Data Cleaning Tool

Dependencies

The backend of the tool is written in Python3 and depends on the following libraries:

Name	URL	Install
scikit-learn	https://scikit-learn.org/stable/index.html	pip install scikit-learn
Flask	https://flask.palletsprojects.com/en/1.1.x/	pip install Flask
Jinja2	https://jinja.palletsprojects.com/en/2.11.x/	pip install Jinja2
Pandas	https://pandas.pydata.org/	pip install pandas
Unidecode	https://pypi.org/project/Unidecode/	pip install Unidecode

Make sure you have Python3 and pip installed with the dependencies in the table above.

Usage

1. Go to data_cleaning/tables.txt and insert the absolute paths of the .csv-files that you want to clean. Do not move, rename or delete this file!
2. Go to the root folder of this project and execute python -m data_cleaning.start_server. This will start the server and process the data.
   • To run the program on a specific port, run python -m data_cleaning.start_server -p PORTNUMBER, with PORTNUMBER any portnumber you want. By default, the program will run on port 5000.
   • Functional dependencies are disabled by default since version v1.1.0. Add --enable-functional-dependencies to the command to enable this functionality.
3. Go to http://127.0.0.1:5000/ (or to another port) to use the client and start your cleaning procedure.