fair-charging-station-data

Fair Charging Station Data

https://github.com/areleu/fair-charging-station-data

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • 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
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (13.2%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

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
Created over 2 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog Contributing License Citation

README.md

DOI

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:

  1. load (Data has to be downloaded manually, sorry but the BNetzA website is not fond of automatic requests.)
  2. clean
  3. annotate
  4. normalise
  5. rename
  6. evaluate
  7. 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

Owner

  • Name: e_arel
  • Login: areleu
  • Kind: user
  • Company: DLR

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

requirements.txt pypi
  • frictionless *
  • jsonschema_rs *
  • oep-client *
  • omi *
  • openpyxl *
  • pandas *
  • requests *