110_prg_ova_cena.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "7a6b7e19-2c3d-4d28-92cd-726936832c66",
   "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": 224,
   "id": "1617ea2b-412c-431b-91f2-8ad580a6f577",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_parquet(os.path.join('data','jizdenky.parquet'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "id": "159f06d9-afd8-4688-afc5-c8c978042b24",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['odkud'].str.contains('Ostrava') | df['odkud'].str.contains('Praha')]\n",
    "df = df[df['kam'].str.contains('Ostrava') | df['kam'].str.contains('Praha')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "id": "f4ad1d77-4d6e-4294-bcd7-b4f81d1c5dd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['prostredek'] != 'autobus']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "id": "656d6523-bd0f-41c2-bb86-457eccab1b97",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['predstih_d'] >= 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "id": "c4ee47b3-2b95-4750-bb32-f616332fe46a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['prestupy'] == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "id": "b22cd96e-24d1-49a7-b2fc-8dfdc05b4679",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.100    351.0\n",
       "0.250    356.0\n",
       "0.500    356.0\n",
       "0.750    356.0\n",
       "0.666    356.0\n",
       "0.800    356.0\n",
       "0.900    356.0\n",
       "0.950    356.0\n",
       "Name: vzdalenost, dtype: float64"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['vzdalenost'].quantile([0.1,0.25,0.5,0.75,0.666,0.8,0.9,0.95])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "id": "6483b743-727c-4bfe-8300-b2372b3bc564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.100    189.0\n",
       "0.250    192.0\n",
       "0.500    202.0\n",
       "0.750    209.0\n",
       "0.666    204.0\n",
       "0.800    209.0\n",
       "0.900    212.0\n",
       "0.950    216.0\n",
       "Name: jizdni_doba, dtype: float64"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['jizdni_doba'].quantile([0.1,0.25,0.5,0.75,0.666,0.8,0.9,0.95])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "id": "201b8579-9688-48ef-b68e-698bcdd78d27",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "216.0"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nejdelsi = df['jizdni_doba'].quantile(0.95)\n",
    "nejdelsi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "id": "d8fb7a81-f7a3-4804-9519-4720a7082846",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['jizdni_doba'] <= nejdelsi]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "d738dba3-cdd0-4291-ad0f-cd7e8e890e57",
   "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": 234,
   "id": "733df5de-4c35-49cb-85d2-6d37d9d1b5eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['LE ne 15:57',\n",
       " 'LE ne 16:00',\n",
       " 'LE ne 16:04',\n",
       " 'LE pá 11:00',\n",
       " 'LE pá 13:00',\n",
       " 'LE pá 13:07']"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nejdrazsi = df[df['predstih_h'] <= 4].groupby('spoj')['cena'].median()\n",
    "nejdrazsi = nejdrazsi[nejdrazsi >= 1000].index.to_list()\n",
    "nejdrazsi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "35436c15-aa12-42de-b192-756dde62733a",
   "metadata": {},
   "outputs": [],
   "source": [
    "medianovacena = df['cena'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "id": "b26eedfd-8e6a-49fb-91ec-67c0545321ba",
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>167849</th>\n",
       "      <td>2024-11-08 20:27:17</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>27 days 14:32:43</td>\n",
       "      <td>27</td>\n",
       "      <td>662.545278</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>55.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167850</th>\n",
       "      <td>2024-11-08 20:27:17</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>27 days 14:32:43</td>\n",
       "      <td>27</td>\n",
       "      <td>662.545278</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>55.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189031</th>\n",
       "      <td>2024-11-09 06:23:25</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>27 days 04:36:35</td>\n",
       "      <td>27</td>\n",
       "      <td>652.609722</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>55.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189032</th>\n",
       "      <td>2024-11-09 06:23:25</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>27 days 04:36:35</td>\n",
       "      <td>27</td>\n",
       "      <td>652.609722</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>55.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202288</th>\n",
       "      <td>2024-11-09 12:25:36</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-11-29 11:00:00</td>\n",
       "      <td>19 days 22:34:24</td>\n",
       "      <td>19</td>\n",
       "      <td>478.573333</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>47.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202293</th>\n",
       "      <td>2024-11-09 12:25:36</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-11-29 11:00:00</td>\n",
       "      <td>19 days 22:34:24</td>\n",
       "      <td>19</td>\n",
       "      <td>478.573333</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>47.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381637</th>\n",
       "      <td>2024-11-13 22:24:42</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>22 days 12:35:18</td>\n",
       "      <td>22</td>\n",
       "      <td>540.588333</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381638</th>\n",
       "      <td>2024-11-13 22:24:42</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>22 days 12:35:18</td>\n",
       "      <td>22</td>\n",
       "      <td>540.588333</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384664</th>\n",
       "      <td>2024-11-14 00:18:44</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>22 days 10:41:16</td>\n",
       "      <td>22</td>\n",
       "      <td>538.687778</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384665</th>\n",
       "      <td>2024-11-14 00:18:44</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>22 days 10:41:16</td>\n",
       "      <td>22</td>\n",
       "      <td>538.687778</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397400</th>\n",
       "      <td>2024-11-14 10:24:07</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>22 days 00:35:53</td>\n",
       "      <td>22</td>\n",
       "      <td>528.598056</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>397401</th>\n",
       "      <td>2024-11-14 10:24:07</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>22 days 00:35:53</td>\n",
       "      <td>22</td>\n",
       "      <td>528.598056</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443710</th>\n",
       "      <td>2024-11-15 14:18:49</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>20 days 20:41:11</td>\n",
       "      <td>20</td>\n",
       "      <td>500.686389</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443717</th>\n",
       "      <td>2024-11-15 14:18:49</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-12-06 11:00:00</td>\n",
       "      <td>20 days 20:41:11</td>\n",
       "      <td>20</td>\n",
       "      <td>500.686389</td>\n",
       "      <td>699.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491500</th>\n",
       "      <td>2024-11-16 18:21:25</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-12-13 11:00:00</td>\n",
       "      <td>26 days 16:38:35</td>\n",
       "      <td>26</td>\n",
       "      <td>640.643056</td>\n",
       "      <td>519.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491501</th>\n",
       "      <td>2024-11-16 18:21:25</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-12-13 11:00:00</td>\n",
       "      <td>26 days 16:38:35</td>\n",
       "      <td>26</td>\n",
       "      <td>640.643056</td>\n",
       "      <td>519.0</td>\n",
       "      <td>None</td>\n",
       "      <td>52.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1257]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>21.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>LE pá 11:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               oscrapovano prodejce        odkud             kam  \\\n",
       "167849 2024-11-08 20:27:17       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "167850 2024-11-08 20:27:17       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "189031 2024-11-09 06:23:25       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "189032 2024-11-09 06:23:25       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "202288 2024-11-09 12:25:36       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "202293 2024-11-09 12:25:36       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "381637 2024-11-13 22:24:42       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "381638 2024-11-13 22:24:42       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "384664 2024-11-14 00:18:44       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "384665 2024-11-14 00:18:44       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "397400 2024-11-14 10:24:07       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "397401 2024-11-14 10:24:07       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "443710 2024-11-15 14:18:49       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "443717 2024-11-15 14:18:49       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "491500 2024-11-16 18:21:25       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "491501 2024-11-16 18:21:25       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "\n",
       "                    odjezd         predstih  predstih_d  predstih_h   cena  \\\n",
       "167849 2024-12-06 11:00:00 27 days 14:32:43          27  662.545278  699.0   \n",
       "167850 2024-12-06 11:00:00 27 days 14:32:43          27  662.545278  699.0   \n",
       "189031 2024-12-06 11:00:00 27 days 04:36:35          27  652.609722  699.0   \n",
       "189032 2024-12-06 11:00:00 27 days 04:36:35          27  652.609722  699.0   \n",
       "202288 2024-11-29 11:00:00 19 days 22:34:24          19  478.573333  699.0   \n",
       "202293 2024-11-29 11:00:00 19 days 22:34:24          19  478.573333  699.0   \n",
       "381637 2024-12-06 11:00:00 22 days 12:35:18          22  540.588333  699.0   \n",
       "381638 2024-12-06 11:00:00 22 days 12:35:18          22  540.588333  699.0   \n",
       "384664 2024-12-06 11:00:00 22 days 10:41:16          22  538.687778  699.0   \n",
       "384665 2024-12-06 11:00:00 22 days 10:41:16          22  538.687778  699.0   \n",
       "397400 2024-12-06 11:00:00 22 days 00:35:53          22  528.598056  699.0   \n",
       "397401 2024-12-06 11:00:00 22 days 00:35:53          22  528.598056  699.0   \n",
       "443710 2024-12-06 11:00:00 20 days 20:41:11          20  500.686389  699.0   \n",
       "443717 2024-12-06 11:00:00 20 days 20:41:11          20  500.686389  699.0   \n",
       "491500 2024-12-13 11:00:00 26 days 16:38:35          26  640.643056  519.0   \n",
       "491501 2024-12-13 11:00:00 26 days 16:38:35          26  640.643056  519.0   \n",
       "\n",
       "       prostredek  volnych_mist obsazenost  jizdni_doba  vzdalenost zpozdeni  \\\n",
       "167849       None          55.0       None        211.0       356.0     None   \n",
       "167850       None          55.0       None        204.0       351.0     None   \n",
       "189031       None          55.0       None        204.0       351.0     None   \n",
       "189032       None          55.0       None        211.0       356.0     None   \n",
       "202288       None          47.0       None        211.0       356.0     None   \n",
       "202293       None          47.0       None        204.0       351.0     None   \n",
       "381637       None          52.0       None        204.0       351.0     None   \n",
       "381638       None          52.0       None        211.0       356.0     None   \n",
       "384664       None          52.0       None        211.0       356.0     None   \n",
       "384665       None          52.0       None        204.0       351.0     None   \n",
       "397400       None          52.0       None        211.0       356.0     None   \n",
       "397401       None          52.0       None        204.0       351.0     None   \n",
       "443710       None          52.0       None        211.0       356.0     None   \n",
       "443717       None          52.0       None        204.0       351.0     None   \n",
       "491500       None          52.0       None        211.0       356.0     None   \n",
       "491501       None          52.0       None        204.0       351.0     None   \n",
       "\n",
       "       cena_poznamka den  prestupy     vlaky mistenka_zdarma nahradni_bus  \\\n",
       "167849          None  pá         0  [LE1257]            None         None   \n",
       "167850          None  pá         0  [LE1257]            None         None   \n",
       "189031          None  pá         0  [LE1257]            None         None   \n",
       "189032          None  pá         0  [LE1257]            None         None   \n",
       "202288          None  pá         0  [LE1257]            None         None   \n",
       "202293          None  pá         0  [LE1257]            None         None   \n",
       "381637          None  pá         0  [LE1257]            None         None   \n",
       "381638          None  pá         0  [LE1257]            None         None   \n",
       "384664          None  pá         0  [LE1257]            None         None   \n",
       "384665          None  pá         0  [LE1257]            None         None   \n",
       "397400          None  pá         0  [LE1257]            None         None   \n",
       "397401          None  pá         0  [LE1257]            None         None   \n",
       "443710          None  pá         0  [LE1257]            None         None   \n",
       "443717          None  pá         0  [LE1257]            None         None   \n",
       "491500          None  pá         0  [LE1257]            None         None   \n",
       "491501          None  pá         0  [LE1257]            None         None   \n",
       "\n",
       "        volna_mista_economy  volna_mista_economy_plus  \\\n",
       "167849                 21.0                      15.0   \n",
       "167850                 21.0                      15.0   \n",
       "189031                 21.0                      15.0   \n",
       "189032                 21.0                      15.0   \n",
       "202288                 21.0                      13.0   \n",
       "202293                 21.0                      13.0   \n",
       "381637                 21.0                      14.0   \n",
       "381638                 21.0                      14.0   \n",
       "384664                 21.0                      14.0   \n",
       "384665                 21.0                      14.0   \n",
       "397400                 21.0                      14.0   \n",
       "397401                 21.0                      14.0   \n",
       "443710                 21.0                      14.0   \n",
       "443717                 21.0                      14.0   \n",
       "491500                 21.0                      13.0   \n",
       "491501                 21.0                      13.0   \n",
       "\n",
       "        volna_mista_economy_business  volna_mista_premium         spoj  \n",
       "167849                          14.0                  5.0  LE pá 11:00  \n",
       "167850                          14.0                  5.0  LE pá 11:00  \n",
       "189031                          14.0                  5.0  LE pá 11:00  \n",
       "189032                          14.0                  5.0  LE pá 11:00  \n",
       "202288                          11.0                  2.0  LE pá 11:00  \n",
       "202293                          11.0                  2.0  LE pá 11:00  \n",
       "381637                          13.0                  4.0  LE pá 11:00  \n",
       "381638                          13.0                  4.0  LE pá 11:00  \n",
       "384664                          13.0                  4.0  LE pá 11:00  \n",
       "384665                          13.0                  4.0  LE pá 11:00  \n",
       "397400                          13.0                  4.0  LE pá 11:00  \n",
       "397401                          13.0                  4.0  LE pá 11:00  \n",
       "443710                          13.0                  4.0  LE pá 11:00  \n",
       "443717                          13.0                  4.0  LE pá 11:00  \n",
       "491500                          13.0                  5.0  LE pá 11:00  \n",
       "491501                          13.0                  5.0  LE pá 11:00  "
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['spoj'].isin(nejdrazsi) & (df['cena'] <= (medianovacena * 1.5))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "id": "03384eb6-bfc7-4643-817e-c517c029dd94",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2279.0"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'LE']['cena'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "4ed767ac-9ed3-4ab0-99af-886377f57eeb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "99.0"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'LE']['cena'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "id": "be91fdad-e824-410c-aa81-4dd04707f77c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23.02020202020202"
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'LE']['cena'].max() / df[df['prodejce'] == 'LE']['cena'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "14c0cba0-787f-4ac1-a67b-2562e0b4f540",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 240,
     "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'].isin(['RJ','LE'])].groupby('predstih_d')['cena'].median().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "id": "a4ed5a31-9597-4106-9f2f-182a8ecf25d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 241,
     "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[df['prodejce'] == 'ČD'].groupby('predstih_d')['cena'].median().plot.bar(figsize=(25,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "c5d55c0a-0095-4e5f-b755-a7744c34ecd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 242,
     "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'] == 'RJ'].groupby('predstih_d')['cena'].median().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "id": "4913ff2c-639c-44b7-9af4-193fd25aa5fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 243,
     "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'] == 'LE'].groupby('predstih_d')['cena'].median().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "id": "de44b0fd-592d-4bec-afd0-1978a8f5767e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "spoj\n",
       "RJ pá 11:50     0.0\n",
       "RJ čt 14:53     0.0\n",
       "RJ ne 10:53     0.0\n",
       "RJ pá 16:53     0.0\n",
       "RJ so 10:53     0.0\n",
       "RJ st 06:52     0.0\n",
       "RJ ne 18:53     0.0\n",
       "RJ ne 16:50     0.0\n",
       "RJ pá 09:50     0.0\n",
       "RJ ne 17:50     0.0\n",
       "RJ čt 17:50     1.0\n",
       "RJ ne 16:53     1.5\n",
       "RJ čt 16:50     2.0\n",
       "RJ pá 13:50     2.0\n",
       "RJ pá 16:50     2.0\n",
       "RJ pá 15:50     2.0\n",
       "RJ ne 13:50     2.5\n",
       "RJ pá 07:53     3.0\n",
       "RJ pá 14:53     4.0\n",
       "RJ ne 14:53     4.0\n",
       "RJ pá 10:53     5.0\n",
       "RJ ne 12:53     5.5\n",
       "RJ so 14:50     6.0\n",
       "RJ pá 14:50     6.0\n",
       "RJ ne 07:50     7.0\n",
       "RJ čt 14:50     7.0\n",
       "RJ ne 14:50     7.0\n",
       "RJ po 07:50     8.0\n",
       "RJ po 14:50     9.0\n",
       "RJ čt 12:53    10.0\n",
       "RJ út 08:53    10.0\n",
       "RJ pá 12:53    10.0\n",
       "RJ pá 08:53    10.0\n",
       "RJ so 08:53    10.0\n",
       "RJ čt 08:53    11.0\n",
       "RJ st 08:53    11.5\n",
       "RJ po 12:53    13.0\n",
       "RJ čt 07:50    13.0\n",
       "RJ so 07:50    13.0\n",
       "RJ ne 08:53    15.0\n",
       "RJ st 14:50    16.0\n",
       "RJ st 12:53    17.0\n",
       "RJ so 12:53    20.5\n",
       "Name: predstih_d, dtype: float64"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['volnych_mist'] == 0].groupby('spoj')['predstih_d'].median().sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "f9b66969-a4c7-4278-bf23-8841289081bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "spoj\n",
       "RJ ne 17:50     0\n",
       "RJ pá 09:50     0\n",
       "RJ st 06:52     0\n",
       "RJ ne 18:53     0\n",
       "RJ pá 16:53     0\n",
       "RJ pá 11:50     0\n",
       "RJ so 10:53     0\n",
       "RJ čt 14:53     0\n",
       "RJ ne 16:50     1\n",
       "RJ ne 10:53     1\n",
       "RJ čt 17:50     1\n",
       "RJ pá 13:50     3\n",
       "RJ čt 16:50     3\n",
       "RJ pá 16:50     4\n",
       "RJ pá 15:50     4\n",
       "RJ ne 16:53     5\n",
       "RJ pá 14:53     5\n",
       "RJ ne 13:50     5\n",
       "RJ pá 07:53     6\n",
       "RJ so 14:50     7\n",
       "RJ ne 14:53     8\n",
       "RJ pá 10:53    11\n",
       "RJ čt 07:50    13\n",
       "RJ po 12:53    14\n",
       "RJ st 08:53    14\n",
       "RJ so 07:50    15\n",
       "RJ st 12:53    17\n",
       "RJ po 14:50    18\n",
       "RJ po 07:50    18\n",
       "RJ čt 14:50    18\n",
       "RJ st 14:50    19\n",
       "RJ pá 14:50    19\n",
       "RJ ne 08:53    19\n",
       "RJ ne 14:50    21\n",
       "RJ ne 07:50    21\n",
       "RJ čt 12:53    23\n",
       "RJ so 12:53    23\n",
       "RJ út 08:53    24\n",
       "RJ čt 08:53    26\n",
       "RJ so 08:53    27\n",
       "RJ pá 12:53    27\n",
       "RJ pá 08:53    27\n",
       "RJ ne 12:53    28\n",
       "Name: predstih_d, dtype: int64"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['volnych_mist'] == 0].groupby('spoj')['predstih_d'].max().sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "6535820a-9f0f-4768-9a35-5b022102f2c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 246,
     "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": 247,
   "id": "a396852e-a3e7-4099-b5d7-8381a9286b77",
   "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>0.998513</td>\n",
       "      <td>0.039641</td>\n",
       "      <td>0.179279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>predstih_d</th>\n",
       "      <td>0.998513</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.038581</td>\n",
       "      <td>0.179339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cena</th>\n",
       "      <td>0.039641</td>\n",
       "      <td>0.038581</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.644018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>volnych_mist</th>\n",
       "      <td>0.179279</td>\n",
       "      <td>0.179339</td>\n",
       "      <td>-0.644018</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    0.998513  0.039641      0.179279\n",
       "predstih_d      0.998513    1.000000  0.038581      0.179339\n",
       "cena            0.039641    0.038581  1.000000     -0.644018\n",
       "volnych_mist    0.179279    0.179339 -0.644018      1.000000"
      ]
     },
     "execution_count": 247,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'RJ'][['predstih_h','predstih_d','cena','volnych_mist']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "id": "bd4e0af2-8280-4022-99b8-0337b94838a6",
   "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>0.999894</td>\n",
       "      <td>-0.422548</td>\n",
       "      <td>0.667913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>predstih_d</th>\n",
       "      <td>0.999894</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.422124</td>\n",
       "      <td>0.667695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cena</th>\n",
       "      <td>-0.422548</td>\n",
       "      <td>-0.422124</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.726625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>volnych_mist</th>\n",
       "      <td>0.667913</td>\n",
       "      <td>0.667695</td>\n",
       "      <td>-0.726625</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    0.999894 -0.422548      0.667913\n",
       "predstih_d      0.999894    1.000000 -0.422124      0.667695\n",
       "cena           -0.422548   -0.422124  1.000000     -0.726625\n",
       "volnych_mist    0.667913    0.667695 -0.726625      1.000000"
      ]
     },
     "execution_count": 248,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'LE'][['predstih_h','predstih_d','cena','volnych_mist']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "id": "ffe5bd59-f306-4ce4-93be-b5acd40b90c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_d'>"
      ]
     },
     "execution_count": 249,
     "metadata": {},
     "output_type": "execute_result"
    },
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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": 250,
   "id": "625fc12b-4f0f-4186-ae65-8bf8852c48d4",
   "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>spoj</th>\n",
       "      <th>predstih_d</th>\n",
       "      <th>cena</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>237193</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>58</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280074</th>\n",
       "      <td>LE st 07:58</td>\n",
       "      <td>50</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202316</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>56</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280075</th>\n",
       "      <td>LE st 07:58</td>\n",
       "      <td>50</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334418</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334415</th>\n",
       "      <td>LE ne 07:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334414</th>\n",
       "      <td>LE ne 07:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334413</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280073</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>50</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334406</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>27</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167886</th>\n",
       "      <td>LE pá 17:06</td>\n",
       "      <td>69</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482699</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>70</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482698</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>70</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241299</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>83</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392776</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>19</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260412</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260413</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>334405</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>27</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392775</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>19</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280072</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>50</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202318</th>\n",
       "      <td>LE ne 07:58</td>\n",
       "      <td>56</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447444</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>25</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512816</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285936</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>85</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447447</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>81</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285941</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>85</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447450</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>81</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447451</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>81</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202317</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>56</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285942</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>85</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447452</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>81</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376236</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>19</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285947</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>86</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285948</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>86</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376235</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>19</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330109</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>34</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202319</th>\n",
       "      <td>LE ne 07:58</td>\n",
       "      <td>56</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285944</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>85</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447470</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>82</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447471</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>82</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343459</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>84</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359527</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>20</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528143</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168333</th>\n",
       "      <td>LE pá 17:13</td>\n",
       "      <td>62</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168334</th>\n",
       "      <td>LE pá 17:06</td>\n",
       "      <td>62</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359551</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359552</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314675</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>22</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528152</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>314682</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>22</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330117</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>34</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539780</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539781</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185002</th>\n",
       "      <td>LE pá 17:13</td>\n",
       "      <td>62</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185001</th>\n",
       "      <td>LE pá 17:06</td>\n",
       "      <td>62</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150258</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539793</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>79</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150111</th>\n",
       "      <td>LE so 21:05</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528157</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>71</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233252</th>\n",
       "      <td>LE ne 07:58</td>\n",
       "      <td>49</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233253</th>\n",
       "      <td>LE ne 07:58</td>\n",
       "      <td>49</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215617</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343452</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>84</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408859</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>67</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408861</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>67</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215625</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311184</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>62</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384711</th>\n",
       "      <td>LE čt 17:06</td>\n",
       "      <td>77</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311183</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>62</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>384714</th>\n",
       "      <td>LE čt 17:13</td>\n",
       "      <td>77</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528174</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>72</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528173</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>72</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343436</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>84</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528163</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>71</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343435</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>84</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343434</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>84</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343433</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>84</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359518</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>20</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512815</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512802</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447437</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>25</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211578</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>31</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207144</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207145</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439839</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>54</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439833</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>54</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439828</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439823</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439818</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256306</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439816</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436525</th>\n",
       "      <td>LE ne 10:58</td>\n",
       "      <td>72</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436524</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>71</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436523</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>71</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351535</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>76</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351536</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>76</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>293000</th>\n",
       "      <td>LE pá 17:13</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>293001</th>\n",
       "      <td>LE pá 17:06</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436526</th>\n",
       "      <td>LE ne 10:58</td>\n",
       "      <td>72</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400806</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>54</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256305</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400805</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>54</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241297</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>83</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458896</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>17</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458904</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>17</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458918</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458919</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458920</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458932</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160586</th>\n",
       "      <td>LE út 09:05</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160585</th>\n",
       "      <td>LE út 09:05</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160584</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160583</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>66</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277273</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277262</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400792</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400793</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>53</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207121</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207122</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351548</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>76</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539794</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>79</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351549</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>76</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306775</th>\n",
       "      <td>LE čt 17:13</td>\n",
       "      <td>72</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462117</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189076</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>70</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496020</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>84</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496021</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>84</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189075</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>70</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237181</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326102</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>74</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462116</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326103</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>74</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487026</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>58</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356342</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356343</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274066</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>22</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274065</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>22</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512792</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211577</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>31</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487027</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>58</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237190</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>23</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237194</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>58</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237210</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>58</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330084</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>29</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443732</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443733</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443734</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330085</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>29</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443744</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405214</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405215</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405228</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405229</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443746</th>\n",
       "      <td>LE st 14:58</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443747</th>\n",
       "      <td>LE st 15:05</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443748</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443749</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>89</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443755</th>\n",
       "      <td>LE st 07:05</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>443756</th>\n",
       "      <td>LE st 06:58</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237214</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>58</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306774</th>\n",
       "      <td>LE čt 17:06</td>\n",
       "      <td>72</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539795</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>79</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167897</th>\n",
       "      <td>LE pá 17:13</td>\n",
       "      <td>69</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322217</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228736</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>71</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228737</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>71</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197586</th>\n",
       "      <td>LE ne 07:58</td>\n",
       "      <td>49</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197584</th>\n",
       "      <td>LE ne 07:58</td>\n",
       "      <td>49</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451734</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>18</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451732</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>18</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322210</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>63</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322211</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>63</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424570</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>26</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322212</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>63</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539818</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>79</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477898</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>80</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520474</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520475</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>282688</th>\n",
       "      <td>LE pá 17:13</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>282698</th>\n",
       "      <td>LE pá 17:06</td>\n",
       "      <td>88</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420438</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>71</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477904</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>80</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477897</th>\n",
       "      <td>LE st 08:58</td>\n",
       "      <td>80</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>282671</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>22</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>282669</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>22</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302089</th>\n",
       "      <td>LE čt 17:13</td>\n",
       "      <td>79</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539796</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>79</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388974</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>87</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224924</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>83</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451757</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>388975</th>\n",
       "      <td>LE ne 08:58</td>\n",
       "      <td>87</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473738</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>86</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473739</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>86</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224917</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>83</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420404</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>19</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420403</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>19</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473762</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>87</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473764</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>87</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470265</th>\n",
       "      <td>LE pá 17:06</td>\n",
       "      <td>55</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>451769</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>65</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470271</th>\n",
       "      <td>LE pá 17:13</td>\n",
       "      <td>55</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322208</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>63</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520449</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520452</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>302088</th>\n",
       "      <td>LE čt 17:06</td>\n",
       "      <td>79</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>420439</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>71</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266217</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>29</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424567</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>26</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266255</th>\n",
       "      <td>LE út 17:06</td>\n",
       "      <td>36</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477905</th>\n",
       "      <td>LE st 10:58</td>\n",
       "      <td>80</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150265</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339290</th>\n",
       "      <td>LE pá 17:13</td>\n",
       "      <td>58</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339292</th>\n",
       "      <td>LE pá 17:06</td>\n",
       "      <td>58</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>322215</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150262</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266226</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>29</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>266249</th>\n",
       "      <td>LE út 17:13</td>\n",
       "      <td>36</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>539809</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>79</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150264</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>64</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477915</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>81</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477910</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>81</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224893</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356242</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462088</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508688</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>2</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180775</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330098</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>34</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224898</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473656</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330066</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356272</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>6</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356273</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>6</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348197</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>24</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356278</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>12</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524644</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>348196</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>24</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531984</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>2</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356243</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211506</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>7</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462081</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462016</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462017</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405211</th>\n",
       "      <td>LE čt 18:57</td>\n",
       "      <td>21</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405212</th>\n",
       "      <td>LE čt 19:04</td>\n",
       "      <td>21</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462044</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176816</th>\n",
       "      <td>LE čt 18:57</td>\n",
       "      <td>26</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532010</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532009</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363519</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>26</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>535982</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>1</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462055</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462056</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520419</th>\n",
       "      <td>LE čt 18:57</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462065</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220418</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>15</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211505</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>7</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220416</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>15</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524602</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>6</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524603</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>6</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520418</th>\n",
       "      <td>LE čt 19:04</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473657</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531986</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>2</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524651</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470248</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>28</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524652</th>\n",
       "      <td>LE po 15:58</td>\n",
       "      <td>50</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356315</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>24</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189047</th>\n",
       "      <td>LE pá 19:04</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189046</th>\n",
       "      <td>LE pá 18:57</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356324</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>24</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237136</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>6</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512706</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512707</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211560</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211561</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211567</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>30</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211568</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>30</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376268</th>\n",
       "      <td>LE st 17:13</td>\n",
       "      <td>34</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524669</th>\n",
       "      <td>LE po 15:58</td>\n",
       "      <td>50</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220395</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>9</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376266</th>\n",
       "      <td>LE st 17:06</td>\n",
       "      <td>34</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473727</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473728</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512778</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189020</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>10</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180740</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>4</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473682</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>7</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458888</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237139</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>6</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458894</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520370</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532027</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>6</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458893</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520369</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>458889</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356288</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>12</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237179</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356291</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363520</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>26</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237178</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237173</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>23</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237172</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>23</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237164</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>470242</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>28</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237163</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473681</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>7</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512690</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>2</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>356299</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512691</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>2</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330102</th>\n",
       "      <td>LE út 08:58</td>\n",
       "      <td>34</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532031</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>6</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524579</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436483</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>10</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256286</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524547</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>2</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424541</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>8</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351449</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351450</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256333</th>\n",
       "      <td>LE po 17:06</td>\n",
       "      <td>56</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241192</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306754</th>\n",
       "      <td>LE čt 18:57</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256336</th>\n",
       "      <td>LE po 17:13</td>\n",
       "      <td>56</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256310</th>\n",
       "      <td>LE po 15:58</td>\n",
       "      <td>56</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330076</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>28</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508720</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439814</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>19</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439809</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>19</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439803</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>18</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241193</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381653</th>\n",
       "      <td>LE pá 18:57</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180770</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508715</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381652</th>\n",
       "      <td>LE pá 19:04</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424542</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>8</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439792</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>18</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256309</th>\n",
       "      <td>LE po 15:58</td>\n",
       "      <td>56</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424525</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>4</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318444</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256291</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400782</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256292</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400783</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256295</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>22</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508785</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508786</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180780</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524546</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>2</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180781</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318462</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>32</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318468</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>32</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508813</th>\n",
       "      <td>LE so 17:13</td>\n",
       "      <td>48</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363464</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>318443</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508826</th>\n",
       "      <td>LE so 17:06</td>\n",
       "      <td>48</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363463</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424524</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>4</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>306750</th>\n",
       "      <td>LE čt 19:04</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180792</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439791</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>12</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381631</th>\n",
       "      <td>LE čt 18:57</td>\n",
       "      <td>14</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330071</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>28</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436515</th>\n",
       "      <td>LE čt 18:57</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241260</th>\n",
       "      <td>LE čt 18:57</td>\n",
       "      <td>25</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424597</th>\n",
       "      <td>LE pá 17:13</td>\n",
       "      <td>49</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326062</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>14</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326051</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436514</th>\n",
       "      <td>LE čt 19:04</td>\n",
       "      <td>27</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326050</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326049</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326047</th>\n",
       "      <td>LE út 08:00</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256238</th>\n",
       "      <td>LE st 18:57</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241269</th>\n",
       "      <td>LE čt 19:04</td>\n",
       "      <td>25</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508695</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>2</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330070</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>13</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>524571</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326035</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>7</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326030</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>7</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224852</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>10</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224853</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>10</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180774</th>\n",
       "      <td>LE út 15:00</td>\n",
       "      <td>17</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176817</th>\n",
       "      <td>LE čt 19:04</td>\n",
       "      <td>26</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424598</th>\n",
       "      <td>LE pá 17:06</td>\n",
       "      <td>49</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>535973</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>1</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256239</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>3</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189019</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>10</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381622</th>\n",
       "      <td>LE čt 19:04</td>\n",
       "      <td>14</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439785</th>\n",
       "      <td>LE st 19:04</td>\n",
       "      <td>12</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381610</th>\n",
       "      <td>LE út 18:57</td>\n",
       "      <td>5</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439777</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400757</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439776</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381600</th>\n",
       "      <td>LE út 19:04</td>\n",
       "      <td>5</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351500</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>12</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326086</th>\n",
       "      <td>LE čt 18:57</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>351506</th>\n",
       "      <td>LE po 19:04</td>\n",
       "      <td>12</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491468</th>\n",
       "      <td>LE so 19:04</td>\n",
       "      <td>7</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491467</th>\n",
       "      <td>LE so 18:57</td>\n",
       "      <td>7</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424553</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>26</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424554</th>\n",
       "      <td>LE st 08:00</td>\n",
       "      <td>26</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>400753</th>\n",
       "      <td>LE po 18:57</td>\n",
       "      <td>11</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>326083</th>\n",
       "      <td>LE čt 19:04</td>\n",
       "      <td>16</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               spoj  predstih_d   cena\n",
       "237193  LE út 08:58          58   99.0\n",
       "280074  LE st 07:58          50   99.0\n",
       "202316  LE ne 08:58          56   99.0\n",
       "280075  LE st 07:58          50   99.0\n",
       "334418  LE ne 08:58          53   99.0\n",
       "334415  LE ne 07:58          53   99.0\n",
       "334414  LE ne 07:58          53   99.0\n",
       "334413  LE ne 08:58          53   99.0\n",
       "280073  LE st 08:58          50   99.0\n",
       "334406  LE út 18:57          27   99.0\n",
       "167886  LE pá 17:06          69   99.0\n",
       "482699  LE so 17:06          70   99.0\n",
       "482698  LE so 17:13          70   99.0\n",
       "241299  LE so 17:13          83   99.0\n",
       "392776  LE út 19:04          19   99.0\n",
       "260412  LE st 19:04          23   99.0\n",
       "260413  LE st 18:57          23   99.0\n",
       "334405  LE út 19:04          27   99.0\n",
       "392775  LE út 18:57          19   99.0\n",
       "280072  LE st 08:58          50   99.0\n",
       "202318  LE ne 07:58          56   99.0\n",
       "447444  LE út 18:57          25   99.0\n",
       "512816  LE út 17:13          65   99.0\n",
       "285936  LE st 10:58          85   99.0\n",
       "447447  LE st 08:58          81   99.0\n",
       "285941  LE st 08:58          85   99.0\n",
       "447450  LE st 08:58          81   99.0\n",
       "447451  LE st 10:58          81   99.0\n",
       "202317  LE ne 08:58          56   99.0\n",
       "285942  LE st 10:58          85   99.0\n",
       "447452  LE st 10:58          81   99.0\n",
       "376236  LE út 19:04          19   99.0\n",
       "285947  LE st 17:06          86   99.0\n",
       "285948  LE st 17:13          86   99.0\n",
       "376235  LE út 18:57          19   99.0\n",
       "330109  LE út 17:13          34   99.0\n",
       "202319  LE ne 07:58          56   99.0\n",
       "285944  LE st 08:58          85   99.0\n",
       "447470  LE st 17:06          82   99.0\n",
       "447471  LE st 17:13          82   99.0\n",
       "343459  LE st 17:06          84   99.0\n",
       "359527  LE út 19:04          20   99.0\n",
       "528143  LE út 19:04          23   99.0\n",
       "168333  LE pá 17:13          62   99.0\n",
       "168334  LE pá 17:06          62   99.0\n",
       "359551  LE po 17:06          89   99.0\n",
       "359552  LE po 17:13          89   99.0\n",
       "314675  LE st 19:04          22   99.0\n",
       "528152  LE út 18:57          23   99.0\n",
       "314682  LE st 18:57          22   99.0\n",
       "330117  LE út 17:06          34   99.0\n",
       "539780  LE st 19:04          23   99.0\n",
       "539781  LE st 18:57          23   99.0\n",
       "185002  LE pá 17:13          62   99.0\n",
       "185001  LE pá 17:06          62   99.0\n",
       "150258  LE so 17:06          64   99.0\n",
       "539793  LE st 08:58          79   99.0\n",
       "150111  LE so 21:05          64   99.0\n",
       "528157  LE út 08:58          71   99.0\n",
       "233252  LE ne 07:58          49   99.0\n",
       "233253  LE ne 07:58          49   99.0\n",
       "215617  LE po 17:13          64   99.0\n",
       "343452  LE st 17:13          84   99.0\n",
       "408859  LE po 17:13          67   99.0\n",
       "408861  LE po 17:06          67   99.0\n",
       "215625  LE po 17:06          64   99.0\n",
       "311184  LE po 17:06          62   99.0\n",
       "384711  LE čt 17:06          77   99.0\n",
       "311183  LE po 17:13          62   99.0\n",
       "384714  LE čt 17:13          77   99.0\n",
       "528174  LE út 17:06          72   99.0\n",
       "528173  LE út 17:13          72   99.0\n",
       "343436  LE st 10:58          84   99.0\n",
       "528163  LE út 08:58          71   99.0\n",
       "343435  LE st 10:58          84   99.0\n",
       "343434  LE st 08:58          84   99.0\n",
       "343433  LE st 08:58          84   99.0\n",
       "359518  LE út 18:57          20   99.0\n",
       "512815  LE út 17:06          65   99.0\n",
       "512802  LE út 08:58          65   99.0\n",
       "447437  LE út 19:04          25   99.0\n",
       "211578  LE út 18:57          31   99.0\n",
       "207144  LE út 17:13          66   99.0\n",
       "207145  LE út 17:06          66   99.0\n",
       "439839  LE st 17:06          54   99.0\n",
       "439833  LE st 17:13          54   99.0\n",
       "439828  LE st 10:58          53   99.0\n",
       "439823  LE st 08:58          53   99.0\n",
       "439818  LE st 10:58          53   99.0\n",
       "256306  LE út 19:04          23   99.0\n",
       "439816  LE st 08:58          53   99.0\n",
       "436525  LE ne 10:58          72   99.0\n",
       "436524  LE ne 08:58          71   99.0\n",
       "436523  LE ne 08:58          71   99.0\n",
       "351535  LE út 08:58          76   99.0\n",
       "351536  LE út 08:58          76   99.0\n",
       "293000  LE pá 17:13          66   99.0\n",
       "293001  LE pá 17:06          66   99.0\n",
       "436526  LE ne 10:58          72   99.0\n",
       "400806  LE út 17:13          54   99.0\n",
       "256305  LE út 18:57          23   99.0\n",
       "400805  LE út 17:06          54   99.0\n",
       "241297  LE so 17:06          83   99.0\n",
       "458896  LE út 18:57          17   99.0\n",
       "458904  LE út 19:04          17   99.0\n",
       "458918  LE út 08:58          66   99.0\n",
       "458919  LE út 08:58          66   99.0\n",
       "458920  LE út 17:13          66   99.0\n",
       "458932  LE út 17:06          66   99.0\n",
       "160586  LE út 09:05          66   99.0\n",
       "160585  LE út 09:05          66   99.0\n",
       "160584  LE út 08:58          66   99.0\n",
       "160583  LE út 08:58          66   99.0\n",
       "277273  LE st 19:04          23   99.0\n",
       "277262  LE st 18:57          23   99.0\n",
       "400792  LE út 08:58          53   99.0\n",
       "400793  LE út 08:58          53   99.0\n",
       "207121  LE út 08:58          65   99.0\n",
       "207122  LE út 08:58          65   99.0\n",
       "351548  LE út 17:13          76   99.0\n",
       "539794  LE st 08:58          79   99.0\n",
       "351549  LE út 17:06          76   99.0\n",
       "306775  LE čt 17:13          72   99.0\n",
       "462117  LE po 17:13          65   99.0\n",
       "189076  LE so 17:13          70   99.0\n",
       "496020  LE ne 08:58          84   99.0\n",
       "496021  LE ne 08:58          84   99.0\n",
       "189075  LE so 17:06          70   99.0\n",
       "237181  LE út 18:57          23   99.0\n",
       "326102  LE so 17:06          74   99.0\n",
       "462116  LE po 17:06          65   99.0\n",
       "326103  LE so 17:13          74   99.0\n",
       "487026  LE po 17:13          58   99.0\n",
       "356342  LE po 17:13          89   99.0\n",
       "356343  LE po 17:06          89   99.0\n",
       "274066  LE út 18:57          22   99.0\n",
       "274065  LE út 19:04          22   99.0\n",
       "512792  LE út 08:58          65   99.0\n",
       "211577  LE út 19:04          31   99.0\n",
       "487027  LE po 17:06          58   99.0\n",
       "237190  LE út 19:04          23   99.0\n",
       "237194  LE út 08:58          58   99.0\n",
       "237210  LE út 17:06          58   99.0\n",
       "330084  LE st 19:04          29   99.0\n",
       "443732  LE st 08:58          88   99.0\n",
       "443733  LE st 08:58          88   99.0\n",
       "443734  LE st 10:58          88   99.0\n",
       "330085  LE st 18:57          29   99.0\n",
       "443744  LE st 10:58          88   99.0\n",
       "405214  LE út 08:58          88   99.0\n",
       "405215  LE út 08:58          88   99.0\n",
       "405228  LE út 17:13          89   99.0\n",
       "405229  LE út 17:06          89   99.0\n",
       "443746  LE st 14:58          89   99.0\n",
       "443747  LE st 15:05          89   99.0\n",
       "443748  LE st 17:06          89   99.0\n",
       "443749  LE st 17:13          89   99.0\n",
       "443755  LE st 07:05          88   99.0\n",
       "443756  LE st 06:58          88   99.0\n",
       "237214  LE út 17:13          58   99.0\n",
       "306774  LE čt 17:06          72   99.0\n",
       "539795  LE st 10:58          79   99.0\n",
       "167897  LE pá 17:13          69   99.0\n",
       "322217  LE st 17:06          64   99.0\n",
       "228736  LE po 17:13          71   99.0\n",
       "228737  LE po 17:06          71   99.0\n",
       "197586  LE ne 07:58          49   99.0\n",
       "197584  LE ne 07:58          49   99.0\n",
       "451734  LE út 18:57          18   99.0\n",
       "451732  LE út 19:04          18   99.0\n",
       "322210  LE st 10:58          63   99.0\n",
       "322211  LE st 08:58          63   99.0\n",
       "424570  LE st 19:04          26   99.0\n",
       "322212  LE st 08:58          63   99.0\n",
       "539818  LE st 17:06          79   99.0\n",
       "477898  LE st 08:58          80   99.0\n",
       "520474  LE út 17:06          65   99.0\n",
       "520475  LE út 17:13          65   99.0\n",
       "282688  LE pá 17:13          88   99.0\n",
       "282698  LE pá 17:06          88   99.0\n",
       "420438  LE so 17:06          71   99.0\n",
       "477904  LE st 10:58          80   99.0\n",
       "477897  LE st 08:58          80   99.0\n",
       "282671  LE út 18:57          22   99.0\n",
       "282669  LE út 19:04          22   99.0\n",
       "302089  LE čt 17:13          79   99.0\n",
       "539796  LE st 10:58          79   99.0\n",
       "388974  LE ne 08:58          87   99.0\n",
       "224924  LE so 17:13          83   99.0\n",
       "451757  LE po 17:06          65   99.0\n",
       "388975  LE ne 08:58          87   99.0\n",
       "473738  LE út 08:58          86   99.0\n",
       "473739  LE út 08:58          86   99.0\n",
       "224917  LE so 17:06          83   99.0\n",
       "420404  LE st 19:04          19   99.0\n",
       "420403  LE st 18:57          19   99.0\n",
       "473762  LE út 17:06          87   99.0\n",
       "473764  LE út 17:13          87   99.0\n",
       "470265  LE pá 17:06          55   99.0\n",
       "451769  LE po 17:13          65   99.0\n",
       "470271  LE pá 17:13          55   99.0\n",
       "322208  LE st 10:58          63   99.0\n",
       "520449  LE út 08:58          64   99.0\n",
       "520452  LE út 08:58          64   99.0\n",
       "302088  LE čt 17:06          79   99.0\n",
       "420439  LE so 17:13          71   99.0\n",
       "266217  LE út 18:57          29   99.0\n",
       "424567  LE st 18:57          26   99.0\n",
       "266255  LE út 17:06          36   99.0\n",
       "477905  LE st 10:58          80   99.0\n",
       "150265  LE so 17:13          64   99.0\n",
       "339290  LE pá 17:13          58   99.0\n",
       "339292  LE pá 17:06          58   99.0\n",
       "322215  LE st 17:13          64   99.0\n",
       "150262  LE so 17:06          64   99.0\n",
       "266226  LE út 19:04          29   99.0\n",
       "266249  LE út 17:13          36   99.0\n",
       "539809  LE st 17:13          79   99.0\n",
       "150264  LE so 17:13          64   99.0\n",
       "477915  LE st 17:06          81   99.0\n",
       "477910  LE st 17:13          81   99.0\n",
       "224893  LE so 18:57          27  169.0\n",
       "356242  LE so 19:04           3  169.0\n",
       "462088  LE po 18:57          16  169.0\n",
       "508688  LE út 18:57           2  169.0\n",
       "180775  LE út 15:00          17  169.0\n",
       "330098  LE út 08:58          34  169.0\n",
       "224898  LE so 19:04          27  169.0\n",
       "473656  LE út 19:04           3  169.0\n",
       "330066  LE po 19:04          13  169.0\n",
       "356272  LE út 18:57           6  169.0\n",
       "356273  LE út 19:04           6  169.0\n",
       "348197  LE so 19:04          24  169.0\n",
       "356278  LE út 08:00          12  169.0\n",
       "524644  LE so 18:57          27  169.0\n",
       "348196  LE so 18:57          24  169.0\n",
       "531984  LE út 18:57           2  169.0\n",
       "356243  LE so 18:57           3  169.0\n",
       "211506  LE so 18:57           7  169.0\n",
       "462081  LE po 19:04          16  169.0\n",
       "462016  LE út 18:57           3  169.0\n",
       "462017  LE út 19:04           3  169.0\n",
       "405211  LE čt 18:57          21  169.0\n",
       "405212  LE čt 19:04          21  169.0\n",
       "462044  LE st 08:00          11  169.0\n",
       "176816  LE čt 18:57          26  169.0\n",
       "532010  LE st 19:04           3  169.0\n",
       "532009  LE st 18:57           3  169.0\n",
       "363519  LE po 19:04          26  169.0\n",
       "535982  LE út 19:04           1  169.0\n",
       "462055  LE st 08:00          11  169.0\n",
       "462056  LE st 19:04          11  169.0\n",
       "520419  LE čt 18:57          11  169.0\n",
       "462065  LE st 18:57          11  169.0\n",
       "220418  LE po 19:04          15  169.0\n",
       "211505  LE so 19:04           7  169.0\n",
       "220416  LE po 18:57          15  169.0\n",
       "524602  LE so 19:04           6  169.0\n",
       "524603  LE so 18:57           6  169.0\n",
       "520418  LE čt 19:04          11  169.0\n",
       "473657  LE út 18:57           3  169.0\n",
       "531986  LE út 19:04           2  169.0\n",
       "524651  LE so 19:04          27  169.0\n",
       "470248  LE so 19:04          28  169.0\n",
       "524652  LE po 15:58          50  169.0\n",
       "356315  LE so 19:04          24  169.0\n",
       "189047  LE pá 19:04          27  169.0\n",
       "189046  LE pá 18:57          27  169.0\n",
       "356324  LE so 18:57          24  169.0\n",
       "237136  LE so 19:04           6  169.0\n",
       "512706  LE st 19:04           3  169.0\n",
       "512707  LE st 18:57           3  169.0\n",
       "211560  LE po 19:04          16  169.0\n",
       "211561  LE po 18:57          16  169.0\n",
       "211567  LE út 15:00          30  169.0\n",
       "211568  LE út 15:00          30  169.0\n",
       "376268  LE st 17:13          34  169.0\n",
       "524669  LE po 15:58          50  169.0\n",
       "220395  LE út 19:04           9  169.0\n",
       "376266  LE st 17:06          34  169.0\n",
       "473727  LE po 19:04          16  169.0\n",
       "473728  LE po 18:57          16  169.0\n",
       "512778  LE po 18:57          22  169.0\n",
       "189020  LE út 19:04          10  169.0\n",
       "180740  LE st 18:57           4  169.0\n",
       "473682  LE so 18:57           7  169.0\n",
       "458888  LE út 15:00          17  169.0\n",
       "237139  LE so 18:57           6  169.0\n",
       "458894  LE út 08:00          17  169.0\n",
       "520370  LE st 19:04           3  169.0\n",
       "532027  LE so 19:04           6  169.0\n",
       "458893  LE út 08:00          17  169.0\n",
       "520369  LE st 18:57           3  169.0\n",
       "458889  LE út 15:00          17  169.0\n",
       "356288  LE út 08:00          12  169.0\n",
       "237179  LE út 08:00          22  169.0\n",
       "356291  LE út 19:04          13  169.0\n",
       "363520  LE po 18:57          26  169.0\n",
       "237178  LE út 08:00          22  169.0\n",
       "237173  LE út 15:00          23  169.0\n",
       "237172  LE út 15:00          23  169.0\n",
       "237164  LE so 19:04          13  169.0\n",
       "470242  LE so 18:57          28  169.0\n",
       "237163  LE so 18:57          13  169.0\n",
       "473681  LE so 19:04           7  169.0\n",
       "512690  LE út 19:04           2  169.0\n",
       "356299  LE út 18:57          13  169.0\n",
       "512691  LE út 18:57           2  169.0\n",
       "330102  LE út 08:58          34  169.0\n",
       "532031  LE so 18:57           6  169.0\n",
       "524579  LE st 18:57           3  169.0\n",
       "436483  LE po 19:04          10  169.0\n",
       "256286  LE út 08:00          22  169.0\n",
       "524547  LE út 18:57           2  169.0\n",
       "424541  LE so 19:04           8  169.0\n",
       "351449  LE so 19:04           3  169.0\n",
       "351450  LE so 18:57           3  169.0\n",
       "256333  LE po 17:06          56  169.0\n",
       "241192  LE st 19:04           3  169.0\n",
       "306754  LE čt 18:57          16  169.0\n",
       "256336  LE po 17:13          56  169.0\n",
       "256310  LE po 15:58          56  169.0\n",
       "330076  LE st 08:00          28  169.0\n",
       "508720  LE st 19:04           3  169.0\n",
       "439814  LE st 18:57          19  169.0\n",
       "439809  LE st 19:04          19  169.0\n",
       "439803  LE st 08:00          18  169.0\n",
       "241193  LE st 18:57           3  169.0\n",
       "381653  LE pá 18:57          22  169.0\n",
       "180770  LE út 08:00          17  169.0\n",
       "508715  LE st 18:57           3  169.0\n",
       "381652  LE pá 19:04          22  169.0\n",
       "424542  LE so 18:57           8  169.0\n",
       "439792  LE st 08:00          18  169.0\n",
       "256309  LE po 15:58          56  169.0\n",
       "424525  LE út 18:57           4  169.0\n",
       "318444  LE po 18:57          27  169.0\n",
       "256291  LE út 15:00          22  169.0\n",
       "400782  LE so 18:57          16  169.0\n",
       "256292  LE út 15:00          22  169.0\n",
       "400783  LE so 19:04          16  169.0\n",
       "256295  LE út 08:00          22  169.0\n",
       "508785  LE so 19:04          27  169.0\n",
       "508786  LE so 18:57          27  169.0\n",
       "180780  LE út 08:00          17  169.0\n",
       "524546  LE út 19:04           2  169.0\n",
       "180781  LE út 19:04          17  169.0\n",
       "318462  LE so 19:04          32  169.0\n",
       "318468  LE so 18:57          32  169.0\n",
       "508813  LE so 17:13          48  169.0\n",
       "363464  LE so 19:04           3  169.0\n",
       "318443  LE po 19:04          27  169.0\n",
       "508826  LE so 17:06          48  169.0\n",
       "363463  LE so 18:57           3  169.0\n",
       "424524  LE út 19:04           4  169.0\n",
       "306750  LE čt 19:04          16  169.0\n",
       "180792  LE út 18:57          17  169.0\n",
       "439791  LE st 18:57          12  169.0\n",
       "381631  LE čt 18:57          14  169.0\n",
       "330071  LE st 08:00          28  169.0\n",
       "436515  LE čt 18:57          27  169.0\n",
       "241260  LE čt 18:57          25  169.0\n",
       "424597  LE pá 17:13          49  169.0\n",
       "326062  LE út 19:04          14  169.0\n",
       "326051  LE út 15:00          13  169.0\n",
       "436514  LE čt 19:04          27  169.0\n",
       "326050  LE út 08:00          13  169.0\n",
       "326049  LE út 15:00          13  169.0\n",
       "326047  LE út 08:00          13  169.0\n",
       "256238  LE st 18:57           3  169.0\n",
       "241269  LE čt 19:04          25  169.0\n",
       "508695  LE út 19:04           2  169.0\n",
       "330070  LE po 18:57          13  169.0\n",
       "524571  LE st 19:04           3  169.0\n",
       "326035  LE út 18:57           7  169.0\n",
       "326030  LE út 19:04           7  169.0\n",
       "224852  LE st 08:00          10  169.0\n",
       "224853  LE st 08:00          10  169.0\n",
       "180774  LE út 15:00          17  169.0\n",
       "176817  LE čt 19:04          26  169.0\n",
       "424598  LE pá 17:06          49  169.0\n",
       "535973  LE út 18:57           1  169.0\n",
       "256239  LE st 19:04           3  169.0\n",
       "189019  LE út 18:57          10  169.0\n",
       "381622  LE čt 19:04          14  169.0\n",
       "439785  LE st 19:04          12  169.0\n",
       "381610  LE út 18:57           5  169.0\n",
       "439777  LE st 08:00          11  169.0\n",
       "400757  LE po 19:04          11  169.0\n",
       "439776  LE st 08:00          11  169.0\n",
       "381600  LE út 19:04           5  169.0\n",
       "351500  LE po 18:57          12  169.0\n",
       "326086  LE čt 18:57          16  169.0\n",
       "351506  LE po 19:04          12  169.0\n",
       "491468  LE so 19:04           7  169.0\n",
       "491467  LE so 18:57           7  169.0\n",
       "424553  LE st 08:00          26  169.0\n",
       "424554  LE st 08:00          26  169.0\n",
       "400753  LE po 18:57          11  169.0\n",
       "326083  LE čt 19:04          16  169.0"
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['spoj','predstih_d','cena']].sort_values(by='cena').head(400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f5ccbef2-3590-45cf-931e-f1c0ee3cf2aa",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "188953bc-2aa4-4b33-aef0-a622d850406e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "id": "3d947c8a-e07a-4378-ba6c-36c24e3062d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "70         [EC 115 Cracovia]\n",
       "71         [EC 143 Ostravan]\n",
       "72        [SC 507 Pendolino]\n",
       "73          [EC 117 Silesia]\n",
       "74        [SC 505 Pendolino]\n",
       "                 ...        \n",
       "542090     [IC 549 Ostravan]\n",
       "542093     [EC 115 Cracovia]\n",
       "542094     [IC 547 Ostravan]\n",
       "542095    [SC 513 Pendolino]\n",
       "542096     [EC 141 Ostravan]\n",
       "Name: vlaky, Length: 40473, dtype: object"
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['prodejce'] == 'ČD']['vlaky']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "e8751a67-babe-47cc-9cf0-1ed98979137a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='odjezd'>"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AAJxDQAEAAM4hoAAAAOcQUAAAgHMIKAAAwDkEFAAA4BwCCgAAcA4BBQAAOIeAAgAAnENAAQAAziGgAAAA54TUdQMAALik1eTV1Rp/cFafAHVyaWMGBQAAOIeAAgAAnENAAQAAziGgAAAA5xBQAACAcwgoAADAOQQUAADgHAIKAABwDgEFAAA4h4ACAACcQ0ABAADOIaAAAADnEFAAAIBzCCgAAMA5BBQAAOAcAgoAAHAOAQUAADiHgAIAAJxDQAEAAM6pdkDZtGmTbr/9diUlJcnj8WjVqlU++81M2dnZSkpKUmRkpHr06KHdu3f7jCkrK9PYsWPVrFkzNW7cWP369dOhQ4dq9EAAAEDDUe2AcuLECV177bV64YUXqtz/1FNPafbs2XrhhRe0detWJSQk6JZbbtGxY8e8Y8aPH6+VK1dq+fLlysvL0/Hjx9W3b1+dOXPG/0cCAAAajJDq3iArK0tZWVlV7jMzPffcc5o2bZr69+8vSVq0aJHi4+O1dOlSjRo1SiUlJZo/f74WL16sXr16SZKWLFmi5ORkrVu3TpmZmTV4OAAAoCGo1WtQDhw4oMLCQvXu3du7LTw8XN27d9fmzZslSdu3b1dFRYXPmKSkJKWnp3vH/FBZWZlKS0t9FgAA0HDVakApLCyUJMXHx/tsj4+P9+4rLCxUWFiYYmJiLjjmh2bOnKno6GjvkpycXJttAwAAxwTkXTwej8dn3cwqbfuhi42ZMmWKSkpKvEt+fn6t9QoAANxTqwElISFBkirNhBQVFXlnVRISElReXq7i4uILjvmh8PBwNWnSxGcBAAANV60GlNTUVCUkJGjt2rXebeXl5dq4caO6dOkiSerQoYNCQ0N9xhQUFOjTTz/1jgEAAJe2ar+L5/jx49q3b593/cCBA9qxY4diY2PVsmVLjR8/Xjk5OUpLS1NaWppycnLUqFEjDR48WJIUHR2t4cOH6+GHH1ZcXJxiY2M1ceJEZWRkeN/VAwAALm3VDijbtm1Tz549vesTJkyQJA0dOlQLFy7UpEmTdOrUKT344IMqLi5Wx44d9cEHHygqKsp7m2effVYhISEaOHCgTp06pZtvvlkLFy5UcHBwLTwkAABQ31U7oPTo0UNmdsH9Ho9H2dnZys7OvuCYiIgI5ebmKjc3t7p3DwAALgF8Fw8AAHAOAQUAADiHgAIAAJxDQAEAAM4hoAAAAOcQUAAAgHMIKAAAwDkEFAAA4BwCCgAAcA4BBQAAOIeAAgAAnENAAQAAziGgAAAA5xBQAACAcwgoAADAOQQUAADgHAIKAABwDgEFAAA4h4ACAACcQ0ABAADOIaAAAADnEFAAAIBzCCgAAMA5BBQAAOAcAgoAAHAOAQUAADiHgAIAAJxDQAEAAM4hoAAAAOcQUAAAgHMIKAAAwDkEFAAA4BwCCgAAcA4BBQAAOIeAAgAAnENAAQAAziGgAAAA54TUdQMAAFRHq8mrqzX+4Kw+Aerk0lOd576mzzsBxSH80jVcP+cvNQA0BJziAQAAziGgAAAA5xBQAACAcwgoAADAOQQUAADgHAIKAABwDgEFAAA4h4ACAACcQ0ABAADOIaAAAADn8FH3AOoMX+8A4EKYQQEAAM4hoAAAAOdwigeo5zhNAqAhYgYFAAA4h4ACAACcU+uneLKzszVjxgyfbfHx8SosLJQkmZlmzJihefPmqbi4WB07dtScOXN09dVX13YrAIAL4NQgXBeQGZSrr75aBQUF3mXXrl3efU899ZRmz56tF154QVu3blVCQoJuueUWHTt2LBCtAACAeiggASUkJEQJCQne5fLLL5f0/ezJc889p2nTpql///5KT0/XokWLdPLkSS1dujQQrQAAgHooIAFl7969SkpKUmpqqgYNGqT9+/dLkg4cOKDCwkL17t3bOzY8PFzdu3fX5s2bL1ivrKxMpaWlPgsAAGi4aj2gdOzYUa+88orWrFmjl19+WYWFherSpYuOHDnivQ4lPj7e5zbnX6NSlZkzZyo6Otq7JCcn13bbAADAIbUeULKysjRgwABlZGSoV69eWr36+wuxFi1a5B3j8Xh8bmNmlbadb8qUKSopKfEu+fn5td02AABwSMDfZty4cWNlZGRo7969SkhIkKRKsyVFRUWVZlXOFx4eriZNmvgsAACg4Qr4J8mWlZVpz549uvHGG5WamqqEhAStXbtW7du3lySVl5dr48aNevLJJwPdCgDUG7wNGJe6Wg8oEydO1O23366WLVuqqKhIjz/+uEpLSzV06FB5PB6NHz9eOTk5SktLU1pamnJyctSoUSMNHjy4tlsBAAD1VK0HlEOHDunee+/VN998o8svv1ydOnXSli1blJKSIkmaNGmSTp06pQcffND7QW0ffPCBoqKiarsV4Cfj1SoAuKXWA8ry5csvut/j8Sg7O1vZ2dm1fdcAAKCB4NuMAVwUs0sA6gIBpZo4WAMAEHh8mzEAAHAOAQUAADiHgAIAAJxDQAEAAM7hIlkADRYXtcM1/J/86ZhBAQAAziGgAAAA5xBQAACAcwgoAADAOQQUAADgHAIKAABwDgEFAAA4h4ACAACcQ0ABAADOIaAAAADnEFAAAIBzCCgAAMA5BBQAAOAcAgoAAHAOAQUAADiHgAIAAJxDQAEAAM4hoAAAAOcQUAAAgHMIKAAAwDkEFAAA4BwCCgAAcA4BBQAAOIeAAgAAnENAAQAAziGgAAAA5xBQAACAcwgoAADAOQQUAADgHAIKAABwDgEFAAA4h4ACAACcQ0ABAADOIaAAAADnEFAAAIBzCCgAAMA5BBQAAOAcAgoAAHAOAQUAADiHgAIAAJxDQAEAAM4hoAAAAOcQUAAAgHMIKAAAwDkEFAAA4BwCCgAAcA4BBQAAOIeAAgAAnFOnAeXFF19UamqqIiIi1KFDB/3pT3+qy3YAAIAj6iygrFixQuPHj9e0adP05z//WTfeeKOysrL01Vdf1VVLAADAEXUWUGbPnq3hw4drxIgRatu2rZ577jklJydr7ty5ddUSAABwREhd3Gl5ebm2b9+uyZMn+2zv3bu3Nm/eXGl8WVmZysrKvOslJSWSpNLS0kpjz5adrFYvVdW4mEDWr8+9B7p+fe69uvXrc+/VrV+fe69u/frce6Dr1+feq1u/Pvde3fpV1T63zcx+vIDVgb/97W8myf7nf/7HZ/sTTzxhrVu3rjR++vTpJomFhYWFhYWlASz5+fk/mhXqZAblHI/H47NuZpW2SdKUKVM0YcIE7/rZs2d19OhRxcXFVTn+h0pLS5WcnKz8/Hw1adKk5o3/jPXrc++Brk/vDbN+fe490PXpvWHWr8+9V7e+menYsWNKSkr60bp1ElCaNWum4OBgFRYW+mwvKipSfHx8pfHh4eEKDw/32da0adNq32+TJk0C8sP5OerX594DXZ/eG2b9+tx7oOvTe8OsX597r0796Ojon1SvTi6SDQsLU4cOHbR27Vqf7WvXrlWXLl3qoiUAAOCQOjvFM2HCBP3mN7/Rddddp86dO2vevHn66quvdP/999dVSwAAwBF1FlDuueceHTlyRI899pgKCgqUnp6ud999VykpKbV+X+Hh4Zo+fXql00T1oX597j3Q9em9Ydavz70Huj69N8z69bn3QNb3mP2U9/oAAAD8fPguHgAA4BwCCgAAcA4BBQAAOIeAAgAAnENAqQe4jhkAcKmp04+6x08THh6uTz75RG3btq3rVuCngoICzZ07V3l5eSooKFBwcLBSU1N15513atiwYQoODq7rFgHAKQ3ybcanTp3S9u3bFRsbq6uuuspn3+nTp/Xaa69pyJAhftffs2ePtmzZos6dO6tNmzb6y1/+oueff15lZWW67777dNNNN/lV9/zvGzrf888/r/vuu09xcXGSpNmzZ/vd+/mKi4u1aNEi7d27V4mJiRo6dKiSk5P9rvfnP/9ZTZs2VWpqqiRpyZIlmjt3rr766iulpKRozJgxGjRokF+1x44dq4EDB+rGG2/0u78fk5ubq23btqlPnz4aOHCgFi9erJkzZ+rs2bPq37+/HnvsMYWEVD/Tb9u2Tb169VJqaqoiIyP10Ucf6de//rXKy8u1Zs0atW3bVmvWrFFUVFQAHhUA15w4cUJLly7V5s2bVVhYKI/Ho/j4eN1www2699571bhx44Dd99dff62XXnpJjz76qN81jhw5op07d+raa69VbGysvvnmG82fP19lZWW6++67a+/FdM2/m9gtf/3rXy0lJcU8Ho8FBQVZ9+7d7fDhw979hYWFFhQU5Hf99957z8LCwiw2NtYiIiLsvffes8svv9x69eplN998s4WEhNgf//hHv2p7PB5r166d9ejRw2fxeDx2/fXXW48ePaxnz55+956YmGjffPONmZnt37/fEhISLCEhwW655RZr0aKFRUdH2549e/yu3759e1u/fr2Zmb388ssWGRlpDz30kM2dO9fGjx9vl112mc2fP9+v2ud+nmlpaTZr1iwrKCjwu8+qPPbYYxYVFWUDBgywhIQEmzVrlsXFxdnjjz9uOTk5dvnll9ujjz7qV+0bbrjBsrOzveuLFy+2jh07mpnZ0aNHrV27dvbQQw/V+DEcP37c5s2bZ8OGDbNbb73VsrKybNiwYfbyyy/b8ePHa1z/QgoLC23GjBk1rpOfn2/Hjh2rtL28vNw2btxYo9rffPONrV+/3o4cOWJmZn//+99t1qxZNmPGDPvss89qVLsqqamp9vnnn9d63fLyclu5cqU99dRTtnjx4hr9XPPz8+3vf/+7d33Tpk02ePBg69q1q/3617+2zZs316jX//iP/7CDBw/WqMaPeeutt+zRRx/19vrHP/7RsrKyLDMz01566aUa1T558qTNnz/f/vmf/9luvfVW69Onj40ZM8bWrVtXo7q7d++2pKQka9q0qd1xxx32u9/9zkaOHGl33HGHNW3a1K644grbvXt3je7jYnbs2FGjv4EfffSRRUdHm8fjsZiYGNu2bZulpqZaWlqaXXnllRYZGWnbt2+vlV4bXEC58847rW/fvvb3v//d9u7da7fffrulpqbal19+aWY1DyidO3e2adOmmZnZsmXLLCYmxqZOnerdP3XqVLvlllv8qp2Tk2OpqamVAk5ISEit/If1eDz29ddfm5nZoEGDrEePHnbixAkzMzt9+rT17dvX/umf/snv+o0aNfI+z+3bt690gHj11Vftqquu8rv3devW2bhx46xZs2YWGhpq/fr1s7ffftvOnDnjd8/n/OIXv7DXX3/dzL7/BQ4ODrYlS5Z497/xxht25ZVX+lU7MjLSvvjiC+/6mTNnLDQ01AoLC83M7IMPPrCkpKQadF+3B72aHvAOHz5s119/vQUFBVlwcLANGTLEJ6jU9Hc2kAfU559/vsolODjYpkyZ4l33V+fOna24uNjMzIqKiiwjI8PCwsIsLS3NIiIirGXLlnbo0CG/a7/77rtmZrZq1SoLCgqyfv362SOPPGJ33XWXhYaG2ttvv+137x6Px4KDg61Xr162fPlyKysr87tWVebOnWshISHWoUMHa9KkiS1ZssSioqJsxIgRNmrUKIuMjLTnnnvOr9p79+61lJQUi4uLs8TERPN4PNanTx/r2LGjBQcH2913320VFRV+1e7Ro4cNGjSoyuejrKzM7r33XuvRo4dftc3MPvnkk4suK1asqNHvU69evWzEiBFWWlpqTz/9tLVo0cJGjBjh3T98+HC78847/a5/vgYXUJo3b247d+702fbggw9ay5Yt7Ysvvqjxwa5Jkya2d+9eM/v+D01ISIjPwW3Xrl0WHx/vd/3/+7//s9atW9vDDz9s5eXlZhaYgFJVENqyZYu1aNHC7/pxcXG2bds2M/v+57Bjxw6f/fv27bPIyEi/ap/fe3l5ua1YscIyMzMtODjYkpKSbOrUqd6fiz8iIyO94crMLDQ01D799FPv+sGDB61Ro0Z+1U5JSbG8vDzv+uHDh83j8djJkyfNzOzAgQMWERHhZ+ffC+RBL9AHvCFDhlinTp1s69attnbtWrvuuuusQ4cOdvToUTP7PqB4PB6/6wfygOrxeKxFixbWqlUrn8Xj8dgVV1xhrVq1stTUVL97P////ciRI61du3be2cNvvvnGunTpYr/97W/9qh0VFWUHDhwwM7OOHTvarFmzfPbn5uZa+/bta9T7ggUL7I477rDQ0FCLi4uzcePG2a5du/yueb62bdvavHnzzMxs/fr1FhERYXPmzPHuX7BggbVt29av2llZWTZq1Cjvi5+ZM2daVlaWmZl9/vnn1qpVK5s+fbpftSMjIy96PN+1a5ffx0mz/z/b7PF4Ki3nttfk9zUmJsY761heXm5BQUH20Ucfefd//PHHdsUVV/hd/3wNLqBERUVVOWU7ZswYa9GihW3atKnWAoqZ2WWXXebz6vjgwYM1/mNz7NgxGzJkiF1zzTW2c+dOCw0NrbWAUlRUZGZmSUlJPn+Azb7/QxkeHu53/fvuu8+GDx9uZmZ33323/du//ZvP/pycHMvIyPCr9vkH6vN9+eWXNn36dEtJSanRzzU1NdXee+89M/v+ABQUFGSvvfaad//q1autVatWftUeN26cpaen23vvvWfr16+3nj17+oSF999/3/7hH/7B797NAnvQC/QBLykpyecAd/r0abvjjjusXbt2duTIkRq/qAjkAfV3v/udtWvXrtIxJxAvKlq3bm3vvPOOz/4PP/zQ7/+X0dHR9sknn5jZ9y8ozv37nH379vkdys18e//666/tySeftDZt2lhQUJBdf/31Nm/ePCstLfW7flUvKs4PPwcOHPC7/0aNGvmcoisrK7PQ0FDvKfJVq1b5/bwnJSXZqlWrLrh/5cqVNZpRbdasmc2fP98OHjxY5bJ69eoa/T41btzYG2zNKv8N/PLLL2v8N/CcBhdQrr/+envllVeq3Dd69Ghr2rRpjX4411xzjfcPmdn3B/7zp/r+9Kc/1egV0/mWLVtm8fHxFhQUVGsHu4yMDGvfvr1ddtll9sYbb/js37hxY42S79/+9jdr1aqVdevWzSZMmGCRkZHWtWtXGzlypHXr1s3CwsJs9erVfvdeVUA55+zZs/bBBx/427pNmzbNLr/8chsxYoSlpqbalClTrGXLljZ37lz7wx/+YMnJyfYv//IvftU+duyYDRw40EJCQszj8ViXLl1s//793v1r1qzxCUP+CORB7+c44P3weo2Kigq78847vSHd5QPqypUrLTk52XJzc73bajOgnHtR0bx580o1Dx486PeLin79+tnkyZPNzCwzM7PSqaiXX37Z0tLS/KptduHf2U2bNtnQoUOtcePG1rhxY7/rn3vBafb9scfj8fgcXzZs2OD3jHBSUpLPzHhxcbF5PB5voNq/f7/fz/v06dMtOjrann76aduxY4cVFBRYYWGh7dixw55++mmLiYmp0TVdmZmZ9vvf//6C+3fs2FGjGck2bdr4zL6/88473tlgs5rPxJ+vwQWUnJwc71RcVR544IEa/XDmzp1b6VXM+aZOneqdRagN+fn5tmrVqlq5yDE7O9tnef/99332T5w40QYNGlSj+yguLrZHHnnErrrqKouIiLCwsDBLSUmxwYMH29atW/2u26pVK++rl0D47rvv7PHHH7e+fft6p7qXLVtmycnJFhcXZ8OGDavxz+DUqVNVXgRaGwJ50Av0AS8jI8P++7//u9L2cyGlZcuWNQooP8cB9dChQ3bTTTfZrbfeagUFBbUaUG677Ta76667LCYmxnvNyDn/+7//6/cp5c8++8zi4uJsyJAh9vvf/94uu+wyu+++++yJJ56wIUOGWHh4uC1YsMDv3oOCgi76oqKkpMR7isYfo0ePtrS0NHv88cftV7/6lQ0dOtTatGlj7733nr3//vuWkZHh9+mvoUOHWvfu3W3Pnj22f/9+u+eee3xOd23YsMGSk5P97n3WrFnea1uCgoK8M5GJiYn25JNP+l3X7Pvr5RYvXnzB/UePHrWFCxf6XT87O9uWLVt2wf1Tp061/v37+13/fA0uoACXqkAd9AJ9wJs0aZL17t27yn0VFRXWr1+/GgWgn+uAevbsWcvJybGEhAQLDg6ulYAybNgwn+WHM20TJ060zMxMv+vv27fPBg0aZFFRUd7TdqGhodalSxdbuXJljXr/sVnPmjp+/LiNGDHC0tPT7f7777fy8nJ7+umnLSwszDwej/Xo0cPv+//666+tU6dO3t+lVq1a2ccff+zd/1//9V/2n//5nzV+DPv377fNmzfb5s2bfWZV67MTJ07Y6dOna6VWg/wcFOBSduDAARUWFkqSEhISvJ9L46rvvvtOJ0+eVJMmTarcf+bMGR06dEgpKSkBuf+TJ08qODhY4eHhtVJv+/btysvL05AhQxQTE1MrNS/kxIkTCg4OVkRERI3qmJmKiop09uxZNWvWTKGhobXU4c/v9OnTqqioqJXPFdq7d6/KysrUpk0bvz4DCTXDR90DDUxqaqo6d+6szp07e8NJfn6+fvvb3wbk/mpaOyQk5ILhRJIOHz6sGTNm+F3/xxw5ckQPPPBArdXr0KGDxo0bp5iYmIA+75J09OhRPfjggzWuc+6DwhITE73hJNC9B6p+RESEoqKiaqV+Wlqa0tPTK4WTmtY+deqU8vLy9Nlnn1Xad/r0ab3yyit+124I9b1qZR4GgNNq+lkldVW7vten94ZZvya1A/1hovW9/vmYswIagLfeeuui+/fv3+9k7fpen94bZv1A1n7kkUeUkZGhbdu26dtvv9WECRN0ww03aMOGDWrZsqXfdRtK/fNxDQrQAAQFBcnj8Vz0m689Ho/OnDnjVO36Xp/eG2b9QNaOj4/XunXrlJGR4d02evRovfPOO/rwww/VuHFjJSUl+f281Pf65+MaFKABSExM1Ouvv66zZ89WuXz88cdO1q7v9em9YdYPZO1Tp05VuqZlzpw56tevn7p3767PP//c79oNof75CChAA9ChQ4eLHjR/7NVgXdWu7/XpvWHWD2TtNm3aaNu2bZW25+bm6o477lC/fv38qttQ6vuolStZANSpTZs2+XzC8Q8dP37cNmzY4Fzt+l6f3htm/UDWDvSHidb3+ufjGhQAAOAcTvEAAADnEFAAAIBzCCgAAMA5BBQAAOAcAgqAn9WGDRvk8Xj07bffVrkeCNnZ2WrXrl3A6gOofQQUAHWqS5cuKigoUHR0dF23AsAhfBcPgDoVFhamhISEum4DgGOYQQFQI2VlZXrooYfUvHlzRUREqGvXrtq6dat3/7vvvqvWrVsrMjJSPXv21MGDB31uX9Upns2bN6tbt26KjIxUcnKyHnroIZ04ccJn/A+XYcOGeW8/a9YsxcfHKyoqSsOHD9fp06cD+RQACAACCoAamTRpkl5//XUtWrRIH3/8sa688kplZmbq6NGjys/PV//+/XXbbbdpx44dGjFihCZPnnzRert27VJmZqb69++vnTt3asWKFcrLy9OYMWMk/f9TQueW9evXKyIiQt26dZMkvfbaa5o+fbqeeOIJbdu2TYmJiXrxxRcD/jwAqF18kiwAv504cUIxMTFauHChBg8eLEmqqKhQq1atNH78eBUXF2vVqlXavXu3PB6PJGny5Ml68sknVVxcrKZNm2rDhg3q2bOnd33IkCGKjIzUSy+95L2fvLw8de/eXSdOnFBERIR3+5EjR9SxY0dlZmZqzpw5kr4PMNdee63mzp3rHdepUyedPn1aO3bs+BmeFQC1gRkUAH774osvVFFRoRtuuMG7LTQ0VL/61a+0Z88e7dmzR506dfKGE0nq3LnzRWtu375dCxcu1GWXXeZdMjMzdfbsWR04cMA7rqKiQgMGDFDLli31/PPPe7fv2bOn0n382H0CcA8XyQLw27kJ2PMDyLnt/n7j69mzZzVq1Cg99NBDlfa1bNnS++8HHnhAX331lbZu3Vrp698B1H/MoADw25VXXqmwsDDl5eV5t1VUVGjbtm1q27atrrrqKm3ZssXnNj9c/6Ff/vKX2r17t6688spKS1hYmCRp9uzZWrFihd566y3FxcX53L5t27bVvk8A7uFlBwC/NW7cWA888ID+9V//VbGxsWrZsqWeeuopnTx5UsOHD9exY8f0zDPPaMKECRo1apT39M3FPPLII+rUqZNGjx6tkSNHqnHjxtqzZ4/Wrl2r3NxcrVu3TpMmTdKcOXPUrFkzFRYWSpIiIyMVHR2tcePGaejQobruuuvUtWtXvfrqq9q9e7d+8Ytf/AzPCIDawgwKgBqZNWuWBgwYoN/85jf65S9/qX379mnNmjWKiYlRy5Yt9frrr+vtt9/Wtddeqz/84Q/Kycm5aL1rrrlGGzdu1N69e3XjjTeqffv2+vd//3clJiZK+v6C2TNnzuj+++9XYmKidxk3bpwk6Z577tGjjz6qRx55RB06dNCXX36pBx54IODPA4Daxbt4ANSpNWvWKCsrS6dPn/aewgEAZlAA1Jmvv/5ab775ptLS0ggnAHxwDQqAOnPbbbfp2LFjfJAagEo4xQMAAJzDKR4AAOAcAgoAAHAOAQUAADiHgAIAAJxDQAEAAM4hoAAAAOcQUAAAgHMIKAAAwDn/Dy1Gqg2TCNkbAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.groupby(df['odjezd'].dt.hour)['volnych_mist'].median().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "id": "b57f3c2b-d4c8-4f1f-971e-d663ce264117",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='odjezd'>"
      ]
     },
     "execution_count": 255,
     "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.groupby(df['odjezd'].dt.hour)['cena'].median().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "id": "32e73aee-9996-4e54-8628-c33ddd36e9af",
   "metadata": {},
   "outputs": [],
   "source": [
    "def obdobi(radek):\n",
    "    return f\"\"\"{radek['odjezd'].dayofweek + 1}-{radek['odjezd'].hour // 4}\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "id": "37d17bda-4878-4512-85ce-b9054613cea2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['obdobi'] = df.apply(lambda row: obdobi(row), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "id": "30460342-4fcb-44db-a73c-58c8980e840f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "obdobi\n",
       "7-3     1.00\n",
       "7-4     5.00\n",
       "5-2     7.00\n",
       "5-3     7.00\n",
       "5-1    11.00\n",
       "5-4    18.00\n",
       "4-3    19.50\n",
       "4-4    26.00\n",
       "7-2    26.00\n",
       "3-2    28.00\n",
       "5-5    28.00\n",
       "7-5    29.00\n",
       "6-2    29.75\n",
       "3-3    30.00\n",
       "1-0    31.00\n",
       "4-2    31.00\n",
       "6-1    31.00\n",
       "1-3    32.00\n",
       "3-1    32.50\n",
       "4-5    32.50\n",
       "Name: volnych_mist, dtype: float64"
      ]
     },
     "execution_count": 262,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df['predstih_h'] <= 4) & (df['prodejce'].isin(['RJ','LE']))].groupby('obdobi')['volnych_mist'].quantile(0.25).nsmallest(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "id": "181d3049-2be0-485a-b11f-4a4b35424d87",
   "metadata": {},
   "outputs": [],
   "source": [
    "spicka = ['5-1','5-2','5-3','5-4','7-3','7-4']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "id": "7777cbe5-11c2-4c98-8137-2688932da2fb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['predstih_24h'] = df['predstih_h'] / 24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "id": "0b2fc434-b2c7-49f4-b34d-c59258c12936",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_24h', ylabel='cena'>"
      ]
     },
     "execution_count": 273,
     "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": 279,
   "id": "1650d369-ee9d-4b80-ad3e-212105ec31ba",
   "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>520294</th>\n",
       "      <td>2024-11-17 12:12:56</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-11-17 13:00:00</td>\n",
       "      <td>0 days 00:47:04</td>\n",
       "      <td>0</td>\n",
       "      <td>0.784444</td>\n",
       "      <td>2279.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1259]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LE ne 13:00</td>\n",
       "      <td>7-3</td>\n",
       "      <td>0.032685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520295</th>\n",
       "      <td>2024-11-17 12:12:56</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-11-17 13:00:00</td>\n",
       "      <td>0 days 00:47:04</td>\n",
       "      <td>0</td>\n",
       "      <td>0.784444</td>\n",
       "      <td>2279.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1259]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LE ne 13:00</td>\n",
       "      <td>7-3</td>\n",
       "      <td>0.032685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436363</th>\n",
       "      <td>2024-11-15 10:11:51</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-11-15 13:00:00</td>\n",
       "      <td>0 days 02:48:09</td>\n",
       "      <td>0</td>\n",
       "      <td>2.802500</td>\n",
       "      <td>1879.0</td>\n",
       "      <td>None</td>\n",
       "      <td>1.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>pá</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1259]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>LE pá 13:00</td>\n",
       "      <td>5-3</td>\n",
       "      <td>0.116771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237056</th>\n",
       "      <td>2024-11-10 08:15:54</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2024-11-10 15:00:00</td>\n",
       "      <td>0 days 06:44:06</td>\n",
       "      <td>0</td>\n",
       "      <td>6.735000</td>\n",
       "      <td>1759.0</td>\n",
       "      <td>None</td>\n",
       "      <td>4.0</td>\n",
       "      <td>None</td>\n",
       "      <td>204.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1261]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LE ne 15:00</td>\n",
       "      <td>7-3</td>\n",
       "      <td>0.280625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237055</th>\n",
       "      <td>2024-11-10 08:15:54</td>\n",
       "      <td>LE</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2024-11-10 15:00:00</td>\n",
       "      <td>0 days 06:44:06</td>\n",
       "      <td>0</td>\n",
       "      <td>6.735000</td>\n",
       "      <td>1759.0</td>\n",
       "      <td>None</td>\n",
       "      <td>4.0</td>\n",
       "      <td>None</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>ne</td>\n",
       "      <td>0</td>\n",
       "      <td>[LE1261]</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>LE ne 15:00</td>\n",
       "      <td>7-3</td>\n",
       "      <td>0.280625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542090</th>\n",
       "      <td>2024-11-17 23:59:53</td>\n",
       "      <td>ČD</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2025-01-22 20:22:00</td>\n",
       "      <td>65 days 20:22:07</td>\n",
       "      <td>65</td>\n",
       "      <td>1580.368611</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vlak</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Předpokládané nízké obsazení]</td>\n",
       "      <td>206.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>[0]</td>\n",
       "      <td>None</td>\n",
       "      <td>st</td>\n",
       "      <td>0</td>\n",
       "      <td>[IC 549 Ostravan]</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>ČD st 20:22</td>\n",
       "      <td>3-5</td>\n",
       "      <td>65.848692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542093</th>\n",
       "      <td>2024-11-17 23:59:53</td>\n",
       "      <td>ČD</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2025-01-22 10:22:00</td>\n",
       "      <td>65 days 10:22:07</td>\n",
       "      <td>65</td>\n",
       "      <td>1570.368611</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vlak</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Předpokládané střední obsazení - doporučujeme...</td>\n",
       "      <td>206.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>[0]</td>\n",
       "      <td>None</td>\n",
       "      <td>st</td>\n",
       "      <td>0</td>\n",
       "      <td>[EC 115 Cracovia]</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>ČD st 10:22</td>\n",
       "      <td>3-2</td>\n",
       "      <td>65.432025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542094</th>\n",
       "      <td>2024-11-17 23:59:53</td>\n",
       "      <td>ČD</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2025-01-22 18:22:00</td>\n",
       "      <td>65 days 18:22:07</td>\n",
       "      <td>65</td>\n",
       "      <td>1578.368611</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vlak</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Předpokládané nízké obsazení]</td>\n",
       "      <td>211.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>[0]</td>\n",
       "      <td>None</td>\n",
       "      <td>st</td>\n",
       "      <td>0</td>\n",
       "      <td>[IC 547 Ostravan]</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>ČD st 18:22</td>\n",
       "      <td>3-4</td>\n",
       "      <td>65.765359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542095</th>\n",
       "      <td>2024-11-17 23:59:53</td>\n",
       "      <td>ČD</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava-Svinov</td>\n",
       "      <td>2025-01-23 16:31:00</td>\n",
       "      <td>66 days 16:31:07</td>\n",
       "      <td>66</td>\n",
       "      <td>1600.518611</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vlak</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Předpokládané nízké obsazení]</td>\n",
       "      <td>184.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>[0]</td>\n",
       "      <td>None</td>\n",
       "      <td>čt</td>\n",
       "      <td>0</td>\n",
       "      <td>[SC 513 Pendolino]</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>ČD čt 16:31</td>\n",
       "      <td>4-4</td>\n",
       "      <td>66.688275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542096</th>\n",
       "      <td>2024-11-17 23:59:53</td>\n",
       "      <td>ČD</td>\n",
       "      <td>Praha hl.n.</td>\n",
       "      <td>Ostrava hl.n.</td>\n",
       "      <td>2025-01-22 08:22:00</td>\n",
       "      <td>65 days 08:22:07</td>\n",
       "      <td>65</td>\n",
       "      <td>1568.368611</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vlak</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[Předpokládané nízké obsazení]</td>\n",
       "      <td>206.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>[0]</td>\n",
       "      <td>None</td>\n",
       "      <td>st</td>\n",
       "      <td>0</td>\n",
       "      <td>[EC 141 Ostravan]</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>ČD st 08:22</td>\n",
       "      <td>3-2</td>\n",
       "      <td>65.348692</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73153 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               oscrapovano prodejce        odkud             kam  \\\n",
       "520294 2024-11-17 12:12:56       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "520295 2024-11-17 12:12:56       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "436363 2024-11-15 10:11:51       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "237056 2024-11-10 08:15:54       LE  Praha hl.n.  Ostrava-Svinov   \n",
       "237055 2024-11-10 08:15:54       LE  Praha hl.n.   Ostrava hl.n.   \n",
       "...                    ...      ...          ...             ...   \n",
       "542090 2024-11-17 23:59:53       ČD  Praha hl.n.   Ostrava hl.n.   \n",
       "542093 2024-11-17 23:59:53       ČD  Praha hl.n.   Ostrava hl.n.   \n",
       "542094 2024-11-17 23:59:53       ČD  Praha hl.n.   Ostrava hl.n.   \n",
       "542095 2024-11-17 23:59:53       ČD  Praha hl.n.  Ostrava-Svinov   \n",
       "542096 2024-11-17 23:59:53       ČD  Praha hl.n.   Ostrava hl.n.   \n",
       "\n",
       "                    odjezd         predstih  predstih_d   predstih_h    cena  \\\n",
       "520294 2024-11-17 13:00:00  0 days 00:47:04           0     0.784444  2279.0   \n",
       "520295 2024-11-17 13:00:00  0 days 00:47:04           0     0.784444  2279.0   \n",
       "436363 2024-11-15 13:00:00  0 days 02:48:09           0     2.802500  1879.0   \n",
       "237056 2024-11-10 15:00:00  0 days 06:44:06           0     6.735000  1759.0   \n",
       "237055 2024-11-10 15:00:00  0 days 06:44:06           0     6.735000  1759.0   \n",
       "...                    ...              ...         ...          ...     ...   \n",
       "542090 2025-01-22 20:22:00 65 days 20:22:07          65  1580.368611     NaN   \n",
       "542093 2025-01-22 10:22:00 65 days 10:22:07          65  1570.368611     NaN   \n",
       "542094 2025-01-22 18:22:00 65 days 18:22:07          65  1578.368611     NaN   \n",
       "542095 2025-01-23 16:31:00 66 days 16:31:07          66  1600.518611     NaN   \n",
       "542096 2025-01-22 08:22:00 65 days 08:22:07          65  1568.368611     NaN   \n",
       "\n",
       "       prostredek  volnych_mist  \\\n",
       "520294       None           1.0   \n",
       "520295       None           1.0   \n",
       "436363       None           1.0   \n",
       "237056       None           4.0   \n",
       "237055       None           4.0   \n",
       "...           ...           ...   \n",
       "542090       vlak           NaN   \n",
       "542093       vlak           NaN   \n",
       "542094       vlak           NaN   \n",
       "542095       vlak           NaN   \n",
       "542096       vlak           NaN   \n",
       "\n",
       "                                               obsazenost  jizdni_doba  \\\n",
       "520294                                               None        204.0   \n",
       "520295                                               None        211.0   \n",
       "436363                                               None        204.0   \n",
       "237056                                               None        204.0   \n",
       "237055                                               None        211.0   \n",
       "...                                                   ...          ...   \n",
       "542090                     [Předpokládané nízké obsazení]        206.0   \n",
       "542093  [Předpokládané střední obsazení - doporučujeme...        206.0   \n",
       "542094                     [Předpokládané nízké obsazení]        211.0   \n",
       "542095                     [Předpokládané nízké obsazení]        184.0   \n",
       "542096                     [Předpokládané nízké obsazení]        206.0   \n",
       "\n",
       "        vzdalenost zpozdeni cena_poznamka den  prestupy               vlaky  \\\n",
       "520294       351.0     None          None  ne         0            [LE1259]   \n",
       "520295       356.0     None          None  ne         0            [LE1259]   \n",
       "436363       351.0     None          None  pá         0            [LE1259]   \n",
       "237056       351.0     None          None  ne         0            [LE1261]   \n",
       "237055       356.0     None          None  ne         0            [LE1261]   \n",
       "...            ...      ...           ...  ..       ...                 ...   \n",
       "542090       356.0      [0]          None  st         0   [IC 549 Ostravan]   \n",
       "542093       356.0      [0]          None  st         0   [EC 115 Cracovia]   \n",
       "542094       356.0      [0]          None  st         0   [IC 547 Ostravan]   \n",
       "542095       351.0      [0]          None  čt         0  [SC 513 Pendolino]   \n",
       "542096       356.0      [0]          None  st         0   [EC 141 Ostravan]   \n",
       "\n",
       "       mistenka_zdarma nahradni_bus  volna_mista_economy  \\\n",
       "520294            None         None                  0.0   \n",
       "520295            None         None                  0.0   \n",
       "436363            None         None                  0.0   \n",
       "237056            None         None                  0.0   \n",
       "237055            None         None                  0.0   \n",
       "...                ...          ...                  ...   \n",
       "542090            None         None                  NaN   \n",
       "542093            None         None                  NaN   \n",
       "542094            None         None                  NaN   \n",
       "542095            None         None                  NaN   \n",
       "542096            None         None                  NaN   \n",
       "\n",
       "        volna_mista_economy_plus  volna_mista_economy_business  \\\n",
       "520294                       0.0                           0.0   \n",
       "520295                       0.0                           0.0   \n",
       "436363                       0.0                           1.0   \n",
       "237056                       0.0                           3.0   \n",
       "237055                       0.0                           3.0   \n",
       "...                          ...                           ...   \n",
       "542090                       NaN                           NaN   \n",
       "542093                       NaN                           NaN   \n",
       "542094                       NaN                           NaN   \n",
       "542095                       NaN                           NaN   \n",
       "542096                       NaN                           NaN   \n",
       "\n",
       "        volna_mista_premium         spoj obdobi  predstih_24h  \n",
       "520294                  1.0  LE ne 13:00    7-3      0.032685  \n",
       "520295                  1.0  LE ne 13:00    7-3      0.032685  \n",
       "436363                  0.0  LE pá 13:00    5-3      0.116771  \n",
       "237056                  1.0  LE ne 15:00    7-3      0.280625  \n",
       "237055                  1.0  LE ne 15:00    7-3      0.280625  \n",
       "...                     ...          ...    ...           ...  \n",
       "542090                  NaN  ČD st 20:22    3-5     65.848692  \n",
       "542093                  NaN  ČD st 10:22    3-2     65.432025  \n",
       "542094                  NaN  ČD st 18:22    3-4     65.765359  \n",
       "542095                  NaN  ČD čt 16:31    4-4     66.688275  \n",
       "542096                  NaN  ČD st 08:22    3-2     65.348692  \n",
       "\n",
       "[73153 rows x 28 columns]"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by=\"cena\",ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "id": "6bd2c1e5-3df7-49f5-8501-40fa51bc0cf1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='predstih_24h', ylabel='cena'>"
      ]
     },
     "execution_count": 275,
     "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'] <= 14)].plot.scatter(x='predstih_24h',y='cena')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "id": "2868ea09-21a2-44fa-afe4-3a397a15bb9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "559.0"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['predstih_h'] <= 24]['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
}