgncDVAZv4Q2IvKgoHdpqnzSb1ODYppl/+oPv6j6u9vBG7Mam/NAtPMUigvBv6eSkgs1HZomOZYZObDmbk8Mw/OzIOp9NeszcxZL4bWwZr5P3IdlasJImI5laaou1tYY6s0cyzuBV4LEBEvpBIUD7a0ys6wHnh7dfTT8cDDmfnL6V7UkU1P2dzyH/+LyuXjViqdN6e3r+LyNHksPgHsA3y92p9/b2aubVvRJWnyWHSFJo/FDcB/iogtwChwXmYuuKvuJo/F+4DLIuK9VDq237EQv1hGxFepfDlYXu2P+RDQD5CZn6fSP3MysBV4HDirqfddgMdKkjSHOrXpSZLUIQwKSVIhg0KSVMigkCQVMigkSYUMCqkkEfGGiDii3XVIT5dBIZWgulrAG6isVCrNawaFNIWIODgifhoRV0bEnRFxTUQ8IyI+GBEbIuKOiFg3vmpxRHwvIv5nRAwCFwBrgU9ExMaIeH5E/KjmvQ+rfSx1MoNCKvY7wGcz84XAI1Tug/KZzHxZZh4FLAFeX7P/oswcyMyPUVku4bzMPCYzfw48HBHHVPc7C/jfLftTSE+DQSEV25aZN1d//zLwCuA1Ubmr4k+AE4Aja/b/WsF7fQE4KyJ6gTcDC/aOc1pYDAqpWP0aNwl8FnhjZv4ucBmVBebG/bbgva4FXkflCuS2hbjukhYmg0IqdmD1/gUAbwF+UP391xGxD5WVi6fyKJWlzwHIzCepLFz3OWx20jxiUEjF7gLeExF3AkupnOQvA+6gctLfUPDaq4DzIuLHEfH86rYrgTHg/5ZXsjS3XD1WmkJEHAx8u9ppPVfv+X5g/8z8q7l6T6lsHXk/CmkhiohvAM+n0gEuzRteUUiSCtlHIUkqZFBIkgoZFJKkQgaFJKmQQSFJKvT/AUBYweCLEJdBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_party(\"שס\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "id": "million-melbourne",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='party', ylabel='votes'>"
      ]
     },
     "execution_count": 362,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_party(\"ודעם\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "id": "precise-baker",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='party', ylabel='votes'>"
      ]
     },
     "execution_count": 363,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_party(\"פה\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "id": "danish-vanilla",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='party', ylabel='votes'>"
      ]
     },
     "execution_count": 364,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_party(\"ל\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "id": "ruled-diesel",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='party', ylabel='votes'>"
      ]
     },
     "execution_count": 365,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_party(\"ג\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "id": "acknowledged-surface",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='party', ylabel='votes'>"
      ]
     },
     "execution_count": 366,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_party(\"אמת\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}