My first-ever #TidyTuesday! 🎉
Sheep ratio decreased. Crop production increased instead!
The plot tracks changes in production volume for each category, alongside their Compound Annual Growth Rate (CAGR). 📈🚜
Code here:
github.com/more-mm/tidy...
#MyFirstTidyTuesday #DataViz #r4ds #DSLC
I feel like a larger-scale replication study of this important topic ("a good life for all within planetary boundaries") would be really empowering for my students. So I would be keen to hear from anyone who knows about useful resources or has done something similar in their classes! #DSLC
A heatmap showing seismic activity at Mount Vesuvius from 2013 to 2024. Each column represents a year, with weeks running vertically. Darker shades indicate stronger seismic events. A square above, indicates year total. The chart shows no clear seasonal trend, but overall activity varies by year.
This week's #TidyTuesday data is all about seismic activity at Mount Vesuvius! 🌋
📊 Two heatmaps showing weekly and annual patterns
🩹 Joined with {patchwork}
🎨 Volcano inspired colour palette
#DataViz #RStats #DSLC #ggplot2
Fun fact: DSLC started in 2017 as an online R for Data Science book club and now it's a community of thousands (dslc.io)! 📈 Proof that learning together catches on. If you're grinding through a data book alone, consider finding a group. #DSLC #rstats #datascience
The chart visualizes the daily number of dogs surrendered to Long Beach Animal Care Services from 2017 to early 2024. Each year is highlighted in a different shade, with vertical lines representing individual surrender events. Notable observations include a drop in surrenders during the COVID-19 pandemic in 2020-2021 and spikes on specific days, such as November 6, 2017, and May 29, 2023, when 10 dogs were surrendered. The overall trend suggests fluctuations in surrender rates, with post-pandemic numbers rising again.
For this week's #TidyTuesday data from Long Beach animal rescue, I focused on when owners surrender dogs 🐕
🎯 Aim: show daily data alongside aggregated counts by year
❓ Why: view temporal patterns on different scales at the same time
📊 How: lollipop chart + heatmap
#DataViz #RStats #DSLC #ggplot2
I finally got around to finishing off this project which:
🦺 scrapes Shakespeare poems and plays using {rvest}
📂 then cleans them up and exports to CSV
📊 to make 195 datasets ready to analyse!
Link: github.com/nrennie/shak...
#RStats #DataScience #DSLC
Grid of proportional area charts (one for each US state) arranged in the shape of the US. Each chart shows the proportion of US customs and border control encounters who are unaccompanied minors, accompanied minors, members of family units, or single adults between Jan 2020 and Nov 2024. Most are single adults, with an increasing proportion of family units in the second half of the time frame.
It's time for #TidyTuesday again! We're looking at data on encounters with US Customs and Border Patrol (via Tony Galvan) 📊
Code: github.com/nrennie/tidy...
#DSLC #RStats #DataViz #ggplot2
A data visualization titled 'Bob's Burgers' shows the distribution of unique words per episode across the first ten seasons of the animated sitcom. The yellow background contrasts with the red density plots, which depict the frequency distribution of unique words. Each season is represented on the vertical axis, from 1 to 14, while the horizontal axis shows the number of unique words, ranging from 800 to 1600. Hamburger icons are scattered within the density plots, representing individual episodes. Text explains that the sitcom follows the Belcher family running a hamburger restaurant and notes that the number of unique words per episode grows slightly over time. Credit is given to the data source and graphic creator at the bottom.
We're looking at Bob's Burgers data (via @sponce1.bsky.social ) for #TidyTuesday this week! 📊 Who knew the world needed a raincloud plot where it's raining hamburgers?
🌧️ Raincloud plot built with {ggplot2}
🍔 Hamburger icons from {emoji}
🐄 Logo added with {cowplot}
#RStats #DSLC #DataViz #ggplot2
I had fun curating this week's #TidyTuesday data (which I scraped from shakespeare.mit.edu using the {rvest} package)! 📦
TidyTuesday Data: github.com/rfordatascie...
You can also find a few more Shakespeare dialogue datasets here: github.com/nrennie/shak...
#RStats #DataViz #DSLC
Horizon chart showing episode ratings for each season of Power Rangers. Seasons 6-10, 17, and 27-28 appear more popular.
We're looking at rating of Power Rangers episodes for #TidyTuesday this week!
🌅 Horizon plot made using {ggHoriPlot}
🎨 Colours from colorbrewer
✍️ Text formatted with {ggtext}
Code: github.com/nrennie/tidy...
#RStats #DataViz #ggplot2 #DSLC
On the left, a spiral showing time since 1850 to 2022 with coloured boxes indicating the time when a World's Fair occurred. On the right, coloured text showing which countries each colour relates to. In more recent years, a wider range of countries are hosting fairs.
We're looking at World's Fairs data for #TidyTuesday this week!
🌀 Plotted long time series data in a spiral using {spiralize}
📷 Combined with text using {ggplot2} and {ggimage}
📊 Coloured text and icons added with {ggtext}
Code: github.com/nrennie/tidy...
#RStats #DSLC #DataViz #ggplot2
A sankey bump chart showing the number of medals won by athletes from each of Africa, Americas, Oceania, Asia, Europe, and Other. Europe takes up the most space.
A (very topical) chart for #TidyTuesday this week - showing the number of medals won by athletes from different continents since the Summer Olympics began!
📊 Chart made with {ggsankey}
🎨 Colours based on Olympic rings
✍️ Fonts from Google Fonts
#RStats #ggplot2 #DataViz #DSLC
a plot of the names of the top 10 American Idol contestants across all seasons arranged in a partial circle. The winners are highlighted in a brighter blue, and the American Idol logo is in the middle of the circle.
For #TidyTuesday this week, I decided to take the opportunity to create an example of using {ggtextcircle}!
⭕ Visualising names of contestants on partial circle with {ggtextcircle}
📷 Added the logo with {ggimage}
📊 Coloured text in subtitle with {ggtext}
Code 👇
#RStats #DataViz #ggplot2 #DSLC
a rank chart showing how the ranking of different Women's football clubs in the FA Women's Super league have changed. Chelsea Women are highlighted.
A quick chart looking at the rankings of different clubs in the FA Wome's Super League for #TidyTuesday this week!
📊 chart made using `plotnine` in Python
✍️ coloured and bold text added with `highlight-text`
Code: github.com/nrennie/tidy...
#Python #DataViz #DSLC #plotnine
a series of 8 area charts arranged in a single row, showing the number of uses of each of the core tidyverse packages during 2023. Hex stickers replace facet labels. ggplot2 is the highest.
For #TidyTuesday, I decided to use {funspotr} to analyse how often I used {tidyverse} packages during my 2023 #TidyTuesday visualisations!
📊 data collected with {funspotr}
📷 images added with {ggtext}
🗺️ colours from {rcartocolor}
Code: github.com/nrennie/tidy...
#RStats #DataViz #ggplot2 #DSLC
12 month 2030 calendar with 11 federal holidays highlighted
12 month 2025 calendar with 11 federal holidays highlighted
12 month 2024 calendar with 11 federal holidays highlighted
For this week's #TidyTuesday data on US federal holidays, I created a simple calendar plot!
📅 Lots of data wrangling with {stringr} & {lubridate}
📊 Calendar plot with {ggcalendar}
💻 Created a parameterised plot function to make a plot for each year
#RStats #DataViz #ggplot2 #DSLC
Diverging bar chart showing spending per year on the 10 vegetables with the highest expenditure across both years. Tomatoes is on top, with all spending in 2020.
A quick bar chart for #TidyTuesday this week, looking at data from the {gardenR} package!
📊 comparing 2020 and 2021 spending with diverging bar chart
🟩 bar charts made with geom_rect in {ggplot2}
✏️ labels added using {ggtext}
Code: github.com/nrennie/tidy...
#RStats #DataViz #DSLC #ggplot2
A stream plot showing coal production since 1900, with colours denoting different types of coal. There amount of coal produced has increased greatly over time, and is still currently increasing.
We're looking at data from Carbon Majors for #TidyTuesday this week!
📊 Streamplot made with {ggstream}
🗺️ Colours from {rcartocolor}
✏️ Text labels added with {ggtext}
Code: github.com/nrennie/tidy...
#RStats #DataViz #DSLC
A map of Europe, with each country represented by a pie chart. The size of the pie chart indicates number of public sector employees. The chart shows split between male and female employees - mostly female in most countries.
A 5x5 grid of record icons with labels below indicating artists and album names for the Rolling Stone's top 25 albums of all time in 2020, with colour of record showing which decade it was released in.
Four coffee cup icons which are partially full - height of cup shows what percentage of people preferred each of coffee A, B, C, or D.
It's been a busy few weeks so I had several weeks of #TidyTuesday to catch up on!
🗺️ {geofacet} to create a map of pie charts
📊 using geom_circle() from {ggforce} to make records
☕ Font Awesome icons + {statebins} to create half-full coffee cups
#RStats #DataViz #R4DS #DSLC
Polar co-ordinate lollipop chart with a log-scale radial axis showing the number of objects launched into space each year. An image of the Earth is in the middle of the chart.
For #TidyTuesday this week, we're looking at objects launched into space!
📊Polar lollipop chart of objects launched per year
📷Image added with {ggimage}
🧮Lots of maths to figure out the geometry!
Code: github.com/nrennie/tidy...
#RStats #R4DS #DSLC #DataViz
