Did you know some charts are better for human perception than others? There have been several studies on graphical perception or how we visually-mentally process graphs. One in particular is a Cleveland & McGill study from 1984! In their study they reviewed position, length and slope in charts. They discussed that the use of position and length are the most accurate for perception.
Charts containing angles such as pie charts, 3D graphs and line graphs / scatter plots are less accurate for perception. Additionally charts containing curvature (such as donut charts and pie charts which contain shading and color saturation) are at the very bottom of the list of accurate charts.
Image taken from Link Cleveland and McGill study from York University
Their study goes into great detail and displays a couple of map examples.
JPM Statistical Discovery website here displays their interpretation of this black and white chart as below (Link);
Image from JPM On Air
The below article from Data in the spotlight has another interpretation for this;
Image from Data in the spotlight article
Recommendations
I think the type of chart you should use, depends to your use case. There are certain charts you should use instead of others. I will walk you through a couple of examples below.
Also to note, if you are a beginner, Andy Kriebel has a great dashboard out there to help you with what charts to use for what analysis here.
For Pie charts, you almost always have to use labels. In the example below can you tell which Region slice is bigger, Central or South? You always have to use labels for close sized slices.
The bar chart is a better alternative, especially if you use a best practice of sorting the longest bar first.
Another example is where a a curve or line chart will be better than using text chart to analyze trends etc. An example is below;
It takes a human longer to view trends etc looking at a text table.
If you use the alternative Line chart you can see the increases and decreases of sales more clearly.
In the use case of viewing year over year data. The recommendation for using a chart with position alone (such as a dot plot) does not work.
The dark grey dots contain sales for the previous year. The teal dots are sales for the current year.
This chart would work better if you added a position element changing it to a Dot Plot instead of a Scatter Plot. You can see which sales increased and decreased now that the dots are connected.
Alternatively an Area chart would also work. You can see the current sales in teal which overlap the previous year in grey. The peaks and valleys display the increases or decreases in sales compared to the previous year.
Check out the article on the Cleveland and McGill study!