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Posts

Posts

Predicting voluntary CEO departures using machine learning

Graphs and analysis using the #TidyTuesday data set for week 18 of 2021 (27/4/2021): "CEO Departures"

Films with MPA ratings on Netflix

Graphs and analysis using the #TidyTuesday data set for week 17 of 2021 (20/4/2021): "Netflix Titles"

Post offices in the USA from 1772 to 2000

Graphs and analysis using the #TidyTuesday data set for week 16 of 2021 (13/4/2021): "US post offices"

Plotting deforestation and its causes

Graphs and analysis using the #TidyTuesday data set for week 15 of 2021 (6/4/2021): "Global deforestation"

Plotting foundations according to shade

Graphs and analysis using the #TidyTuesday data set for week 14 of 2021 (30/3/2021): "Makeup Shades"

UN Votes: Plotting votes on United Nations resolutions

Graphs and analysis using the #TidyTuesday data set for week 13 of 2021 (23/3/2021): "UN Votes"

Video Games and Sliced

Graphs and analysis using the #TidyTuesday data set for week 12 of 2021 (16/3/2021): "Video Games and Sliced"

Bechdel Test

Graphs using the #TidyTuesday data set for week 11 of 2021 (9/3/2021): "Bechdel Test"

Welcome

Welcome to my TidyTuesday blog. This site features graphs and analysis of various data sets from the R for Data Science (R4DS) #TidyTuesday project.

Footnotes

    Corrections

    If you see mistakes or want to suggest changes, please create an issue on the source repository.

    Reuse

    Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/rnnh/TidyTuesday/, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".