Our main activities are relatively similar between countries, with some differences depending on economic development (based on this week #TidyTuesday )

#RStats code: https://github.com/BjnNowak/TidyTuesday/blob/main/SC_HumanDat.R

Catching up on last week's #TidyTuesday, and keeping it simple with some line charts! This plot uses two of my favourite #ggplot2 extension packages:

🗺️ {geofacet} for visualising data across different geographic regions

📈 {gghighlight} for highlighting a subset of values in a chart, here showing each state in relation to others

Code: https://github.com/nrennie/tidytuesday/tree/main/2023/2023-09-05

#RStats #DataViz #R4DS

#tidytuesday Week 36: Just created a dumbbell chart 📊 comparing mean wages of union members and non-union workers by educational background from 2013 to 2022. Check it out! #r4ds #rstats #ggplot #DataViz #TidyTuesday 🔗code: https://bit.ly/3sOE4Pk

This week's #rstats #tidytuesday was about union membership in the US 👩‍🏭 .

I graphed a couple different relationships, and my code can be found here: https://github.com/sharleenw/tidytuesday/tree/master/2023-09-05-union_membership

Here is my #viz for the #TidyTuesday challenge – W36. This one is about union membership in the United States, 1970-2022.
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This week's data comes from the Union Membership, Coverage, and Earnings from the CPS.
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📂: https://github.com/poncest/tidytuesday/tree/main/2023/Week_36
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#rstats | #r4ds | #tidyverse | #dataviz | #ggplot2

#TidyTuesday
#Caturday
#SilentSunday

what else?

Today's #TidyTuesday was on the top of union vs. non-union wages in the US. I took the opportunity to learn how to make both a static and interactive treemap.

https://lsinks.github.io/posts/2023-09-05-TidyTuesday-Labor/labor.html

I'm thinking about trying a new thing to trick myself into interacting with more humans at #positconf: I'm going to give myself a checklist of quests (basically a scavenger hunt for people). I'll need to find someone who I've known online for at least a year but haven't met irl, someone who worked in S/S+, someone who has done that week's #TidyTuesday, etc. What else should I put on my list? #RStats #introverts

📊 Explore fair use findings by court in our latest data visualization! 🏛️📜 Discover how different courts handle copyright issues. #r4ds #rstats #ggplot #DataViz #TidyTuesday #Copyright #FairUse 🔗 https://bit.ly/3L4Qf0H

The @R4DSCommunity welcomes you to week 36 of #TidyTuesday! We're exploring Union Membership in the United States!

📂 https://tidytues.day/2023/2023-09-05
🗞️ https://onlinelibrary.wiley.com/doi/10.1111/irel.12330

#RStats #DataViz #PyData #tidyverse #r4ds

Delighted to share that both of my entries for the 2023 Information is Beautiful Awards made it onto the longlist! These were both created using #rstats, straight from the data, and they were both made as part of the #TidyTuesday challenge...

Belated #TidyTuesday looking at fair use cases in the USA. Kept it simple with a dotplot - modified to use icons instead of dots!

Code: https://github.com/nrennie/tidytuesday/tree/main/2023/2023-08-29

#RStats #DataViz #R4DS

I'm very happy to see four of my data visualisations long-listed at the 2023 Information is Beautiful Awards! All of mine were made using #RStats, using publicly available data - most of them shared via #TidyTuesday!

You can see mine and other visualisations at: https://www.informationisbeautifulawards.com/showcase?award=2023

#DataViz #IIBAwards #InformationIsBeautiful

To be clear, I do not think #TidyTuesday sends spam email 🙊 but rather that there was a recent dataset on spam email.

For this week's #TidyTuesday (fair use; week 35), I tackled a problem in the dataset description: Joining fair_use_cases with fair_use_findings, despite the values not lining up for a "clean" join.

I was achieved a 100% match rate between the two datasets using a combination of fuzzy joining, string cleaning, and column binding.

🔗 https://tylerburleigh.com/blog/2023/08/31

#rstats

I found the warning for this week's #tidytuesday interesting: "There are two datasets this week for which the rows align, but the values might not precisely line up for a clean join -- a case you often have to deal with in real-world data." I explored how the length of the case title impacted the ease of matching the two dfs. (And matching on the first 10 char was a dramatic improvement over the whole string.)

https://lsinks.github.io/posts/2023-08-29-TidyTuesday-fair-use/tidytuesday35-fair-use.html

It's #TidyTuesday y'all! Show us what you made on our Slack at https://r4ds.io/join (find the #chat-tidytuesday channel)!

RT @jonthegeek https://fosstodon.org/@jonthegeek/110967484094299101

The @R4DSCommunity welcomes you to week 35 of #TidyTuesday! We're exploring Fair Use!

📁 https://tidytues.day/2023/2023-08-29
📰 https://www.copyright.gov/fair-use/

#RStats #DataViz #PyData #tidyverse #r4ds

#TidyTuesday week 35 - Fair use court cases in the U.S. 🇺🇸Read my blog post here: https://jonathankitt.netlify.app/posts/2023-08-29-tt-fair-use/Code here: https://github.com/KittJonathan/tidytuesday/blob/main/scripts/tt_2023_w35_fair_use.R
Many thanks to @danoehm for explaining how to add icons in script titles! #RStats #R4DS #data #fairuse #US

For last week's #tidytuesday, I explored how to make Sankey plots. I discovered that one of the more popular packages (ggsankey) doesn't work for aggregated data like we had with the refugee dataset, while networkD3 worked perfectly. This produces interactive viz- a static thumbnail is shown here.

https://lsinks.github.io/posts/2023-08-28-TidyTuesday-Refugees/TidyTuesday34-refugees.html

The @R4DSCommunity welcomes you to week 35 of #TidyTuesday! We're exploring Fair Use!

📁 https://tidytues.day/2023/2023-08-29
📰 https://www.copyright.gov/fair-use/

#RStats #DataViz #PyData #tidyverse #r4ds