Now there is so much data that it is no longer realistic to perceive them using tables. At the same time, charts allow us to quickly and efficiently analyze large datasets, highlight relationships, and patterns, focus on the important, and in the end – it’s just beautiful!
Of course, not all economists and financiers are data visualization experts, and as a result, we are constantly faced with incomprehensible graphs and charts. This article describes 10 of the most common mistakes in using visualizations and helpful tips to fix them.
- The vertical Y-axis does not start from 0
Histograms (bar graphs) are mainly used to visualize relative sizes. Accordingly, if the user of information sees that one bar on the graph is twice as large as the other, he subconsciously concludes that there is a twofold difference in quantitative value. But this comparison will be wrong if the axis does not start from zero.
This error, leading to a significant distortion of the proportions, is the most common.
2. The time axis incorrectly reflects the integrity of the period
Let’s imagine a situation when in the first half of the year the company had sales only in January, February, April, and June. And for March and May, there were no sales. In the diagram, we simply do not see these “dips”.
This is because Excel interprets months in this case as a category, not as a continuous dimension, and makes equal tick marks for unequal intervals. In this case, the data source must explicitly state that sales were zero in March and May.
3. Choosing the wrong chart type
The graph allows you to express the idea that the data carries in the most complete and accurate way, so it is very important to choose the appropriate type of chart. Bar charts are better understood when comparing categories, line charts when showing a category change over time, and pie charts to visualize the structure.
4. Using 3D effects
Beauty in graphics isn’t always synonymous with clarity. Due to the addition of an additional third dimension to the diagrams, a strong distortion of proportions occurs according to the principle of a close/distant object.
For this reason, most 3D visualizations do not at least make information clearer. On a 3D pie chart, it is often not clear which sector is larger or smaller. which is not observed on 2D diagrams of the same graph.
- Poor or redundant design
The following points can be highlighted that definitely do not contribute to a better perception:
- lack of a title;
- no axle labels;
- serif font;
- an abundance of black auxiliary lines;
- vertical or diagonal inscriptions – they are much worse readable;
- a separate legend (of course with a black borderline), if it is possible to label the data on the diagram itself.
If you want to see some really cool designs, take a look at projects by professionals who are ready to help you. For example, can be considered the data visualization service from Fuselab Creative and you will definitely be satisfied with such cooperation.
6. Too many categories
Dividing a pie chart (or even a regular histogram) into a large number of sectors makes it impossible to quickly compare categories, especially small ones. Often it turns out just informational rubbish.
The best visualization practitioners advise dividing the structure into a maximum of 4-5 parts. As a last resort, you can always apply category grouping or divide information into multiple diagrams.
7. Lack of accent
If there is no accent on the diagram, the gaze does not cling to anything – you risk getting the unfocused attention of the information consumer.
This is especially important when preparing visualizations for presentations. Highlighting with color, in contrast, is the best way. You can also make annotations – text inserts explaining the behavior/change of the graph at specified points.
8. Distortion when grouped into the “Others” category
The “Others” category is best done only when only a small part of the data is grouped into it. Otherwise, you can easily distort the perception of information.
For example, in the graph, the category “Others” is hidden, which may lead to the idea that the rest of the categories contain complete data. But if you add this category, then the graph shows a slightly different picture.
9. Incorrect use of averaged data
Imagine two graphs. On the first, we see a positive dynamics of sales, the company is doing well. But if you expand the same information on the categories of goods sold, then the situation appears in a completely different light. It turns out that all but one category is experiencing a decline in sales. And only due to this very category, the enterprise as a whole was able to sell more this year than last. There is something to think about here, isn’t it?
Averages or totals can be a great way to quickly gauge a business for some key metrics, but always remember that they can hide a lot of interesting information.
10. Pie charts do not display whole info (100%)
Sometimes pie charts are mistakenly used not only to demonstrate the structure of a whole but simply to compare categories – for example, average salaries by the department. The result is information about nothing. After all, the sum of average salaries by the department is not equal to the average salary at the enterprise. Instead, it is more correct to use aggregation by the number of employees, or the amount of the total payroll.
Epilogue
Graphs and charts help make sense of data and turn information into knowledge. It is very important to use this powerful tool correctly. After all, an incorrectly implemented visualization can not only slow down the perception of data but also distort it, pushing for the wrong decisions. Understanding common graphic mistakes will help you avoid them and realize the full potential of visualizations, making clear, balanced, honest graphs and diagrams.