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…pyter Notebook format.
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docs/jupyter_notebooks/e1_pull_DWD_historical_to_all_output_formats.ipynb
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|---|---|---|
| @@ -1,126 +1,126 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "# AixWeather Tutorial\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Enable logging, this is just get more feedback through the terminal\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "import logging\nlogging.basicConfig(level=\"DEBUG\")\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Choose the project class according to the desired weather data origin.\nCheck the project classes file or the API documentation to see which classes are available.\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "from aixweather.project_class import ProjectClassDWDHistorical\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Step 0: Initiate the project class which contains or creates all variables and functions.\nFor this, we use the datetime module to specify dates.\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "import datetime as dt\nDWD_pull_project = ProjectClassDWDHistorical(\n start=dt.datetime(2022, 1, 1),\n end=dt.datetime(2023, 1, 1),\n station=15000,\n # specify whether nan-values should be filled when exporting\n fillna=True,\n # define results path if desired\n abs_result_folder_path=None,\n)\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Step 1: Import historical weather from the DWD open access database\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "DWD_pull_project.import_data()\nprint(\n f\"\\nHow the imported data looks like:\\n{DWD_pull_project.imported_data.head()}\\n\"\n)\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Step 2: Convert this imported data to the core format\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "DWD_pull_project.data_2_core_data()\nprint(f\"\\nHow the core data looks like:\\n{DWD_pull_project.core_data.head()}\\n\")\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "you may also use data quality check utils, like:\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "from aixweather.data_quality_checks import plot_heatmap_missing_values\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "plot data quality\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "plot = plot_heatmap_missing_values(DWD_pull_project.core_data)\nplot.show()\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Step 3: Convert this core data to an output data format of your choice\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "DWD_pull_project.core_2_csv()\nDWD_pull_project.core_2_json()\nDWD_pull_project.core_2_pickle()\nDWD_pull_project.core_2_mos()\nDWD_pull_project.core_2_epw()\n" | ||
| } | ||
| ], | ||
| "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": "3.6.4" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "# AixWeather Tutorial\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Enable logging, this is just get more feedback through the terminal\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "import logging\nlogging.basicConfig(level=\"DEBUG\")\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Choose the project class according to the desired weather data origin.\nCheck the project classes file or the API documentation to see which classes are available.\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "from aixweather.project_class import ProjectClassDWDHistorical\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Step 0: Initiate the project class which contains or creates all variables and functions.\nFor this, we use the datetime module to specify dates.\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "import datetime as dt\nDWD_pull_project = ProjectClassDWDHistorical(\n start=dt.datetime(2022, 1, 1),\n end=dt.datetime(2023, 1, 1),\n station=15000,\n # specify whether nan-values should be filled when exporting\n fillna=True,\n # define results path if desired\n abs_result_folder_path=None,\n)\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Step 1: Import historical weather from the DWD open access database\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "DWD_pull_project.import_data()\nprint(\n f\"\\nHow the imported data looks like:\\n{DWD_pull_project.imported_data.head()}\\n\"\n)\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Step 2: Convert this imported data to the core format\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "DWD_pull_project.data_2_core_data()\nprint(f\"\\nHow the core data looks like:\\n{DWD_pull_project.core_data.head()}\\n\")\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "you may also use data quality check utils, like:\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "from aixweather.data_quality_checks import plot_heatmap_missing_values\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "plot data quality\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "plot = plot_heatmap_missing_values(DWD_pull_project.core_data)\nplot.show()\n" | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": "Step 3: Convert this core data to an output data format of your choice\n" | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": "DWD_pull_project.core_2_csv()\nDWD_pull_project.core_2_json()\nDWD_pull_project.core_2_pickle()\nDWD_pull_project.core_2_mos()\nDWD_pull_project.core_2_epw()\n" | ||
| } | ||
| ], | ||
| "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": "3.6.4" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |