506 lines
147 KiB
Text
506 lines
147 KiB
Text
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Musterbeispiel Data Processing\n",
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"\n",
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"Notwendige Packages befinden sich in `requirements.txt` - installieren mit `pip install -r requirements.txt`.\n",
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"\n",
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"Die Verwendung eines Virtual Environments (venv) wird empfohlen (`py -m venv .venv`, dann `.venv/scripts/activate` bzw. `.venv/bin/activate`)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import pathlib\n",
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"import pandas as pd\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib.dates as mdates\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Beschreibung des Datensatzes\n",
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"\n",
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"- Datensatz beinhaltet Daten der Wetterstation Freiburg des Deutschen Wetterdienstes\n",
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"- Datensatz ist csv mit Trennzeichen `;`\n",
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"- Datensatz umfasst 6 Spalten:\n",
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"\n",
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"\n",
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"| | STATIONS_ID | MESS_DATUM | QN_4 | TT_TER | RF_TER | eor |\n",
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"|--------------------|-----------------------|------------------------------|----------------------|-----------------------|----------------------------|------------|\n",
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"| Beschreibung | ID der Wetterstation | Datum und Stunde der Messung | Qualität der Messung | Temperatur | Relative Luftfeutchtigkeit | End of Row |\n",
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"| Datentyp | Integer | String (Format yyyymmddhh) | Integer | Float | Float | String |\n",
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"| Fehlende Einträge | Nein | Nein | Nein | Ja (-999) | Ja (-999) | Nein |\n",
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"| Relevant | Nein | Ja | Teilweise | Ja | Ja | Nein |\n",
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"\n",
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"\n",
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"## Schritte der Datenverarbeitung\n",
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"\n",
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"1. Einlesen des Datensatzes\n",
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"2. Konvertierung der Datumsspalte in datetime objekte\n",
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"3. Entfernen nicht benötigter Spalten\n",
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"4. Plotten der Daten für bessere Übersicht\n",
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"5. Identifizieren und kompensieren von Fehlerwerten durch Interpolation\n",
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"6. Plotten des Ergebnisses"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>STATIONS_ID</th>\n",
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" <th>MESS_DATUM</th>\n",
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" <th>QN_4</th>\n",
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" <th>TT_TER</th>\n",
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" <th>RF_TER</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>count</th>\n",
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" <td>1939.0</td>\n",
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" <td>1.939000e+03</td>\n",
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" <td>1939.000000</td>\n",
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" <td>1939.000000</td>\n",
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" <td>1939.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>mean</th>\n",
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" <td>1443.0</td>\n",
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" <td>2.023268e+09</td>\n",
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" <td>5.121712</td>\n",
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" <td>-1.439144</td>\n",
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" <td>58.563177</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>std</th>\n",
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" <td>0.0</td>\n",
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" <td>5.373317e+05</td>\n",
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" <td>3.262451</td>\n",
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" <td>114.311663</td>\n",
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" <td>122.156135</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>min</th>\n",
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" <td>1443.0</td>\n",
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" <td>2.022111e+09</td>\n",
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" <td>1.000000</td>\n",
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" <td>-999.000000</td>\n",
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" <td>-999.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>25%</th>\n",
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" <td>1443.0</td>\n",
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" <td>2.023042e+09</td>\n",
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" <td>3.000000</td>\n",
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" <td>6.200000</td>\n",
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" <td>59.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>50%</th>\n",
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" <td>1443.0</td>\n",
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" <td>2.023092e+09</td>\n",
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" <td>3.000000</td>\n",
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" <td>10.900000</td>\n",
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" <td>74.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>75%</th>\n",
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" <td>1443.0</td>\n",
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" <td>2.024012e+09</td>\n",
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" <td>9.000000</td>\n",
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" <td>16.600000</td>\n",
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" <td>87.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>max</th>\n",
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" <td>1443.0</td>\n",
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" <td>2.024052e+09</td>\n",
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" <td>9.000000</td>\n",
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" <td>34.300000</td>\n",
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" <td>100.000000</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" STATIONS_ID MESS_DATUM QN_4 TT_TER RF_TER\n",
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"count 1939.0 1.939000e+03 1939.000000 1939.000000 1939.000000\n",
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"mean 1443.0 2.023268e+09 5.121712 -1.439144 58.563177\n",
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"std 0.0 5.373317e+05 3.262451 114.311663 122.156135\n",
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"min 1443.0 2.022111e+09 1.000000 -999.000000 -999.000000\n",
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"25% 1443.0 2.023042e+09 3.000000 6.200000 59.000000\n",
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"50% 1443.0 2.023092e+09 3.000000 10.900000 74.000000\n",
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"75% 1443.0 2.024012e+09 9.000000 16.600000 87.000000\n",
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"max 1443.0 2.024052e+09 9.000000 34.300000 100.000000"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Einlesen der Wetterdaten. Diese müssen sich im selben ordner wie dieses Notebook befinden\n",
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"datafile = pathlib.Path() / \"wetterdaten_freiburg_2022_2024.csv\"\n",
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"data = pd.read_csv(datafile, sep=\";\")\n",
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"\n",
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"# Struktur des pandas dataframes ausgeben\n",
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"data.describe()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>MESS_DATUM</th>\n",
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" <th>TT_TER</th>\n",
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" <th>RF_TER</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>count</th>\n",
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" <td>1939</td>\n",
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" <td>1939.000000</td>\n",
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" <td>1939.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>mean</th>\n",
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" <td>2023-09-03 09:01:23.548220672</td>\n",
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" <td>-1.439144</td>\n",
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" <td>58.563177</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>min</th>\n",
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" <td>2022-11-13 06:00:00</td>\n",
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" <td>-999.000000</td>\n",
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" <td>-999.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>25%</th>\n",
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" <td>2023-04-23 15:00:00</td>\n",
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" <td>6.200000</td>\n",
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" <td>59.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>50%</th>\n",
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" <td>2023-09-16 12:00:00</td>\n",
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" <td>10.900000</td>\n",
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" <td>74.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>75%</th>\n",
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" <td>2024-01-15 15:00:00</td>\n",
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" <td>16.600000</td>\n",
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" <td>87.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>max</th>\n",
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" <td>2024-05-15 18:00:00</td>\n",
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" <td>34.300000</td>\n",
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" <td>100.000000</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>std</th>\n",
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" <td>NaN</td>\n",
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" <td>114.311663</td>\n",
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" <td>122.156135</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" MESS_DATUM TT_TER RF_TER\n",
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"count 1939 1939.000000 1939.000000\n",
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"mean 2023-09-03 09:01:23.548220672 -1.439144 58.563177\n",
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"min 2022-11-13 06:00:00 -999.000000 -999.000000\n",
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"25% 2023-04-23 15:00:00 6.200000 59.000000\n",
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"50% 2023-09-16 12:00:00 10.900000 74.000000\n",
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"75% 2024-01-15 15:00:00 16.600000 87.000000\n",
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"max 2024-05-15 18:00:00 34.300000 100.000000\n",
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"std NaN 114.311663 122.156135"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Datumswerte konvertieren\n",
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"data[\"MESS_DATUM\"] = pd.to_datetime(data[\"MESS_DATUM\"], format=\"%Y%m%d%H\")\n",
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"\n",
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"# Nicht benötigte Spalten entfernen\n",
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"data.drop([\"STATIONS_ID\", \"QN_4\", \"eor\"], axis=1, inplace=True)\n",
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"\n",
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"# Struktur des pandas dataframes ausgeben\n",
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"data.describe()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
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"text/plain": [
|
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"<Figure size 1000x400 with 2 Axes>"
|
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]
|
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},
|
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"metadata": {},
|
|
"output_type": "display_data"
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}
|
|
],
|
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"source": [
|
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"# Daten plotten (Temperatur und Luftfeuchtigkeit)\n",
|
|
"fig = plt.figure(figsize=(10, 4))\n",
|
|
"ax = plt.subplot(1, 2, 1)\n",
|
|
"ax.plot(data[\"MESS_DATUM\"], data[\"TT_TER\"])\n",
|
|
"ax.set_title(\"Temperatur\")\n",
|
|
"monthyearFmt = mdates.DateFormatter('%m-%Y')\n",
|
|
"ax.xaxis.set_major_formatter(monthyearFmt)\n",
|
|
"_ = plt.xticks(rotation=90)\n",
|
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"\n",
|
|
"ax = plt.subplot(1, 2, 2)\n",
|
|
"ax.plot(data[\"MESS_DATUM\"], data[\"RF_TER\"])\n",
|
|
"ax.set_title(\"Relative Luftfeuchtigkeit\")\n",
|
|
"monthyearFmt = mdates.DateFormatter('%m-%Y')\n",
|
|
"ax.xaxis.set_major_formatter(monthyearFmt)\n",
|
|
"_ = plt.xticks(rotation=90)\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
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"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<div>\n",
|
|
"<style scoped>\n",
|
|
" .dataframe tbody tr th:only-of-type {\n",
|
|
" vertical-align: middle;\n",
|
|
" }\n",
|
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"\n",
|
|
" .dataframe tbody tr th {\n",
|
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" vertical-align: top;\n",
|
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" }\n",
|
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"\n",
|
|
" .dataframe thead th {\n",
|
|
" text-align: right;\n",
|
|
" }\n",
|
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"</style>\n",
|
|
"<table border=\"1\" class=\"dataframe\">\n",
|
|
" <thead>\n",
|
|
" <tr style=\"text-align: right;\">\n",
|
|
" <th></th>\n",
|
|
" <th>MESS_DATUM</th>\n",
|
|
" <th>TT_TER</th>\n",
|
|
" <th>RF_TER</th>\n",
|
|
" </tr>\n",
|
|
" </thead>\n",
|
|
" <tbody>\n",
|
|
" <tr>\n",
|
|
" <th>count</th>\n",
|
|
" <td>1939</td>\n",
|
|
" <td>1939.000000</td>\n",
|
|
" <td>1939.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>mean</th>\n",
|
|
" <td>2023-09-03 09:01:23.548220672</td>\n",
|
|
" <td>11.634683</td>\n",
|
|
" <td>72.296029</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>min</th>\n",
|
|
" <td>2022-11-13 06:00:00</td>\n",
|
|
" <td>-9.100000</td>\n",
|
|
" <td>20.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>25%</th>\n",
|
|
" <td>2023-04-23 15:00:00</td>\n",
|
|
" <td>6.500000</td>\n",
|
|
" <td>60.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>50%</th>\n",
|
|
" <td>2023-09-16 12:00:00</td>\n",
|
|
" <td>11.100000</td>\n",
|
|
" <td>75.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>75%</th>\n",
|
|
" <td>2024-01-15 15:00:00</td>\n",
|
|
" <td>16.700000</td>\n",
|
|
" <td>87.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>max</th>\n",
|
|
" <td>2024-05-15 18:00:00</td>\n",
|
|
" <td>34.300000</td>\n",
|
|
" <td>100.000000</td>\n",
|
|
" </tr>\n",
|
|
" <tr>\n",
|
|
" <th>std</th>\n",
|
|
" <td>NaN</td>\n",
|
|
" <td>7.940810</td>\n",
|
|
" <td>17.596512</td>\n",
|
|
" </tr>\n",
|
|
" </tbody>\n",
|
|
"</table>\n",
|
|
"</div>"
|
|
],
|
|
"text/plain": [
|
|
" MESS_DATUM TT_TER RF_TER\n",
|
|
"count 1939 1939.000000 1939.000000\n",
|
|
"mean 2023-09-03 09:01:23.548220672 11.634683 72.296029\n",
|
|
"min 2022-11-13 06:00:00 -9.100000 20.000000\n",
|
|
"25% 2023-04-23 15:00:00 6.500000 60.000000\n",
|
|
"50% 2023-09-16 12:00:00 11.100000 75.000000\n",
|
|
"75% 2024-01-15 15:00:00 16.700000 87.000000\n",
|
|
"max 2024-05-15 18:00:00 34.300000 100.000000\n",
|
|
"std NaN 7.940810 17.596512"
|
|
]
|
|
},
|
|
"execution_count": 5,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# Fehlerwerte vereinheitlichen\n",
|
|
"data.replace(-999, np.nan, inplace=True)\n",
|
|
"\n",
|
|
"# Fehlende Werte durch Interpolation ersetzen\n",
|
|
"data[\"TT_TER\"] = data[\"TT_TER\"].interpolate()\n",
|
|
"data[\"RF_TER\"] = data[\"RF_TER\"].interpolate()\n",
|
|
"\n",
|
|
"# Struktur des pandas dataframes ausgeben\n",
|
|
"data.describe()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
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"text/plain": [
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"<Figure size 1000x400 with 2 Axes>"
|
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]
|
|
},
|
|
"metadata": {},
|
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"output_type": "display_data"
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}
|
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],
|
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"source": [
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"# Überarbeitete Daten plotten (Temperatur und Luftfeuchtigkeit)\n",
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"fig = plt.figure(figsize=(10, 4))\n",
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"ax = plt.subplot(1, 2, 1)\n",
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"ax.plot(data[\"MESS_DATUM\"], data[\"TT_TER\"])\n",
|
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"ax.set_title(\"Temperatur\")\n",
|
|
"monthyearFmt = mdates.DateFormatter('%m-%Y')\n",
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"ax.xaxis.set_major_formatter(monthyearFmt)\n",
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"_ = plt.xticks(rotation=90)\n",
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"\n",
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"ax = plt.subplot(1, 2, 2)\n",
|
|
"ax.plot(data[\"MESS_DATUM\"], data[\"RF_TER\"])\n",
|
|
"ax.set_title(\"Relative Luftfeuchtigkeit\")\n",
|
|
"monthyearFmt = mdates.DateFormatter('%m-%Y')\n",
|
|
"ax.xaxis.set_major_formatter(monthyearFmt)\n",
|
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"_ = plt.xticks(rotation=90)\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
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"kernelspec": {
|
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"display_name": ".venv",
|
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"language": "python",
|
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"name": "python3"
|
|
},
|
|
"language_info": {
|
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"codemirror_mode": {
|
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"name": "ipython",
|
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"version": 3
|
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},
|
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"file_extension": ".py",
|
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"mimetype": "text/x-python",
|
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"name": "python",
|
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"nbconvert_exporter": "python",
|
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"pygments_lexer": "ipython3",
|
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"version": "3.11.0"
|
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}
|
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|
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"nbformat": 4,
|
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"nbformat_minor": 2
|
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