https://github.com/jonek/pv-city-mastr

Extract and analyze data about photovoltaic systems in Germany
https://github.com/jonek/pv-city-mastr

data-analysis germany jupyter-notebook pandas photovolatic-power photovoltaic

Last synced: 2 days ago
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Extract and analyze data about photovoltaic systems in Germany

• Host: GitHub
• URL: https://github.com/jonek/pv-city-mastr
• Owner: jonek
• Created: 2020-06-17T22:46:18.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-06-24T23:23:59.000Z (over 4 years ago)
• Last Synced: 2024-11-14T04:54:10.321Z (2 months ago)
• Topics: data-analysis, germany, jupyter-notebook, pandas, photovolatic-power, photovoltaic
• Language: Jupyter Notebook
• Size: 164 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Analyse Photovoltaic Systems in MaStR

The tools and data in this repository provide insight into photovoltaic systems deployed in Germany.

## Data Source

The analysed data is provided by the German [Markstammdatenregister](https://www.bundesnetzagentur.de/DE/Sachgebiete/ElektrizitaetundGas/Unternehmen_Institutionen/DatenaustauschundMonitoring/Marktstammdatenregister/MaStR_node.html#doc514816bodyText4) (MaStR).

## Data Processing

You can reproduce the following data processing steps on your computer:

1. Download data (from MaStR): [data/README.md](data/README.md)

2. Convert data from Excel to CSV

   - Migration parts 1 and 2 (data before Jan 2019): [notebooks/convert-MaStR-Migration-to-CSV.ipynb](notebooks/convert-MaStR-Migration-to-CSV.ipynb)

   - data since Jan 2019: [notebooks/convert-MaStR-since20190131-to-CSV.ipynb](notebooks/convert-MaStR-since20190131-to-CSV.ipynb)

3. Extract data for a given city

   - Migration parts 1 and 2: [notebooks/extract-city-from-MaStR-before20190201.ipynb](notebooks/extract-city-from-MaStR-before20190201.ipynb)

   - data since Jan 2019: [notebooks/extract-city-from-MaStR-since20190131.ipynb](notebooks/extract-city-from-MaStR-since20190131.ipynb)

4. Combine data partitions

   - Migration part 1

   - Migration part 2

   - data since 2019

Each step is implemented in a shell script or a Jupyter notebook.

## Data Visualisation

Either in a Jupyter notebook or in an Observable. (TODO)

## Data Partitioning

To enable further analysis of the data, the combined partitions (see "Data Processing" step 4 above) are split up again.

This results in handable chunks of data, one partition per federal state (German: *Bundesland*).

You can find these partitions in `states/.csv`. (TODO)