Invention Patents vs Research Articles Ratio study on WIPO, OECD, EU tables

1 DataSets for Paper-Patent comparison}
Three datasets for paper/patent related data.
The first three files are in Excel format the 4th in Python. The initial dataset is located first.
Then selected subset and calculations are generated.
1.1 Article/patent ratio according to Global Innovation Index}
World Bank declared this dataset is classified as Public under the Access to Information Classification Policy under Definition: Scientific and technical journal articles refer to the number of scientific and engineering articles published in a lot of fields. Scientific and technical article counts are from journals classified by the Institute for Scientific Information's Science Citation Index (SCI) and Social Sciences Citation Index (SSCI).
We isolated two codes:
1. WIPO, Patent applications, residents indicator code 2012,
2. SCIMAGO, Scientific and technical journal articles indicator code 2015

Dutta, S., Lanvin, B., Wunsch-Vincent, S., 2020. Global innovation index 2020. WIPO, Johnson Cornell University.
URL: https://www.globalinnovationindex.org/about-gii.

1.2 Article - patent ratio according to Global Innovation Index}
All classifications and numbers are per country GDP. We focus on three items:
1. PCT patents by origin/bn PPP USD GDP,
2. Scientific and technical articles/bn PPP USD GDP and
3. Citable documents H-index
OECD, 2014. Patents by main technology and by international patent classification (ipc) URL: https://www.oecd-ilibrary.org/content/data/data-00508-en ,
doi: https://doi.org/10.1787/data-00508-en

1.3 Article Patent Ratio according European Patent office
Scientific and technical journal articles - tcdata360. URL: https://tcdata360.worldbank.org/indicators/IP.JRN.ARTC.SC?country=BRA&indicator=2015&viz=line_chart&years=2003,2016 .
Download link https://tcdata360-backend.worldbank.org/api/v1/datasets/56/dump.csv

1.4 PYTHON sheet to solve min-max scaling data for PATENT/PAPER ratio
To compare patents with papers, normalize my data with min-max scaling method
The formula for calculating normalized score is the following
X new = (X — X min)/ (X max — X min)
1 Python 1 PDF file