
This post is an opinion. The mix of traditional and simplified characters is intentional.
Made with R and Inkscape.
What if your client or stakeholder asks to make the dashboard you prepared to be more eye-catching, beautiful, or just cool? In such cases, we have one job – a very subtle one – to enhance UI without sacrificing UX, dataviz or information designs, maybe even enhancing them altogether.
CONTINUE >>>This post is an opinion. The mix of traditional and simplified characters is intentional.
Made with R and Inkscape.
You can find maybe 1000 articles with “most important”, “essential” or “golden” rules of data visualization and their set will be unique every time.
Here, I will try to extract principles for data visualization from the underlying reasons why data visualization is even a thing.
Šiame straipsnyje pasidalinsiu rekomenduojamomis duomenų vizualizavimo priemonėmis priklausomai nuo to, kokiu tikslu jos piešiamos.
CONTINUE >>>Lawful – following the best data visualization rules.
Neutral – basically following the defaults.
Chaotic – doing some “design”.
Good – trying to provide information in a clear way.
Neutral – you just need numbers, here are your numbers.
Evil – let’s pick fancy chart!
How is the pie chart among “good” ones?
What: Type distributions among men and among women.
When: Data was gathered in 2018.
Where: A selection of mostly western countries with representative samples.
Source: MBTI Manual Global Supplements Series | The Myers-Briggs Company (themyersbriggs.com)
What: % of all respondents in a country which represent this type. Country = 100% , but wider bars indicate, that this % of this type is among the top 3 highest in all listed countries. If you’re looking for this type – it is best to look in this country.
When: Data was gathered in 2018.
Where: Only the countries with representative samples are portrayed in the chart.
Source: MBTI Manual Global Supplements Series | The Myers-Briggs Company (themyersbriggs.com)
What: Annual inflation of different items. “Energy” is an aggregate compiled from “Transport” and “Housing” items, so it does overlap with them.
When: 1997-2021
Where: European Union – from 15 countries in 1996, to 27 countries in 2021.
Source: Eurostat database
What: Annual inflation rate and 3-month interbank rate.
When: Every month from January 1990 till January or February 2022 (latest data available).
Where: All countries available in the OECD database (OECD countries + some other countries) which have data for 2022 (that’s why no China here) except Luxembourg.
Source: OECD
Tableau is famous for following the best of the best practices in the DataViz world, but there are still plenty of ways to make misleading charts.
CONTINUE >>>What: The chart shows average daily gain in $ if $1000 were invested at a date on x-axis. Total gain was divided by the number of days between the day of investing and June 13, 2021. Gains were calculated on average 30-day prices.
When: from March 28, 2013, till June 13, 2021
Source: investing.com and coingecko.com
Are the default settings more universal or less universal? Do different vendors have different attitudes towards what should be the default setting?
CONTINUE >>>In the Northern hemisphere the summer is warmer than the winter (i.e. normal), in the Southern hemisphere the winter is warmer than the summer (i.e. Australian), around the equator there is not much difference during the year.
What: The difference between monthly mean temperature and annual mean temperature.
When: Some weather stations have data since the XVIII century.
Where: All the weather stations in the world binned at each 10th latitude. Only stations with full-year datasets used in calculations.
Source: Global Historical Climatology Network-Monthly (GHCN-M) temperature dataset https://www.ncdc.noaa.gov/ghcn-monthly