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Data visualizations produced for #TidyTuesdayChallenge, a challenge hosted by R for Data Science.

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TidyTuesday

About

Taken directly from the R For Data Science TidyTuesday README:

A weekly data project aimed at the R ecosystem. As this project was borne out of the R4DS Online Learning Community and the R for Data Science textbook, an emphasis was placed on understanding how to summarize and arrange data to make meaningful charts with ggplot2, tidyr, dplyr, and other tools in the tidyverse ecosystem. However, any code-based methodology is welcome - just please remember to share the code used to generate the results.

Sub-Repositories

I've categorized the code for graphics based on year. You can find code notebooks and more visuals in the sub repositories listed below. Within these folders, you will find code organized by week (e.g. W1, W2, etc).

Gallery of Examples

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Student mobility among top participating countries (based on # of students sent and received) between 2014 and 2020. Screenshot

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Popular board games throughout the ages based on ownership. Data from BoardGameGeek. Screenshot

Exploring average ratings per episode by Doctor from various Doctor Who seasons. Data visualization inspired by Cédirc Scherer. Screenshot

Table graphic summarizing outcomes and scores from World Cricket 1996 (data from ESPN). Screenshot

Network visualization representing the taxonomc classification of a few different spider families. Data from World Spiders Database. Screenshot

About

Data visualizations produced for #TidyTuesdayChallenge, a challenge hosted by R for Data Science.

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