lrmendes / who-data-mining

Python algorithm for converting WHO official COVID daily reporting tables (PDF) into simple data format (Pandas / CSV file).

World Health Organization - PDF Data Mining

Python algorithm for converting WHO official COVID daily reporting tables (PDF) into simple data format (Pandas / CSV file).

Project Overview

This code is an adaptation of Lain's tutorial code, posted at: http://www.degeneratestate.org/posts/2016/Jun/15/extracting-tabular-data-from-pdfs/

The main adaptation is this code suitable for reading the tables of daily reports of the World Health Organization (WHO) on COVID.

Features

• Converts Official COVID PDF tables to CSV.
• Query Algorithms for data visualization.

Core Libraries

• PDF Mining: https://github.com/pdfminer/pdfminer.six
• Data Manipulation: https://github.com/pandas-dev/pandas
• Data Visualization: https://github.com/mwaskom/seaborn

How it works?

• Place a PDF* inside input folder.
• Run "WHO_PDF_MINER.py" and set pdf_file_name variable as the name of your PDF.
• The Output CSV will be created in the output folder with the same name as the PDF.

*You can download official WHO pdfs from this link: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/

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PDF Miner Algorithm:

Input PDF (PdfMiner)

Output CSV (Pandas)

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Query Algorithms (Pandas / Seaborn):

One Country Plot -> By Given Dates & Attributes (Full Dataset)

One Country Plot -> By Given Dates & Column/Attribute

  

One Date Plot -> By Given Column/Attribute

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