<p>Every Monday the R for Data Science (R4DS) releases a new dataset on their GitHub that has been tamed, but does not always adhere to “tidy” data principles. This dataset will come from an article with an interesting plot. Our goal is to take a look at the raw data, and generate either a copy of the original plot or a novel take on the data! You can obviously use whatever techniques you feel are appropriate, but the data will be organized in a way that tidyverse tools will work well!</p> <p>We will come together and work in teams helping each other solve this weeks TidyTuesday challenge. TidyTuesdays are a great way to improve R skills and get involved in the community!</p> <p>* To participate in TidyTuesday, you need to do a few things *</p> <p>Create and save an image of a plot from R<br/>- Save the code used to recreate your plot (include data tidy steps!)<br/>- Submit the plot and code on Twitter<br/>- Use the #TidyTuesday hashtag (you can also tag me @thomas_mock)<br/>- Browse other submissions and like/comment on their work!</p> <p>However, that might seem like a lot! So at minimum please submit your plot with the hashtag #TidyTuesday.</p> <p>* Rules for TidyTuesday *</p> <p>We welcome all newcomers, enthusiasts, and experts to participate, but be mindful of a few things:</p> <p>- This is NOT about criticizing the original authors. They are people like you and me and they have feelings. Focus on the data, the charts and improving your own techniques.<br/>- This is NOT about criticizing or tearing down your fellow #RStats practitioners! Be supportive and kind to each other! Like other’s posts and help promote the #RStats community!<br/>- The data set comes from the source article or the source that the article credits. Be mindful that the data is what it is and Tidy Tuesday is designed to help you practice data visualization and basic data wrangling.<br/>- Use the hashtag #TidyTuesday on Twitter if you create your own version and would like to share it.<br/>- Include a picture of the visualisation when you post to Twitter.<br/>- Include a copy of the code used to create your visualization when you post to Twitter. Comment your code wherever possible to help yourself and others understand your process!<br/>- Focus on improving your craft, even if you end up with someting simple! - Make something quick, but purposeful!<br/>- Give credit to the original data source whenever possible.</p>