109_prg_brn_cena.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2aabb29b-3717-4d3b-b269-2f577b750de7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "pd.set_option('display.max_columns', 100)\n",
    "pd.set_option('display.max_rows', 500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2a53f8c4-94d0-4abd-ae58-aa6e82fa2986",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_parquet(os.path.join('data','jizdenky.parquet'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8dc21043-1dcb-458c-aa7e-bf98648464af",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['odkud'].str.contains('Brno') | df['odkud'].str.contains('Praha')]\n",
    "df = df[df['kam'].str.contains('Brno') | df['kam'].str.contains('Praha')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0cd0832a-586c-4c8a-82b8-a5ca49ca0e83",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['prostredek'] != 'autobus']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "dbbd1145-8dee-49b5-9228-7e239d697765",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['prestupy'] == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5bddb1e0-30ba-40e3-8ff2-a571695a8af6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['predstih_h'] > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e8c79234-ebb4-4409-a803-bfcd1fe6e6a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['jizdni_doba'] < 180]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "99e8b3b3-0bc0-43dd-9274-7cbb7d4708e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['spoj'] = df.apply(lambda row: f\"\"\"{row['prodejce']} {row['den']} {row['odjezd'].hour:02}:{row['odjezd'].minute:02}\"\"\", axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "aaa3b20e-4c20-45b7-9087-054ecf29fdf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "nejdrazsi = df[df['predstih_h'] <= 4].groupby('spoj')['cena'].median()\n",
    "nejdrazsi = nejdrazsi[nejdrazsi >= 500].index.to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a39bfc0b-348e-472e-8582-eaf9437f59d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAioAAAG0CAYAAAActAwdAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAAA3iklEQVR4nO3dfXgU5b3/8c/mOUAIJEgeJCRpDYonoB6wSLQQnknFKFiRWgVOEbUCSgG1QFujVaBaARstrZYCghJ6qqEqgqAIykE8kBYF6kNU0CAJUYSEYEwgfH9/+GMOSxJIIJg78f26rrkuZu7vzNyT3Zv97MzurM/MTAAAAA4KaOwOAAAA1IagAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgrKDG7sDpOHr0qPbs2aOIiAj5fL7G7g4AAKgDM9PBgwcVHx+vgIC6nStpkkFlz549SkhIaOxuAACA01BQUKAOHTrUqbZJBpWIiAhJ3xxo69atG7k3AACgLkpLS5WQkOC9jtdFkwwqxy73tG7dmqACAEATU5+PbdTrw7Tz5s1T165dvYDQs2dPrVy50msfPXq0fD6f33TZZZf5baOiokITJkxQu3bt1LJlS2VmZmr37t316QYAAPiOqFdQ6dChg2bNmqUtW7Zoy5Yt6tu3r66++mrt2LHDqxk8eLAKCwu96aWXXvLbxsSJE5Wbm6ucnBxt2LBBZWVlGjJkiKqqqhrmiAAAQLPhO9NfT46KitLDDz+sMWPGaPTo0Tpw4ICWL19eY21JSYnOOeccLV68WNdff72k//tg7EsvvaRBgwbVuF5FRYUqKiq8+WPXuEpKSrj0AwBAE1FaWqrIyMh6vX6f9n1UqqqqlJOTo0OHDqlnz57e8nXr1ql9+/bq1KmTxo4dq+LiYq8tLy9Phw8f1sCBA71l8fHxSk1N1caNG2vd18yZMxUZGelNfOMHAIDvhnoHlW3btqlVq1YKDQ3VbbfdptzcXF144YWSpIyMDD399NNau3atHnnkEW3evFl9+/b1zoYUFRUpJCREbdu29dtmTEyMioqKat3n1KlTVVJS4k0FBQX17TYAAGiC6v2tn/PPP19bt27VgQMH9Oyzz2rUqFFav369LrzwQu9yjiSlpqaqe/fuSkxM1IoVKzRs2LBat2lmJ/0EcGhoqEJDQ+vbVQAA0MTV+4xKSEiIzjvvPHXv3l0zZ87URRddpEcffbTG2ri4OCUmJio/P1+SFBsbq8rKSu3fv9+vrri4WDExMafRfQAA0Jyd8W/9mJnfB12Pt2/fPhUUFCguLk6S1K1bNwUHB2vNmjVeTWFhobZv3660tLQz7QoAAGhm6nXpZ9q0acrIyFBCQoIOHjyonJwcrVu3TqtWrVJZWZmysrJ07bXXKi4uTrt27dK0adPUrl07DR06VJIUGRmpMWPGaPLkyYqOjlZUVJSmTJmiLl26qH///mflAAEAQNNVr6Cyd+9e3XTTTSosLFRkZKS6du2qVatWacCAASovL9e2bdv01FNP6cCBA4qLi1OfPn20bNkyv1vlzpkzR0FBQRo+fLjKy8vVr18/LVy4UIGBgQ1+cAAAoGk74/uoNIbT+R42AABoXN/qfVQAAADONoIKAABwFkEFAAA4i6ACAACcVe870wKNIemXK6ot2zXrykboiXuawt+mrn1srLq6Ohv7bQqPX0NqzL+h68+HxjqOs7HNhtweZ1QAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwVlBjdwBwXdIvV1RbtmvWlY3QEwD47uGMCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZ9Qoq8+bNU9euXdW6dWu1bt1aPXv21MqVK712M1NWVpbi4+MVHh6u9PR07dixw28bFRUVmjBhgtq1a6eWLVsqMzNTu3fvbpijAQAAzUq9gkqHDh00a9YsbdmyRVu2bFHfvn119dVXe2HkoYce0uzZs/XYY49p8+bNio2N1YABA3Tw4EFvGxMnTlRubq5ycnK0YcMGlZWVaciQIaqqqmrYIwMAAE1evYLKVVddpR/96Efq1KmTOnXqpAcffFCtWrXSpk2bZGaaO3eupk+frmHDhik1NVWLFi3SV199pWeeeUaSVFJSovnz5+uRRx5R//79dckll2jJkiXatm2bXnnllVr3W1FRodLSUr8JAAA0f6f9GZWqqirl5OTo0KFD6tmzp3bu3KmioiINHDjQqwkNDVXv3r21ceNGSVJeXp4OHz7sVxMfH6/U1FSvpiYzZ85UZGSkNyUkJJxutwEAQBMSVN8Vtm3bpp49e+rrr79Wq1atlJubqwsvvNALGjExMX71MTEx+uSTTyRJRUVFCgkJUdu2bavVFBUV1brPqVOnatKkSd58aWmpX1hJ+uWKauvsmnVltWVNsa4p9PHbqKurs/E3PJN9u/63+baeh65rCsfh+hhtCn/Dumoux3I2jqMx/jb1Dirnn3++tm7dqgMHDujZZ5/VqFGjtH79eq/d5/P51ZtZtWUnOlVNaGioQkND69tVAADQxNX70k9ISIjOO+88de/eXTNnztRFF12kRx99VLGxsZJU7cxIcXGxd5YlNjZWlZWV2r9/f601AAAAx5zxfVTMTBUVFUpOTlZsbKzWrFnjtVVWVmr9+vVKS0uTJHXr1k3BwcF+NYWFhdq+fbtXAwAAcEy9Lv1MmzZNGRkZSkhI0MGDB5WTk6N169Zp1apV8vl8mjhxombMmKGUlBSlpKRoxowZatGihW644QZJUmRkpMaMGaPJkycrOjpaUVFRmjJlirp06aL+/fuflQMEAABNV72Cyt69e3XTTTepsLBQkZGR6tq1q1atWqUBAwZIku6++26Vl5fr9ttv1/79+9WjRw+tXr1aERER3jbmzJmjoKAgDR8+XOXl5erXr58WLlyowMDAhj0yAADQ5NUrqMyfP/+k7T6fT1lZWcrKyqq1JiwsTNnZ2crOzq7PrgEAwHcQv/UDAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnFWvoDJz5kxdeumlioiIUPv27XXNNdfo/fff96sZPXq0fD6f33TZZZf51VRUVGjChAlq166dWrZsqczMTO3evfvMjwYAADQr9Qoq69ev17hx47Rp0yatWbNGR44c0cCBA3Xo0CG/usGDB6uwsNCbXnrpJb/2iRMnKjc3Vzk5OdqwYYPKyso0ZMgQVVVVnfkRAQCAZiOoPsWrVq3ym1+wYIHat2+vvLw89erVy1seGhqq2NjYGrdRUlKi+fPna/Hixerfv78kacmSJUpISNArr7yiQYMGVVunoqJCFRUV3nxpaWl9ug0AAJqoM/qMSklJiSQpKirKb/m6devUvn17derUSWPHjlVxcbHXlpeXp8OHD2vgwIHesvj4eKWmpmrjxo017mfmzJmKjIz0poSEhDPpNgAAaCJOO6iYmSZNmqQrrrhCqamp3vKMjAw9/fTTWrt2rR555BFt3rxZffv29c6IFBUVKSQkRG3btvXbXkxMjIqKimrc19SpU1VSUuJNBQUFp9ttAADQhNTr0s/xxo8fr3feeUcbNmzwW3799dd7/05NTVX37t2VmJioFStWaNiwYbVuz8zk8/lqbAsNDVVoaOjpdhUAADRRp3VGZcKECXr++ef12muvqUOHDietjYuLU2JiovLz8yVJsbGxqqys1P79+/3qiouLFRMTczrdAQAAzVS9goqZafz48Xruuee0du1aJScnn3Kdffv2qaCgQHFxcZKkbt26KTg4WGvWrPFqCgsLtX37dqWlpdWz+wAAoDmr16WfcePG6ZlnntE//vEPRUREeJ8piYyMVHh4uMrKypSVlaVrr71WcXFx2rVrl6ZNm6Z27dpp6NChXu2YMWM0efJkRUdHKyoqSlOmTFGXLl28bwEBAABI9Qwq8+bNkySlp6f7LV+wYIFGjx6twMBAbdu2TU899ZQOHDiguLg49enTR8uWLVNERIRXP2fOHAUFBWn48OEqLy9Xv379tHDhQgUGBp75EQEAgGajXkHFzE7aHh4erpdffvmU2wkLC1N2drays7Prs3sAAPAdw2/9AAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM6qV1CZOXOmLr30UkVERKh9+/a65ppr9P777/vVmJmysrIUHx+v8PBwpaena8eOHX41FRUVmjBhgtq1a6eWLVsqMzNTu3fvPvOjAQAAzUq9gsr69es1btw4bdq0SWvWrNGRI0c0cOBAHTp0yKt56KGHNHv2bD322GPavHmzYmNjNWDAAB08eNCrmThxonJzc5WTk6MNGzaorKxMQ4YMUVVVVcMdGQAAaPKC6lO8atUqv/kFCxaoffv2ysvLU69evWRmmjt3rqZPn65hw4ZJkhYtWqSYmBg988wzuvXWW1VSUqL58+dr8eLF6t+/vyRpyZIlSkhI0CuvvKJBgwY10KEBAICm7ow+o1JSUiJJioqKkiTt3LlTRUVFGjhwoFcTGhqq3r17a+PGjZKkvLw8HT582K8mPj5eqampXs2JKioqVFpa6jcBAIDm77SDiplp0qRJuuKKK5SamipJKioqkiTFxMT41cbExHhtRUVFCgkJUdu2bWutOdHMmTMVGRnpTQkJCafbbQAA0IScdlAZP3683nnnHS1durRam8/n85s3s2rLTnSymqlTp6qkpMSbCgoKTrfbAACgCTmtoDJhwgQ9//zzeu2119ShQwdveWxsrCRVOzNSXFzsnWWJjY1VZWWl9u/fX2vNiUJDQ9W6dWu/CQAANH/1CipmpvHjx+u5557T2rVrlZyc7NeenJys2NhYrVmzxltWWVmp9evXKy0tTZLUrVs3BQcH+9UUFhZq+/btXg0AAIBUz2/9jBs3Ts8884z+8Y9/KCIiwjtzEhkZqfDwcPl8Pk2cOFEzZsxQSkqKUlJSNGPGDLVo0UI33HCDVztmzBhNnjxZ0dHRioqK0pQpU9SlSxfvW0AAAABSPYPKvHnzJEnp6el+yxcsWKDRo0dLku6++26Vl5fr9ttv1/79+9WjRw+tXr1aERERXv2cOXMUFBSk4cOHq7y8XP369dPChQsVGBh4ZkcDAACalXoFFTM7ZY3P51NWVpaysrJqrQkLC1N2drays7Prs3sAAPAdw2/9AAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGfVO6i8/vrruuqqqxQfHy+fz6fly5f7tY8ePVo+n89vuuyyy/xqKioqNGHCBLVr104tW7ZUZmamdu/efUYHAgAAmp96B5VDhw7poosu0mOPPVZrzeDBg1VYWOhNL730kl/7xIkTlZubq5ycHG3YsEFlZWUaMmSIqqqq6n8EAACg2Qqq7woZGRnKyMg4aU1oaKhiY2NrbCspKdH8+fO1ePFi9e/fX5K0ZMkSJSQk6JVXXtGgQYPq2yUAANBMnZXPqKxbt07t27dXp06dNHbsWBUXF3tteXl5Onz4sAYOHOgti4+PV2pqqjZu3Fjj9ioqKlRaWuo3AQCA5q/Bg0pGRoaefvpprV27Vo888og2b96svn37qqKiQpJUVFSkkJAQtW3b1m+9mJgYFRUV1bjNmTNnKjIy0psSEhIautsAAMBB9b70cyrXX3+99+/U1FR1795diYmJWrFihYYNG1bremYmn89XY9vUqVM1adIkb760tJSwAgDAd8BZ/3pyXFycEhMTlZ+fL0mKjY1VZWWl9u/f71dXXFysmJiYGrcRGhqq1q1b+00AAKD5O+tBZd++fSooKFBcXJwkqVu3bgoODtaaNWu8msLCQm3fvl1paWlnuzsAAKAJqfeln7KyMn344Yfe/M6dO7V161ZFRUUpKipKWVlZuvbaaxUXF6ddu3Zp2rRpateunYYOHSpJioyM1JgxYzR58mRFR0crKipKU6ZMUZcuXbxvAQEAAEinEVS2bNmiPn36ePPHPjsyatQozZs3T9u2bdNTTz2lAwcOKC4uTn369NGyZcsUERHhrTNnzhwFBQVp+PDhKi8vV79+/bRw4UIFBgY2wCEBAIDmot5BJT09XWZWa/vLL798ym2EhYUpOztb2dnZ9d09AAD4DuG3fgAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICz6h1UXn/9dV111VWKj4+Xz+fT8uXL/drNTFlZWYqPj1d4eLjS09O1Y8cOv5qKigpNmDBB7dq1U8uWLZWZmandu3ef0YEAAIDmp95B5dChQ7rooov02GOP1dj+0EMPafbs2Xrssce0efNmxcbGasCAATp48KBXM3HiROXm5ionJ0cbNmxQWVmZhgwZoqqqqtM/EgAA0OwE1XeFjIwMZWRk1NhmZpo7d66mT5+uYcOGSZIWLVqkmJgYPfPMM7r11ltVUlKi+fPna/Hixerfv78kacmSJUpISNArr7yiQYMGncHhAACA5qRBP6Oyc+dOFRUVaeDAgd6y0NBQ9e7dWxs3bpQk5eXl6fDhw3418fHxSk1N9WpOVFFRodLSUr8JAAA0fw0aVIqKiiRJMTExfstjYmK8tqKiIoWEhKht27a11pxo5syZioyM9KaEhISG7DYAAHDUWfnWj8/n85s3s2rLTnSymqlTp6qkpMSbCgoKGqyvAADAXQ0aVGJjYyWp2pmR4uJi7yxLbGysKisrtX///lprThQaGqrWrVv7TQAAoPlr0KCSnJys2NhYrVmzxltWWVmp9evXKy0tTZLUrVs3BQcH+9UUFhZq+/btXg0AAIB0Gt/6KSsr04cffujN79y5U1u3blVUVJQ6duyoiRMnasaMGUpJSVFKSopmzJihFi1a6IYbbpAkRUZGasyYMZo8ebKio6MVFRWlKVOmqEuXLt63gAAAAKTTCCpbtmxRnz59vPlJkyZJkkaNGqWFCxfq7rvvVnl5uW6//Xbt379fPXr00OrVqxUREeGtM2fOHAUFBWn48OEqLy9Xv379tHDhQgUGBjbAIQEAgOai3kElPT1dZlZru8/nU1ZWlrKysmqtCQsLU3Z2trKzs+u7ewAA8B3Cb/0AAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZzV4UMnKypLP5/ObYmNjvXYzU1ZWluLj4xUeHq709HTt2LGjobsBAACagbNyRuU//uM/VFhY6E3btm3z2h566CHNnj1bjz32mDZv3qzY2FgNGDBABw8ePBtdAQAATdhZCSpBQUGKjY31pnPOOUfSN2dT5s6dq+nTp2vYsGFKTU3VokWL9NVXX+mZZ545G10BAABN2FkJKvn5+YqPj1dycrJGjBihjz/+WJK0c+dOFRUVaeDAgV5taGioevfurY0bN9a6vYqKCpWWlvpNAACg+WvwoNKjRw899dRTevnll/Xkk0+qqKhIaWlp2rdvn4qKiiRJMTExfuvExMR4bTWZOXOmIiMjvSkhIaGhuw0AABzU4EElIyND1157rbp06aL+/ftrxYoVkqRFixZ5NT6fz28dM6u27HhTp05VSUmJNxUUFDR0twEAgIPO+teTW7ZsqS5duig/P9/79s+JZ0+Ki4urnWU5XmhoqFq3bu03AQCA5u+sB5WKigq9++67iouLU3JysmJjY7VmzRqvvbKyUuvXr1daWtrZ7goAAGhighp6g1OmTNFVV12ljh07qri4WA888IBKS0s1atQo+Xw+TZw4UTNmzFBKSopSUlI0Y8YMtWjRQjfccENDdwUAADRxDR5Udu/erZ/85Cf64osvdM455+iyyy7Tpk2blJiYKEm6++67VV5erttvv1379+9Xjx49tHr1akVERDR0VwAAQBPX4EElJyfnpO0+n09ZWVnKyspq6F0DAIBmht/6AQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAAAgLMIKgAAwFkEFQAA4CyCCgAAcBZBBQAAOIugAgAAnEVQAQAAziKoAAAAZxFUAACAswgqAADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABnEVQAAICzCCoAAMBZBBUAAOAsggoAAHAWQQUAADiLoAIAAJxFUAEAAM5q1KDyxz/+UcnJyQoLC1O3bt30xhtvNGZ3AACAYxotqCxbtkwTJ07U9OnT9a9//Us//OEPlZGRoU8//bSxugQAABzTaEFl9uzZGjNmjG6++WZ17txZc+fOVUJCgubNm9dYXQIAAI4JaoydVlZWKi8vT7/85S/9lg8cOFAbN26sVl9RUaGKigpvvqSkRJJUWloqSTpa8VW1dY61Ha8p1jWFPrpe1xT66HpdU+hjU6xrCn10va4p9NH1um9z38dqzazGftTIGsFnn31mkux//ud//JY/+OCD1qlTp2r19957r0liYmJiYmJiagZTQUFBnTNDo5xROcbn8/nNm1m1ZZI0depUTZo0yZs/evSovvzyS0VHR3v1paWlSkhIUEFBgVq3bn3S/da1lrraud7H5lLXFProel1T6KPrdU2hj67XNYU+fht1ZqaDBw8qPj6+1vVO1ChBpV27dgoMDFRRUZHf8uLiYsXExFSrDw0NVWhoqN+yNm3a1Ljt1q1bn/LJUt9a6tzb93etrin00fW6ptBH1+uaQh9dr2sKfTzbdZGRkadc53iN8mHakJAQdevWTWvWrPFbvmbNGqWlpTVGlwAAgIMa7dLPpEmTdNNNN6l79+7q2bOnnnjiCX366ae67bbbGqtLAADAMY0WVK6//nrt27dP999/vwoLC5WamqqXXnpJiYmJp7W90NBQ3XvvvdUuEZ1JLXXu7fu7VtcU+uh6XVPoo+t1TaGPrtc1hT425t/mZHxm9fmOEAAAwLeH3/oBAADOIqgAAABnEVQAAICzCCoAAMBZBJVvGZ9dBgCg7hr1FvpnYvfu3Zo3b542btyooqIi+Xw+xcTEKC0tTbfddpsSEhIau4s1Cg0N1dtvv63OnTs3dlfqrLCwUPPmzdOGDRtUWFiowMBAJScn65prrtHo0aMVGBjY2F0EADRTTfLryRs2bFBGRoYSEhI0cOBAxcTEyMxUXFysNWvWqKCgQCtXrtTll19+ym0VFBTo3nvv1V//+leVl5crLy9PUVFRuvDCC/3qvv76a/3tb3/TyJEj9e6772rTpk3q2bOnLrjgAr333nt69NFHVVFRoRtvvFF9+/b1+22i4z366KO68cYbFR0dLUmaPXu2X/v+/fu1aNEi5efnKy4uTqNGjVJCQoL+9a9/qU2bNkpOTpYkLVmyRPPmzdOnn36qxMREjR8/XiNGjNCECRM0fPhw/fCHPzzlsWdnZ2vLli268sorNXz4cC1evFgzZ87U0aNHNWzYMN1///3aunWr+vfvr+TkZIWHh+utt97ST3/6U1VWVurll19W586d9fLLLysiIuKU+0PjOHTokJ555plqof7yyy/XT37yE7Vs2fKU29i7d6/+/Oc/6ze/+Y2kb94otGnTRq1atfKrO3z4sN5880316tVL+/bt0zvvvKOLLrpIUVFR+uKLLzR//nxVVFTouuuuO2lY/973vqeXX35ZKSkpNbYfPnxYK1as8MbJ0KFDvePYvXu3wsLC1K5dO0nSG2+8oT/96U/eWBk3bpx69uypRx55RD/+8Y/rdO+mF154QVu2bNHgwYPVs2dPrV27Vr///e+9sXLLLbdIksrLy7V06dIaQ32/fv1OuR80nuY4To7tq6ax0qSe/6f9E8iNqHv37jZx4sRa2ydOnGjdu3ev07a2bt1qAQEB9v7771tiYqL5fD4LCAiw3r172549e7y6oqIiCwgIsJUrV1pISIhFRUVZWFiYrVy50s455xzr37+/9evXz4KCguzVV181n89nF198saWnp/tNPp/PLr30UktPT7c+ffpYXFycffHFF2Zm9vHHH1tsbKzFxsbagAEDrEOHDhYZGWnvvvuuXXLJJbZ27VozM3vyySctPDzc7rjjDps3b55NnDjRWrVqZfPnz/f6n5KSYrNmzbLCwsIaj/v++++3iIgIu/baay02NtZmzZpl0dHR9sADD9iMGTPsnHPOsd/85jd2+eWXW1ZWlrfe4sWLrUePHmZm9uWXX9rFF19sd9xxh9deVlZmTzzxhI0ePdoGDx5sGRkZNnr0aHvyySetrKysTo9JUVGR3Xfffd58QUGBHTx4sFpdZWWlrV+/3pv/4osvbO3atbZv3z4zM/v8889t1qxZdt9999m///3vk+4zOTnZPvjgg1rbKysrLTc31x566CFbvHixdywFBQX2+eefe3Wvv/663XDDDXbFFVfYT3/6U9u4caOZmf3+97+3Xbt21eHozZ5//nn7zW9+46376quvWkZGhg0aNMj+/Oc/e3VfffWVzZ8/3/7rv/7LBg8ebFdeeaWNHz/eXnnlFa9mx44dFh8fb23atLGrr77abrnlFhs7dqxdffXV1qZNGzv33HNtx44dp+zTsXGyZ88eu/TSSy0gIMACAwNt5MiRfo/NsXHy1ltvWWRkpPl8Pmvbtq1t2bLFkpOTLSUlxc477zwLDw+3vLw8e/TRR2ucAgMDberUqd58z549bf/+/WZmVlxcbF26dLGQkBBLSUmxsLAw69ixo+3evdvMzHr27GkvvfSSmZktX77cAgICLDMz0+655x4bOnSoBQcH2wsvvGA+n88CAwOtf//+lpOTYxUVFTUe+7x58ywoKMi6detmrVu3tiVLllhERITdfPPNduutt1p4eLjNnTvX8vPzLTEx0aKjoy0uLs58Pp9deeWV1qNHDwsMDLTrrrvODh8+bGaME8bJ2RknZlbnsdKYz//6apJBJSwszN57771a2999910LCwszM7N//OMfJ53mzJljAQEBds0119iQIUPs888/t/z8fLvqqqssOTnZPvnkEzP7vydWz549bfr06WZmtnTpUmvbtq1NmzbN2/e0adNswIABNmPGDEtOTrZXX33Vr29BQUF+T3ifz2d79+41M7MRI0ZYenq6HTp0yMzMvv76axsyZIj9+Mc/thYtWnh9ueSSS/wGopnZ008/bRdeeKH5fD575ZVX7M4777R27dpZcHCwZWZm2gsvvGBVVVVe/fe+9z179tlnzeybwRUYGGhLlizx2p977jlvoHz00Ufe8qqqKgsODraioiIzM1u9erXFx8ebWeMNdjNrtBdG118U09PTbcSIETXur6Kiwn7yk59Yenq6vf322yedli1bZgEBATZy5Ei77LLLbPPmzbZmzRrr3r27devWzb788kvvMfH5fNa/f3+7+eabrbS01B5++GHr0KGD3Xzzzd6+x4wZY9dcc435fD7r0KGDJSUl+U0+n8/OPfdcS0pKsuTkZL9xMnbsWLv44ou9EP7FF19YWlqa/exnPzMzs4iICNu5c6eZmfXo0cNmzZrld9zZ2dl2ySWXmM/nswULFtjVV19twcHBFh0dbXfeeadt27bNr75z5872xBNPmJnZ2rVrLSwszB5//HGvfcGCBda5c2fLyMiwW2+91RtnM2fOtIyMDDMz++CDDywpKcnuvfdexgnj5KyNEzOr81hprOf/6WiSQSU5Odn++te/1tr+17/+1e9BCwgIMJ/PV+sUEBBg7du3t3feecdvO7fffrt17NjRPvroI2+wt27d2vLz883smxftoKAgy8vL89bZtm2bxcTEmJnZ//7v/1qnTp1s8uTJVllZaWYnDyo1BZtNmzZZhw4dLDo62rZs2WJmZu3bt7etW7f61X344YcWHh7ut73KykpbtmyZDRo0yAIDAy0+Pt6mTZtm+fn5Fh4e7gUfM7Pg4GDbvn27N79r1y5r0aKFJSYm2oYNG7zle/bsMZ/PZ1999ZWZme3cudMLhY012M2s0V4YXX9RDA8PP+mL3rZt27znTW3j5NjygIAAi4+Pt7feestb/+uvv7arr77aLr74Ytu3b583Ttq2beu9O6+srPTePR7zz3/+084991y75ZZb7OKLL672Tv5k46RTp0724osv+tW/9tprlpSUZGZmkZGR9vbbb5vZN2Pl2L+P+fDDD61FixZ+29y7d6/97ne/swsuuMACAgLs0ksvtSeeeMJKS0trHCvHP247d+60Fi1aWIsWLfzONlRUVFhwcLB3xnT58uWWlJTEOGGcnLVxYlb3sdJYz//T0SSDyuOPP24hISE2btw4W758ub355pu2adMmW758uY0bN85CQ0Nt3rx5ZmYWHx9vubm5tW7rX//6lwUEBFhERESNpz3Hjx9vHTp0sNdff71aUDEza9Wqld8Zh127dnkv3GZmBw8etJEjR1rXrl3tnXfeseDg4Gr/ARcXF3t9PT4smH3zJAgNDbUbb7zRxowZY2Zm1113nf3qV7/yq5sxY4Z16dLF78l3vE8++cTuvfdeS0xMtICAAEtOTraVK1ea2TcDNiAgwP72t7959StWrLCkpCS78847LTU11VauXGlr1661Pn36WHp6ule3atUq+/73v29m1miD3cwa7YXR9RfF+Ph4W758ea2PSW5ursXHx1u7du1s/vz5tmvXrhqnFStWWEBAgLVs2bLaqf/Dhw/bNddc4z3Hj9Ude2Eyqz5OPvnkE2+c5ObmWkJCgmVnZ5/08Tg2Ttq3b1/tebZr1y4LDQ01M7PMzEz75S9/aWZmgwYN8k6JH/Pkk09aSkpKrWPl9ddft1GjRlnLli2tZcuW3vg3M/vss8/M5/PZihUrvPp169ZZhw4dLD4+3u9Ny/79+83n81lpaamZfXNpNzQ0lHHCODlr4+TYY1KXsdJYz//T0SSDiplZTk6O9ejRw4KCgrzBGxQUZD169LBly5Z5dVdddZX9+te/rnU7W7du9T438tRTT9VYM27cOGvTpo0FBARY165dvRd4s2/+Uzn+utsbb7zhnc053tKlSy0mJsYCAgKqDfQuXbrYJZdcYq1atbLnnnvOb73169fbueeea5999pklJSVZr169bNKkSRYeHm5XXHGFjR071nr16mUhISG2YsWKWp98xxw9etRWr15t06dPt3POOcduvvlmS05OtqlTp1rHjh1t3rx59qc//ckSEhLsF7/4hR08eNCGDx/u/Z3T0tLs448/9rb38ssvewGnsQa7mTXaC6PrL4r33nuvRUZG2sMPP2xbt261wsJCKyoqsq1bt9rDDz9sbdu2tfvuu88GDRpkv/3tb2t83Mz+b5x06dLF/v73v1drP/a4dOzY0QICAuyCCy7wOzv44osvemfhzP7vTOExu3fvtr59+9rgwYOtsLCwxsfjRz/6kQ0dOtTatm3rXUY45s033/TOZP773/+26OhoGzlypP32t7+1Vq1a2Y033mgPPvigjRw50kJDQ23BggUWEBBw0rFSUlJiTzzxhI0bN85SUlLsgQcesB/84Ac2atQou+CCC2zlypW2atUq69Kli/3sZz+zUaNGWe/eve3dd9+1jz/+2K6//nq75JJL/B67hIQExgnj5KyNE7O6j5XGev6fjiYbVI6prKy0PXv22J49e7zLK8d7/fXX/YLFicrKymzdunU2Y8YM75RgTX7+85+bz+ezefPmVXvXcLxp06Z5Zz5OVFBQYMuXL/f7sFxWVpbftGrVKr91pkyZYiNGjDCzbwbZPffcYxdeeKGFhYVZSEiIJSYm2g033GCbN282M7OkpCTv3cLJHDlyxB544AEbMmSIdxp26dKllpCQYNHR0TZ69Gi/fpaXl9f4Qb3jNdZgN7NGe2F0/UXRzGzWrFne9fmAgADv3XhcXJz97ne/M7NvPpO0ePHiWvv35Zdf2sKFC+3uu++2gQMH1lhz+PBhy8zMtICAAMvKyrKlS5fWur1p06bZsGHD/JYdPXrUZsyYYbGxsRYYGOj3eIwePdpvOv7sn9k342TQoEHe/IcffmgjRoywiIgI741McHCwpaWleWdYTxXqjykrK7Obb77ZUlNT7bbbbrPKykp7+OGHLSQkxHw+n6Wnp9vevXtt7969dtlll3l/56SkJPvnP//pbee///u/7Q9/+APjhHFy1saJWd3HSmM9/09Hkw8qcMu3PdiPXXtvzBdGl18Uj/fxxx/bxo0bbePGjX5nxerj8OHDVlJSUmv7kSNH6vStjUOHDtnXX39dY9uWLVts7ty53mcs6qKsrMzKy8urLT969KgVFRXV+kbmTJSXl3vvzI/3wQcfVDvTeqLGeFE0a/xxcv311zepcXL82aaTOXr0qN98bePkWN2pxsmxulONk9mzZ9d5nBzbZm1j5cS6Uzl06FCdnv913d7JNMn7qMB9O3fuVFFRkSQpNjbWu/9LfRw5ckRfffWVWrduXWN7VVWVdu/eXaf7AHz11VcKDAxUaGhotba8vDxt2LBBI0eOVNu2bevUt0OHDikwMFBhYWHeMvv/9/I5evSo2rVrp+Dg4Dptqy6+/vprHT58uNr9avLz81VRUaELLrhAQUFN9v6N31mME7fHSUhISJ1u0Ol6XVPpY234nw1nRXJycrX/dI+/ud7JHF9X23++krRnzx7dd999p9yeJO3bt6/WfXfr1k3dunWrVx+//PLLanW+/3+DqNqO5WROVRcWFqawsLBqdbXd6Ol0bmTYXOokOd/HYzeNTEtLU8+ePfXee+/poYce8rtppKQ63VwyKChIn332mZ599tmT1h1Tl23WVNeyZUu99957mjx5co11aWlpOv/880+5vePr7r///tM65tPdb1BQUL1u0FlVVaVZs2Z5N+isjSt1s2fPdv5YTrzJaZ2c8TkZoI6O3ffh265rzH03dl1db2TYXOrMzPk+1vWmkQ1dZ2aNtm/X63y+ut2g0/U6M2sSfawvLv2gwTz//PMnbf/44481efJk5ebmNmhdVVVVo+3b9brMzEwdOXJECxYs0IEDBzRp0iRt375d69atU8eOHbV3717Fx8c3m7qqqioNHTrU6T726NFDffv21QMPPKCcnBzdfvvt+vnPf64HH3xQkjR9+nRt3rxZZWVlDVq3evVqpaWlNcq+Xa/r06ePnnzySf3lL3/xO/sUHByst99+2zs7NnPmTKfrmkof6+204g1Qg5Pd96Gm+z80VF1j7tv1urreyLC51JmZ832s600jG7rOzBpt367XmdXtBp1Noa6p9LE+Ak4/4gD+4uLi9Oyzz+ro0aM1Tv/85z/PSl1j7tv1uvLy8mofHnz88ceVmZmp3r1764MPPmhWdU2lj8cEBAQoLCxMbdq08ZZFRESopKTkrNY15r5drbv00kuVl5enzz//XN27d9e2bdvk8/l0Itfrmkof64OgggbTrVs3v/BwIp/PJzNr8LrG3LfrdRdccIG2bNlSrT07O1tXX321MjMzJanZ1DWFPiYlJenDDz/02t9880117NjRmy8oKFBcXFyD1zXmvl2vO6ZVq1ZatGiRpk6dqgEDBqiqqko1cb2uqfSxrvjWDxrMXXfdpUOHDtXaft555+m1115TQEBAg9Y15r5dr9u4caOWLl2qm266qVrNY489pqNHj+pPf/qThg4d2izqJDnfx5///Od+/3mnpqb61a5cuVJ9+/ZV9+7dG7ROUqPt2/W6E40YMUJXXHGF8vLyTvq1btfrmkofT4UP0wIAAGdx6QcAADiLoAIAAJxFUAEAAM4iqAAAAGcRVAB865KSkjR37tzTXn/hwoV+98PIysrSxRdffMb9Ol56eromTpzYoNsEUH8EFQBOqynUXH/99TXeQA1A88N9VACclsrKSoWEhDTKvsPDwxUeHt4o+wbw7eKMCgBJ31zqGD9+vMaPH682bdooOjpav/rVr7y7/yYlJemBBx7Q6NGjFRkZqbFjx0qSNm7cqF69eik8PFwJCQm64447/G5GV1xcrKuuukrh4eFKTk7W008/XW3fWVlZ6tixo0JDQxUfH6877rjD69Mnn3yiX/ziF/L5fN7tuE+89HPM4sWLlZSUpMjISI0YMUIHDx6s07EfOnRII0eOVKtWrRQXF6dHHnmkXn87AGcPQQWAZ9GiRQoKCtJbb72lP/zhD5ozZ47+8pe/eO0PP/ywUlNTlZeXp1//+tfatm2bBg0apGHDhumdd97RsmXLtGHDBo0fP95bZ/To0dq1a5fWrl2rv//97/rjH/+o4uJir/3vf/+75syZoz//+c/Kz8/X8uXL1aVLF0nSc889pw4dOuj+++9XYWGhCgsLa+37Rx99pOXLl+vFF1/Uiy++qPXr12vWrFl1Ou677rpLr732mnJzc7V69WqtW7dOeXl59f3zATgbzugnDQE0G71797bOnTvb0aNHvWX33HOPde7c2czMEhMT7ZprrvFb56abbrJbbrnFb9kbb7xhAQEBVl5ebu+//75Jsk2bNnnt7777rkmyOXPmmJnZI488Yp06dfJ+bfVEiYmJXu0xCxYssMjISG/+3nvvtRYtWlhpaam37K677rIePXqc8rgPHjxoISEhlpOT4y3bt2+fhYeH25133nnK9QGcXZxRAeC57LLL/H7ttGfPnsrPz/d+L6V79+5+9Xl5eVq4cKFatWrlTYMGDdLRo0e1c+dOvfvuuwoKCvJb74ILLvC7bHPdddepvLxc3/ve9zR27Fjl5ubqyJEj9e57UlKSIiIivPm4uDi/Mze1+eijj1RZWamePXt6y6KionT++efXuw8AGh5BBUCdtWzZ0m/+6NGjuvXWW7V161Zvevvtt5Wfn6/vf//73udbTvZT7wkJCXr//ff1+OOPKzw8XLfffrt69eqlw4cP16tvwcHBfvM+n09Hjx495XrGz50BTiOoAPBs2rSp2nxKSooCAwNrrP/P//xP7dixQ+edd161KSQkRJ07d9aRI0e0ZcsWb533339fBw4c8NtOeHi4MjMz9Yc//EHr1q3Tm2++qW3btkmSQkJCGuSn4mtz3nnnKTg42O/Y9+/fz9efAUcQVAB4CgoKNGnSJL3//vtaunSpsrOzdeedd9Zaf8899+jNN9/UuHHjtHXrVuXn5+v555/XhAkTJEnnn3++Bg8erLFjx+qtt95SXl6ebr75Zr+vFi9cuFDz58/X9u3b9fHHH2vx4sUKDw/3fho+KSlJr7/+uj777DN98cUXDX7MrVq10pgxY3TXXXfp1Vdf1fbt2zV69GgFBPDfI+ACRiIAz8iRI1VeXq4f/OAHGjdunCZMmKBbbrml1vquXbtq/fr1ys/P1w9/+ENdcskl+vWvf624uDivZsGCBUpISFDv3r01bNgw3XLLLWrfvr3X3qZNGz355JO6/PLL1bVrV7366qt64YUXFB0dLUm6//77tWvXLn3/+9/XOeecc1aO++GHH1avXr2UmZmp/v3764orrlC3bt3Oyr4A1I/PuEALQN/cs+Tiiy8+o1vbA0BD44wKAABwFkEFQLP26aef+n19+sTp008/bewuAjgJLv0AaNaOHDmiXbt21dqelJSkoCB+9gxwFUEFAAA4i0s/AADAWQQVAADgLIIKAABwFkEFAAA4i6ACAACcRVABAADOIqgAAABn/T88xAZckJEpKQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['prodejce'].isin(['RJ'])].groupby('predstih_d')['cena'].median().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f672112e-4605-4a30-aaee-67e42917c74d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'ČD'].groupby('predstih_d')['cena'].median().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5e3b1ca8-88b9-4b2b-80a8-42a502c89e42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ČD pá 00:03',\n",
       " 'ČD pá 22:03',\n",
       " 'ČD pá 19:44',\n",
       " 'ČD pá 18:44',\n",
       " 'ČD pá 18:03',\n",
       " 'ČD pá 17:44',\n",
       " 'ČD pá 14:03',\n",
       " 'ČD pá 15:44',\n",
       " 'ČD pá 14:44',\n",
       " 'ČD pá 16:44',\n",
       " 'ČD pá 00:40',\n",
       " 'ČD pá 16:03',\n",
       " 'ČD pá 13:44',\n",
       " 'ČD pá 21:03',\n",
       " 'ČD pá 08:03',\n",
       " 'ČD pá 11:44',\n",
       " 'ČD pá 10:44',\n",
       " 'ČD pá 10:03',\n",
       " 'ČD pá 12:44',\n",
       " 'ČD pá 08:44',\n",
       " 'ČD pá 12:03',\n",
       " 'ČD pá 09:44',\n",
       " 'ČD pá 07:44',\n",
       " 'ČD pá 06:44',\n",
       " 'ČD pá 05:44',\n",
       " 'ČD pá 04:42',\n",
       " 'ČD pá 08:39',\n",
       " 'ČD pá 12:39',\n",
       " 'ČD pá 18:39',\n",
       " 'ČD pá 17:39',\n",
       " 'ČD pá 16:39',\n",
       " 'ČD pá 14:39',\n",
       " 'ČD pá 13:39',\n",
       " 'ČD pá 15:39',\n",
       " 'ČD pá 00:29',\n",
       " 'ČD pá 03:10',\n",
       " 'ČD pá 04:26',\n",
       " 'ČD pá 19:39',\n",
       " 'ČD pá 20:39',\n",
       " 'ČD pá 10:39',\n",
       " 'ČD pá 09:39',\n",
       " 'ČD pá 11:39',\n",
       " 'ČD pá 07:39',\n",
       " 'ČD pá 06:39',\n",
       " 'ČD pá 05:39',\n",
       " 'ČD so 22:03',\n",
       " 'ČD so 21:03',\n",
       " 'ČD so 00:03',\n",
       " 'ČD so 00:40',\n",
       " 'ČD so 04:42',\n",
       " 'ČD so 10:03',\n",
       " 'ČD so 07:44',\n",
       " 'ČD so 08:03',\n",
       " 'ČD so 08:44',\n",
       " 'ČD so 05:44',\n",
       " 'ČD so 18:44',\n",
       " 'ČD so 19:44',\n",
       " 'ČD so 16:44',\n",
       " 'ČD so 06:44',\n",
       " 'ČD so 09:44',\n",
       " 'ČD so 12:03',\n",
       " 'ČD so 11:44',\n",
       " 'ČD so 12:44',\n",
       " 'ČD so 13:44',\n",
       " 'ČD so 14:03',\n",
       " 'ČD so 16:03',\n",
       " 'ČD so 14:44',\n",
       " 'ČD so 17:44',\n",
       " 'ČD so 18:03',\n",
       " 'ČD so 10:44',\n",
       " 'ČD so 15:44',\n",
       " 'ČD so 15:39',\n",
       " 'ČD so 16:39',\n",
       " 'ČD so 17:39',\n",
       " 'ČD so 18:39',\n",
       " 'ČD so 21:39',\n",
       " 'ČD so 19:39',\n",
       " 'ČD so 20:39',\n",
       " 'ČD so 05:39',\n",
       " 'ČD so 04:26',\n",
       " 'ČD so 09:39',\n",
       " 'ČD so 00:29',\n",
       " 'ČD so 03:10',\n",
       " 'ČD so 14:39',\n",
       " 'ČD so 13:39',\n",
       " 'ČD so 07:39',\n",
       " 'ČD so 08:39',\n",
       " 'ČD so 06:39',\n",
       " 'ČD so 12:39',\n",
       " 'ČD so 10:39',\n",
       " 'ČD so 11:39',\n",
       " 'ČD ne 17:44',\n",
       " 'ČD ne 14:44',\n",
       " 'ČD ne 16:03',\n",
       " 'ČD ne 16:44',\n",
       " 'ČD ne 18:03',\n",
       " 'ČD ne 15:44',\n",
       " 'ČD ne 18:44',\n",
       " 'ČD ne 19:44',\n",
       " 'ČD ne 21:03',\n",
       " 'ČD ne 12:44',\n",
       " 'ČD ne 07:44',\n",
       " 'ČD ne 14:03',\n",
       " 'ČD ne 13:44',\n",
       " 'ČD ne 12:03',\n",
       " 'ČD ne 22:03',\n",
       " 'ČD ne 05:44',\n",
       " 'ČD ne 00:40',\n",
       " 'ČD ne 00:03',\n",
       " 'ČD ne 06:44',\n",
       " 'ČD ne 08:03',\n",
       " 'ČD ne 09:44',\n",
       " 'ČD ne 10:03',\n",
       " 'ČD ne 10:44',\n",
       " 'ČD ne 11:44',\n",
       " 'ČD ne 08:44',\n",
       " 'ČD ne 09:39',\n",
       " 'ČD ne 21:39',\n",
       " 'ČD ne 16:39',\n",
       " 'ČD ne 19:39',\n",
       " 'ČD ne 20:39',\n",
       " 'ČD ne 00:29',\n",
       " 'ČD ne 06:39',\n",
       " 'ČD ne 05:39',\n",
       " 'ČD ne 03:10',\n",
       " 'ČD ne 07:39',\n",
       " 'ČD ne 18:39',\n",
       " 'ČD ne 08:39',\n",
       " 'ČD ne 10:39',\n",
       " 'ČD ne 11:39',\n",
       " 'ČD ne 12:39',\n",
       " 'ČD ne 13:39',\n",
       " 'ČD ne 15:39',\n",
       " 'ČD ne 17:39',\n",
       " 'ČD ne 14:39',\n",
       " 'ČD po 00:03',\n",
       " 'ČD po 04:42',\n",
       " 'ČD po 05:44',\n",
       " 'ČD po 10:44',\n",
       " 'ČD po 06:44',\n",
       " 'ČD po 00:40',\n",
       " 'ČD po 08:03',\n",
       " 'ČD po 08:44',\n",
       " 'ČD po 09:44',\n",
       " 'ČD po 10:03',\n",
       " 'ČD po 11:44',\n",
       " 'ČD po 07:44',\n",
       " 'ČD po 12:03',\n",
       " 'ČD po 21:03',\n",
       " 'ČD po 14:44',\n",
       " 'ČD po 12:44',\n",
       " 'ČD po 13:44',\n",
       " 'ČD po 14:03',\n",
       " 'ČD po 15:44',\n",
       " 'ČD po 16:44',\n",
       " 'ČD po 17:44',\n",
       " 'ČD po 18:03',\n",
       " 'ČD po 22:03',\n",
       " 'ČD po 18:44',\n",
       " 'ČD po 19:44',\n",
       " 'ČD po 16:03',\n",
       " 'ČD po 12:39',\n",
       " 'ČD po 18:39',\n",
       " 'ČD po 17:39',\n",
       " 'ČD po 15:39',\n",
       " 'ČD po 19:39',\n",
       " 'ČD po 14:39',\n",
       " 'ČD po 16:39',\n",
       " 'ČD po 00:29',\n",
       " 'ČD po 13:39',\n",
       " 'ČD po 04:26',\n",
       " 'ČD po 03:10',\n",
       " 'ČD po 09:39',\n",
       " 'ČD po 11:39',\n",
       " 'ČD po 08:39',\n",
       " 'ČD po 10:39',\n",
       " 'ČD po 06:39',\n",
       " 'ČD po 05:39',\n",
       " 'ČD po 07:39',\n",
       " 'ČD út 00:40',\n",
       " 'ČD út 04:42',\n",
       " 'ČD út 12:03',\n",
       " 'ČD út 21:03',\n",
       " 'ČD út 05:44',\n",
       " 'ČD út 09:44',\n",
       " 'ČD út 10:03',\n",
       " 'ČD út 10:44',\n",
       " 'ČD út 08:03',\n",
       " 'ČD út 22:03',\n",
       " 'ČD út 07:44',\n",
       " 'ČD út 08:44',\n",
       " 'ČD út 11:44',\n",
       " 'ČD út 00:03',\n",
       " 'ČD út 15:44',\n",
       " 'ČD út 14:03',\n",
       " 'ČD út 14:44',\n",
       " 'ČD út 16:03',\n",
       " 'ČD út 06:44',\n",
       " 'ČD út 13:44',\n",
       " 'ČD út 16:44',\n",
       " 'ČD út 17:44',\n",
       " 'ČD út 18:03',\n",
       " 'ČD út 18:44',\n",
       " 'ČD út 12:44',\n",
       " 'ČD út 19:44',\n",
       " 'ČD út 14:39',\n",
       " 'ČD út 00:29',\n",
       " 'ČD út 03:10',\n",
       " 'ČD út 09:39',\n",
       " 'ČD út 05:39',\n",
       " 'ČD út 07:39',\n",
       " 'ČD út 06:39',\n",
       " 'ČD út 08:39',\n",
       " 'ČD út 10:39',\n",
       " 'ČD út 04:26',\n",
       " 'ČD út 15:39',\n",
       " 'ČD út 16:39',\n",
       " 'ČD út 11:39',\n",
       " 'ČD út 12:39',\n",
       " 'ČD út 20:39',\n",
       " 'ČD út 18:39',\n",
       " 'ČD út 17:39',\n",
       " 'ČD út 13:39',\n",
       " 'ČD út 19:39',\n",
       " 'ČD st 14:44',\n",
       " 'ČD st 16:03',\n",
       " 'ČD st 04:42',\n",
       " 'ČD st 16:44',\n",
       " 'ČD st 17:44',\n",
       " 'ČD st 09:44',\n",
       " 'ČD st 05:44',\n",
       " 'ČD st 15:44',\n",
       " 'ČD st 06:44',\n",
       " 'ČD st 18:03',\n",
       " 'ČD st 10:03',\n",
       " 'ČD st 08:44',\n",
       " 'ČD st 19:44',\n",
       " 'ČD st 08:03',\n",
       " 'ČD st 00:40',\n",
       " 'ČD st 14:03',\n",
       " 'ČD st 13:44',\n",
       " 'ČD st 12:44',\n",
       " 'ČD st 07:44',\n",
       " 'ČD st 11:44',\n",
       " 'ČD st 10:44',\n",
       " 'ČD st 00:03',\n",
       " 'ČD st 22:03',\n",
       " 'ČD st 18:44',\n",
       " 'ČD st 21:03',\n",
       " 'ČD st 12:03',\n",
       " 'ČD st 09:39',\n",
       " 'ČD st 08:39',\n",
       " 'ČD st 07:39',\n",
       " 'ČD st 05:39',\n",
       " 'ČD st 04:26',\n",
       " 'ČD st 03:10',\n",
       " 'ČD st 00:29',\n",
       " 'ČD st 12:39',\n",
       " 'ČD st 10:39',\n",
       " 'ČD st 06:39',\n",
       " 'ČD st 11:39',\n",
       " 'ČD st 18:39',\n",
       " 'ČD st 16:39',\n",
       " 'ČD st 19:39',\n",
       " 'ČD st 20:39',\n",
       " 'ČD st 15:39',\n",
       " 'ČD st 13:39',\n",
       " 'ČD st 14:39',\n",
       " 'ČD st 17:39',\n",
       " 'ČD čt 05:44',\n",
       " 'ČD čt 04:42',\n",
       " 'ČD čt 00:03',\n",
       " 'ČD čt 16:03',\n",
       " 'ČD čt 08:44',\n",
       " 'ČD čt 18:44',\n",
       " 'ČD čt 21:03',\n",
       " 'ČD čt 19:44',\n",
       " 'ČD čt 14:03',\n",
       " 'ČD čt 18:03',\n",
       " 'ČD čt 13:44',\n",
       " 'ČD čt 17:44',\n",
       " 'ČD čt 22:03',\n",
       " 'ČD čt 16:44',\n",
       " 'ČD čt 07:44',\n",
       " 'ČD čt 14:44',\n",
       " 'ČD čt 00:40',\n",
       " 'ČD čt 15:44',\n",
       " 'ČD čt 12:44',\n",
       " 'ČD čt 12:03',\n",
       " 'ČD čt 06:44',\n",
       " 'ČD čt 10:44',\n",
       " 'ČD čt 10:03',\n",
       " 'ČD čt 09:44',\n",
       " 'ČD čt 08:03',\n",
       " 'ČD čt 11:44',\n",
       " 'ČD čt 04:26',\n",
       " 'ČD čt 06:39',\n",
       " 'ČD čt 07:39',\n",
       " 'ČD čt 08:39',\n",
       " 'ČD čt 10:39',\n",
       " 'ČD čt 09:39',\n",
       " 'ČD čt 11:39',\n",
       " 'ČD čt 03:10',\n",
       " 'ČD čt 00:29',\n",
       " 'ČD čt 05:39',\n",
       " 'ČD čt 20:39',\n",
       " 'ČD čt 19:39',\n",
       " 'ČD čt 14:39',\n",
       " 'ČD čt 15:39',\n",
       " 'ČD čt 16:39',\n",
       " 'ČD čt 13:39',\n",
       " 'ČD čt 18:39',\n",
       " 'ČD čt 12:39',\n",
       " 'ČD čt 17:39',\n",
       " 'ČD po 20:39',\n",
       " 'ČD út 21:39',\n",
       " 'ČD st 21:39',\n",
       " 'ČD čt 21:39',\n",
       " 'ČD pá 21:39',\n",
       " 'ČD po 21:39',\n",
       " 'ČD so 16:23',\n",
       " 'ČD so 18:23',\n",
       " 'ČD so 14:23',\n",
       " 'RJ st 20:56',\n",
       " 'RJ st 18:15',\n",
       " 'RJ st 17:15',\n",
       " 'RJ čt 20:56',\n",
       " 'RJ pá 06:15',\n",
       " 'RJ pá 07:15',\n",
       " 'RJ pá 09:15',\n",
       " 'RJ pá 11:15',\n",
       " 'RJ pá 13:15',\n",
       " 'RJ pá 15:15',\n",
       " 'RJ pá 16:15',\n",
       " 'RJ čt 18:15',\n",
       " 'RJ pá 17:15',\n",
       " 'RJ čt 06:15',\n",
       " 'RJ čt 07:15',\n",
       " 'RJ čt 09:15',\n",
       " 'RJ čt 13:15',\n",
       " 'RJ čt 15:15',\n",
       " 'RJ čt 16:15',\n",
       " 'RJ čt 17:15',\n",
       " 'RJ čt 11:15',\n",
       " 'RJ so 16:15',\n",
       " 'RJ ne 06:15',\n",
       " 'RJ ne 07:15',\n",
       " 'RJ ne 09:15',\n",
       " 'RJ ne 11:15',\n",
       " 'RJ ne 13:15',\n",
       " 'RJ ne 15:15',\n",
       " 'RJ ne 16:15',\n",
       " 'RJ ne 17:15',\n",
       " 'RJ ne 18:15',\n",
       " 'RJ ne 20:56',\n",
       " 'RJ pá 18:15',\n",
       " 'RJ pá 20:56',\n",
       " 'RJ so 06:15',\n",
       " 'RJ so 07:15',\n",
       " 'RJ so 09:15',\n",
       " 'RJ so 11:15',\n",
       " 'RJ so 13:15',\n",
       " 'RJ so 15:15',\n",
       " 'RJ so 17:15',\n",
       " 'RJ so 18:15',\n",
       " 'RJ so 20:56',\n",
       " 'RJ ne 08:09',\n",
       " 'RJ ne 07:09',\n",
       " 'RJ ne 06:09',\n",
       " 'RJ ne 05:03',\n",
       " 'RJ ne 12:09',\n",
       " 'RJ ne 14:09',\n",
       " 'RJ ne 16:09',\n",
       " 'RJ ne 18:09',\n",
       " 'RJ ne 19:09',\n",
       " 'RJ ne 10:09',\n",
       " 'RJ po 20:56',\n",
       " 'RJ po 18:15',\n",
       " 'RJ po 17:15',\n",
       " 'RJ po 13:15',\n",
       " 'RJ po 11:15',\n",
       " 'RJ po 09:15',\n",
       " 'RJ po 06:15',\n",
       " 'RJ po 15:15',\n",
       " 'RJ po 16:15',\n",
       " 'RJ po 07:15',\n",
       " 'RJ út 20:56',\n",
       " 'RJ út 18:15',\n",
       " 'RJ út 17:15',\n",
       " 'RJ út 06:15',\n",
       " 'RJ út 07:15',\n",
       " 'RJ út 09:15',\n",
       " 'RJ út 11:15',\n",
       " 'RJ út 13:15',\n",
       " 'RJ út 15:15',\n",
       " 'RJ út 16:15',\n",
       " 'RJ st 06:15',\n",
       " 'RJ st 07:15',\n",
       " 'RJ st 09:15',\n",
       " 'RJ st 11:15',\n",
       " 'RJ st 13:15',\n",
       " 'RJ st 15:15',\n",
       " 'RJ st 16:15',\n",
       " 'RJ čt 18:09',\n",
       " 'RJ čt 16:09',\n",
       " 'RJ čt 19:09',\n",
       " 'RJ čt 14:09',\n",
       " 'RJ čt 08:09',\n",
       " 'RJ čt 06:09',\n",
       " 'RJ čt 07:09',\n",
       " 'RJ čt 05:03',\n",
       " 'RJ čt 10:09',\n",
       " 'RJ čt 12:09',\n",
       " 'RJ pá 08:09',\n",
       " 'RJ pá 07:09',\n",
       " 'RJ pá 06:09',\n",
       " 'RJ pá 05:03',\n",
       " 'RJ pá 10:09',\n",
       " 'RJ pá 18:09',\n",
       " 'RJ pá 16:09',\n",
       " 'RJ pá 19:09',\n",
       " 'RJ pá 14:09',\n",
       " 'RJ pá 12:09',\n",
       " 'RJ so 14:09',\n",
       " 'RJ so 16:09',\n",
       " 'RJ so 18:09',\n",
       " 'RJ so 19:09',\n",
       " 'RJ so 10:09',\n",
       " 'RJ so 08:09',\n",
       " 'RJ so 06:09',\n",
       " 'RJ so 12:09',\n",
       " 'RJ so 07:09',\n",
       " 'RJ so 05:03',\n",
       " 'RJ po 10:09',\n",
       " 'RJ po 12:09',\n",
       " 'RJ po 14:09',\n",
       " 'RJ po 16:09',\n",
       " 'RJ po 18:09',\n",
       " 'RJ po 19:09',\n",
       " 'RJ po 07:09',\n",
       " 'RJ po 08:09',\n",
       " 'RJ po 06:09',\n",
       " 'RJ po 05:03',\n",
       " 'RJ út 10:09',\n",
       " 'RJ út 19:09',\n",
       " 'RJ út 18:09',\n",
       " 'RJ út 14:09',\n",
       " 'RJ út 12:09',\n",
       " 'RJ út 08:09',\n",
       " 'RJ út 16:09',\n",
       " 'RJ út 07:09',\n",
       " 'RJ út 06:09',\n",
       " 'RJ út 05:03',\n",
       " 'RJ st 08:09',\n",
       " 'RJ st 19:09',\n",
       " 'RJ st 18:09',\n",
       " 'RJ st 16:09',\n",
       " 'RJ st 14:09',\n",
       " 'RJ st 12:09',\n",
       " 'RJ st 07:09',\n",
       " 'RJ st 10:09',\n",
       " 'RJ st 05:03',\n",
       " 'RJ st 06:09']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "listopad = df[df['odjezd'] < '2024-12-01']['spoj'].drop_duplicates().to_list()\n",
    "listopad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "9fcba2bb-646d-4856-b4f3-3c0590f8d4ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ČD čt 06:39',\n",
       " 'ČD čt 10:39',\n",
       " 'ČD čt 09:39',\n",
       " 'ČD čt 08:39',\n",
       " 'ČD pá 00:29',\n",
       " 'ČD čt 07:39',\n",
       " 'ČD čt 20:39',\n",
       " 'ČD čt 21:39',\n",
       " 'ČD pá 03:10',\n",
       " 'ČD čt 12:39',\n",
       " 'ČD pá 04:26',\n",
       " 'ČD čt 13:39',\n",
       " 'ČD čt 11:39',\n",
       " 'ČD čt 19:39',\n",
       " 'ČD čt 17:39',\n",
       " 'ČD čt 18:39',\n",
       " 'ČD čt 15:39',\n",
       " 'ČD čt 14:39',\n",
       " 'ČD čt 16:39',\n",
       " 'ČD čt 08:40',\n",
       " 'ČD čt 11:42',\n",
       " 'ČD čt 10:35',\n",
       " 'ČD čt 09:42',\n",
       " 'ČD pá 04:39',\n",
       " 'ČD čt 06:42',\n",
       " 'ČD čt 07:42',\n",
       " 'ČD čt 05:42',\n",
       " 'ČD čt 12:42',\n",
       " 'ČD čt 13:42',\n",
       " 'ČD pá 00:36',\n",
       " 'ČD čt 16:42',\n",
       " 'ČD čt 18:42',\n",
       " 'ČD čt 19:42',\n",
       " 'ČD čt 17:42',\n",
       " 'ČD čt 22:01',\n",
       " 'ČD pá 00:01',\n",
       " 'ČD čt 15:42',\n",
       " 'ČD čt 14:42',\n",
       " 'ČD čt 21:01',\n",
       " 'ČD so 08:39',\n",
       " 'ČD pá 10:39',\n",
       " 'ČD pá 12:39',\n",
       " 'ČD pá 13:39',\n",
       " 'ČD so 06:39',\n",
       " 'ČD so 03:10',\n",
       " 'ČD pá 14:39',\n",
       " 'ČD pá 15:39',\n",
       " 'ČD so 07:39',\n",
       " 'ČD pá 09:39',\n",
       " 'ČD so 04:26',\n",
       " 'ČD so 00:29',\n",
       " 'ČD pá 21:39',\n",
       " 'ČD pá 20:39',\n",
       " 'ČD pá 19:39',\n",
       " 'ČD pá 17:39',\n",
       " 'ČD pá 16:39',\n",
       " 'ČD pá 11:39',\n",
       " 'ČD pá 18:39',\n",
       " 'ČD so 05:39',\n",
       " 'ČD pá 12:42',\n",
       " 'ČD pá 10:35',\n",
       " 'ČD pá 11:42',\n",
       " 'ČD pá 17:42',\n",
       " 'ČD pá 13:42',\n",
       " 'ČD pá 14:42',\n",
       " 'ČD pá 15:42',\n",
       " 'ČD pá 16:42',\n",
       " 'ČD pá 18:42',\n",
       " 'ČD so 00:01',\n",
       " 'ČD so 05:42',\n",
       " 'ČD pá 19:42',\n",
       " 'ČD pá 21:01',\n",
       " 'ČD so 00:36',\n",
       " 'ČD so 04:39',\n",
       " 'ČD pá 22:01',\n",
       " 'ČD so 08:40',\n",
       " 'ČD so 07:42',\n",
       " 'ČD so 06:42',\n",
       " 'ČD so 16:39',\n",
       " 'ČD so 14:39',\n",
       " 'ČD ne 06:39',\n",
       " 'ČD ne 05:39',\n",
       " 'ČD ne 03:10',\n",
       " 'ČD so 21:39',\n",
       " 'ČD so 19:39',\n",
       " 'ČD so 15:39',\n",
       " 'ČD so 20:39',\n",
       " 'ČD so 18:39',\n",
       " 'ČD ne 00:29',\n",
       " 'ČD so 13:39',\n",
       " 'ČD so 17:39',\n",
       " 'ČD ne 09:39',\n",
       " 'ČD ne 10:39',\n",
       " 'ČD ne 11:39',\n",
       " 'ČD ne 08:39',\n",
       " 'ČD ne 07:39',\n",
       " 'ČD so 12:39',\n",
       " 'ČD so 11:39',\n",
       " 'ČD so 18:42',\n",
       " 'ČD so 11:42',\n",
       " 'ČD so 12:42',\n",
       " 'ČD so 13:42',\n",
       " 'ČD so 14:42',\n",
       " 'ČD so 16:42',\n",
       " 'ČD so 17:42',\n",
       " 'ČD ne 11:42',\n",
       " 'ČD so 15:42',\n",
       " 'ČD ne 00:01',\n",
       " 'ČD ne 07:42',\n",
       " 'ČD so 22:01',\n",
       " 'ČD ne 00:36',\n",
       " 'ČD so 19:42',\n",
       " 'ČD so 21:01',\n",
       " 'ČD ne 06:42',\n",
       " 'ČD ne 05:42',\n",
       " 'ČD ne 08:40',\n",
       " 'ČD ne 09:42',\n",
       " 'ČD ne 10:35',\n",
       " 'ČD st 15:39',\n",
       " 'ČD st 16:39',\n",
       " 'ČD čt 05:39',\n",
       " 'ČD čt 03:10',\n",
       " 'ČD čt 00:29',\n",
       " 'ČD čt 04:26',\n",
       " 'ČD st 20:39',\n",
       " 'ČD st 19:39',\n",
       " 'ČD st 18:39',\n",
       " 'ČD st 17:39',\n",
       " 'ČD st 21:39',\n",
       " 'ČD st 16:42',\n",
       " 'ČD st 17:42',\n",
       " 'ČD st 18:42',\n",
       " 'ČD st 15:42',\n",
       " 'ČD čt 00:36',\n",
       " 'ČD st 21:01',\n",
       " 'ČD st 22:01',\n",
       " 'ČD čt 00:01',\n",
       " 'ČD čt 04:39',\n",
       " 'ČD st 19:42',\n",
       " 'ČD st 13:42',\n",
       " 'ČD st 12:42',\n",
       " 'ČD st 14:42',\n",
       " 'ČD st 13:39',\n",
       " 'ČD st 14:39',\n",
       " 'ČD st 12:39',\n",
       " 'ČD ne 15:39',\n",
       " 'ČD ne 14:39',\n",
       " 'ČD ne 12:39',\n",
       " 'ČD ne 13:39',\n",
       " 'ČD ne 15:42',\n",
       " 'ČD ne 13:42',\n",
       " 'ČD ne 12:42',\n",
       " 'ČD ne 14:42',\n",
       " 'ČD so 09:42',\n",
       " 'ČD so 10:35',\n",
       " 'ČD út 13:39',\n",
       " 'ČD út 20:39',\n",
       " 'ČD út 19:39',\n",
       " 'ČD út 18:39',\n",
       " 'ČD út 17:39',\n",
       " 'ČD út 16:39',\n",
       " 'ČD út 14:39',\n",
       " 'ČD út 00:29',\n",
       " 'ČD út 15:39',\n",
       " 'ČD út 09:39',\n",
       " 'ČD út 12:39',\n",
       " 'ČD út 05:39',\n",
       " 'ČD út 06:39',\n",
       " 'ČD út 07:39',\n",
       " 'ČD út 04:26',\n",
       " 'ČD út 08:39',\n",
       " 'ČD út 10:39',\n",
       " 'ČD út 11:39',\n",
       " 'ČD út 03:10',\n",
       " 'ČD út 18:42',\n",
       " 'ČD út 17:42',\n",
       " 'ČD út 16:42',\n",
       " 'ČD út 15:42',\n",
       " 'ČD út 14:42',\n",
       " 'ČD út 13:42',\n",
       " 'ČD út 12:42',\n",
       " 'ČD út 19:42',\n",
       " 'ČD út 21:01',\n",
       " 'ČD út 22:01',\n",
       " 'ČD út 10:35',\n",
       " 'ČD út 09:42',\n",
       " 'ČD út 08:40',\n",
       " 'ČD út 11:42',\n",
       " 'ČD út 06:42',\n",
       " 'ČD út 00:01',\n",
       " 'ČD út 00:36',\n",
       " 'ČD út 07:42',\n",
       " 'ČD út 05:42',\n",
       " 'ČD út 04:39',\n",
       " 'ČD so 10:39',\n",
       " 'ČD st 05:42',\n",
       " 'ČD st 06:42',\n",
       " 'ČD st 07:42',\n",
       " 'ČD st 00:36',\n",
       " 'ČD st 04:39',\n",
       " 'ČD st 00:01',\n",
       " 'ČD st 10:35',\n",
       " 'ČD st 11:42',\n",
       " 'ČD st 08:40',\n",
       " 'ČD st 09:42',\n",
       " 'ČD st 11:39',\n",
       " 'ČD st 10:39',\n",
       " 'ČD st 05:39',\n",
       " 'ČD st 09:39',\n",
       " 'ČD st 04:26',\n",
       " 'ČD út 21:39',\n",
       " 'ČD st 00:29',\n",
       " 'ČD st 03:10',\n",
       " 'ČD st 06:39',\n",
       " 'ČD st 07:39',\n",
       " 'ČD st 08:39',\n",
       " 'ČD pá 09:42',\n",
       " 'ČD pá 06:42',\n",
       " 'ČD pá 07:42',\n",
       " 'ČD pá 05:42',\n",
       " 'ČD pá 08:40',\n",
       " 'ČD pá 06:39',\n",
       " 'ČD pá 08:39',\n",
       " 'ČD pá 05:39',\n",
       " 'ČD pá 07:39',\n",
       " 'ČD po 21:39',\n",
       " 'ČD po 18:39',\n",
       " 'ČD po 19:39',\n",
       " 'ČD po 20:39',\n",
       " 'ČD po 21:01',\n",
       " 'ČD po 19:42',\n",
       " 'ČD po 18:42',\n",
       " 'ČD po 22:01',\n",
       " 'ČD so 09:39',\n",
       " 'ČD ne 20:39',\n",
       " 'ČD po 00:29',\n",
       " 'ČD ne 16:39',\n",
       " 'ČD ne 21:39',\n",
       " 'ČD ne 18:39',\n",
       " 'ČD po 03:10',\n",
       " 'ČD ne 19:39',\n",
       " 'ČD ne 17:39',\n",
       " 'ČD po 04:26',\n",
       " 'ČD ne 21:01',\n",
       " 'ČD ne 17:42',\n",
       " 'ČD ne 18:42',\n",
       " 'ČD ne 19:42',\n",
       " 'ČD ne 22:01',\n",
       " 'ČD po 00:36',\n",
       " 'ČD ne 16:42',\n",
       " 'ČD po 00:01',\n",
       " 'ČD po 05:42',\n",
       " 'ČD po 04:39',\n",
       " 'ČD po 05:39',\n",
       " 'ČD po 06:42',\n",
       " 'ČD po 15:42',\n",
       " 'ČD po 14:42',\n",
       " 'ČD po 13:42',\n",
       " 'ČD po 12:42',\n",
       " 'ČD po 07:42',\n",
       " 'ČD po 09:42',\n",
       " 'ČD po 10:35',\n",
       " 'ČD po 11:42',\n",
       " 'ČD po 08:40',\n",
       " 'ČD po 16:42',\n",
       " 'ČD po 17:42',\n",
       " 'ČD po 12:39',\n",
       " 'ČD po 11:39',\n",
       " 'ČD po 10:39',\n",
       " 'ČD po 09:39',\n",
       " 'ČD po 07:39',\n",
       " 'ČD po 08:39',\n",
       " 'ČD po 17:39',\n",
       " 'ČD po 14:39',\n",
       " 'ČD po 15:39',\n",
       " 'ČD po 16:39',\n",
       " 'ČD po 13:39',\n",
       " 'ČD po 06:39',\n",
       " 'ČD po 00:40',\n",
       " 'RJ pá 20:47',\n",
       " 'RJ pá 18:16',\n",
       " 'RJ pá 17:16',\n",
       " 'RJ pá 15:16',\n",
       " 'RJ pá 16:16',\n",
       " 'RJ pá 09:16',\n",
       " 'RJ pá 07:16',\n",
       " 'RJ pá 06:13',\n",
       " 'RJ pá 11:16',\n",
       " 'RJ pá 13:16',\n",
       " 'RJ so 20:47',\n",
       " 'RJ so 18:16',\n",
       " 'RJ so 17:16',\n",
       " 'RJ so 16:16',\n",
       " 'RJ so 15:16',\n",
       " 'RJ so 06:13',\n",
       " 'RJ so 07:16',\n",
       " 'RJ so 09:16',\n",
       " 'RJ so 13:16',\n",
       " 'RJ so 11:16',\n",
       " 'RJ ne 06:13',\n",
       " 'RJ ne 20:47',\n",
       " 'RJ ne 18:16',\n",
       " 'RJ ne 17:16',\n",
       " 'RJ ne 16:16',\n",
       " 'RJ ne 15:16',\n",
       " 'RJ ne 13:16',\n",
       " 'RJ ne 11:16',\n",
       " 'RJ ne 09:16',\n",
       " 'RJ ne 07:16',\n",
       " 'ČD so 00:40']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "leden = df[df['odjezd'] > '2025-01-01']['spoj'].drop_duplicates().to_list()\n",
    "leden"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f5a99e4e-5f1c-4af8-b108-9c379b9ee6af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ČD pá 08:39',\n",
       " 'ČD pá 12:39',\n",
       " 'ČD pá 18:39',\n",
       " 'ČD pá 17:39',\n",
       " 'ČD pá 16:39',\n",
       " 'ČD pá 14:39',\n",
       " 'ČD pá 13:39',\n",
       " 'ČD pá 15:39',\n",
       " 'ČD pá 00:29',\n",
       " 'ČD pá 03:10',\n",
       " 'ČD pá 04:26',\n",
       " 'ČD pá 19:39',\n",
       " 'ČD pá 20:39',\n",
       " 'ČD pá 10:39',\n",
       " 'ČD pá 09:39',\n",
       " 'ČD pá 11:39',\n",
       " 'ČD pá 07:39',\n",
       " 'ČD pá 06:39',\n",
       " 'ČD pá 05:39',\n",
       " 'ČD so 00:40',\n",
       " 'ČD so 15:39',\n",
       " 'ČD so 16:39',\n",
       " 'ČD so 17:39',\n",
       " 'ČD so 18:39',\n",
       " 'ČD so 21:39',\n",
       " 'ČD so 19:39',\n",
       " 'ČD so 20:39',\n",
       " 'ČD so 05:39',\n",
       " 'ČD so 04:26',\n",
       " 'ČD so 09:39',\n",
       " 'ČD so 00:29',\n",
       " 'ČD so 03:10',\n",
       " 'ČD so 14:39',\n",
       " 'ČD so 13:39',\n",
       " 'ČD so 07:39',\n",
       " 'ČD so 08:39',\n",
       " 'ČD so 06:39',\n",
       " 'ČD so 12:39',\n",
       " 'ČD so 10:39',\n",
       " 'ČD so 11:39',\n",
       " 'ČD ne 09:39',\n",
       " 'ČD ne 21:39',\n",
       " 'ČD ne 16:39',\n",
       " 'ČD ne 19:39',\n",
       " 'ČD ne 20:39',\n",
       " 'ČD ne 00:29',\n",
       " 'ČD ne 06:39',\n",
       " 'ČD ne 05:39',\n",
       " 'ČD ne 03:10',\n",
       " 'ČD ne 07:39',\n",
       " 'ČD ne 18:39',\n",
       " 'ČD ne 08:39',\n",
       " 'ČD ne 10:39',\n",
       " 'ČD ne 11:39',\n",
       " 'ČD ne 12:39',\n",
       " 'ČD ne 13:39',\n",
       " 'ČD ne 15:39',\n",
       " 'ČD ne 17:39',\n",
       " 'ČD ne 14:39',\n",
       " 'ČD po 00:40',\n",
       " 'ČD po 12:39',\n",
       " 'ČD po 18:39',\n",
       " 'ČD po 17:39',\n",
       " 'ČD po 15:39',\n",
       " 'ČD po 19:39',\n",
       " 'ČD po 14:39',\n",
       " 'ČD po 16:39',\n",
       " 'ČD po 00:29',\n",
       " 'ČD po 13:39',\n",
       " 'ČD po 04:26',\n",
       " 'ČD po 03:10',\n",
       " 'ČD po 09:39',\n",
       " 'ČD po 11:39',\n",
       " 'ČD po 08:39',\n",
       " 'ČD po 10:39',\n",
       " 'ČD po 06:39',\n",
       " 'ČD po 05:39',\n",
       " 'ČD po 07:39',\n",
       " 'ČD út 14:39',\n",
       " 'ČD út 00:29',\n",
       " 'ČD út 03:10',\n",
       " 'ČD út 09:39',\n",
       " 'ČD út 05:39',\n",
       " 'ČD út 07:39',\n",
       " 'ČD út 06:39',\n",
       " 'ČD út 08:39',\n",
       " 'ČD út 10:39',\n",
       " 'ČD út 04:26',\n",
       " 'ČD út 15:39',\n",
       " 'ČD út 16:39',\n",
       " 'ČD út 11:39',\n",
       " 'ČD út 12:39',\n",
       " 'ČD út 20:39',\n",
       " 'ČD út 18:39',\n",
       " 'ČD út 17:39',\n",
       " 'ČD út 13:39',\n",
       " 'ČD út 19:39',\n",
       " 'ČD st 09:39',\n",
       " 'ČD st 08:39',\n",
       " 'ČD st 07:39',\n",
       " 'ČD st 05:39',\n",
       " 'ČD st 04:26',\n",
       " 'ČD st 03:10',\n",
       " 'ČD st 00:29',\n",
       " 'ČD st 12:39',\n",
       " 'ČD st 10:39',\n",
       " 'ČD st 06:39',\n",
       " 'ČD st 11:39',\n",
       " 'ČD st 18:39',\n",
       " 'ČD st 16:39',\n",
       " 'ČD st 19:39',\n",
       " 'ČD st 20:39',\n",
       " 'ČD st 15:39',\n",
       " 'ČD st 13:39',\n",
       " 'ČD st 14:39',\n",
       " 'ČD st 17:39',\n",
       " 'ČD čt 04:26',\n",
       " 'ČD čt 06:39',\n",
       " 'ČD čt 07:39',\n",
       " 'ČD čt 08:39',\n",
       " 'ČD čt 10:39',\n",
       " 'ČD čt 09:39',\n",
       " 'ČD čt 11:39',\n",
       " 'ČD čt 03:10',\n",
       " 'ČD čt 00:29',\n",
       " 'ČD čt 05:39',\n",
       " 'ČD čt 20:39',\n",
       " 'ČD čt 19:39',\n",
       " 'ČD čt 14:39',\n",
       " 'ČD čt 15:39',\n",
       " 'ČD čt 16:39',\n",
       " 'ČD čt 13:39',\n",
       " 'ČD čt 18:39',\n",
       " 'ČD čt 12:39',\n",
       " 'ČD čt 17:39',\n",
       " 'ČD po 20:39',\n",
       " 'ČD út 21:39',\n",
       " 'ČD st 21:39',\n",
       " 'ČD čt 21:39',\n",
       " 'ČD pá 21:39',\n",
       " 'ČD po 21:39']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[x for x in listopad if x in leden]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f18645f6-0c74-476c-b664-fadc6881874d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ČD pá 00:03',\n",
       " 'ČD pá 22:03',\n",
       " 'ČD pá 19:44',\n",
       " 'ČD pá 18:44',\n",
       " 'ČD pá 18:03',\n",
       " 'ČD pá 17:44',\n",
       " 'ČD pá 14:03',\n",
       " 'ČD pá 15:44',\n",
       " 'ČD pá 14:44',\n",
       " 'ČD pá 16:44',\n",
       " 'ČD pá 00:40',\n",
       " 'ČD pá 16:03',\n",
       " 'ČD pá 13:44',\n",
       " 'ČD pá 21:03',\n",
       " 'ČD pá 08:03',\n",
       " 'ČD pá 11:44',\n",
       " 'ČD pá 10:44',\n",
       " 'ČD pá 10:03',\n",
       " 'ČD pá 12:44',\n",
       " 'ČD pá 08:44',\n",
       " 'ČD pá 12:03',\n",
       " 'ČD pá 09:44',\n",
       " 'ČD pá 07:44',\n",
       " 'ČD pá 06:44',\n",
       " 'ČD pá 05:44',\n",
       " 'ČD pá 04:42',\n",
       " 'ČD so 22:03',\n",
       " 'ČD so 21:03',\n",
       " 'ČD so 00:03',\n",
       " 'ČD so 04:42',\n",
       " 'ČD so 10:03',\n",
       " 'ČD so 07:44',\n",
       " 'ČD so 08:03',\n",
       " 'ČD so 08:44',\n",
       " 'ČD so 05:44',\n",
       " 'ČD so 18:44',\n",
       " 'ČD so 19:44',\n",
       " 'ČD so 16:44',\n",
       " 'ČD so 06:44',\n",
       " 'ČD so 09:44',\n",
       " 'ČD so 12:03',\n",
       " 'ČD so 11:44',\n",
       " 'ČD so 12:44',\n",
       " 'ČD so 13:44',\n",
       " 'ČD so 14:03',\n",
       " 'ČD so 16:03',\n",
       " 'ČD so 14:44',\n",
       " 'ČD so 17:44',\n",
       " 'ČD so 18:03',\n",
       " 'ČD so 10:44',\n",
       " 'ČD so 15:44',\n",
       " 'ČD ne 17:44',\n",
       " 'ČD ne 14:44',\n",
       " 'ČD ne 16:03',\n",
       " 'ČD ne 16:44',\n",
       " 'ČD ne 18:03',\n",
       " 'ČD ne 15:44',\n",
       " 'ČD ne 18:44',\n",
       " 'ČD ne 19:44',\n",
       " 'ČD ne 21:03',\n",
       " 'ČD ne 12:44',\n",
       " 'ČD ne 07:44',\n",
       " 'ČD ne 14:03',\n",
       " 'ČD ne 13:44',\n",
       " 'ČD ne 12:03',\n",
       " 'ČD ne 22:03',\n",
       " 'ČD ne 05:44',\n",
       " 'ČD ne 00:40',\n",
       " 'ČD ne 00:03',\n",
       " 'ČD ne 06:44',\n",
       " 'ČD ne 08:03',\n",
       " 'ČD ne 09:44',\n",
       " 'ČD ne 10:03',\n",
       " 'ČD ne 10:44',\n",
       " 'ČD ne 11:44',\n",
       " 'ČD ne 08:44',\n",
       " 'ČD po 00:03',\n",
       " 'ČD po 04:42',\n",
       " 'ČD po 05:44',\n",
       " 'ČD po 10:44',\n",
       " 'ČD po 06:44',\n",
       " 'ČD po 08:03',\n",
       " 'ČD po 08:44',\n",
       " 'ČD po 09:44',\n",
       " 'ČD po 10:03',\n",
       " 'ČD po 11:44',\n",
       " 'ČD po 07:44',\n",
       " 'ČD po 12:03',\n",
       " 'ČD po 21:03',\n",
       " 'ČD po 14:44',\n",
       " 'ČD po 12:44',\n",
       " 'ČD po 13:44',\n",
       " 'ČD po 14:03',\n",
       " 'ČD po 15:44',\n",
       " 'ČD po 16:44',\n",
       " 'ČD po 17:44',\n",
       " 'ČD po 18:03',\n",
       " 'ČD po 22:03',\n",
       " 'ČD po 18:44',\n",
       " 'ČD po 19:44',\n",
       " 'ČD po 16:03',\n",
       " 'ČD út 00:40',\n",
       " 'ČD út 04:42',\n",
       " 'ČD út 12:03',\n",
       " 'ČD út 21:03',\n",
       " 'ČD út 05:44',\n",
       " 'ČD út 09:44',\n",
       " 'ČD út 10:03',\n",
       " 'ČD út 10:44',\n",
       " 'ČD út 08:03',\n",
       " 'ČD út 22:03',\n",
       " 'ČD út 07:44',\n",
       " 'ČD út 08:44',\n",
       " 'ČD út 11:44',\n",
       " 'ČD út 00:03',\n",
       " 'ČD út 15:44',\n",
       " 'ČD út 14:03',\n",
       " 'ČD út 14:44',\n",
       " 'ČD út 16:03',\n",
       " 'ČD út 06:44',\n",
       " 'ČD út 13:44',\n",
       " 'ČD út 16:44',\n",
       " 'ČD út 17:44',\n",
       " 'ČD út 18:03',\n",
       " 'ČD út 18:44',\n",
       " 'ČD út 12:44',\n",
       " 'ČD út 19:44',\n",
       " 'ČD st 14:44',\n",
       " 'ČD st 16:03',\n",
       " 'ČD st 04:42',\n",
       " 'ČD st 16:44',\n",
       " 'ČD st 17:44',\n",
       " 'ČD st 09:44',\n",
       " 'ČD st 05:44',\n",
       " 'ČD st 15:44',\n",
       " 'ČD st 06:44',\n",
       " 'ČD st 18:03',\n",
       " 'ČD st 10:03',\n",
       " 'ČD st 08:44',\n",
       " 'ČD st 19:44',\n",
       " 'ČD st 08:03',\n",
       " 'ČD st 00:40',\n",
       " 'ČD st 14:03',\n",
       " 'ČD st 13:44',\n",
       " 'ČD st 12:44',\n",
       " 'ČD st 07:44',\n",
       " 'ČD st 11:44',\n",
       " 'ČD st 10:44',\n",
       " 'ČD st 00:03',\n",
       " 'ČD st 22:03',\n",
       " 'ČD st 18:44',\n",
       " 'ČD st 21:03',\n",
       " 'ČD st 12:03',\n",
       " 'ČD čt 05:44',\n",
       " 'ČD čt 04:42',\n",
       " 'ČD čt 00:03',\n",
       " 'ČD čt 16:03',\n",
       " 'ČD čt 08:44',\n",
       " 'ČD čt 18:44',\n",
       " 'ČD čt 21:03',\n",
       " 'ČD čt 19:44',\n",
       " 'ČD čt 14:03',\n",
       " 'ČD čt 18:03',\n",
       " 'ČD čt 13:44',\n",
       " 'ČD čt 17:44',\n",
       " 'ČD čt 22:03',\n",
       " 'ČD čt 16:44',\n",
       " 'ČD čt 07:44',\n",
       " 'ČD čt 14:44',\n",
       " 'ČD čt 00:40',\n",
       " 'ČD čt 15:44',\n",
       " 'ČD čt 12:44',\n",
       " 'ČD čt 12:03',\n",
       " 'ČD čt 06:44',\n",
       " 'ČD čt 10:44',\n",
       " 'ČD čt 10:03',\n",
       " 'ČD čt 09:44',\n",
       " 'ČD čt 08:03',\n",
       " 'ČD čt 11:44',\n",
       " 'ČD so 16:23',\n",
       " 'ČD so 18:23',\n",
       " 'ČD so 14:23',\n",
       " 'RJ st 20:56',\n",
       " 'RJ st 18:15',\n",
       " 'RJ st 17:15',\n",
       " 'RJ čt 20:56',\n",
       " 'RJ pá 06:15',\n",
       " 'RJ pá 07:15',\n",
       " 'RJ pá 09:15',\n",
       " 'RJ pá 11:15',\n",
       " 'RJ pá 13:15',\n",
       " 'RJ pá 15:15',\n",
       " 'RJ pá 16:15',\n",
       " 'RJ čt 18:15',\n",
       " 'RJ pá 17:15',\n",
       " 'RJ čt 06:15',\n",
       " 'RJ čt 07:15',\n",
       " 'RJ čt 09:15',\n",
       " 'RJ čt 13:15',\n",
       " 'RJ čt 15:15',\n",
       " 'RJ čt 16:15',\n",
       " 'RJ čt 17:15',\n",
       " 'RJ čt 11:15',\n",
       " 'RJ so 16:15',\n",
       " 'RJ ne 06:15',\n",
       " 'RJ ne 07:15',\n",
       " 'RJ ne 09:15',\n",
       " 'RJ ne 11:15',\n",
       " 'RJ ne 13:15',\n",
       " 'RJ ne 15:15',\n",
       " 'RJ ne 16:15',\n",
       " 'RJ ne 17:15',\n",
       " 'RJ ne 18:15',\n",
       " 'RJ ne 20:56',\n",
       " 'RJ pá 18:15',\n",
       " 'RJ pá 20:56',\n",
       " 'RJ so 06:15',\n",
       " 'RJ so 07:15',\n",
       " 'RJ so 09:15',\n",
       " 'RJ so 11:15',\n",
       " 'RJ so 13:15',\n",
       " 'RJ so 15:15',\n",
       " 'RJ so 17:15',\n",
       " 'RJ so 18:15',\n",
       " 'RJ so 20:56',\n",
       " 'RJ ne 08:09',\n",
       " 'RJ ne 07:09',\n",
       " 'RJ ne 06:09',\n",
       " 'RJ ne 05:03',\n",
       " 'RJ ne 12:09',\n",
       " 'RJ ne 14:09',\n",
       " 'RJ ne 16:09',\n",
       " 'RJ ne 18:09',\n",
       " 'RJ ne 19:09',\n",
       " 'RJ ne 10:09',\n",
       " 'RJ po 20:56',\n",
       " 'RJ po 18:15',\n",
       " 'RJ po 17:15',\n",
       " 'RJ po 13:15',\n",
       " 'RJ po 11:15',\n",
       " 'RJ po 09:15',\n",
       " 'RJ po 06:15',\n",
       " 'RJ po 15:15',\n",
       " 'RJ po 16:15',\n",
       " 'RJ po 07:15',\n",
       " 'RJ út 20:56',\n",
       " 'RJ út 18:15',\n",
       " 'RJ út 17:15',\n",
       " 'RJ út 06:15',\n",
       " 'RJ út 07:15',\n",
       " 'RJ út 09:15',\n",
       " 'RJ út 11:15',\n",
       " 'RJ út 13:15',\n",
       " 'RJ út 15:15',\n",
       " 'RJ út 16:15',\n",
       " 'RJ st 06:15',\n",
       " 'RJ st 07:15',\n",
       " 'RJ st 09:15',\n",
       " 'RJ st 11:15',\n",
       " 'RJ st 13:15',\n",
       " 'RJ st 15:15',\n",
       " 'RJ st 16:15',\n",
       " 'RJ čt 18:09',\n",
       " 'RJ čt 16:09',\n",
       " 'RJ čt 19:09',\n",
       " 'RJ čt 14:09',\n",
       " 'RJ čt 08:09',\n",
       " 'RJ čt 06:09',\n",
       " 'RJ čt 07:09',\n",
       " 'RJ čt 05:03',\n",
       " 'RJ čt 10:09',\n",
       " 'RJ čt 12:09',\n",
       " 'RJ pá 08:09',\n",
       " 'RJ pá 07:09',\n",
       " 'RJ pá 06:09',\n",
       " 'RJ pá 05:03',\n",
       " 'RJ pá 10:09',\n",
       " 'RJ pá 18:09',\n",
       " 'RJ pá 16:09',\n",
       " 'RJ pá 19:09',\n",
       " 'RJ pá 14:09',\n",
       " 'RJ pá 12:09',\n",
       " 'RJ so 14:09',\n",
       " 'RJ so 16:09',\n",
       " 'RJ so 18:09',\n",
       " 'RJ so 19:09',\n",
       " 'RJ so 10:09',\n",
       " 'RJ so 08:09',\n",
       " 'RJ so 06:09',\n",
       " 'RJ so 12:09',\n",
       " 'RJ so 07:09',\n",
       " 'RJ so 05:03',\n",
       " 'RJ po 10:09',\n",
       " 'RJ po 12:09',\n",
       " 'RJ po 14:09',\n",
       " 'RJ po 16:09',\n",
       " 'RJ po 18:09',\n",
       " 'RJ po 19:09',\n",
       " 'RJ po 07:09',\n",
       " 'RJ po 08:09',\n",
       " 'RJ po 06:09',\n",
       " 'RJ po 05:03',\n",
       " 'RJ út 10:09',\n",
       " 'RJ út 19:09',\n",
       " 'RJ út 18:09',\n",
       " 'RJ út 14:09',\n",
       " 'RJ út 12:09',\n",
       " 'RJ út 08:09',\n",
       " 'RJ út 16:09',\n",
       " 'RJ út 07:09',\n",
       " 'RJ út 06:09',\n",
       " 'RJ út 05:03',\n",
       " 'RJ st 08:09',\n",
       " 'RJ st 19:09',\n",
       " 'RJ st 18:09',\n",
       " 'RJ st 16:09',\n",
       " 'RJ st 14:09',\n",
       " 'RJ st 12:09',\n",
       " 'RJ st 07:09',\n",
       " 'RJ st 10:09',\n",
       " 'RJ st 05:03',\n",
       " 'RJ st 06:09']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[x for x in listopad if x not in leden]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "46c6c9d6-633c-4af2-84c4-42f775db1a73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ČD čt 08:40',\n",
       " 'ČD čt 11:42',\n",
       " 'ČD čt 10:35',\n",
       " 'ČD čt 09:42',\n",
       " 'ČD pá 04:39',\n",
       " 'ČD čt 06:42',\n",
       " 'ČD čt 07:42',\n",
       " 'ČD čt 05:42',\n",
       " 'ČD čt 12:42',\n",
       " 'ČD čt 13:42',\n",
       " 'ČD pá 00:36',\n",
       " 'ČD čt 16:42',\n",
       " 'ČD čt 18:42',\n",
       " 'ČD čt 19:42',\n",
       " 'ČD čt 17:42',\n",
       " 'ČD čt 22:01',\n",
       " 'ČD pá 00:01',\n",
       " 'ČD čt 15:42',\n",
       " 'ČD čt 14:42',\n",
       " 'ČD čt 21:01',\n",
       " 'ČD pá 12:42',\n",
       " 'ČD pá 10:35',\n",
       " 'ČD pá 11:42',\n",
       " 'ČD pá 17:42',\n",
       " 'ČD pá 13:42',\n",
       " 'ČD pá 14:42',\n",
       " 'ČD pá 15:42',\n",
       " 'ČD pá 16:42',\n",
       " 'ČD pá 18:42',\n",
       " 'ČD so 00:01',\n",
       " 'ČD so 05:42',\n",
       " 'ČD pá 19:42',\n",
       " 'ČD pá 21:01',\n",
       " 'ČD so 00:36',\n",
       " 'ČD so 04:39',\n",
       " 'ČD pá 22:01',\n",
       " 'ČD so 08:40',\n",
       " 'ČD so 07:42',\n",
       " 'ČD so 06:42',\n",
       " 'ČD so 18:42',\n",
       " 'ČD so 11:42',\n",
       " 'ČD so 12:42',\n",
       " 'ČD so 13:42',\n",
       " 'ČD so 14:42',\n",
       " 'ČD so 16:42',\n",
       " 'ČD so 17:42',\n",
       " 'ČD ne 11:42',\n",
       " 'ČD so 15:42',\n",
       " 'ČD ne 00:01',\n",
       " 'ČD ne 07:42',\n",
       " 'ČD so 22:01',\n",
       " 'ČD ne 00:36',\n",
       " 'ČD so 19:42',\n",
       " 'ČD so 21:01',\n",
       " 'ČD ne 06:42',\n",
       " 'ČD ne 05:42',\n",
       " 'ČD ne 08:40',\n",
       " 'ČD ne 09:42',\n",
       " 'ČD ne 10:35',\n",
       " 'ČD st 16:42',\n",
       " 'ČD st 17:42',\n",
       " 'ČD st 18:42',\n",
       " 'ČD st 15:42',\n",
       " 'ČD čt 00:36',\n",
       " 'ČD st 21:01',\n",
       " 'ČD st 22:01',\n",
       " 'ČD čt 00:01',\n",
       " 'ČD čt 04:39',\n",
       " 'ČD st 19:42',\n",
       " 'ČD st 13:42',\n",
       " 'ČD st 12:42',\n",
       " 'ČD st 14:42',\n",
       " 'ČD ne 15:42',\n",
       " 'ČD ne 13:42',\n",
       " 'ČD ne 12:42',\n",
       " 'ČD ne 14:42',\n",
       " 'ČD so 09:42',\n",
       " 'ČD so 10:35',\n",
       " 'ČD út 18:42',\n",
       " 'ČD út 17:42',\n",
       " 'ČD út 16:42',\n",
       " 'ČD út 15:42',\n",
       " 'ČD út 14:42',\n",
       " 'ČD út 13:42',\n",
       " 'ČD út 12:42',\n",
       " 'ČD út 19:42',\n",
       " 'ČD út 21:01',\n",
       " 'ČD út 22:01',\n",
       " 'ČD út 10:35',\n",
       " 'ČD út 09:42',\n",
       " 'ČD út 08:40',\n",
       " 'ČD út 11:42',\n",
       " 'ČD út 06:42',\n",
       " 'ČD út 00:01',\n",
       " 'ČD út 00:36',\n",
       " 'ČD út 07:42',\n",
       " 'ČD út 05:42',\n",
       " 'ČD út 04:39',\n",
       " 'ČD st 05:42',\n",
       " 'ČD st 06:42',\n",
       " 'ČD st 07:42',\n",
       " 'ČD st 00:36',\n",
       " 'ČD st 04:39',\n",
       " 'ČD st 00:01',\n",
       " 'ČD st 10:35',\n",
       " 'ČD st 11:42',\n",
       " 'ČD st 08:40',\n",
       " 'ČD st 09:42',\n",
       " 'ČD pá 09:42',\n",
       " 'ČD pá 06:42',\n",
       " 'ČD pá 07:42',\n",
       " 'ČD pá 05:42',\n",
       " 'ČD pá 08:40',\n",
       " 'ČD po 21:01',\n",
       " 'ČD po 19:42',\n",
       " 'ČD po 18:42',\n",
       " 'ČD po 22:01',\n",
       " 'ČD ne 21:01',\n",
       " 'ČD ne 17:42',\n",
       " 'ČD ne 18:42',\n",
       " 'ČD ne 19:42',\n",
       " 'ČD ne 22:01',\n",
       " 'ČD po 00:36',\n",
       " 'ČD ne 16:42',\n",
       " 'ČD po 00:01',\n",
       " 'ČD po 05:42',\n",
       " 'ČD po 04:39',\n",
       " 'ČD po 06:42',\n",
       " 'ČD po 15:42',\n",
       " 'ČD po 14:42',\n",
       " 'ČD po 13:42',\n",
       " 'ČD po 12:42',\n",
       " 'ČD po 07:42',\n",
       " 'ČD po 09:42',\n",
       " 'ČD po 10:35',\n",
       " 'ČD po 11:42',\n",
       " 'ČD po 08:40',\n",
       " 'ČD po 16:42',\n",
       " 'ČD po 17:42',\n",
       " 'RJ pá 20:47',\n",
       " 'RJ pá 18:16',\n",
       " 'RJ pá 17:16',\n",
       " 'RJ pá 15:16',\n",
       " 'RJ pá 16:16',\n",
       " 'RJ pá 09:16',\n",
       " 'RJ pá 07:16',\n",
       " 'RJ pá 06:13',\n",
       " 'RJ pá 11:16',\n",
       " 'RJ pá 13:16',\n",
       " 'RJ so 20:47',\n",
       " 'RJ so 18:16',\n",
       " 'RJ so 17:16',\n",
       " 'RJ so 16:16',\n",
       " 'RJ so 15:16',\n",
       " 'RJ so 06:13',\n",
       " 'RJ so 07:16',\n",
       " 'RJ so 09:16',\n",
       " 'RJ so 13:16',\n",
       " 'RJ so 11:16',\n",
       " 'RJ ne 06:13',\n",
       " 'RJ ne 20:47',\n",
       " 'RJ ne 18:16',\n",
       " 'RJ ne 17:16',\n",
       " 'RJ ne 16:16',\n",
       " 'RJ ne 15:16',\n",
       " 'RJ ne 13:16',\n",
       " 'RJ ne 11:16',\n",
       " 'RJ ne 09:16',\n",
       " 'RJ ne 07:16']"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[x for x in leden if x not in listopad]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c1f9dd06-7db8-4a6a-9417-db47b5dce1df",
   "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>predstih_h</th>\n",
       "      <th>predstih_d</th>\n",
       "      <th>cena</th>\n",
       "      <th>volnych_mist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>predstih_h</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.999487</td>\n",
       "      <td>0.101949</td>\n",
       "      <td>0.092771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>predstih_d</th>\n",
       "      <td>0.999487</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.101799</td>\n",
       "      <td>0.092779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cena</th>\n",
       "      <td>0.101949</td>\n",
       "      <td>0.101799</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.640644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>volnych_mist</th>\n",
       "      <td>0.092771</td>\n",
       "      <td>0.092779</td>\n",
       "      <td>-0.640644</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              predstih_h  predstih_d      cena  volnych_mist\n",
       "predstih_h      1.000000    0.999487  0.101949      0.092771\n",
       "predstih_d      0.999487    1.000000  0.101799      0.092779\n",
       "cena            0.101949    0.101799  1.000000     -0.640644\n",
       "volnych_mist    0.092771    0.092779 -0.640644      1.000000"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'RJ'][['predstih_h','predstih_d','cena','volnych_mist']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b6975372-c908-460e-ab9e-3007bd36a89b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "obsazenost\n",
       "Předpokládané nízké obsazení                                              329.0\n",
       "Předpokládané střední obsazení - doporučujeme včasné pořízení místenky    359.0\n",
       "Předpokládané vysoké obsazení - doporučujeme včasné pořízení místenky     419.0\n",
       "Téměr vyprodaná místa k sezení                                            329.0\n",
       "Name: cena, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'ČD'].explode('obsazenost').groupby('obsazenost')['cena'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "772a5a0f-9e1f-4f32-b2e9-87f752429935",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.drop_duplicates(subset=['odjezd','odkud','kam','predstih_d'], keep='last').groupby('predstih_d')['cena'].median().plot.bar(figsize=(25,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "e6f35cd1-bdf9-4def-ac78-bd06b2bb881b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.drop_duplicates(subset=['odjezd','odkud','kam','predstih_d'], keep='last').groupby('predstih_d')['cena'].min().plot.bar(figsize=(25,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "897b0ab9-d171-402d-b10f-8c7f926da43b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\micha\\AppData\\Local\\Temp\\ipykernel_5520\\3902872103.py:1: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  df.groupby(['odkud','spoj'])['cena'].min().nsmallest(20)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "odkud  spoj       \n",
       "Brno   RJ ne 05:03     99.0\n",
       "       RJ pá 05:03     99.0\n",
       "       RJ so 05:03     99.0\n",
       "       RJ st 05:03     99.0\n",
       "       RJ út 05:03     99.0\n",
       "       RJ čt 05:03     99.0\n",
       "Praha  RJ po 20:56     99.0\n",
       "       RJ st 20:56     99.0\n",
       "       RJ út 20:56     99.0\n",
       "       RJ čt 20:56     99.0\n",
       "Brno   RJ ne 06:09    179.0\n",
       "       RJ po 05:03    179.0\n",
       "       RJ po 06:09    179.0\n",
       "       RJ po 19:09    179.0\n",
       "       RJ út 18:09    179.0\n",
       "       RJ út 19:09    179.0\n",
       "Praha  RJ ne 06:15    179.0\n",
       "       RJ po 18:15    179.0\n",
       "       RJ po 20:47    179.0\n",
       "       RJ st 06:15    179.0\n",
       "Name: cena, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['odkud','spoj'])['cena'].min().nsmallest(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3dfcb869-7ced-47d6-b781-045cee1d879f",
   "metadata": {},
   "outputs": [],
   "source": [
    "def obdobi(radek):\n",
    "    return f\"\"\"{radek['odjezd'].dayofweek + 1}-{radek['odjezd'].hour // 4}\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "aeda9139-6132-495d-a67a-e3e9b672c933",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['obdobi'] = df.apply(lambda row: obdobi(row), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c44c1ff8-6b30-478f-a5d9-d532a42796fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "obdobi\n",
       "5-3    449.0\n",
       "5-0    435.0\n",
       "5-2    419.0\n",
       "7-0    419.0\n",
       "7-3    419.0\n",
       "5-4    399.0\n",
       "7-4    399.0\n",
       "1-0    379.0\n",
       "3-0    359.0\n",
       "4-2    359.0\n",
       "Name: cena, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(\"obdobi\")['cena'].median().nlargest(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7144bd49-a1d1-4d0a-9404-5ba4a975f80a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['5-3', '5-0', '5-2', '7-0', '7-3']"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spicka = df.groupby(\"obdobi\")['cena'].median().nlargest(5).index.to_list()\n",
    "spicka"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "16f9b1e6-db16-4560-90ec-b5bfc4abc0c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d', ylabel='cena'>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[(df['predstih_d'] <= 28)].plot.scatter(x='predstih_d',y='cena')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "1ce71c64-ff30-4d93-a16e-e7a416a8e0f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.10    299.0\n",
       "0.25    329.0\n",
       "0.33    329.0\n",
       "0.50    359.0\n",
       "0.66    359.0\n",
       "0.75    404.0\n",
       "0.90    449.0\n",
       "1.00    639.0\n",
       "Name: cena, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['predstih_h'] <= 24]['cena'].quantile([0.1,0.25,0.33,0.5,0.66,0.75,0.9,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "2738b931-e98b-46f3-9ceb-b65d9fc9e42a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "spoj\n",
       "ČD pá 00:40    545.0\n",
       "RJ ne 18:15    524.0\n",
       "RJ pá 10:09    524.0\n",
       "ČD ne 00:29    519.0\n",
       "ČD ne 00:40    519.0\n",
       "ČD pá 00:29    519.0\n",
       "ČD so 00:29    519.0\n",
       "ČD so 00:40    519.0\n",
       "ČD st 00:40    519.0\n",
       "ČD út 00:40    519.0\n",
       "ČD čt 00:29    519.0\n",
       "ČD čt 00:40    519.0\n",
       "RJ ne 17:15    499.0\n",
       "ČD po 00:29    479.0\n",
       "ČD po 00:40    479.0\n",
       "ČD st 00:29    479.0\n",
       "ČD út 00:29    479.0\n",
       "ČD pá 12:44    475.0\n",
       "ČD pá 13:44    475.0\n",
       "ČD pá 14:44    475.0\n",
       "Name: cena, dtype: float64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['predstih_h'] <= 24].groupby(\"spoj\")['cena'].median().nlargest(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "bd42c77d-e428-4c11-a42e-172408b8ab0e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "359.0"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['predstih_h'] <= 24]['cena'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "ce26f8b0-4e9b-4d0b-b1ba-1fd2fa9a8637",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['predstih_24h'] = df['predstih_h'] / 24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "8be5bb21-67c2-450d-ab96-02023d2e5faf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_24h', ylabel='cena'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['obdobi'].isin(spicka) & (df['predstih_d'] <= 28)].plot.scatter(x='predstih_24h',y='cena')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2788bbea-4f26-40af-82a8-093ba745dad2",
   "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>oscrapovano</th>\n",
       "      <th>prodejce</th>\n",
       "      <th>odkud</th>\n",
       "      <th>kam</th>\n",
       "      <th>odjezd</th>\n",
       "      <th>predstih</th>\n",
       "      <th>predstih_d</th>\n",
       "      <th>predstih_h</th>\n",
       "      <th>cena</th>\n",
       "      <th>prostredek</th>\n",
       "      <th>volnych_mist</th>\n",
       "      <th>obsazenost</th>\n",
       "      <th>jizdni_doba</th>\n",
       "      <th>vzdalenost</th>\n",
       "      <th>zpozdeni</th>\n",
       "      <th>cena_poznamka</th>\n",
       "      <th>den</th>\n",
       "      <th>prestupy</th>\n",
       "      <th>vlaky</th>\n",
       "      <th>mistenka_zdarma</th>\n",
       "      <th>nahradni_bus</th>\n",
       "      <th>volna_mista_economy</th>\n",
       "      <th>volna_mista_economy_plus</th>\n",
       "      <th>volna_mista_economy_business</th>\n",
       "      <th>volna_mista_premium</th>\n",
       "      <th>spoj</th>\n",
       "      <th>obdobi</th>\n",
       "      <th>predstih_24h</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>469556</th>\n",
       "      <td>2024-11-16 08:09:29</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-17 18:09:00</td>\n",
       "      <td>1 days 09:59:31</td>\n",
       "      <td>1</td>\n",
       "      <td>33.991944</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 18:09</td>\n",
       "      <td>7-4</td>\n",
       "      <td>1.416331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214962</th>\n",
       "      <td>2024-11-09 18:14:10</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-17 12:09:00</td>\n",
       "      <td>7 days 17:54:50</td>\n",
       "      <td>7</td>\n",
       "      <td>185.913889</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 12:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>7.746412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>289719</th>\n",
       "      <td>2024-11-11 18:12:34</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-15 10:09:00</td>\n",
       "      <td>3 days 15:56:26</td>\n",
       "      <td>3</td>\n",
       "      <td>87.940556</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>3.664190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210403</th>\n",
       "      <td>2024-11-09 16:07:55</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-17 12:09:00</td>\n",
       "      <td>7 days 20:01:05</td>\n",
       "      <td>7</td>\n",
       "      <td>188.018056</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 12:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>7.834086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210534</th>\n",
       "      <td>2024-11-09 16:08:19</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-22 14:09:00</td>\n",
       "      <td>12 days 22:00:41</td>\n",
       "      <td>12</td>\n",
       "      <td>310.011389</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 14:09</td>\n",
       "      <td>5-3</td>\n",
       "      <td>12.917141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210571</th>\n",
       "      <td>2024-11-09 16:08:26</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-24 14:09:00</td>\n",
       "      <td>14 days 22:00:34</td>\n",
       "      <td>14</td>\n",
       "      <td>358.009444</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>14.917060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>594963</th>\n",
       "      <td>2024-11-19 12:06:31</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Praha</td>\n",
       "      <td>Brno</td>\n",
       "      <td>2024-11-22 13:15:00</td>\n",
       "      <td>3 days 01:08:29</td>\n",
       "      <td>3</td>\n",
       "      <td>73.141389</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>151.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 13:15</td>\n",
       "      <td>5-3</td>\n",
       "      <td>3.047558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>615426</th>\n",
       "      <td>2024-11-19 22:08:53</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-13 10:09:00</td>\n",
       "      <td>23 days 12:00:07</td>\n",
       "      <td>23</td>\n",
       "      <td>564.001944</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>23.500081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447275</th>\n",
       "      <td>2024-11-15 16:13:33</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 10:09:00</td>\n",
       "      <td>13 days 17:55:27</td>\n",
       "      <td>13</td>\n",
       "      <td>329.924167</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>13.746840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215125</th>\n",
       "      <td>2024-11-09 18:14:42</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-24 14:09:00</td>\n",
       "      <td>14 days 19:54:18</td>\n",
       "      <td>14</td>\n",
       "      <td>355.905000</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>14.829375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210224</th>\n",
       "      <td>2024-11-09 16:07:15</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-10 18:09:00</td>\n",
       "      <td>1 days 02:01:45</td>\n",
       "      <td>1</td>\n",
       "      <td>26.029167</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 18:09</td>\n",
       "      <td>7-4</td>\n",
       "      <td>1.084549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>391906</th>\n",
       "      <td>2024-11-14 08:06:13</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Praha</td>\n",
       "      <td>Brno</td>\n",
       "      <td>2024-11-22 11:15:00</td>\n",
       "      <td>8 days 03:08:47</td>\n",
       "      <td>8</td>\n",
       "      <td>195.146389</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>151.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 11:15</td>\n",
       "      <td>5-2</td>\n",
       "      <td>8.131100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215428</th>\n",
       "      <td>2024-11-09 18:15:42</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-06 10:09:00</td>\n",
       "      <td>26 days 15:53:18</td>\n",
       "      <td>26</td>\n",
       "      <td>639.888333</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>26.662014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>562539</th>\n",
       "      <td>2024-11-18 16:08:37</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-22 08:09:00</td>\n",
       "      <td>3 days 16:00:23</td>\n",
       "      <td>3</td>\n",
       "      <td>88.006389</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 08:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>3.666933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285689</th>\n",
       "      <td>2024-11-11 16:10:27</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-15 10:09:00</td>\n",
       "      <td>3 days 17:58:33</td>\n",
       "      <td>3</td>\n",
       "      <td>89.975833</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>3.748993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219937</th>\n",
       "      <td>2024-11-09 19:14:08</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-17 12:09:00</td>\n",
       "      <td>7 days 16:54:52</td>\n",
       "      <td>7</td>\n",
       "      <td>184.914444</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 12:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>7.704769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220097</th>\n",
       "      <td>2024-11-09 19:14:39</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-24 14:09:00</td>\n",
       "      <td>14 days 18:54:21</td>\n",
       "      <td>14</td>\n",
       "      <td>354.905833</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>14.787743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220235</th>\n",
       "      <td>2024-11-09 19:15:02</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 16:09:00</td>\n",
       "      <td>19 days 20:53:58</td>\n",
       "      <td>19</td>\n",
       "      <td>476.899444</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 16:09</td>\n",
       "      <td>5-4</td>\n",
       "      <td>19.870810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>595002</th>\n",
       "      <td>2024-11-19 12:06:43</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Praha</td>\n",
       "      <td>Brno</td>\n",
       "      <td>2024-11-24 15:15:00</td>\n",
       "      <td>5 days 03:08:17</td>\n",
       "      <td>5</td>\n",
       "      <td>123.138056</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>151.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 15:15</td>\n",
       "      <td>7-3</td>\n",
       "      <td>5.130752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388630</th>\n",
       "      <td>2024-11-14 06:16:11</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 10:09:00</td>\n",
       "      <td>15 days 03:52:49</td>\n",
       "      <td>15</td>\n",
       "      <td>363.880278</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>15.161678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112668</th>\n",
       "      <td>2024-11-06 21:44:41</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-13 10:09:00</td>\n",
       "      <td>36 days 12:24:19</td>\n",
       "      <td>36</td>\n",
       "      <td>876.405278</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>5.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>36.516887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>455095</th>\n",
       "      <td>2024-11-15 19:10:46</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 10:09:00</td>\n",
       "      <td>13 days 14:58:14</td>\n",
       "      <td>13</td>\n",
       "      <td>326.970556</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>13.623773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196986</th>\n",
       "      <td>2024-11-09 10:14:50</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-22 14:09:00</td>\n",
       "      <td>13 days 03:54:10</td>\n",
       "      <td>13</td>\n",
       "      <td>315.902778</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 14:09</td>\n",
       "      <td>5-3</td>\n",
       "      <td>13.162616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458426</th>\n",
       "      <td>2024-11-15 22:09:17</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-16 10:09:00</td>\n",
       "      <td>0 days 11:59:43</td>\n",
       "      <td>0</td>\n",
       "      <td>11.995278</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>so</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ so 10:09</td>\n",
       "      <td>6-2</td>\n",
       "      <td>0.499803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197038</th>\n",
       "      <td>2024-11-09 10:14:59</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-24 14:09:00</td>\n",
       "      <td>15 days 03:54:01</td>\n",
       "      <td>15</td>\n",
       "      <td>363.900278</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>15.162512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296135</th>\n",
       "      <td>2024-11-11 22:08:32</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-06 10:09:00</td>\n",
       "      <td>24 days 12:00:28</td>\n",
       "      <td>24</td>\n",
       "      <td>588.007778</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>24.500324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295989</th>\n",
       "      <td>2024-11-11 22:07:55</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 10:09:00</td>\n",
       "      <td>17 days 12:01:05</td>\n",
       "      <td>17</td>\n",
       "      <td>420.018056</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>17.500752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295988</th>\n",
       "      <td>2024-11-11 22:07:55</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 16:09:00</td>\n",
       "      <td>17 days 18:01:05</td>\n",
       "      <td>17</td>\n",
       "      <td>426.018056</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 16:09</td>\n",
       "      <td>5-4</td>\n",
       "      <td>17.750752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295865</th>\n",
       "      <td>2024-11-11 22:07:30</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-24 14:09:00</td>\n",
       "      <td>12 days 16:01:30</td>\n",
       "      <td>12</td>\n",
       "      <td>304.025000</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>12.667708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201364</th>\n",
       "      <td>2024-11-09 12:14:33</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-22 14:09:00</td>\n",
       "      <td>13 days 01:54:27</td>\n",
       "      <td>13</td>\n",
       "      <td>313.907500</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 14:09</td>\n",
       "      <td>5-3</td>\n",
       "      <td>13.079479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450651</th>\n",
       "      <td>2024-11-15 18:09:36</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 10:09:00</td>\n",
       "      <td>13 days 15:59:24</td>\n",
       "      <td>13</td>\n",
       "      <td>327.990000</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>13.666250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201426</th>\n",
       "      <td>2024-11-09 12:14:44</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-24 14:09:00</td>\n",
       "      <td>15 days 01:54:16</td>\n",
       "      <td>15</td>\n",
       "      <td>361.904444</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>15.079352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512001</th>\n",
       "      <td>2024-11-17 08:13:14</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Praha</td>\n",
       "      <td>Brno</td>\n",
       "      <td>2024-11-17 16:15:00</td>\n",
       "      <td>0 days 08:01:46</td>\n",
       "      <td>0</td>\n",
       "      <td>8.029444</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>151.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 16:15</td>\n",
       "      <td>7-4</td>\n",
       "      <td>0.334560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206266</th>\n",
       "      <td>2024-11-09 14:14:11</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-10 14:09:00</td>\n",
       "      <td>0 days 23:54:49</td>\n",
       "      <td>0</td>\n",
       "      <td>23.913611</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>0.996400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206427</th>\n",
       "      <td>2024-11-09 14:14:48</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-17 12:09:00</td>\n",
       "      <td>7 days 21:54:12</td>\n",
       "      <td>7</td>\n",
       "      <td>189.903333</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 12:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>7.912639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206540</th>\n",
       "      <td>2024-11-09 14:15:12</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-22 14:09:00</td>\n",
       "      <td>12 days 23:53:48</td>\n",
       "      <td>12</td>\n",
       "      <td>311.896667</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 14:09</td>\n",
       "      <td>5-3</td>\n",
       "      <td>12.995694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450952</th>\n",
       "      <td>2024-11-15 18:11:03</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-15 14:09:00</td>\n",
       "      <td>29 days 19:57:57</td>\n",
       "      <td>29</td>\n",
       "      <td>715.965833</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>29.831910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206589</th>\n",
       "      <td>2024-11-09 14:15:25</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-24 14:09:00</td>\n",
       "      <td>14 days 23:53:35</td>\n",
       "      <td>14</td>\n",
       "      <td>359.893056</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>14.995544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>395708</th>\n",
       "      <td>2024-11-14 10:09:30</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Praha</td>\n",
       "      <td>Brno</td>\n",
       "      <td>2024-11-22 11:15:00</td>\n",
       "      <td>8 days 01:05:30</td>\n",
       "      <td>8</td>\n",
       "      <td>193.091667</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>151.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 11:15</td>\n",
       "      <td>5-2</td>\n",
       "      <td>8.045486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112595</th>\n",
       "      <td>2024-11-06 21:44:25</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-06 10:09:00</td>\n",
       "      <td>29 days 12:24:35</td>\n",
       "      <td>29</td>\n",
       "      <td>708.409722</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>29.517072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244388</th>\n",
       "      <td>2024-11-10 12:08:28</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-15 12:09:00</td>\n",
       "      <td>5 days 00:00:32</td>\n",
       "      <td>5</td>\n",
       "      <td>120.008889</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 12:09</td>\n",
       "      <td>5-3</td>\n",
       "      <td>5.000370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570621</th>\n",
       "      <td>2024-11-18 19:05:12</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-15 14:09:00</td>\n",
       "      <td>26 days 19:03:48</td>\n",
       "      <td>26</td>\n",
       "      <td>643.063333</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ ne 14:09</td>\n",
       "      <td>7-3</td>\n",
       "      <td>26.794306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>588473</th>\n",
       "      <td>2024-11-19 08:13:24</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-07 08:09:00</td>\n",
       "      <td>17 days 23:55:36</td>\n",
       "      <td>17</td>\n",
       "      <td>431.926667</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>so</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ so 08:09</td>\n",
       "      <td>6-2</td>\n",
       "      <td>17.996944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232400</th>\n",
       "      <td>2024-11-10 06:13:47</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 16:09:00</td>\n",
       "      <td>19 days 09:55:13</td>\n",
       "      <td>19</td>\n",
       "      <td>465.920278</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 16:09</td>\n",
       "      <td>5-4</td>\n",
       "      <td>19.413345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232530</th>\n",
       "      <td>2024-11-10 06:14:19</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-06 10:09:00</td>\n",
       "      <td>26 days 03:54:41</td>\n",
       "      <td>26</td>\n",
       "      <td>627.911389</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>26.162975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570214</th>\n",
       "      <td>2024-11-18 19:03:55</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 10:09:00</td>\n",
       "      <td>10 days 15:05:05</td>\n",
       "      <td>10</td>\n",
       "      <td>255.084722</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>10.628530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570410</th>\n",
       "      <td>2024-11-18 19:04:33</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-07 08:09:00</td>\n",
       "      <td>18 days 13:04:27</td>\n",
       "      <td>18</td>\n",
       "      <td>445.074167</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>so</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ so 08:09</td>\n",
       "      <td>6-2</td>\n",
       "      <td>18.544757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>570567</th>\n",
       "      <td>2024-11-18 19:05:03</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-12-13 10:09:00</td>\n",
       "      <td>24 days 15:03:57</td>\n",
       "      <td>24</td>\n",
       "      <td>591.065833</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>24.627743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>404795</th>\n",
       "      <td>2024-11-14 14:16:41</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-29 10:09:00</td>\n",
       "      <td>14 days 19:52:19</td>\n",
       "      <td>14</td>\n",
       "      <td>355.871944</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>2.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>14.827998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>269815</th>\n",
       "      <td>2024-11-11 06:12:01</td>\n",
       "      <td>RJ</td>\n",
       "      <td>Brno</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2024-11-15 10:09:00</td>\n",
       "      <td>4 days 03:56:59</td>\n",
       "      <td>4</td>\n",
       "      <td>99.949722</td>\n",
       "      <td>639.0</td>\n",
       "      <td>vlak</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>148.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RJ pá 10:09</td>\n",
       "      <td>5-2</td>\n",
       "      <td>4.164572</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               oscrapovano prodejce  odkud    kam              odjezd  \\\n",
       "469556 2024-11-16 08:09:29       RJ   Brno  Praha 2024-11-17 18:09:00   \n",
       "214962 2024-11-09 18:14:10       RJ   Brno  Praha 2024-11-17 12:09:00   \n",
       "289719 2024-11-11 18:12:34       RJ   Brno  Praha 2024-11-15 10:09:00   \n",
       "210403 2024-11-09 16:07:55       RJ   Brno  Praha 2024-11-17 12:09:00   \n",
       "210534 2024-11-09 16:08:19       RJ   Brno  Praha 2024-11-22 14:09:00   \n",
       "210571 2024-11-09 16:08:26       RJ   Brno  Praha 2024-11-24 14:09:00   \n",
       "594963 2024-11-19 12:06:31       RJ  Praha   Brno 2024-11-22 13:15:00   \n",
       "615426 2024-11-19 22:08:53       RJ   Brno  Praha 2024-12-13 10:09:00   \n",
       "447275 2024-11-15 16:13:33       RJ   Brno  Praha 2024-11-29 10:09:00   \n",
       "215125 2024-11-09 18:14:42       RJ   Brno  Praha 2024-11-24 14:09:00   \n",
       "210224 2024-11-09 16:07:15       RJ   Brno  Praha 2024-11-10 18:09:00   \n",
       "391906 2024-11-14 08:06:13       RJ  Praha   Brno 2024-11-22 11:15:00   \n",
       "215428 2024-11-09 18:15:42       RJ   Brno  Praha 2024-12-06 10:09:00   \n",
       "562539 2024-11-18 16:08:37       RJ   Brno  Praha 2024-11-22 08:09:00   \n",
       "285689 2024-11-11 16:10:27       RJ   Brno  Praha 2024-11-15 10:09:00   \n",
       "219937 2024-11-09 19:14:08       RJ   Brno  Praha 2024-11-17 12:09:00   \n",
       "220097 2024-11-09 19:14:39       RJ   Brno  Praha 2024-11-24 14:09:00   \n",
       "220235 2024-11-09 19:15:02       RJ   Brno  Praha 2024-11-29 16:09:00   \n",
       "595002 2024-11-19 12:06:43       RJ  Praha   Brno 2024-11-24 15:15:00   \n",
       "388630 2024-11-14 06:16:11       RJ   Brno  Praha 2024-11-29 10:09:00   \n",
       "112668 2024-11-06 21:44:41       RJ   Brno  Praha 2024-12-13 10:09:00   \n",
       "455095 2024-11-15 19:10:46       RJ   Brno  Praha 2024-11-29 10:09:00   \n",
       "196986 2024-11-09 10:14:50       RJ   Brno  Praha 2024-11-22 14:09:00   \n",
       "458426 2024-11-15 22:09:17       RJ   Brno  Praha 2024-11-16 10:09:00   \n",
       "197038 2024-11-09 10:14:59       RJ   Brno  Praha 2024-11-24 14:09:00   \n",
       "296135 2024-11-11 22:08:32       RJ   Brno  Praha 2024-12-06 10:09:00   \n",
       "295989 2024-11-11 22:07:55       RJ   Brno  Praha 2024-11-29 10:09:00   \n",
       "295988 2024-11-11 22:07:55       RJ   Brno  Praha 2024-11-29 16:09:00   \n",
       "295865 2024-11-11 22:07:30       RJ   Brno  Praha 2024-11-24 14:09:00   \n",
       "201364 2024-11-09 12:14:33       RJ   Brno  Praha 2024-11-22 14:09:00   \n",
       "450651 2024-11-15 18:09:36       RJ   Brno  Praha 2024-11-29 10:09:00   \n",
       "201426 2024-11-09 12:14:44       RJ   Brno  Praha 2024-11-24 14:09:00   \n",
       "512001 2024-11-17 08:13:14       RJ  Praha   Brno 2024-11-17 16:15:00   \n",
       "206266 2024-11-09 14:14:11       RJ   Brno  Praha 2024-11-10 14:09:00   \n",
       "206427 2024-11-09 14:14:48       RJ   Brno  Praha 2024-11-17 12:09:00   \n",
       "206540 2024-11-09 14:15:12       RJ   Brno  Praha 2024-11-22 14:09:00   \n",
       "450952 2024-11-15 18:11:03       RJ   Brno  Praha 2024-12-15 14:09:00   \n",
       "206589 2024-11-09 14:15:25       RJ   Brno  Praha 2024-11-24 14:09:00   \n",
       "395708 2024-11-14 10:09:30       RJ  Praha   Brno 2024-11-22 11:15:00   \n",
       "112595 2024-11-06 21:44:25       RJ   Brno  Praha 2024-12-06 10:09:00   \n",
       "244388 2024-11-10 12:08:28       RJ   Brno  Praha 2024-11-15 12:09:00   \n",
       "570621 2024-11-18 19:05:12       RJ   Brno  Praha 2024-12-15 14:09:00   \n",
       "588473 2024-11-19 08:13:24       RJ   Brno  Praha 2024-12-07 08:09:00   \n",
       "232400 2024-11-10 06:13:47       RJ   Brno  Praha 2024-11-29 16:09:00   \n",
       "232530 2024-11-10 06:14:19       RJ   Brno  Praha 2024-12-06 10:09:00   \n",
       "570214 2024-11-18 19:03:55       RJ   Brno  Praha 2024-11-29 10:09:00   \n",
       "570410 2024-11-18 19:04:33       RJ   Brno  Praha 2024-12-07 08:09:00   \n",
       "570567 2024-11-18 19:05:03       RJ   Brno  Praha 2024-12-13 10:09:00   \n",
       "404795 2024-11-14 14:16:41       RJ   Brno  Praha 2024-11-29 10:09:00   \n",
       "269815 2024-11-11 06:12:01       RJ   Brno  Praha 2024-11-15 10:09:00   \n",
       "\n",
       "               predstih  predstih_d  predstih_h   cena prostredek  \\\n",
       "469556  1 days 09:59:31           1   33.991944  639.0       vlak   \n",
       "214962  7 days 17:54:50           7  185.913889  639.0       vlak   \n",
       "289719  3 days 15:56:26           3   87.940556  639.0       vlak   \n",
       "210403  7 days 20:01:05           7  188.018056  639.0       vlak   \n",
       "210534 12 days 22:00:41          12  310.011389  639.0       vlak   \n",
       "210571 14 days 22:00:34          14  358.009444  639.0       vlak   \n",
       "594963  3 days 01:08:29           3   73.141389  639.0       vlak   \n",
       "615426 23 days 12:00:07          23  564.001944  639.0       vlak   \n",
       "447275 13 days 17:55:27          13  329.924167  639.0       vlak   \n",
       "215125 14 days 19:54:18          14  355.905000  639.0       vlak   \n",
       "210224  1 days 02:01:45           1   26.029167  639.0       vlak   \n",
       "391906  8 days 03:08:47           8  195.146389  639.0       vlak   \n",
       "215428 26 days 15:53:18          26  639.888333  639.0       vlak   \n",
       "562539  3 days 16:00:23           3   88.006389  639.0       vlak   \n",
       "285689  3 days 17:58:33           3   89.975833  639.0       vlak   \n",
       "219937  7 days 16:54:52           7  184.914444  639.0       vlak   \n",
       "220097 14 days 18:54:21          14  354.905833  639.0       vlak   \n",
       "220235 19 days 20:53:58          19  476.899444  639.0       vlak   \n",
       "595002  5 days 03:08:17           5  123.138056  639.0       vlak   \n",
       "388630 15 days 03:52:49          15  363.880278  639.0       vlak   \n",
       "112668 36 days 12:24:19          36  876.405278  639.0       vlak   \n",
       "455095 13 days 14:58:14          13  326.970556  639.0       vlak   \n",
       "196986 13 days 03:54:10          13  315.902778  639.0       vlak   \n",
       "458426  0 days 11:59:43           0   11.995278  639.0       vlak   \n",
       "197038 15 days 03:54:01          15  363.900278  639.0       vlak   \n",
       "296135 24 days 12:00:28          24  588.007778  639.0       vlak   \n",
       "295989 17 days 12:01:05          17  420.018056  639.0       vlak   \n",
       "295988 17 days 18:01:05          17  426.018056  639.0       vlak   \n",
       "295865 12 days 16:01:30          12  304.025000  639.0       vlak   \n",
       "201364 13 days 01:54:27          13  313.907500  639.0       vlak   \n",
       "450651 13 days 15:59:24          13  327.990000  639.0       vlak   \n",
       "201426 15 days 01:54:16          15  361.904444  639.0       vlak   \n",
       "512001  0 days 08:01:46           0    8.029444  639.0       vlak   \n",
       "206266  0 days 23:54:49           0   23.913611  639.0       vlak   \n",
       "206427  7 days 21:54:12           7  189.903333  639.0       vlak   \n",
       "206540 12 days 23:53:48          12  311.896667  639.0       vlak   \n",
       "450952 29 days 19:57:57          29  715.965833  639.0       vlak   \n",
       "206589 14 days 23:53:35          14  359.893056  639.0       vlak   \n",
       "395708  8 days 01:05:30           8  193.091667  639.0       vlak   \n",
       "112595 29 days 12:24:35          29  708.409722  639.0       vlak   \n",
       "244388  5 days 00:00:32           5  120.008889  639.0       vlak   \n",
       "570621 26 days 19:03:48          26  643.063333  639.0       vlak   \n",
       "588473 17 days 23:55:36          17  431.926667  639.0       vlak   \n",
       "232400 19 days 09:55:13          19  465.920278  639.0       vlak   \n",
       "232530 26 days 03:54:41          26  627.911389  639.0       vlak   \n",
       "570214 10 days 15:05:05          10  255.084722  639.0       vlak   \n",
       "570410 18 days 13:04:27          18  445.074167  639.0       vlak   \n",
       "570567 24 days 15:03:57          24  591.065833  639.0       vlak   \n",
       "404795 14 days 19:52:19          14  355.871944  639.0       vlak   \n",
       "269815  4 days 03:56:59           4   99.949722  639.0       vlak   \n",
       "\n",
       "        volnych_mist obsazenost  jizdni_doba  vzdalenost zpozdeni  \\\n",
       "469556           2.0       None        148.0         NaN     None   \n",
       "214962           1.0       None        148.0         NaN     None   \n",
       "289719           1.0       None        148.0         NaN     None   \n",
       "210403           2.0       None        148.0         NaN     None   \n",
       "210534           2.0       None        148.0         NaN     None   \n",
       "210571           1.0       None        148.0         NaN     None   \n",
       "594963           2.0       None        151.0         NaN     None   \n",
       "615426           1.0       None        148.0         NaN     None   \n",
       "447275           2.0       None        148.0         NaN     None   \n",
       "215125           1.0       None        148.0         NaN     None   \n",
       "210224           1.0       None        148.0         NaN     None   \n",
       "391906           1.0       None        151.0         NaN     None   \n",
       "215428           1.0       None        148.0         NaN     None   \n",
       "562539           1.0       None        148.0         NaN     None   \n",
       "285689           1.0       None        148.0         NaN     None   \n",
       "219937           1.0       None        148.0         NaN     None   \n",
       "220097           1.0       None        148.0         NaN     None   \n",
       "220235           2.0       None        148.0         NaN     None   \n",
       "595002           2.0       None        151.0         NaN     None   \n",
       "388630           2.0       None        148.0         NaN     None   \n",
       "112668           5.0       None        148.0         NaN     None   \n",
       "455095           2.0       None        148.0         NaN     None   \n",
       "196986           2.0       None        148.0         NaN     None   \n",
       "458426           2.0       None        148.0         NaN     None   \n",
       "197038           1.0       None        148.0         NaN     None   \n",
       "296135           1.0       None        148.0         NaN     None   \n",
       "295989           2.0       None        148.0         NaN     None   \n",
       "295988           1.0       None        148.0         NaN     None   \n",
       "295865           1.0       None        148.0         NaN     None   \n",
       "201364           2.0       None        148.0         NaN     None   \n",
       "450651           2.0       None        148.0         NaN     None   \n",
       "201426           1.0       None        148.0         NaN     None   \n",
       "512001           1.0       None        151.0         NaN     None   \n",
       "206266           1.0       None        148.0         NaN     None   \n",
       "206427           2.0       None        148.0         NaN     None   \n",
       "206540           2.0       None        148.0         NaN     None   \n",
       "450952           2.0       None        150.0         NaN     None   \n",
       "206589           1.0       None        148.0         NaN     None   \n",
       "395708           1.0       None        151.0         NaN     None   \n",
       "112595           1.0       None        148.0         NaN     None   \n",
       "244388           1.0       None        148.0         NaN     None   \n",
       "570621           1.0       None        150.0         NaN     None   \n",
       "588473           1.0       None        148.0         NaN     None   \n",
       "232400           2.0       None        148.0         NaN     None   \n",
       "232530           1.0       None        148.0         NaN     None   \n",
       "570214           1.0       None        148.0         NaN     None   \n",
       "570410           1.0       None        148.0         NaN     None   \n",
       "570567           2.0       None        148.0         NaN     None   \n",
       "404795           2.0       None        148.0         NaN     None   \n",
       "269815           1.0       None        148.0         NaN     None   \n",
       "\n",
       "       cena_poznamka den  prestupy vlaky mistenka_zdarma nahradni_bus  \\\n",
       "469556          None  ne         0  None            None         None   \n",
       "214962          None  ne         0  None            None         None   \n",
       "289719          None  pá         0  None            None         None   \n",
       "210403          None  ne         0  None            None         None   \n",
       "210534          None  pá         0  None            None         None   \n",
       "210571          None  ne         0  None            None         None   \n",
       "594963          None  pá         0  None            None         None   \n",
       "615426          None  pá         0  None            None         None   \n",
       "447275          None  pá         0  None            None         None   \n",
       "215125          None  ne         0  None            None         None   \n",
       "210224          None  ne         0  None            None         None   \n",
       "391906          None  pá         0  None            None         None   \n",
       "215428          None  pá         0  None            None         None   \n",
       "562539          None  pá         0  None            None         None   \n",
       "285689          None  pá         0  None            None         None   \n",
       "219937          None  ne         0  None            None         None   \n",
       "220097          None  ne         0  None            None         None   \n",
       "220235          None  pá         0  None            None         None   \n",
       "595002          None  ne         0  None            None         None   \n",
       "388630          None  pá         0  None            None         None   \n",
       "112668          None  pá         0  None            None         None   \n",
       "455095          None  pá         0  None            None         None   \n",
       "196986          None  pá         0  None            None         None   \n",
       "458426          None  so         0  None            None         None   \n",
       "197038          None  ne         0  None            None         None   \n",
       "296135          None  pá         0  None            None         None   \n",
       "295989          None  pá         0  None            None         None   \n",
       "295988          None  pá         0  None            None         None   \n",
       "295865          None  ne         0  None            None         None   \n",
       "201364          None  pá         0  None            None         None   \n",
       "450651          None  pá         0  None            None         None   \n",
       "201426          None  ne         0  None            None         None   \n",
       "512001          None  ne         0  None            None         None   \n",
       "206266          None  ne         0  None            None         None   \n",
       "206427          None  ne         0  None            None         None   \n",
       "206540          None  pá         0  None            None         None   \n",
       "450952          None  ne         0  None            None         None   \n",
       "206589          None  ne         0  None            None         None   \n",
       "395708          None  pá         0  None            None         None   \n",
       "112595          None  pá         0  None            None         None   \n",
       "244388          None  pá         0  None            None         None   \n",
       "570621          None  ne         0  None            None         None   \n",
       "588473          None  so         0  None            None         None   \n",
       "232400          None  pá         0  None            None         None   \n",
       "232530          None  pá         0  None            None         None   \n",
       "570214          None  pá         0  None            None         None   \n",
       "570410          None  so         0  None            None         None   \n",
       "570567          None  pá         0  None            None         None   \n",
       "404795          None  pá         0  None            None         None   \n",
       "269815          None  pá         0  None            None         None   \n",
       "\n",
       "        volna_mista_economy  volna_mista_economy_plus  \\\n",
       "469556                  NaN                       NaN   \n",
       "214962                  NaN                       NaN   \n",
       "289719                  NaN                       NaN   \n",
       "210403                  NaN                       NaN   \n",
       "210534                  NaN                       NaN   \n",
       "210571                  NaN                       NaN   \n",
       "594963                  NaN                       NaN   \n",
       "615426                  NaN                       NaN   \n",
       "447275                  NaN                       NaN   \n",
       "215125                  NaN                       NaN   \n",
       "210224                  NaN                       NaN   \n",
       "391906                  NaN                       NaN   \n",
       "215428                  NaN                       NaN   \n",
       "562539                  NaN                       NaN   \n",
       "285689                  NaN                       NaN   \n",
       "219937                  NaN                       NaN   \n",
       "220097                  NaN                       NaN   \n",
       "220235                  NaN                       NaN   \n",
       "595002                  NaN                       NaN   \n",
       "388630                  NaN                       NaN   \n",
       "112668                  NaN                       NaN   \n",
       "455095                  NaN                       NaN   \n",
       "196986                  NaN                       NaN   \n",
       "458426                  NaN                       NaN   \n",
       "197038                  NaN                       NaN   \n",
       "296135                  NaN                       NaN   \n",
       "295989                  NaN                       NaN   \n",
       "295988                  NaN                       NaN   \n",
       "295865                  NaN                       NaN   \n",
       "201364                  NaN                       NaN   \n",
       "450651                  NaN                       NaN   \n",
       "201426                  NaN                       NaN   \n",
       "512001                  NaN                       NaN   \n",
       "206266                  NaN                       NaN   \n",
       "206427                  NaN                       NaN   \n",
       "206540                  NaN                       NaN   \n",
       "450952                  NaN                       NaN   \n",
       "206589                  NaN                       NaN   \n",
       "395708                  NaN                       NaN   \n",
       "112595                  NaN                       NaN   \n",
       "244388                  NaN                       NaN   \n",
       "570621                  NaN                       NaN   \n",
       "588473                  NaN                       NaN   \n",
       "232400                  NaN                       NaN   \n",
       "232530                  NaN                       NaN   \n",
       "570214                  NaN                       NaN   \n",
       "570410                  NaN                       NaN   \n",
       "570567                  NaN                       NaN   \n",
       "404795                  NaN                       NaN   \n",
       "269815                  NaN                       NaN   \n",
       "\n",
       "        volna_mista_economy_business  volna_mista_premium         spoj obdobi  \\\n",
       "469556                           NaN                  NaN  RJ ne 18:09    7-4   \n",
       "214962                           NaN                  NaN  RJ ne 12:09    7-3   \n",
       "289719                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "210403                           NaN                  NaN  RJ ne 12:09    7-3   \n",
       "210534                           NaN                  NaN  RJ pá 14:09    5-3   \n",
       "210571                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "594963                           NaN                  NaN  RJ pá 13:15    5-3   \n",
       "615426                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "447275                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "215125                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "210224                           NaN                  NaN  RJ ne 18:09    7-4   \n",
       "391906                           NaN                  NaN  RJ pá 11:15    5-2   \n",
       "215428                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "562539                           NaN                  NaN  RJ pá 08:09    5-2   \n",
       "285689                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "219937                           NaN                  NaN  RJ ne 12:09    7-3   \n",
       "220097                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "220235                           NaN                  NaN  RJ pá 16:09    5-4   \n",
       "595002                           NaN                  NaN  RJ ne 15:15    7-3   \n",
       "388630                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "112668                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "455095                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "196986                           NaN                  NaN  RJ pá 14:09    5-3   \n",
       "458426                           NaN                  NaN  RJ so 10:09    6-2   \n",
       "197038                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "296135                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "295989                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "295988                           NaN                  NaN  RJ pá 16:09    5-4   \n",
       "295865                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "201364                           NaN                  NaN  RJ pá 14:09    5-3   \n",
       "450651                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "201426                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "512001                           NaN                  NaN  RJ ne 16:15    7-4   \n",
       "206266                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "206427                           NaN                  NaN  RJ ne 12:09    7-3   \n",
       "206540                           NaN                  NaN  RJ pá 14:09    5-3   \n",
       "450952                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "206589                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "395708                           NaN                  NaN  RJ pá 11:15    5-2   \n",
       "112595                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "244388                           NaN                  NaN  RJ pá 12:09    5-3   \n",
       "570621                           NaN                  NaN  RJ ne 14:09    7-3   \n",
       "588473                           NaN                  NaN  RJ so 08:09    6-2   \n",
       "232400                           NaN                  NaN  RJ pá 16:09    5-4   \n",
       "232530                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "570214                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "570410                           NaN                  NaN  RJ so 08:09    6-2   \n",
       "570567                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "404795                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "269815                           NaN                  NaN  RJ pá 10:09    5-2   \n",
       "\n",
       "        predstih_24h  \n",
       "469556      1.416331  \n",
       "214962      7.746412  \n",
       "289719      3.664190  \n",
       "210403      7.834086  \n",
       "210534     12.917141  \n",
       "210571     14.917060  \n",
       "594963      3.047558  \n",
       "615426     23.500081  \n",
       "447275     13.746840  \n",
       "215125     14.829375  \n",
       "210224      1.084549  \n",
       "391906      8.131100  \n",
       "215428     26.662014  \n",
       "562539      3.666933  \n",
       "285689      3.748993  \n",
       "219937      7.704769  \n",
       "220097     14.787743  \n",
       "220235     19.870810  \n",
       "595002      5.130752  \n",
       "388630     15.161678  \n",
       "112668     36.516887  \n",
       "455095     13.623773  \n",
       "196986     13.162616  \n",
       "458426      0.499803  \n",
       "197038     15.162512  \n",
       "296135     24.500324  \n",
       "295989     17.500752  \n",
       "295988     17.750752  \n",
       "295865     12.667708  \n",
       "201364     13.079479  \n",
       "450651     13.666250  \n",
       "201426     15.079352  \n",
       "512001      0.334560  \n",
       "206266      0.996400  \n",
       "206427      7.912639  \n",
       "206540     12.995694  \n",
       "450952     29.831910  \n",
       "206589     14.995544  \n",
       "395708      8.045486  \n",
       "112595     29.517072  \n",
       "244388      5.000370  \n",
       "570621     26.794306  \n",
       "588473     17.996944  \n",
       "232400     19.413345  \n",
       "232530     26.162975  \n",
       "570214     10.628530  \n",
       "570410     18.544757  \n",
       "570567     24.627743  \n",
       "404795     14.827998  \n",
       "269815      4.164572  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=\"cena\",ascending=False).head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "64365208-6b09-4441-849d-0242faa482a1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "predstih_d\n",
       "0     359.0\n",
       "1     359.0\n",
       "2     359.0\n",
       "3     359.0\n",
       "4     329.0\n",
       "5     329.0\n",
       "6     359.0\n",
       "7     359.0\n",
       "8     329.0\n",
       "9     329.0\n",
       "10    329.0\n",
       "11    329.0\n",
       "12    329.0\n",
       "13    329.0\n",
       "14    329.0\n",
       "15    329.0\n",
       "16    329.0\n",
       "18    329.0\n",
       "20    329.0\n",
       "22    329.0\n",
       "23    329.0\n",
       "25    329.0\n",
       "26    329.0\n",
       "28    329.0\n",
       "30    329.0\n",
       "33    329.0\n",
       "34    329.0\n",
       "36    329.0\n",
       "37    329.0\n",
       "45    329.0\n",
       "46    329.0\n",
       "47    329.0\n",
       "58    329.0\n",
       "59    329.0\n",
       "60      NaN\n",
       "64      NaN\n",
       "66      NaN\n",
       "67      NaN\n",
       "68      NaN\n",
       "74      NaN\n",
       "75      NaN\n",
       "76      NaN\n",
       "77      NaN\n",
       "78      NaN\n",
       "79      NaN\n",
       "80      NaN\n",
       "88      NaN\n",
       "Name: cena, dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['spoj'] == 'ČD čt 09:39'].groupby(\"predstih_d\")['cena'].median()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.12.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}