Usually in our monthly newsletter we feature a single “chart of the month”, but this time we are featuring April as the “month of the chart” and making a chart for each day. Cédric Scherer and Dominic Royé have organised the #30DayChartChallenge on Twitter, inspired by the success of the similar #30DayMapChallenge, as a chance for aspiring and experienced data visualisation enthusiasts to practise, try new tools and techniques, and to share ideas. They provided 30 topics that allow a range of interpretation, which have been enthusiastically taken up by over 130 people and organisations around the world.
The team at Infometrics thought this would be a good opportunity to try some new things and highlight some interesting New Zealand economic (and economic-adjacent) data. It wasn’t well-timed for us, with quite a lot of work on this month, but even though we didn’t manage the pace of one chart per day we did manage to produce 30 between five of us – Andrew Beattie, Brad Olsen, David Friggens, Nick Brunsdon and Paul Barkle. We mostly used Datawrapper and the R programming language, but produced a couple with Excel, Powerpoint and even the game Townscaper.
Enjoy our offerings below, and be inspired and educated by the wealth of creativity on display from other challenge participants.
We're joining #30DayChartChallenge this month, though we'll be quiet over Easter. For Day 1 (part-to-whole) here's a treemap of NZ's chocolate exports last year, made with #rstats by Technical Lead @dakvid pic.twitter.com/z7bstHSLLl
— Infometrics (@InfometricsNZ) April 1, 2021
A #30DayChartChallenge catch up: Day 2 (pictogram). Did you know that Auckland (the urban area, not the region) has the same number of people as the next 11 cities? pic.twitter.com/8IX49PXJCB
— Infometrics (@InfometricsNZ) April 8, 2021
Another #30DayChartChallenge catchup. For Day 2 (historical) we look at the historical popularity of Bitcoin. It may look like we subcontracted to @Michael1979 but we have worked hard to develop this inhouse expertise.#rstats with theme_excel ? pic.twitter.com/eDcqeNWSvD
— Infometrics (@InfometricsNZ) April 13, 2021
It's been a very busy April for us so #30DayChartChallenge has had to keep playing catch up. But @dakvid still found time to read. And to make some charts about books. For Day 4 (magical) he was inspired by @maxthamt to compare fantasy book series pic.twitter.com/eDKNU9JjaS
— Infometrics (@InfometricsNZ) April 21, 2021
How did the @covid19nz restrictions affect traffic volumes last year? Here are three #rstats plots for #30DayChartChallenge.
— Infometrics (@InfometricsNZ) April 21, 2021
Day 5 (slope) A slope chart clearly shows traffic dropped across the country. Auckland dominated absolute #'s so per capita needed to show relative change pic.twitter.com/CjRIvIa9AU
Why not make a housing bar chart using houses ?️? For #30DayChartChallenge day 6 (experimental) @dakvid tried this out using @OskSta's enchanting #Townscaper game ? pic.twitter.com/gwzD0fW4Gc
— Infometrics (@InfometricsNZ) April 9, 2021
Sometimes a map isn't the best viz for geographical data – differences in area can make the data misleading. For Day 7 (physical) of #30DayChartChallenge @dakvid made a scatter plot comparing area & population of the 67 local councils in NZ. pic.twitter.com/lRjrGgXdH3
— Infometrics (@InfometricsNZ) April 7, 2021
Our #30DayChartChallenge has gone to the dogs ? so for a Day 8 (animals) catch up, economist Andrew Beattie looked at the most popular dog breeds in NZ. Another treemap made with #rstats pic.twitter.com/JeRdn2dGk3
— Infometrics (@InfometricsNZ) April 23, 2021
For #30DayChartChallenge Day 9 (statistics), economist Paul Barkle wonders how much rent has gone up each year across New Zealand. His a bar chart shows the 10 year average for each region.
— Infometrics (@InfometricsNZ) April 9, 2021
Made with @Datawrapper pic.twitter.com/dFejhclJBV
#30DayChartChallenge Day 10 (abstract)
— Infometrics (@InfometricsNZ) April 24, 2021
Hopefully not too abstract. Answers on the back of a postcard.
Simple ggplot geom_col, with width=1.3 on the bars. #rstats pic.twitter.com/qi10ifT6zL
Day 11 (circular). Weekly traffic volumes in Auckland throughout 2020. The effects of the lockdowns are unmissable. #30DayChartChallenge pic.twitter.com/62C03ss6Mv
— Infometrics (@InfometricsNZ) April 21, 2021
#30DayChartChallenge day 12 (strips)
— Infometrics (@InfometricsNZ) April 28, 2021
Nick Brunsdon's stacked bar chart looks at changes in New Zealand population pic.twitter.com/NQvgnaOGFn
Day 13 (correlation). Do traffic volumes correlate with @covid19nz restrictions? ? After the last two charts it shouldn't be a surprise, but here's a trend line on an Auckland scatter plot just to be clear.
— Infometrics (@InfometricsNZ) April 21, 2021
The dots are jittered a little for clarity.#30DayChartChallenge pic.twitter.com/xCGvww9hak
#30DayChartChallenge day 14 (space) – New Zealand land cover. A treemap in Excel by Nick Brunsdon. pic.twitter.com/DPkhkvWrcf
— Infometrics (@InfometricsNZ) April 22, 2021
#30DayChartChallenge day 15 (multivariate)@dakvid took the data from the three bar charts in day 23 and made a scatter plot of NZ regions for a different perspective.
— Infometrics (@InfometricsNZ) April 28, 2021
A good choice for @Datawrapper – see the interactive version here: https://t.co/tovmAAkuZB pic.twitter.com/JfJwbutQCz
For #30DayChartChallenge day 16 (trees), Senior Economist Nick Brunsdon looked at what happens to all the trees the NZ forestry sector chops down.
— Infometrics (@InfometricsNZ) April 22, 2021
A nice donut chart made in Excel. pic.twitter.com/hIRg9e7DL4
And for Day 17 (pop culture) some more books! ? #30DayChartChallenge pic.twitter.com/82sRNCfxqT
— Infometrics (@InfometricsNZ) April 21, 2021
#30DayChartChallenge day 18 (connections)
— Infometrics (@InfometricsNZ) April 28, 2021
Seeing our friends and whanau from across the ditch as flights with Australia get going again.
A @Datawrapper line chart from @BradOlsenNZL pic.twitter.com/xQHKmf9p2d
#30DayChartChallenge Day 19 (global change)@BradOlsenNZL looks at the change in where New Zealand's imports have come from.
— Infometrics (@InfometricsNZ) April 28, 2021
Another @Datawrapper gem pic.twitter.com/6M4LG1dRg9
#30DayChartChallenge Day 20 (upwards)
— Infometrics (@InfometricsNZ) April 26, 2021
On first glance, spending activity in NZ seems to be going crazy at present. But as @BradOlsenNZL’s chart shows, the Level 4 lockdown last year means y-o-y comparisons in April will be wild. Made with @Datawrapper https://t.co/50ssu8QqTn pic.twitter.com/2f3Z97MPwE
#30DayChartChallenge Day 21 (downwards)
— Infometrics (@InfometricsNZ) April 23, 2021
What's going down in New Zealand? Home ownership rates!
There are some big arrows in Nick Brunsdon's arrow plot, made with Datawrapper. pic.twitter.com/TumuGYHPd1
#30DayChartChallenge Day 22 (animation)@orphee_mickalad won the recent Palmerston North City Council by-election after 10 iterations of counting. Single Transferable Vote (STV) counts can be confusing – @dakvid's animated bar chart shows the transfer of votes#rstats {gganimate} pic.twitter.com/IvAv7sB70P
— Infometrics (@InfometricsNZ) April 23, 2021
#30DayChartChallenge day 23 (tiles)
— Infometrics (@InfometricsNZ) April 28, 2021
Nick Brunsdon uses some indicators from our Quarterly Economic Monitor to look at how the regions economies performed last year.
Made with @Datawrapper pic.twitter.com/0H2p60KJS3
#30DayChartChallenge day 24 (monochrome)
— Infometrics (@InfometricsNZ) April 28, 2021
New Zealand's population by overseas birthplace.
A @Datawrapper bar chart from Nick Brunsdon. pic.twitter.com/EjzTtbpoLs
#30DayChartChallenge Day 25 (demographic)
— Infometrics (@InfometricsNZ) April 25, 2021
Here's a map of NZ's territorial authorities showing the projected ratio of children to seniors in each area in nearly 20 years time.
Made by Senior Economist Nick Brunsdon in Datawrapper. Interactive version here: https://t.co/TjVcH13Ond pic.twitter.com/Gwk9Pk3QLn
#30DayChartChallenge Day 26 (trends)
— Infometrics (@InfometricsNZ) April 26, 2021
If you are a renter anywhere in New Zealand you will have noticed a distinct trend over the last five years. Nick Brunsdon's arrow plot shows us the pointy ends. pic.twitter.com/LbvyW9Benc
It's back to school for Senior Economist @BradOlsenNZL with a look at the most popular school subjects. We're pleased to see economics in the top 20.#30DayChartChallenge day 27 (educational)
— Infometrics (@InfometricsNZ) April 28, 2021
Made with @Datawrapper pic.twitter.com/156QddnWjn
#30DayChartChallenge day 28 (future)
— Infometrics (@InfometricsNZ) April 28, 2021
Some of our charts show the changing international trade links. Are school students learning the (more relevant) languages of the future?@dakvid made a more Tufte-like slopechart in #rstats to see the changes pic.twitter.com/dGjPp3oI8p
#30DayChartChallenge day 29 (deviations)
— Infometrics (@InfometricsNZ) April 28, 2021
How are regional population growths expected to deviate from the national average? Nick Brunsdon investigates with some more @Datawrapper bar charts. pic.twitter.com/TDuR7ZvCXe
We finish #30DayChartChallenge a day early (day 30: 3D). After 27-29 serious attempts at good data visualisations we thought we'd try to make the worst chart we could. A gold star if you can count 7 or more viz crimes (including the 3d pie chart). Just because Excel lets you… ? pic.twitter.com/AXq55mAJ1f
— Infometrics (@InfometricsNZ) April 28, 2021