Who are the European dataworkers?

In this repository you will find a pipeline that combines, cleans and analyzes work-related data to yield insights on data workers' amount, education and how they think regarding several socioeconomic matters across the Europe:

• This pipeline retrieves data from a (*) database, University of Chicago's API containing data on normalized taxonomy of jobs and Eurostat country codes.

• The tables that this pipeline produces are related with

  1. Quantity and percentage of workers having the same job in 26 EU countries and within an specific country
  2. Reasons they posit for and against a universal living wage
  3. Skills data workers exhibit in different educational level ranges

• Providing a specific country to the pipeline, it shows information, otherwise, the pipeline will return the result for all countries.

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Photo by KOBU Agency on Unsplash

Status

Work-in-progress (Alpha)

Technology stack

• Type: Standalone

• Language: Python

• Libraries:

  Pandas
  Sqlalchemy
  Request
  BeautifulSoup4

Core technical concepts and inspiration

If you are thinking to work in a data position in Europe, you might want to check how many workers carry out the taks you know how to do and which is their opinion on socioeconomic issues. Definitely, it will give you a sense of who well could you live in that country performing that job!

Usage

Parameters: Introduce a country have its information retrieved or introduce any other character to have the information for all countries

Folder structure

└── project
    ├── __trash__
    ├── .gitignore
    ├── .env
    ├── requeriments.txt
    ├── README.md
    ├── main_script.py
    ├── notebooks
    │   ├── Acquisition.ipynb
    │   └── Wrangling.ipynb
    ├── package1
    │   ├── m_acquisition.py
    │   └── m_wrangling.py
    │   └── m_analysis.py
    │   └── m_reporting.py
    └── data
        ├── raw
        ├── processed
        └── results

Do not forget to include __trash__ and .env in .gitignore

ToDo

As next steps it will be interesting to enrich the data with socioeconomic conditions by country and each data position type demand.

Contact info

For further information do not hesitate to contact cuadradobrionescarmen@gmail.com

Last but not Least!

If you are interested in continuing building this project, please start to commit!