passagiere/Flugpassagiere_ab_ZRH_pro_Monat_seit_2000.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6bf89552",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import requests"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa864ab4",
   "metadata": {},
   "source": [
    "#### Infos zum Datensatz\n",
    "##### Art des Verkehrs\n",
    "* Linienverkehr: Flüge zur gewerbsmässigen Beförderung von Personen oder Gütern, wenn sie während einer Mindestdauer so regelmässig oder häufig erfolgen, dass es sich erkennbar um eine systematische Folge von Flügen handelt, und im Personenverkehr in der Öffentlichkeit Sitzplätze zum Einzelkauf angeboten werden.\n",
    "* Charterverkehr: Gelegentliche Flugverbindungen, bei denen meist Reiseveranstalter bei einer Fluggesellschaft bestimmte Flüge kaufen. Die Plätze darin werden dann beispielsweise zusammen mit einer Unterkunft zu einem Pauschalreise-Angebot gebündelt.\n",
    "\n",
    "##### Art der Passagiere\n",
    "* Lokal- und Transferpassagiere: Die Lokalpassagiere eines Flughafens beginnen oder beenden ihre Flugreise an diesem Flughafen. Die Transferpassagiere eines Flughafens sind Umsteiger und fliegen mit einem anderen Flugzeug (andere Flugnummer) weiter, als sie angekommen sind. Sie werden zweimal gezählt: einmal bei der Landung und einmal beim Start.\n",
    "* Transitpassagiere: Die Transitpassagiere eines Flughafens fliegen nach einer Zwischenlandung mit dem gleichen Flugzeug (gleiche Flugnummer) weiter. Sie werden zweimal gezählt: einmal bei der Landung und einmal beim Start.\n",
    "\n",
    "##### Schlussfolgerung\n",
    "Es reicht eine Unterteilung in Linien- und Chartverkehr. Die Lokal- und Transferpassagiere können mit den Transitpassagieren zusammengenommen werden. Transferpassagiere und Transitpassagiere unterscheiden sich nur darin, dass sie das Flugzeug nicht wechseln."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10b02272",
   "metadata": {},
   "source": [
    "## 1. Schritt: Daten einlesen"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c30e5f70",
   "metadata": {},
   "source": [
    "Wir fragen die Daten direkt aus STAT-TAB (Bundesamt für Statistik ab)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "823e1a8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://www.pxweb.bfs.admin.ch/api/v1/de/px-x-1107020000_102/px-x-1107020000_102.px' #Die URL für die Abfrage direkt aus STAT-TAB\n",
    "\n",
    "#Die JSON-Abfrage für die gewünschten Daten\n",
    "myobj =  {\n",
    "  \"query\": [\n",
    "    {\n",
    "      \"code\": \"Flughafen\",\n",
    "      \"selection\": {\n",
    "        \"filter\": \"item\",\n",
    "        \"values\": [\n",
    "          \"103\"\n",
    "        ]\n",
    "      }\n",
    "    },\n",
    "    {\n",
    "      \"code\": \"Art des Verkehrs\",\n",
    "      \"selection\": {\n",
    "        \"filter\": \"item\",\n",
    "        \"values\": [\n",
    "          \"2\",\n",
    "          \"3\"\n",
    "        ]\n",
    "      }\n",
    "    },\n",
    "    {\n",
    "      \"code\": \"Monat\",\n",
    "      \"selection\": {\n",
    "        \"filter\": \"item\",\n",
    "        \"values\": [\n",
    "          \"1\",\n",
    "          \"2\",\n",
    "          \"3\",\n",
    "          \"4\",\n",
    "          \"5\",\n",
    "          \"6\",\n",
    "          \"7\",\n",
    "          \"8\",\n",
    "          \"9\",\n",
    "          \"10\",\n",
    "          \"11\",\n",
    "          \"12\"\n",
    "        ]\n",
    "      }\n",
    "    },\n",
    "    {\n",
    "      \"code\": \"Jahr\",\n",
    "      \"selection\": {\n",
    "        \"filter\": \"item\",\n",
    "        \"values\": [\n",
    "          \"0\",\n",
    "          \"1\",\n",
    "          \"2\",\n",
    "          \"3\",\n",
    "          \"4\",\n",
    "          \"5\",\n",
    "          \"6\",\n",
    "          \"7\",\n",
    "          \"8\",\n",
    "          \"9\",\n",
    "          \"10\",\n",
    "          \"11\",\n",
    "          \"12\",\n",
    "          \"13\",\n",
    "          \"14\",\n",
    "          \"15\",\n",
    "          \"16\",\n",
    "          \"17\",\n",
    "          \"18\",\n",
    "          \"19\",\n",
    "          \"20\",\n",
    "          \"21\"\n",
    "        ]\n",
    "      }\n",
    "    }\n",
    "  ],\n",
    "  \"response\": {\n",
    "    \"format\": \"json-stat\"\n",
    "  }\n",
    "}\n",
    "\n",
    "data = requests.post(url, json = myobj) #Die Daten abspeichern"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4061ba07",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  'dimension': {'Flughafen': {'label': 'Flughafen',\n",
       "    'category': {'index': {'103': 0}, 'label': {'103': '... Zürich Kloten'}}},\n",
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       "  'label': 'Flugpassagiere im Linien- und Charterverkehr nach Flughafen, Art des Verkehrs, Art der Passagiere, Monat und Jahr',\n",
       "  'source': 'BFS - Luftverkehr, Linien- und Charterverkehr - © BFS',\n",
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       "   47222,\n",
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       "   33630,\n",
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       "   88260,\n",
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       "   1284,\n",
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       "   3067,\n",
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       "   3475,\n",
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       "   0,\n",
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       "   1742,\n",
       "   ...]}}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Erster Blick in die Struktur der Daten\n",
    "data.json()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5f241965",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['status', 'dimension', 'label', 'source', 'updated', 'value']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Die oberste Ebene 'dataset' genauer anschauen\n",
    "list(data.json()['dataset'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "81a05265",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Flughafen',\n",
       " 'Art des Verkehrs',\n",
       " 'Art der Passagiere',\n",
       " 'Monat',\n",
       " 'Jahr',\n",
       " 'id',\n",
       " 'size',\n",
       " 'role']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Relevant sind 'value' (=Wert) und einige der Angaben unter 'dimension'\n",
    "list(data.json()['dataset']['dimension'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6e41b305",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Die relevanten Daten als Listen herausfiltern.\n",
    "monat = data.json()['dataset']['dimension']['Monat']['category']['label']\n",
    "monat = list(monat.values())\n",
    "jahr = data.json()['dataset']['dimension']['Jahr']['category']['label']\n",
    "jahr = list(jahr.values())\n",
    "passagiere = data.json()['dataset']['value']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "399ace5f",
   "metadata": {},
   "source": [
    "Die Daten (Anzahl Passagiere) liegt in einer Liste vor, die verschiedene Dimensions beinhaltet. Konkret: Zuerst sind die Zahlen der Art des Verkehrs \"Linienverkehr\" kombiniert mit der Art der Passagiere \"Lokal- und Transferpassagiere\" hintereinander abgebildet. Dabei werden erst die Zahlen aller Januare von 2021 bis 2000 zurück hintereinander abgebildet, danach alle Februare usw. Wenn alle Monate durch sind, folgt die Art des Verkehrs \"Linienverkehr\" jetzt kombiniert mit der Art der Passagiere \"Transitpassagiere\", wiederum für alle Monate. Danach noch zweimal für die Art des Verkehrs \"Charterverkehr\".\n",
    "\n",
    "Das heisst auch, es sind pro Jahr vier verschiedene Januare, vier verschiedene Februare usw. enthalten, also 4 x 12 = 48 Monate. Die Länge der Liste passagiere ergibt sich aus diesen 48 Monaten und den Anzahl Jahren, die abgefragt werden."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "333d8bca",
   "metadata": {},
   "source": [
    "Im Datensatz sind n Anzahl Jahre enthalten. Das heisst, es gibt in der Liste passagiere n Einträge eines Monats einer Verkehr-/Passagier-Art. Nach diesen n einzelnen Werten folgt jeweils der nächste Monat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1bd9a18b",
   "metadata": {},
   "outputs": [],
   "source": [
    "n = int(len(passagiere))/48 #Pro Jahr sind 48 Monate (4x12) enthalten. Die Länge der Liste durch 48 ergibt die Anzahl Jahre.\n",
    "n = int(n)\n",
    "monate=[passagiere[i:i + n] for i in range(0, len(passagiere), n)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae59e479",
   "metadata": {},
   "source": [
    "Wir haben nun für alle Monate einzelne Listen, die wiederum in einer Liste enthalten sind. Jeweils 12 Listen sind ein Jahr (Januar bis Februar) für die oben erwähnten unterschiedlichen Verkehrsarten und Passagierarten. Daraus können wir unterschiedliche Dataframes machen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cf173aea",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfpaxlinielokal = pd.DataFrame(monate[0:12])\n",
    "dfpaxlinietransit = pd.DataFrame(monate[12:24])\n",
    "dfpaxcharterlokal = pd.DataFrame(monate[24:36])\n",
    "dfpaxchartertransit = pd.DataFrame(monate[36:48])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c93b4341",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Indexe als Monate\n",
    "dfpaxlinielokal.index = monat\n",
    "dfpaxlinietransit.index = monat\n",
    "dfpaxcharterlokal.index = monat\n",
    "dfpaxchartertransit.index = monat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "28b2b052",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Jahre als Header\n",
    "dfpaxlinielokal.columns = jahr\n",
    "dfpaxlinietransit.columns = jahr\n",
    "dfpaxcharterlokal.columns = jahr\n",
    "dfpaxchartertransit.columns = jahr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "944111d7",
   "metadata": {},
   "source": [
    "Wir haben nun vier Dataframes:\n",
    "- Linienverkehr/Lokal- und Transferpassagiere\n",
    "- Linienverkehr/Transitpassagiere\n",
    "- Charterverkehr/Lokal- und Transferpassagiere\n",
    "- Charterverkehr/Transitpassagiere\n",
    "\n",
    "Diese liegen in einer Art Matrix vor. Für die Weiterbearbeitung wäre es günstiger, die Dataframes wären in einem Wide-Format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "6dabd909",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'German_Germany.1252'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import locale\n",
    "locale.setlocale(locale.LC_ALL, 'deu_deu') #locale auf Deutsch umstellen, weil wir mit Datumsangaben arbeiten müssen"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fcbf2607",
   "metadata": {},
   "source": [
    "Um aus der Matrix eine Tabelle mit einer Zeile zu machen, müssen wir das einzelne Dataframe zuerst \"stacken\" und dann pivotieren. Danach konvertieren wir die Spalten, die jetzt als Text in zwei Header-Leveln vorliegen als Datetime-Format und sortieren."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "20534169",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfpaxlinielokal = dfpaxlinielokal.stack().reset_index().pivot_table(columns=[\"level_1\",\"level_0\"])\n",
    "dfpaxlinietransit = dfpaxlinietransit.stack().reset_index().pivot_table(columns=[\"level_1\",\"level_0\"])\n",
    "dfpaxcharterlokal = dfpaxcharterlokal.stack().reset_index().pivot_table(columns=[\"level_1\",\"level_0\"])\n",
    "dfpaxchartertransit = dfpaxchartertransit.stack().reset_index().pivot_table(columns=[\"level_1\",\"level_0\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9df8752d",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfpaxlinielokal.columns = pd.to_datetime([\"-\".join(col).strip() for col in dfpaxlinielokal.columns.values],format=\"%Y-%B\")\n",
    "dfpaxlinielokal = dfpaxlinielokal.reindex(sorted(dfpaxlinielokal.columns, key=lambda x: (x.year, x.month)), axis=1) \n",
    "dfpaxlinietransit.columns = pd.to_datetime([\"-\".join(col).strip() for col in dfpaxlinietransit.columns.values],format=\"%Y-%B\")\n",
    "dfpaxlinietransit = dfpaxlinietransit.reindex(sorted(dfpaxlinietransit.columns, key=lambda x: (x.year, x.month)), axis=1) \n",
    "dfpaxcharterlokal.columns = pd.to_datetime([\"-\".join(col).strip() for col in dfpaxcharterlokal.columns.values],format=\"%Y-%B\")\n",
    "dfpaxcharterlokal = dfpaxcharterlokal.reindex(sorted(dfpaxcharterlokal.columns, key=lambda x: (x.year, x.month)), axis=1) \n",
    "dfpaxchartertransit.columns = pd.to_datetime([\"-\".join(col).strip() for col in dfpaxchartertransit.columns.values],format=\"%Y-%B\")\n",
    "dfpaxchartertransit = dfpaxchartertransit.reindex(sorted(dfpaxchartertransit.columns, key=lambda x: (x.year, x.month)), axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89e83122",
   "metadata": {},
   "source": [
    "Die Header würden jetzt im Muster 2021-01-01 angezeigt, weshalb wir diese wiederum zu Strings nach dem Muster 2021-Jan konvertieren."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5953f552",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfpaxlinielokal.columns = [col.strftime(\"%Y-%b\") for col in dfpaxlinielokal.columns]\n",
    "dfpaxlinietransit.columns = [col.strftime(\"%Y-%b\") for col in dfpaxlinietransit.columns]\n",
    "dfpaxcharterlokal.columns = [col.strftime(\"%Y-%b\") for col in dfpaxcharterlokal.columns]\n",
    "dfpaxchartertransit.columns = [col.strftime(\"%Y-%b\") for col in dfpaxchartertransit.columns]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "926fa4b3",
   "metadata": {},
   "source": [
    "Nun führen wir die vier Dataframes zu einem zusammen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fcbee994",
   "metadata": {},
   "outputs": [],
   "source": [
    "frames = [dfpaxlinielokal, dfpaxlinietransit, dfpaxcharterlokal, dfpaxchartertransit]\n",
    "df = pd.concat(frames)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36b0f563",
   "metadata": {},
   "source": [
    "Damit der Index stimmt, ergänzen wir eine weitere Column, die wir dann zum Index machen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a28cbcb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "index = [\"Linenverkehr, Lokal- und Transferpassagiere\", \"Linienverkehr, Transitpassagiere\", \"Charterverkehr, Lokal- und Transferpassagiere\", \"Charterverkehr, Transitpassagiere\"]\n",
    "df[\"index\"] = index\n",
    "df.set_index(\"index\", inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f68d728b",
   "metadata": {},
   "source": [
    "Wie oben bei den Infos zu den Daten vermerkt, reicht eine Unterteilung in Linien- und Charterverkehr. Wir zählen deshalb  zusammen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "aaed3562",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_row1 = df.loc[\"Linenverkehr, Lokal- und Transferpassagiere\"] + df.loc[\"Linienverkehr, Transitpassagiere\"]\n",
    "new_row2 = df.loc[\"Charterverkehr, Lokal- und Transferpassagiere\"] + df.loc[\"Charterverkehr, Transitpassagiere\"]\n",
    "\n",
    "new_row1.name = \"Linienverkehr\"\n",
    "new_row2.name = \"Charterverkehr\"\n",
    "df = df.append([new_row1, new_row2])\n",
    "df.drop(df.index[0:4], inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e46ebec2",
   "metadata": {},
   "source": [
    "## 2. Schritt: Daten auswerten"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0d3643c",
   "metadata": {},
   "source": [
    "In einem ersten Schritt schauen wir uns an, wie sich die Zahl der Flugpassagiere entwickelt hat."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "48c4b8f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.T.plot(figsize=(15,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e008f25f",
   "metadata": {},
   "source": [
    "Indem wir uns den Zeitraum ab 2018 anschauen, können wir Jahresmuster erkennen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "45e66226",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.iloc[0:1,216:].T.plot(figsize=(15,6), grid=True) #Linienverkehr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "712141af",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.iloc[1:2,216:].T.plot(figsize=(15,6), grid=True) #Charterverkehr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f96fdc57",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Dataframe abspeichern\n",
    "df.to_csv('Passagiere-ab-ZRH-pro-Monat-seit-2000.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba03a005",
   "metadata": {},
   "source": [
    "Nun analysieren wir Veränderungen zum Vorjahr und zum Vormonat. Dazu hängen wir der transponierten Tabelle die Spalten mit Vorjahres- (YoY) und Vormonatsveränderungen (MoM) an."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8341e33d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_vorjahr = df.T\n",
    "df_vorjahr[\"Linie YoY\"] = df_vorjahr[\"Linienverkehr\"].pct_change(12).mul(100)\n",
    "df_vorjahr[\"Charter YoY\"] = df_vorjahr[\"Charterverkehr\"].pct_change(12).mul(100)\n",
    "df_vorjahr[\"Linie MoM\"] = df_vorjahr[\"Linienverkehr\"].pct_change().mul(100)\n",
    "df_vorjahr[\"Charter MoM\"] = df_vorjahr[\"Charterverkehr\"].pct_change().mul(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8e4b586b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_vorjahr.iloc[216:,4:5].plot(kind=\"bar\", figsize=(15,6)) #Vormonat, Linienverkehr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "db2c31a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_vorjahr.iloc[216:,2:3].plot(kind=\"bar\", figsize=(15,6)) #Vorjahr, Linienverkehr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e16cc707",
   "metadata": {},
   "source": [
    "Die Grafik hat ein offensichtliches Problem: Der Einbruch wegen der Pandemie (ab März 2000) kann allerhöchstens 100 Prozent sein. Die Erholung im 2021 scheint extrem hoch, sie wird aber mit den Pandemiemonaten 2020 verglichen und ist deshalb überzeichnet. Selbst im April mit einem Plus von rund 1400% zum Vorjahr sind die Flugbewegungen noch deutlicher unter dem Vor-Pandemie-Wert. Für die Erholung des Flugverkehrs sind deshalb Vergleiche mit 2019 sinnvoller. Deshalb erstellen wir zwei Dataframes, eines mit 2019er-Werten, eines mit jenen danach. Und eruieren dann jeweils die Differenz der Monate während der Pandemie mit jenen vor der Pandemie."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a80f18d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_2019 = df.iloc[:,228:240].T.reset_index()\n",
    "df_pandemie = df.iloc[:,240:].T.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "474109b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Dataframes mit unterschiedlichen Längen\n",
    "difflinie = df_pandemie['Linienverkehr'].sub(df_pandemie['index'].str.split('-').str[-1].map(dict(zip(df_2019['index'].str.split('-').str[-1], df_2019['Linienverkehr']))))\n",
    "diffcharter = df_pandemie['Charterverkehr'].sub(df_pandemie['index'].str.split('-').str[-1].map(dict(zip(df_2019['index'].str.split('-').str[-1], df_2019['Charterverkehr']))))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19d32fe7",
   "metadata": {},
   "source": [
    "Die Erklärung dieser Codezeile bzw. Codezeilen (es ist zweimal dasselbe Vorgehen):\n",
    "* Im ersten Teil des Teils nach .sub (zum Teil davor weiter unten) (bis vor .map) nehmen wir den Monat des Pandemie-Dfs.\n",
    "* Auf diesen Teil wenden wir später .map an.\n",
    "* In der Klammer nach .map wird ein Dictionary erzeugt mit dem Monat des 2019-Dataframes und dem entsprechenden Wert des Monats im gleichen Dataframe.\n",
    "* Der Key dieses Dictionarys ist dann jeweils der Monat. \n",
    "* .map nimmt nun den Monat vom ersten Teil (also vom Pandemie-Dataframe) und sucht den korrekten Key vom Dictionary (also den Monat vom 2019-Dataframe) und gibt den Wert davon aus.\n",
    "* In der Klammer nach .sub steht also am Ende ein Wert, der vom Wert vom Teil vor .sub abgezogen wird. Vor .sub steht das Pandemie-Dataframe. Es ergibt sich also am Schluss: Monatswert im Pandemie-Dataframe minus Monatswert im 2019er-Dataframe gleich Differenz vom Monat ab 2020 zum gleichen Monat im Jahr 2019."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "020ef903",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Neue Spalten dem Dataframe anhängen\n",
    "df_pandemie['Linienverkehr zu 2019'] = difflinie\n",
    "df_pandemie['Charterverkehr zu 2019'] = diffcharter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "3735e9ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pandemie.set_index('index', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a7ff59b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='index'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_pandemie.iloc[:,2:3].plot(kind=\"bar\", figsize=(15,6)) #Unterschiede zum Vor-Pandemie-Monat, Linienverkehr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "964d059f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='index'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_pandemie.iloc[:,3:4].plot(kind=\"bar\", figsize=(15,6)) #Unterschiede zum Vor-Pandemie-Monat, Charterverkehr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94f3945d",
   "metadata": {},
   "source": [
    "Nun berechnen wir die Unterschiede in Prozent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "e1ccaf05",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_pandemie['Linienverkehr zu 2019 in %'] = df_pandemie['Linienverkehr zu 2019']/(df_pandemie[\"Linienverkehr\"] - df_pandemie['Linienverkehr zu 2019'])*100\n",
    "df_pandemie['Charterverkehr zu 2019 in %'] = df_pandemie['Charterverkehr zu 2019']/(df_pandemie[\"Charterverkehr\"] - df_pandemie['Charterverkehr zu 2019'])*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4734beee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='index'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7pSRpSDkzp6Sh4LZFeo5H6iRJkiSpYhZ1kiRJklQxizpJkiRJqpjn1EmSVDDPG5IkrYpH6iRJkiSpYhZ1kiRJklQxizpJkiRJqphFnSRJkiRVzIlSJEnSoDmRiyQ1zyN1kiRJklQxizpJkiRJqphFnSRJkiRVzKJOkiRJkirmRCmSJEnqyolwpDp4pE6SJEmSKuaROknSiOaRCElS7TxSJ0mSJEkVs6iTJEmSpIpZ1EmSJElSxSzqJEmSJKliTpQiSZKGrdInwik9n6Q6eKROkiRJkipmUSdJkiRJFbOokyRJkqSKWdRJkiRJUsUs6iRJkiSpYhZ1kiRJklQxf9JAGiGcNluSJGl48kidJEmSJFXMok6SJEmSKmZRJ0mSJEkVs6iTJEmSpIpZ1EmSJElSxSzqJEmSJKliFnWSJEmSVDGLOkmSJEmqmEWdJEmSJFVsTNMBJEmSpKH29NNPs3DhQp588smmo0irNHbsWMaNG8d66623Wve3qJMkSdKwt3DhQjbeeGMmTJhARDQdRxpQZrJkyRIWLlzIdtttt1qPcfilJEmShr0nn3ySzTff3IJOxYsINt988zU6qmxRJ0mSpBHBgk61WNO/VYs6SZIkaR3YaKONVlj2hS98gS9/+csrfdzcuXP54Ac/OFSxVmnChAk89NBDq3Xfiy66iPe///1DnOg5999/P/vttx877bQTO++8M//yL/+ybN3DDz/MgQceyPbbb8+BBx7II488AsCSJUvYb7/92GijjVbIOmvWLHbddVd23nlnTj755K6vOXv2bGbMmLHaGR988EH22WcfdtllFy677LJly6dOncqiRYvW4H87MM+pkyRJ0ogzYfr31urzLZjx5kE97j3vec8q7zNp0iQmTZo0qOfv1TPPPDNkzzt69Oien2fMmDF86lOfYvfdd+ePf/wje+yxBwceeCATJ05kxowZ7L///kyfPp0ZM2YwY8YMZs6cydixY/nEJz7Brbfeyq233rrsuZYsWcKHP/xh5s2bx5ZbbskxxxzDD3/4Q/bff//lXvOQQw7hkEMOWe2MX//61znmmGM46qijmDJlCoceeijf/e532X333dl66617bgOwqJPWmsFuzCVJ0sh1+umns9FGG3HSSSex7777sueee3Lttdfy6KOPcuGFF/IXf/EXXHfddZxzzjlcccUVPP7443zgAx/glltuYenSpZx++ulMnTqViy66iNmzZ/PEE0/wm9/8hsMOO4yzzz6b888/n3vvvZezzz4baB1JmzdvHp/97Gf56le/ymc+8xn+/Oc/s+eee3LeeecxevRoNtpoI0488USuvPJKPvWpTy3L+qc//YnDDjuMadOmcfTRR3fNAbBo0SKmTJmyXA5ghefdZ599lt3/TW9607LXueWWW7jnnns47bTTeMtb3sIRRxyx7PGPPfbYcu231VZbsdVWWwGw8cYbs9NOO/G73/2OiRMncvnll3PdddcBcMwxx7Dvvvsyc+ZMNtxwQ/bZZx/uvvvu5Z7rnnvuYYcddmDLLbcE4IADDuDb3/72CkXdRRddxNy5c/nc5z7HscceyyabbMLcuXP5/e9/z9lnn70sb5/11luPP/3pTzz11FOMGjWKpUuXcu655/Ld7353Df9aBtbT8MuI+KuIuC0ino2ISf3WfTQi7o6IuyLioI7le0TELe11nwkHN0uSJEkALF26lDlz5nDuuefy8Y9/fIX1Z511Fq9//eu56aabuPbaa/nwhz/M448/DsD8+fOZNWsWt9xyC7NmzeL+++/niCOO4NJLL132+FmzZnHkkUdyxx13MGvWLK6//nrmz5/P6NGj+drXvgbA448/zi677MKNN964rPB67LHHOPjggzn66KM57rjj1jjHQM8LsPXWWzN//nzmz5/Pcccdx7Rp03jJS16yxm23YMECbr75Zvbcc08A/vCHPywr+LbaaiseeOCBlT7+5S9/OXfeeScLFixg6dKlXHbZZcuyr8zixYv56U9/yhVXXMH06dNXWH/00Udz5ZVXMmXKFE4//XTOO+883vGOd/C85z1vjf+PA+n1SN2twOHAv3YujIiJwFHAzsDWwDURsUNmPgOcDxwP3AB8H5gC/KDHHBoBPBImSZKGu8MPPxyAPfbYgwULFqyw/qqrrmL27Nmcc845QGtWz9/+9rcA7L///my66aYATJw4kfvuu4999tmHl770pdxwww1sv/323HXXXey99958/vOfZ968ebz61a8GWkfhXvjCFwIwevRopk2bttzrTp06lZNPPpm3v/3tg8qx7bbbdn3eTtdffz1f/OIX+clPfrLG7fbYY48xbdo0zj33XDbZZJM1fjzAZpttxvnnn8+RRx7JqFGjeO1rX8s999yzyscdeuihjBo1iokTJ/KHP/xhhfWbbrop3/tea7jvI488wsyZM7n00ks57rjjeOSRR/jQhz7Ea17zmkFl7tNTUZeZd0DX2VmmAt/IzKeAeyPibmByRCwANsnM/24/7svAoVjUSZIkSWywwQZAq7BaunTpCuszk29/+9u84hWvWG75jTfeuOyx/R9/5JFHcskll7Djjjty2GGHERFkJscccwyf/OQnV3iNsWPHrnC+2957780PfvADjj766GWPX9Mc3Z63z+LFi3nXu97F7Nmzl00oM2bMGJ599tll/+8///nPXR/79NNPM23aNN7+9rcvK4oBXvSiF7F48WK22morFi9evKxoXZmDDz6Ygw8+GIALLrhgtc776/z/ZuZK73vGGWdwyimn8PWvf5099tiDo48+mqlTp3Lttdeu8nVWZqhmv9wG6DxWubC9bJv29f7LJUmSJK3CQQcdxGc/+9llxcPNN9+8ysccfvjhXHbZZXz961/nyCOPBFpH0771rW8tG5L48MMPc9999w34HGeccQabb745733vewedYyBPP/00b33rW5k5cyY77LDDsuUTJkxg3rx5AFx++eU8/fTTKzw2M3nXu97FTjvtxIknnrjcukMOOYSLL74YgIsvvnjZOX8r09cejzzyCOeddx7vfve7B/3/6u/Xv/41ixYt4nWvex1PPPEEo0aNIiLW6PfoBrLKoi4iromIW7tcVtYq3c6Ty5UsH+i1j4+IuREx98EHH1xVVEmSJKlYTzzxBOPGjVt2+fSnP73Gz3Hqqafy9NNPs+uuu7LLLrtw6qmnrvIxm2222bJhkJMnTwZawyLPPPNM3vCGN7Drrrty4IEHsnjx4pU+z7nnnsuTTz7JySefPKgcA/nZz37GTTfdxGmnncZuu+3GbrvtxqJFizjuuOP48Y9/zOTJk7nxxhvZcMMNV3js9ddfz1e+8hV+9KMfLXvs97//fQCmT5/O1Vdfzfbbb8/VV1+93PluEyZM4MQTT+Siiy5i3Lhx3H777QCccMIJTJw4kb333pvp06cvV2T26pRTTuHMM88E4G1vexsXXXQRe+21FyeddFLPzx2rOkS4Wk8ScR1wUmbObd/+KEBmfrJ9+0rgdGABcG1m7the/jZg38z8P6t6jUmTJuXcuXN7zipJkqSR54477mCnnXZqOoa02rr9zUbEvMxc4fcthmr45WzgqIjYICK2A7YH5mTmYuCPEbFXe9bLdwCXD1EGSZIkSRr2ev1Jg8MiYiHwGuB77SNyZOZtwCXA7cB/Au9rz3wJ8LfAF4G7gd/gJCmSJEmSNGi9zn75HeA7A6w7Cziry/K5wC69vK4kSZIkqWWohl9KkiRJRVkbc0lI68Ka/q1a1EmSJGnYGzt2LEuWLLGwU/EykyVLljB27NjVfkxPwy8lSZKkGowbN46FCxfiz2SpBmPHjmXcuHGrfX+LOkmSJA176623Htttt13TMaQh4fBLSZIkSaqYRZ0kSZIkVcyiTpIkSZIqFrXMABQRDwL3rcWn3AJ4aC0+39pUcjYwX6/M1xvzDV7J2cB8vTJfb8w3eCVnA/P1yny9Wdv5XpKZW/ZfWE1Rt7ZFxNzMnNR0jm5Kzgbm65X5emO+wSs5G5ivV+brjfkGr+RsYL5ema836yqfwy8lSZIkqWIWdZIkSZJUsZFc1F3QdICVKDkbmK9X5uuN+Qav5Gxgvl6ZrzfmG7ySs4H5emW+3qyTfCP2nDpJkiRJGg5G8pE6SZIkSaqeRZ0kSZIkVcyiTtWLlm2bziFJ0khgvyuVZ0QVdRExOiK2jojxfZemM3WKiPUjYteIeGVErN90nk4RcWFE7NZv2enNpFletk4MvazpHFKpCt+2nLA6y5oSESv8wGtJIuKHEfGmfsuKmjTAvndw7Heluq3rbcuImSglIj4AnAb8AXi2vTgzc9fmUj0nIt4MfAH4DRDAdsD/ycwfNBqsLSIWAg8Bn87ML7eX/Twzd282WUtEfB64KDNvajpLp4i4JDPfGhG3AJ0ftqCgvz+AiHgtMAEY07es771uSpd2W7aKQtovIj7TZfH/D8zNzMvXdZ7+Kti2rLAdiYibM/NVTWXqFBG/Bu4FZgGXZuYjDUdaTkTcA9wP/CgzP95eVtK22b53kOx3B8d+tzc19Ltg39v1NUdQUXc3sGdmLmk6SzcRcSfwlsy8u337ZcD3MnPHZpO1RMTPgX2BrwG/BU4Abipox+t2YAfgPuBxCtn4RMRWmbk4Il7SbX1m3reuM3UTEV8BXgbMB55pL87M/GBjoYCB2q1PCe3XPiqyI/DN9qJpwG3AtsA9mfl3DUUDyt22RMTbgKOBfYCfdKzaGHgmMw9oJFgXETEZOAo4FLgd+EZmfrXRUG3tbfNk4DO0/ub+Gri2oB1/+95Bst8ddC773R7U0O+CfW83Y1Z9l2HjfloVfKke6Hvj2+4BHmgqTBeRmf8DHNwe/vFjYNNmIy3njU0H6CYzF7f/LWIjuBKTgIlZ2Lc8FbQbwMuB12fmUoCIOB+4CjgQuKXJYG2lblt+BiwGtgA+1bH8j8AvG0k0gMycA8yJiH8EPg1cDBRR1NHaNi8F3hsRxwI/BTZrNtJy7HsHz353EOx3e1NBu/Wx7+1nJBV19wDXRcT3gKf6Fmbmp5uLBBFxePvqbRHxfeASWoe9/wooaUjD7L4rmXl6RMwFTmwwz3Iy876I2J3Wt/4JXJ+ZP2841jIRsRfwWWAnYH1gNPB4Zm7SaLDn3Aq8mNZOdnEi4o88NxxkfWA9ymm/bYANeW7HdUNg68x8JiKeGvhh60zXbUvfticzL20iVHvH4b6IOCMzf9y5LiLeQ2vYSuMiYhPgMFpH6l4GfIfWkbFSLGunzLyoPXTqfQ3m6c++d/Dsd3tgv9ubwvtdsO9dwUgq6n7bvqzfvpTi4I7rfwBe177+IIV82xoRo4G9O5dl5hXAFc0kWlFEfIzWB6bvQ/LvEfHNzDyzwVidPkdrp/CbtL6dewetb5lKsQVwe0TMYfkdr0Oai/SczNy483ZEHEo5O9ZnA/Mj4jpaw4/+EvjHiNgQuKbJYG1jWXHb8gJa257kuc9MU06NiKcy80cAEfERWkPOiijqgF/QmhDijMz874azrCAz/zUi9gG2z8x/p9XPfaLhWJ3sewfBfnetsN/tQeH9Ltj3rmDEnFOn3kTEbOBvMrPIYTQRcQfwqsx8sn37fwE/z8ydmk3WEhFzM3NSRPyy73yDiPhZZr626WwAEfG6bsv7H0EpSUTckJl7NZ0DWudw0OrsApiTmYsajlSNiNiC1o7qh4EptM6ROCozn240WFtERGZmRGxM63yXx5rO1CkiTqO1w/qKzNwhIrYGvpmZe6/ioSqc/W5v7HfXvpL6XbDv7W/EHKmL1rTUJwM706qeAcjM1zcWqkNE7ACcD7woM3eJiF2BQwr6xutJ4JaIuJrWCdEANH1Cb4cFtN7XJ9u3N6A141ApnojWdLbzI+JsWsMtNmw40zIldyKw3FApaP0UyyS6z861zkXEX7av9s2K+PKIeHlm/ldTmTqVvm3JzIci4hBa36zOA44o7ByTndsTGryAVo33IHBMZt7acK4+hwGvAn4OkJmL2gVoEex7e2K/2xv73R6U3O+CfW/X1yyr7xw6EXEVrSmpTwLeAxwDPJiZH2k0WFtE/JjWN9X/2jezVUTcmpm7NJusJSKO6bY8My9e11m6iYjLgFcDV9Pa6BxIa8KAB6D5TrA9m9QDtMak/z2tk93P63cSbWNKHzsfEf/ecXMprZ2Jf8vMxic0iIjvdtwcS+tbw3kF7bQWuW3p+JuL9r/r03pvk9YRsVL+9n4GnJKZ17Zv7wv8Y0Hf9s/JzMnRnuq+PfTov5uegbCPfe/g2e/2xn63NyX3u2Df282IOVIHbJ6ZF0bECe1vR37cbvBSPC8z50RE57KlTYXpr5ROZCW+0770ua6hHF11zCb1J+DjTWbppvSx85n5/zWdYSCZ2XluDhGxLa2x/qUoctvS/2+uYBv2FXQAmXldu3AqxSUR8a/A8yPiOOCdwL81nKmTfe8g2e/2xn63NyX3u2Df281IKur6zs9YHK0fBFwEjGswT38PRes3LBIgIo6ggBmRImKlU4uX8m1w/86v/eE+KjP/qaFIfTmqaL/+MvOyiJjedI6I+CwDD/d4itZQn69l5h/XXapVWgg0/i1/hyK3LQDtoVFvpzU0L2n9BtzXMvPPjQZb3j0RcSrwlfbtv6b1Y+RFyMxzIuJA4H+AVwAfy8yrG47Vyb53DdXSb9jvrl32uz0b8X3vSCrqzoyITYEP0ZridhNah+NL8T7gAmDHiPgdrZ2GtzcbCYBnaf1B/gfwXVrfeBWpPeHCXwFvozXV7XdW/oh1oor2K3js/NyVrBtDqxi4lNawn0b06wBHAbvRmjGxFEVuWyJiIq0p26+ndS5d0Jr18pSImJqZtzUYr9M7aX3LfymtjP8FFPMNdkQ8H3iU1rTZvypwUg373jVXRb8B9ru9sN/tjX3vikbMOXWlioi9MvOGjtsbAqNK+gYkInaktcE+mNY36f8BXJXtH3xsUntCgMOAo4EdaHUoR2ZmMd8El9x+fUofO78yEfH9zHxTg6/fed7LUmBBZl7fVJ6BlLZtiYgfAjP6H1WKiANoncO2XzPJ6tA+ynkBcCit34IbBbyE1jbwPYUd7SxO6X1vyf2G/e7aYb/bcwb73v6vNdyLutIPI/ed3N6+/t+Z+ZomcqyuiDgS+Dwws+khFu08fwLmAP8X+GlmZkTck5kvbThaV6W1X40i4vTMPL3pHAMpaAjSwcAv+84ridZvSk0D7gNOyMxGhxBGxJ2ZueMA6+7IhqdFb+9wDdR3ZGa+a13m6S8izqD1Y+jv6eu/2jvbnwfuy8xTG85n37uWlNZv2O+OPKX3u2DfCyNj+GXph5E7z6AcO+C9GhQR29D6Ac/DaE0d+/eUMcQC4B9oZTsf+I+ImNVwnhWU3H6l73gN4BDg9KZDdCp0CNJZwF4AEfEWWueCvY3W9PdfAA5qLhoAoyJig8x8qnNhRIyljL6p2488jwf+Dhi9bqN0dTgwOTOf6FuQmX+MiPcCNwCNFnXY9/ak5H4D+92e2O+uPfa9yyuh4xxSqzN7VER8f11kGcCoiNiM1tCZvuvLOpvMfLixZCybknVjWudrHAv05Vk/Il7QdL7M/GfgnyPipbQ+NJcBW0fER4DvZOavmsxXevtR/o5XN7Hquwy9AYYgvbSgIUjZscN/OHBhZs4D5rV3/Jv2ZeDbEfH+zFwAEBETgM/w3KQkjcnMb/ddb29f/gH4S2AGcGFTuTo821nQ9cnMxyKi8SE49r2DV3q/Yb/bM/vdHtj3DmzYD7/spqTDyBGxgNZJvd0+MNn0cIZ2vr4/kr5/+7I2nq+biHglrY7myMx8WcNZFlBZ+/VXwtj5ThExKjOfLSBH0UOQ2jPAvRZ4gtYJ2tMyc2573e2ZObHJfO0c76f1w9TPay96HDgnMz/bXKrnRMROwCm0vmH9J+CrpZyTExG/oDWxTLe+49rM/N/rNtGq2feunhr7Dfvdtct+d2D2vSt57RFa1C0bS6/hp6QdhxqV1n4RcRCtySC2odVBLwIuz8z/bDjX39Ma3rMhrZPwZwFXF9SxvJPW0aX/AR7IzCnt5a+iVTjt32S+Tu1vXilpuFFEfJPWbHTn0PrG/5nO9U1/219yUTIQ+97hq7R+oza1tF9EfCwzz2g4g33vQK89Qou6m7P96+4lKv3DXUG+onccbL/VFxHn0hpe8WVav0EDrd+4egfw68w8oaFoy3QMQToK2B44jQKGIMGy80peCPyi71vWiNgKWC8zf9touC5K+mwMh2/7S2PfO3glZ4Oy+o1ubL+1IyJ+m5njm84B9r1dX3eEFnXFHEbupvQPdwX5St9xsP1WU0T8KjN36LI8aP0m1/YNxBpQSUOQunHHZnir4P217x2kkrNBWf1GN7bf6ouI/xloFfC/MrO4+Tjse1tGDfULlCAiDoqI8yNidkRcDnw+IqY0nWslijkhdQCl59uj6QCrYPutvicjYnKX5a8GnlzXYVbDtMz8hxI7lbZDmg6wCkV/NiLi9KYzrELR72/HN9YfazrLAEr++ys5G5TVb3Rj+62+R4HtM3OTfpeNgcUNZxuIfS8j4EhdDcO3+qvg28yi8pV6ztVAbL/VFxG705o2e2Oe+/xuS2us+nvbM0oVw2+De1PaZ6M/39+1o6QhXJ1K/vsrOVunEs656sb2W6MMZwKzM3NOl3UzM/MjDcRaKbfN7dcZAUVd8cO3St6phrLz1VC02369i4gX02q/ABZm5u8bjtRV6TvVpe3YlPzZ6Mb3d/XVOISrTwk71gMpORuUW7D3sf2GJ7fN7dcZAUXdL4F39//GoT2k68LMfGUzyZblOJeCd6oryFd00W77rR0RsV5mPt1v2RaZ+VBTmbopaacayi6aSv9sdOP7u/oi4rfAqzPzD13W3Z+Z2zYQa7WUvGNdQrbKC3bbbzXV0u9CedvmgQz1lwojoagrevhW6TvVFeQrvWi3/XoQEfvR+iHqDYCbgePzuR+qbny4ReE71edScNFU+mejncX3d5BKH8JV8o51ydmg/ILd9utN6f3uyoz0I7FFfBswlDLz58CeBQ/fejIiJnfp+EqZCKL0fMcC50frd676F+3HNpSpk+3Xm7OBgzLztog4Arg6Iv4mM2+g4RPfV7JT/cGIeGPTO9XAmwYommYBvwKazlf0Z8P3tzeZ+X9Xsq6Ec3IeZSU71us+znIepdxs0PpMvARYIR+t3w1r2qPYfr0ott9dDe8Gmj4ncaVfKgzlaw/7oq7Dkv6FXCGHkY+l7J3qYyk4XwVF+7HYfr1YPzNvA8jMb0XEHcClETGd5347rClF71RTeNFE4Z8NfH/XioKHcJW8Y11ythoKdtuvNyX3u40WTavpURr6UmEkDL+s4jBywTvVQBX5St1xAGy/wYqIucBbOtsrIsYBVwAvy9YUy01lK33oatFDz/uU+tnw/e1NLX2vBq/UfqMWpbZfyf1uO0vpw1cbG3o+Eoq6m4BjOw4jfxL4m8y8IQqaLafUD3efUvPVsuNg+w1ORBwAPJiZv+i3/PnA+zLzrEaCUf5OdZ9Si6Y+BX82fH97YN/bu1Kzld5v9LH9Bqfkfredo+jzdRuVmcP6Avyi3+2dgbuAw4CfF5BvP1o7DA8CVwETOtaZb9X5bgJ2bl8/Avg1sFf79s0F5LP9hvkFeDGtH46dBLy46Txd8q3XZdkWBeQq+rPh+9tzLvveYZitnaHofsP281LCpYlt8yiGv6fb32QCkK1xwvsDpwGNz67GcyekbglcQOuE1L3a60o4IbX0fMuN/aY1U93FEXEYBYz9xvbrSURsGhEzIuLOiFjSvtzRXvb8pvO1LcnMeZk5N9tHSSJii6ZDRcR+EbEQWBQRV0XEhI7VVzUUq1Ppn40+vr+DY987eCVng8L7DWy/nlTS7xIR63VZNqK3zSOhqJsOvKhzQWYuBPYFZjQRqJ+iP9yUn6/0HQfbrzeXAI8A+2bm5pm5Oa1vYR8BvtlksAp2qt2x6YHvb8/sewev5GxQfr9h+/Wm2H4X3DavVNOHJ0f6BZhLvyE9tKbNng/80XyrzHcA8L+7LH8+cEoB+Wy/3vLdNZh16yhb0UNoKH/4W+mfDd/fYXwp+e+v5GztLKX3G7Zfb/mK7XfbGdw2D/TaTf/n10HjbkrrW8E7gSXtyx3tZc8vIF/pH+6i85V+sf16br+rgJOBF3UsexHwEeCahrMVvVPtjo3vb8P57HuHYbYaLrZfz+1XbL/bzuK2eYDLSJj98krgR8DF+dz5EC8GjgEOyMwDm8yn3kTEpsBHaQ2v2LK9+AHgcmBGZj7aTLI6lN5+EbEZrWFcU2l1Kknrt4dmAzMz8+EGs5U+7XPRM5iVzve3N/a9w1fp/UbpSm+/kvtdcNu80tceAUXdXZn5ijVdt65U8OEuPV/ROw62X+8iYkda33LdkJmPdSyfkpn/2WCuoneqS1fBZ8P3twf2vYNXcjYov9+w/XpXar/bzuC2eQAjYaKU+yLi5IhYdsJ2RLwoIj4CDOkvu6+mok9Ipfx8EzJzZuc3Npn5+8ycCYxvMFcf268HEfFBWh3x+4FbI2Jqx+p/bCZVS2Ze079TaS9/tIROpYIZzIr+bPj+9sy+d/BKzgaF9xvYfj0pud8Ft80rMxKKuiOBzYEfR8QjEfEwcB3wAuCtTQZrK/rDTfn5St9xsP16cxywR2YeSmvWvFMj4oT2ukZn+Ktgp9odmx74/vbMvnfwSs4G5fcbtl9viu13wW3zygz7oi4zHwH+ndY3Dttm5gsyc6ds/eL85GbTAeV/uEvPV/qOg+3Xm9F9Qz8ycwGtDuaNEfFpmu9cSt+pdsemN76/PbDv7UnJ2aD8fsP2603J/S64bR7QsC/qSj+MTPkf7qLzVbDjYPv15vcRsVvfjXZH8xZgC+CVTYVqK3qnGndseuX72wP73p6UnK2GfsP2603J/S64bR5YNjz151BfgFuAjdrXJ9CaavSE9u2bm87XzrEjrSl4N+q3fErT2UrPB3yQ1lS2lwELgKkd6xqf2tb26znfOPpNDdyxbu+Gs5U+7fNmwExaU8o/AjxMa0r5mcALms7XzljyZ8P3t7d89r3DN1vR/Ybt13O+Yvvddga3zQO9dtP/+XXQuLf3u70R8J/Ap4H5BeQr/cNder6idxxsv+F7aXLDvQYZ3bHx/W0qm33vMMzWzlB0v2H7De+L2+aVvG7T//F10LA/Anbrt2wM8GXgmQLyFf3hriBf6TsOtt8wvjS14V7NbO7Y+P42mc++dxhma2cout+w/Yb/xW1z98uwP6cOeAfw+84Fmbk0M98B/GUzkZZT+gmppecrfey37TdMVXDOUNEzmFH4Z8P3t2f2vYNXcjYov9+w/YYxt80DG/ZFXWYuzI6TKfutu35d5+mi9A936flK33Gw/Yav0neq3bHpje9vD+x7e1JyNii/37D9hje3zQOI9uFANSQixgFLu3V+EbF3051f6flKZ/sNXxFxe2ZO7Li9EfAt4Hbg9Zm5W1PZ2nl+BJyYmfM7lo0BvgS8PTNHN5WtnaXoz4bv7/BW8t9fydlqYPsNb26bV/LaFnWStOZK36l2x6Y3vr+SVB63zSt5bYs6SVpz7lQPb76/klQet80Ds6iTJEmSpIoN+4lSJEmSJGk4s6iTJEmSpIpZ1EmSRpyI+Nka3n/fiLhiqPJIktQLizpJ0oiTma9tOoMkSWuLRZ0kacSJiMfa/+4bEddFxLci4s6I+FpERHvdlPaynwKHdzx2w4j4UkTcFBE3R8TU9vLPRMTH2tcPioj/igj7WUnSkBvTdABJkhr2KmBnYBFwPbB3RMwF/g14PXA3MKvj/qcAP8rMd0bE84E5EXENMB24KSJ+AnwGeFNmPrvu/huSpJHKbxAlSSPdnMxc2C7A5gMTgB2BezPz19n67Z+vdtz/DcD0iJgPXAeMBcZn5hPAccDVwOcy8zfr7H8gSRrRPFInSRrpnuq4/gzP9Y0D/ZBrANMy864u614JLAG2XnvxJElaOY/USZK0ojuB7SLiZe3bb+tYdyXwgY5z717V/vclwIdoDed8Y0TsuQ7zSpJGMIs6SZL6ycwngeOB77UnSrmvY/UngPWAX0bErcAn2gXehcBJmbkIeBfwxYgYu46jS5JGoGidKiBJkiRJqpFH6iRJkiSpYhZ1kiRJklQxizpJkiRJqphFnSRJkiRVzKJOkiRJkipmUSdJkiRJFbOokyRJkqSKWdRJkiRJUsX+H5aeGVfzPCaxAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_pandemie.iloc[:,4:5].plot(kind=\"bar\", figsize=(15,6)) #Unterschiede zum Vor-Pandemie-Monat in %, Linienverkehr "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b97c68da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='index'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_pandemie.iloc[:,5:6].plot(kind=\"bar\", figsize=(15,6)) #Unterschiede zum Vor-Pandemie-Monat in Prozent, Charterverkehr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "59713b12",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Veränderung in einer CSV-Datei abspeichern\n",
    "df_pandemie[['Linienverkehr zu 2019','Linienverkehr zu 2019 in %']].to_csv('Passagierentwicklung-ab-ZRH-in-der-Pandemie.csv')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}