tidytuesday VS tidytuesday

TidyTuesday is a weekly data cleaning project where a new, interesting data source is linked to each week: https://github.com/rfordatascience/tidytuesday

For R, I don't have specific resources, but I remember I started out with doing tidytuesdays challenge (https://github.com/rfordatascience/tidytuesday).

Tidy Tuesday has data and links to more data. The nice thing about those data sets is that you can search for what other people did with the data on social media (e.g. Twitter).

Dataset: https://github.com/rfordatascience/tidytuesday/tree/master/data/2022/2022-11-01

What you're describing is contributing to open source. Some things I'd suggest doing: - learn some git first - create GitHub account and create at least a practice repo - look at learning community-related repos, like Tidy Tuesday - follow R "power" users, people associated with RStudio, and similar folks on social media. Those folks will sometimes mention projects aimed at beginners.

Data: TidyTuesday April 4

The Tidy Tuesday git repo has a lot of example datasets to work with.

I mostly use ggplot2 in R for visualisations which means that The R Graph Gallery is my starting point for inspiration. The best thing to do is start with a simple idea that tells a story, and one of the best guys out there that does this is Cedric Scherer. He is involved a bit with the TidyTuesday project which I wish I had more time to play around with, and is a great starting point for developing a library of vis techniques.

This was my submission to the [TidyTuesday](https://github.com/rfordatascience/tidytuesday) challenge this week ([see my original Twitter post here](https://twitter.com/MrPecners/status/1526761640410095622)). * Tools used: I built this with R using the {wordcloud2} package, which itself uses the [wordcloud2.js library](https://github.com/timdream/wordcloud2.js/).* **Code**: https://github.com/Pecners/tidytuesday/blob/master/2022/2022-05-17/final_plot.R* **Data source**: This data was scraped from the Eurovision website by Tanya Shapiro (Twitter: @tanya_shapiro). You can access the data on TidyTuesday's repo [here](https://github.com/rfordatascience/tidytuesday/blob/master/data/2022/2022-05-17/eurovision.csv).I honestly don't know much about the history of Eurovision, but it seems there was only a final round up until 2004. In any case, that's how the data was provided. Therefore, there are more songs per year from years since 2004.To process the title text, I removed stopwords from 15 languages, and I removed leading apostrophes (e.g. l'amour became amour).

R code here.

Tools: R (code here)