banderam/tidytuesday

Collection of #TidyTuesday code and visualizations

tidytuesday

This repo is a collection of my #TidyTuesday code and visualisations. #TidyTuesday is a project organized by the R4DS Online Learning Community, that emphasize on understanding how to summarize, arrange and visualize data by leveraging the tools available in the tidyverse ecosystem.

2021 Week 13 - UN Votes

Using the data from Harvard's Dataverse: "United Nations General Assembly Voting Data", I focused on lone votes, to explore how many times a country stood alone at the United Nations.

Source code here

2021 Week 15 - Deforestation

This week TidyTuesday was about Forest and Deforestation. The data comes from Our World in Data: Hannah Ritchie and Max Roser (2021) - "Forests and Deforestation". I used the data about Net forest conversion in every countries, and joined them with their young population data from the Data World Bank, trying to spot some curious details.

Source code here

2021 Week 16 - US Post Offices

This week data come from: "Blevins, Cameron; Helbock, Richard W., 2021, "US Post Offices", https://doi.org/10.7910/DVN/NUKCNA, Harvard Dataverse, V1, UNF:6:8ROmiI5/4qA8jHrt62PpyA== [fileUNF]"

US Post Offices is a spatial-historical dataset containing records for 166,140 post offices that operated in the United States between 1639 and 2000. The dataset provides a year-by-year snapshot of the national postal system over multiple centuries, making it one of the most fine-grained and expansive datasets currently available for studying the historical geography of the United States.

Their website has more details:

• US Post Offices

I never used gganimate before, so I challenged myself trying to reproduce the animation from the website:

Source code here