Why do most people make charts that are just a piece of crap?

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Data visualization is a powerful tool for clearly articulating complex information data.

Through visual information, our brains can more effectively synthesize and retain information content, enhancing the understanding of information. But if the data is not visualized correctly, it may do more harm than good. The wrong chart can reduce the information of the data, or worse, the exact opposite!

This is why perfect data visualization is extremely dependent on design.

Designers to do, not only choose the right chart type, but also in an easy to understand the way to present information, design a more intuitive navigation system, so that the audience to do as much as possible to reduce the trouble of understanding, to do at a glance.

Of course, not all designers are data visualization experts, which is why most of the charts look so bad, it's a piece of crap!

Here are 10 examples of data visualization, including the mistakes you may make and how to quickly fix remediation.

Error 1: Confusing pie chart segmentation

Pie chart, is one of the simplest charts. But someone likes to make it very complicated.

The pie chart should be designed intuitively and clearly, and in theory a pie chart should not be split over 5 blocks. Here are two ways to focus your attention instantly on the point you want to express.

The first type: Place the largest part at the 12 o'clock Azimuth, clockwise. The second part 12 o'clock, counterclockwise direction. The rest of the section can be placed below and continue counterclockwise.

Method Two: The largest piece starts 12 o'clock and rotates clockwise. The remaining parts are arranged in descending order, clockwise.

Error 2. Using incoherent lines in a line chart

Dashed lines, dotted lines are easy to distract. Instead, using solid lines and colors makes it easy to differentiate between each other.

Error 3: Data sorting is confusing

Your content should guide the reader in a logical and intuitive way to understand the data. So, remember to sort the data categories alphabetically, in order of size, or in value.

Error 4: Data blurred

Make sure no data is lost or designed. For example, when you use a standard area chart, you can add transparency to ensure that all the data is visible to the reader.

Error 5: Let the reader interpret it himself

The designer should make the chart as easy as possible to help the reader understand the data. For example, a trend line is added to the scatter plot to emphasize the trend.

Error 6. Distort data

Make sure that all visualizations are accurate. For example, the bubble chart size should be expanded by region, not diameter.

ERROR 7. Use different colors on a single thermal map

The color used too much, will give the data to increase the unbearable weight, on the contrary, designers should use the same color, or analogy.

Error 8. Bar chart too fat or too thin

Perhaps your report is very creative, very exciting, but remember the level of graphic design to keep up. The interval between bars should be 1/2 column width.

Error 9: It is difficult to compare data

Comparisons are a good way to show differences in data, but if your readers are not easy to see the difference, then your comparison is meaningless. Make sure that all the data is presented in front of the reader, choosing the most appropriate comparison method.

Error 10: Using a 3D chart

Although they look cool, the 3d shape distorts the perception and therefore distorts the data. Adhere to the 2-dimensional to ensure accurate data.

How about the above 10, have you been shot?

Why do most people make charts just a piece of crap?