tidytuesday
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Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tidytuesday
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Too old to continue my education? I'm lost.
For R, I don't have specific resources, but I remember I started out with doing tidytuesdays challenge (https://github.com/rfordatascience/tidytuesday).
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[OC] Popularity of Horror Movie Poster Color Schemes from 1970
Dataset: https://github.com/rfordatascience/tidytuesday/tree/master/data/2022/2022-11-01
- R projects/applications
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Really enjoying the R side of my degree.
If you don’t have the ability to do a real project in R but want experience, you can join a group of R users that get weekly data and perform some type of data tidying and then plotting. It will also really help you build a profile with your skills with coding and data viz https://github.com/rfordatascience/tidytuesday
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Sample datasets to practice skills
In addition, tidytuesday puts out a new dataset every week. Some are easy, some aren't, but that's life: https://github.com/rfordatascience/tidytuesday
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List of Places to Find Datasets
https://github.com/rfordatascience/tidytuesday A lot of datasets for analysis
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Useful databases
Tidy Tuesday is pretty good https://github.com/rfordatascience/tidytuesday
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has anyone got some good books?
For visualizations, you could follow/participate in TidyTuesday: a weekly "challenge" where you are given some data and plots to generate with that data. A lot of people participate, and most (if not all) post their code online. You can find most of them on Twitter with the #TidyTuesday hashtag. There's also the #30DayChartChallenge in the same vein. You can track some of the recurring participants' websites/github repositories to see their work & code (just to mention a few from the top of my head: Cedric Scherer, Lisa Debruine).
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where to practice R basics?
Check out TidyTuesday - it's a weekly project curated by the R4DS online learning community where participants are encouraged to get their hands dirty with some fairly simple projects. Most people share their solutions, so if you get stuck you can always look at how other people attempted it.
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[OC] Word cloud of Eurovision song titles (1956-2022)
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).
OKRs-self-learning
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Starting my #66DaysofData Journey
If you want an example of a self-learning plan check out Sophia Li's (OKR).
What are some alternatives?
data - Data and code behind the articles and graphics at FiveThirtyEight
gganimate - A Grammar of Animated Graphics
cheatsheets - Posit Cheat Sheets - Can also be found at https://posit.co/resources/cheatsheets/.
r4ds - R for data science: a book
awesome-public-datasets - A topic-centric list of HQ open datasets.
ggsunburst
big-mac-data - Data and methodology for the Big Mac index
EconomicTracker - Download data from the Opportunity Insights Economic Tracker — https://tracktherecovery.org/
dataRetrieval - This R package is designed to obtain USGS or EPA water quality sample data, streamflow data, and metadata directly from web services.
swirl - :cyclone: Learn R, in R.
data-screencasts - Code from live exploratory analyses of data in R
ebayScraper - Scrape all eBay sold listings to determine average/median pricing, plot listings over time with trend lines, and extract to excel