tidytuesday
data-screencasts
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tidytuesday | data-screencasts | |
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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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Recommendation for interesting datasets to work with?
TidyTuesday is a weekly data cleaning project where a new, interesting data source is linked to each week: https://github.com/rfordatascience/tidytuesday
- Rfordatascience/tidytuesday: Official repo for the tidytuesday project
- [OC] Tornados in the U.S. are becoming more frequent in off-peak months
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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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First Project
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).
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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
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Tips on getting experience in R on GitHub
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.
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[OC] 2021-22 EPL Home/Away Goal Differential
Data: TidyTuesday April 4
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Publicly available datasets?
The Tidy Tuesday git repo has a lot of example datasets to work with.
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[OC] Kyle Feldt and his Chevalier Sheriffs: An Infographic of Feldt's NRL Tries
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.
data-screencasts
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[OC] Post office locations in the continental US: 1770-2002
R code for the animation: https://github.com/dgrtwo/data-screencasts/blob/master/2021_04_13_post_offices.Rmd
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
OKRs-self-learning - Sophia's OKRs for learning how to code.
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.