fair-charging-station-data
Fair Charging Station Data
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.2%) to scientific vocabulary
Repository
Fair Charging Station Data
Basic Info
- Host: GitHub
- Owner: areleu
- License: bsd-3-clause
- Language: Python
- Default Branch: main
- Size: 171 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 2
Metadata Files
README.md
FAIR Charging Station Data
This repository produces two clean datasets for Charging station data based on the data provided by the german BNetzA. More info on the source can be found at their Charging Station Website (German). Just in case it is not clear, no data is provided in this repository, you have to download it yourself. Run The download script once, it will throw an error on where to store the data to use this tool properly.
Execution
This script should theoretically work with any version of python able to run pandas and frictionless. If it is not obvious, you have to install the requirements.txt in your python environment.
bash
pip install -r requirements.txt
or simply
bash
pip install pandas requests frictionless omi openpyxl jsonschema_rs
Each script has to be run with the directory where you want to have the data as current working directory. You run them with python normally, for example:
bash
python src/clean.py
To get the proper data run the scripts in the following order:
- load (Data has to be downloaded manually, sorry but the BNetzA website is not fond of automatic requests.)
- clean
- annotate
- normalise
- rename
- evaluate
- publish
Annotated CSV
The source files are in xlsx, which is a limited format. The provider offers csv files, but it has formatting errors as it seems that it is the output of using excel directly to save as csv.
The annotate function of this repository will produce a clean dataset with minimal modification of the source material.
Normalised CSV
The normalised data contains the source material structured in such a way that can be better handled with relational databases. The charging stations and the connection sockets are separated in two different tables.
Renamed CSV
These files contain the output of the previous scripts but with column names translated to English and deprived of special characters.
Caveats
The cleaning script will remove duplicate entries, this was not decided lightly as it can be the case that two columns are in the same place with the exact same characteristics. It is not possible, with our resources to validate or deny this, but these duplicate entries seem to be more of a input error than actual multiple columns with similar characteristics.
It is the case that columns with different characteristics share a place, these are kept.
Data Sources
- BNetzA Data
- OEP Metadata schema used in evaluate.py
Owner
- Name: e_arel
- Login: areleu
- Kind: user
- Company: DLR
- Repositories: 1
- Profile: https://github.com/areleu
Citation (CITATION.cff)
cff-version: 1.2.0
message: "Please cite this if you use the software. To cite the data, refer to its license."
authors:
- family-names: Arellano Ruiz
given-names: Eugenio Salvador
orcid: https://orcid.org/0000-0003-2508-3976
- family-names: Miorelli
given-names: Fabia
orcid: https://orcid.org/0000-0001-5095-5401
title: "FAIR Charging Station Data"
version: 0.0.1
doi: 10.5281/zenodo.10201024
date-released: 32.11.2023
GitHub Events
Total
- Issues event: 1
- Push event: 15
- Pull request event: 2
- Create event: 2
Last Year
- Issues event: 1
- Push event: 15
- Pull request event: 2
- Create event: 2
Dependencies
- frictionless *
- jsonschema_rs *
- oep-client *
- omi *
- openpyxl *
- pandas *
- requests *