Being something of an eco-warrior myself, I am interested in the development of electric vehicle industry to date as well as the possible future. So I decided to search for open-source data available on this topic.
Fortunately for me, I was able to find some interesting data which was made available from the German government through "gov.de". The dataset came in the form of a csv file. This will be a brief look at the spacial analysis I did.
[This project is in Progress]
Tools:
- Excel
- VLOOKUP, IF and OR statements
- Tableau Public for visualizations
Data:
- > 44,000 Rows & 18 variables
- Germany (all 16 Bundesländer)
- open source data
Step 1: Data Cleaning
I imported the file to Excel. I chose to use Excel at this point, because the dataset was not very large and I had no plans as yet to perform any major statistical analyses.
The data came with street names and house numbers, as well as Coordinate points for each charging station. Even the names of the operators were included. I decided to delete street names and addresses from the working data, because of privacy concerns. There were public as well as private operators named.
Apart from the data which I considered sensitive, I left the names of the operators, because with the help of a formula, I was able to extract whether the owner/operator of each charging station was a private person, business or public enterprise. More on this later!
I ended up deleting several columns which were not useful or had far too many missing values to be reliable (i.e. >10% missing values).
Step 2: Data Wrangling
After the basic inspection and cleaning up of the dataset, I noticed that the zip codes (PLZ) were either broken or imported into Excel incorrectly. WIth the help of a concatenate funtion I remedied this problem.
Image by Gerd Altmann from Pixabay
Placeholder text by Mnguni Zulu. Photograph by A. Krebs.