chart planet
graphic insights about the world we live in
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 – it has no 3D effect, the pie chart is marginalized, there are no curved lines, no dashed lines, and the colour palettes are near perfect. One will question whether dashed lines are really a bad practice, another one will easily recreate curved lines with the “data-densification” technique, and here I will argue that there are still plenty of ways to make misleading charts in Tableau.
May this article draw your attention to what the dark practices might be, and whether to use them or to recognize and fight them is the decision to make for each reader.
This is the simplest and probably most used dark practice in real life – simply cutting the axis above zero. Whether it is a good or dark practice depends a lot on the context. Line chart allows to do this “legally”, but here I’m adding some more distortion by changing colours to a more dramatic hue and additionally encoding the size of a bubble to a variable.
Tableau allows for bubble charts that look cool, but are rarely useful to communicate changes in values until your aim is to hide that subtle change. If there is a KPI on your dashboard you don’t really want anyone to see changing – use bubbles. Leaving out the printed numbers would render this visualization practically useless.
However, the same bubbles could actually emphasize the difference if placed one above the other – this would be more like an unnecessary overdesigning rather than dark practice.
Bubbles are very effective to obscure comparisons between categories. The same could be achieved also with colour, and Tableau allows it to happen so easily! Of course, the top and bottom values are easily seen, but the middle is quite muddy, it would be very difficult to sort them without printed numbers.
Both dark practices shown here would be difficult to reproduce on Excel.
I’ve seen such stacking more as a result of trying to make a cooler chart rather than a dark practice (it was a donut chart by the way). But it could be used to conceal the true difference in numbers. Additionally – make the part you want to look bigger much more saturated, and put the border of the same colour around both bars. No smart reader would be fooled by such arrangements, but if there are more charts to digest on the page, the message might slip unnoticed.
Scatterplots are not that easy to read and get for the untrained audience and that is why they are not used often, however they are perfect to show a relation between two variables. Line charts might be used to show the relation, but they could be used to hide that relation – removing lines and making markers a bit oversized effectively obscures the actual direction of data.
This was the actual problem I faced in my job – how to explicitly show profit numbers and somehow make the loss at one period be not that very visible. First of all, we could make the profit and loss to be the same colour, then move the number of loss above – as those of profit, then remove the reference line and finally make the bars thinner. Again – acute reader would quickly recognize dark practices used against him, but only if he is not overwhelmed with charts.
And finally the trick as old as Excel – 3D pie charts are notorious for distorting reality and more often than not they distort it unintenionally, however clever masters of dark practices utilize this feature to their benefit.
With smart preparation of data, dynamic 3D charts are still possible in Tableau. The one seen here is drawn “by hand”, feeding Tableau exact coordinate of each point. A more saturated colour and annotation further serve exaggeration of our company’s market share.
Click the tabs in the visualization above to see all the interactive versions of charts in this article.
Dark practice is not making bad decisions about data vizualizations. It’s making smart intentional decisions to distort viewers’ perception of the data.
Dark practice is not faking the data, it is making the data to appear showing what it might not be showing.
Dark practice is not lying, it is not telling the truth.
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
What: GDP per capita, chain linked volumes (2010) in euro
When: 2004-2020
Where: Current EU members (as of 2021)
The question is it easy to replicate the default settings of one charting software in another charting software bothered me for some time. Are the default settings more universal or less universal? Do different vendors have different attitudes towards what should be the default setting?
I chose to work with a line chart because different software interprets differently how to arrange multiple series in a bar chart – some tools stack them, some not. By adjusting this arrangement I would lose the defaultness, while without any corrections the charts would be less comparable. I made all charts squared, so they fit better in the grid.
This comparison does not include online tools like Datawrapper because a significant part of their settings are the interactions – tooltips, highlights, etc and here only static images are compared. I would like to include JMP, but my trial period has already expired. Python and Javascript libraries are not included, because I don’t know how to use them.
I believe this exercise is of little use, but it was fun to do it!
Turime ir vakcinas ir griežtas priemones valstybės mastu suvaldyti ligos siautėjimą.
Su viltimi, kad viskas bus tik geriau stebiu Covid-19 ligos paplitimą Lietuvoje ir pasaulyje. Duomenys savaitiniai. Atnaujinama nereguliariai.
Ne visi sergantys šia liga yra testujami ir užfiksuojami, nes trūksta tiek pačių testų, tiek darbo jėgos medicinos sektoriuje, taigi gali būti, kad žmogus susirgo ir mirė nepastebėtas. Taip pat dėl sergančiųjų antplūdžio ligoninėse žmonės nesulaukę medicininės pagalbos gali mirti ir nuo kitų ligų, nuo kurių galėtų būti išgelbėti. Dėl to svarbu stebėti ne Covid-19 mirtis, bet perteklines mirtis.
Pasveikusiųjų duomenys yra ypatingai nepatikimi, nes prioritetas visad yra testuoti naujai susirgusius, o ne pasveikusius. Pasveiko gerokai daugiau žmonių nei skelbia oficiali statistika pasaulyje, taigi ir sergančiųjų yra mažiau. Čia pasveikusiųjų skaičius įvertintas teoriškai – jei žmogus per 4 savaites nuo ligos nenumirė – vadinasi pasveiko. Tai nėra tikslu, bet geriau negu oficialūs duomenys.
Čia gali sužinoti kokia dalis žmonių iš tavo savivaldybės išvyko gyventi į kitas Lietuvos savivaldybes.
Arba jei esi iš Neringos, Palangos, Vilniaus ar Kauno – kokia dalis atvyko.
Šis grafikas parodo kiek lietuvių gyvena užsienio šalyse ir atvirkščiai – jis nerodo srauto, t.y. migracijos.
Stebina tai, kad Rusijoje ir Lenkijoje gyvena daugiau lietuvių nei Norvegijoje ar Airijoje.
Šaltinis: United Nations, Department of Economic and Social Affairs, Population Division (2019). International Migrant Stock 2019. (United Nations database, POP/DB/MIG/Stock/Rev.2019).
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
The question arises because we’re having Climate Change and not Global Warming.
Only 6 weather stations in the world have a statistically significant negative temperature trend since 2000.
Most of them are located around the equator, one is in Antarctica.
There are 391 weather stations that have at least 5 full years of data since 2000 and which have a significant trend (p-value is less than 5%).
In 385 of those stations, the temperature is rising.
When: 2000 January – 2020 December.
Where: Weather stations that have at least 5 full years of data during the period in question and have a significant regression coefficient (p-value < 5%).
Source: Global Historical Climatology Network-Monthly (GHCN-M) temperature dataset https://www.ncdc.noaa.gov/ghcn-monthly
What: share of the total world’s GDP
When: 1990-2019
Where: top 14 world countries by GDP each year
Source: Worldbank database
There are 9 countries in the Arabian peninsula, some of them are considered rich while others suffer from poverty and never ending wars. If the Arabian peninsula were one country it would be the 11th largest economy in the world.
What: GDP in constant 2010 USD
When: 2019
Where: All the countries in the world. “Others” were calculated by subtracting the shown countries from the total world GDP estimated by Worldbank. Countries of the Arabian peninsula are Saudi Arabia, United Arab Emirates, Iraq, Qatar, Kuwait, Oman, Bahrain, Jordan, Yemen.
Source: Worldbank database
ASEAN is an economic union of Southeast Asian countries. From 1999 to 2019 it experienced considerable growth becoming the 5th largest economy in the world if we count the EU as one unit as well.
Indonesia is the biggest country in the union, but all of them contribute to growth, most growing their GDP by more than 5% a year during 1999-2019 with the only exception being Brunei.
For comparison: the annual average growth in the EU was 1,6% a year and in China, it was 9,0% during the same period. The current composition of the EU was used for the calculations.
What: GDP in constant 2010 USD
When: 1999-2019
Where: All the countries in the world. “Others” were calculated by subtracting the shown countries from the total world GDP estimated by Worldbank.
Source: Worldbank database
Africa is made up of more than 50 countries, most of them are poor compared to the rest of the world. If Africa were one country it would be the 8th largest economy in the world.
This chart is made without any numbers intentionally, they’d distract from the message. The ranking of the countries in the donut chart is “Algeria first”.
What: GDP in constant 2010 USD
When: 2019
Where: All the countries in the world. “Others” were calculated by subtracting the shown countries from the total world GDP estimated by Worldbank.
Source: Worldbank database
