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‎.github/workflows/book.yml‎

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name: deploy-book
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on:
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push:
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branches:
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- main
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concurrency:
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group: pages
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cancel-in-progress: true
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permissions:
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contents: read
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pages: write
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id-token: write
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jobs:
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deploy-book:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v6
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- name: Set up Python 3.11
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uses: actions/setup-python@v6
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with:
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python-version: 3.11
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cache: pip
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install -r requirements.txt
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pip show jupyter-book
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jupyter-book --version
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- name: Build the book
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run: |
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jupyter book build
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ls -la _build/html
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- name: Upload artifact
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uses: actions/upload-pages-artifact@v4
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with:
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path: "_build/html"
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- name: Deploy to GitHub Pages
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id: deployment
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uses: actions/deploy-pages@v4

‎.gitignore‎

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# Python
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__pycache__/
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*.py[cod]
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*.pyo
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*.pyd
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.Python
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# Virtual environment
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.venv/
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# Jupyter
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.ipynb_checkpoints/
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*.ipynb_checkpoints
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# Jupyter Book v2 build output
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_build/
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# Trained model artifacts
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*.pt
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*.pt.ckpt
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*.pkl
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# Data files
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data/
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# Environment variables
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.env
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# macOS
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.DS_Store
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# Editor
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.vscode/
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.idea/

‎00_load-dwd-data.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "c93fb23f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Wetterdienst: https://pypi.org/project/wetterdienst/\n",
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"from wetterdienst import Settings\n",
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"from wetterdienst.provider.dwd.observation import DwdObservationRequest, DwdObservationMetadata"
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]
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},
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{
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"cell_type": "markdown",
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"id": "6906bc4d",
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"metadata": {},
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"source": [
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"DWD - Stations with station IDs: https://www.dwd.de/DE/leistungen/klimadatendeutschland/stationsuebersicht.html\n"
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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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"id": "c15656a2",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"<class 'pandas.core.frame.DataFrame'>\n",
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"DatetimeIndex: 91315 entries, 1975-01-01 to 2024-12-31\n",
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"Data columns (total 15 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 station_id 91315 non-null object \n",
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" 1 wind_gust_max 86857 non-null float64\n",
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" 2 wind_speed 90284 non-null float64\n",
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" 3 precipitation_height 90913 non-null float64\n",
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" 4 precipitation_form 91086 non-null float64\n",
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" 5 sunshine_duration 91054 non-null float64\n",
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" 6 snow_depth 89281 non-null float64\n",
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" 7 cloud_cover_total 91179 non-null float64\n",
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" 8 pressure_vapor 91260 non-null float64\n",
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" 9 pressure_air_site 91289 non-null float64\n",
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" 10 temperature_air_mean_2m 91304 non-null float64\n",
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" 11 humidity 91260 non-null float64\n",
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" 12 temperature_air_max_2m 91304 non-null float64\n",
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" 13 temperature_air_min_2m 91304 non-null float64\n",
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" 14 temperature_air_min_0_05m 72718 non-null float64\n",
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"dtypes: float64(14), object(1)\n",
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"memory usage: 11.1+ MB\n"
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]
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}
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],
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"source": [
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"# Load daily climate summary data from ...\n",
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"# 183 - Arkona\n",
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"# 722 - Brocken\n",
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"# 2667 - Köln-Bonn\n",
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"# 2932 - Leipzig\n",
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"# 5792 - Zugspitze\n",
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"# ... for years 1975-2024 \n",
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"request = DwdObservationRequest(\n",
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" parameters=DwdObservationMetadata.daily.climate_summary,\n",
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" start_date=\"1975-01-01\",\n",
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" end_date=\"2024-12-31\",\n",
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" settings=Settings(\n",
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" ts_shape=\"wide\", # tidy data\n",
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" ts_humanize=True, # humanized parameters\n",
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" ts_convert_units=False # do not convert values to SI units\n",
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" )\n",
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").filter_by_station_id([183, 722, 2667, 2932, 5792])\n",
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"\n",
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"# Load values\n",
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"df = request.values.all().df.to_pandas().set_index(\"date\")\n",
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"# Drop columns with quality flags and just on distinct value\n",
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"df_selected = df.loc[:, ~df.columns.str.startswith(\"qn_\") & (df.nunique() != 1)]\n",
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"# Remove timezone from datetime index, this triggers warnings in some tsa libraries\n",
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"df_selected.index = df_selected.index.tz_convert(None)\n",
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"df_selected.info()"
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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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"id": "0d5d838c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Save data station-wise\n",
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"for station_id in df_selected.station_id.unique():\n",
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" station_data = df_selected[df_selected.station_id == station_id]\n",
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" station_data = station_data.drop(columns=[\"station_id\"])\n",
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" station_data.to_csv(f\"data/dwd_{station_id}_climate.csv\", sep=';', index=True)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "tsa-overview (3.14.0)",
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"language": "python",
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"name": "python3"
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},
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"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": "3.13.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎01_time-series-properties.ipynb‎

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