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data-cleaning's Introduction

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.

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