Order your data
When displaying the value of several entities, ordering them makes the graph much more insightful.
To cut or not to cut?
Cutting the Y-axis is one of the most controversial practice in data viz. See why.
The spaghetti chart
A line graph with too many lines becomes unreadable: it is called a spaghetti graph.
The human eye is bad at reading angles. See how to replace the most criticized chart ever.
Play with histogram bin size
Always try different bin sizes when you build a histogram, it can lead to different insights.
Do boxplots hide information?
Boxplots are a great way to summarize a distribution but hide the sample size and their distribution.
The problem with error bars
Barplots with error bars must be used with great care. See why and how to replace them.
Too many distributions.
If you need to compare the distributions of many variables, don't clutter your graphic.
Too many points on your scatter plot makes it unreadable? Techniques exist to avoid overplotting.
The rainbow color palette
Avoid the rainbow color palette when you map a numeric variable. So many better palettes exist.
Faceting: horizontal or vertical?
Placing the individual plot horizontally or vertically is an important choice to make.
Don't be counter intuitive
Your audience is used to a few dataviz standards. Not respecting standards can be misleading.
The problem with dual axes
Using dual axes is a good way to manipulate the history behind your data. Avoid it. (blog by datawrapper)
Always double-check the values written on the chart. Does your sum make sense?
Barplots with radial coordinates
This kind of barplot distorts reality: outer bars tend to look bigger than inner ones.
Connect your dots
If your X-axis is ordered, connecting the dots will make the message much clearer.
Color that communicates nothing
A bad use of colors can be misleading. If your color does not represent anything, don't use it.
Bubble size: radius or area?
When using bubbles on a chart, their area must be proportional to the underlying variable. Not their radius.
When axis labels break your neck
Having long and vertical axis labels can be annoying. If you can, flip your chart.
Circular barplots and distortion
Set a sufficient inner circle size to avoid bar shape distortion.
The issue with 3D
Except in a few rare situations, 3D must be avoided. It distorts reality.
Mind the aspect ratio
Avoid extreme aspect ratios. They can make a plot unreadable.
The issue with stacking
Stacking makes it difficult to analyze each represented group. See when to use it.
Don't ask the reader to do mental arithmetic, it is hard to compare shapes.
Area is a poor metaphor
Human brains struggle to translate areas to precise values. Prefer other shapes.
Grouped barplots must be grouped
In a grouped barplot, bars in the same group must be close one to each other. It makes grouping obvious.
De-clutter your graphic
Keep only what's necessary on your graphic: 3d, color effect, redundant info, etc. hide the story.
Mind your legend
A few tips for a useful legend. Hint: you should worry if you have 14 groups.
Consistency between charts
If you present several graphics, be consistent. Does each color always represent the same group?
Spider chart and its caveats
Spider or radar charts are often criticized in dataviz, here is an overview of the topic.
What you should consider when doing a heatmap
Heatmaps are a powerful way of visualizing information. A few features must be considered.
The Simpson paradox
When a trend appears in several different groups of data but reverses when these groups are combined
Annotate your chart
Help the reader understand your point: highlight the important part
The Moire effect
If you have a barplot with many bars of similar length, consider a lollipop chart instead.
Choropleth and normalization
If you don't scale your data, your choropleth will basically look like a population map.
How to read a log scale
Comparing percentage change on a linear scale can be misleading, use a log scale instead. By datawrapper.
There is no 'L' in choropleth
And people won't miss an opportunity to make you notice..