Data Visualization – How to Choose the Right Chart?
Now you get a data table from your boss, what are you going to do to process the data and make your boss satisfied?
From Excel Easy
Using the pivot table or Excel chart to show them better? It’s maybe a good idea, but this may take a lot of time… What about this?
Let’s look at the following dashboard together. Isn’t it very cool? How many types of charts can you name?
Manufacturing Command Room Made by FineReport
What is the best way for others to understand your data? For me, it’s data visualization. You have to admit that the above dashboard makes the data vivid and clear, much stronger than Excel.
Now you know the charm of data visualization. However, how to choose the right chart to show your data is the most important thing. If you choose the wrong chart, it may give others some misunderstandings.
Next, I will teach you how to choose the right chart from my prospect of view.
Choosing the Right Chart to Make Data Visualization
I will tell you the top 8 types of charts and their points for attention.
Ramification – Stacked Column Chart
Advantages: The column chart uses the height of the column to clearly reflect the difference in data. In general, it is used to reflect the comparison between classified items, and it can also be used to reflect the time trend.
Note: The limitation of the column chart is that it is only suitable for small and medium-sized data sets, and it is not easy to distinguish when there is more data. Generally speaking, no more than 10.
Generally speaking, the horizontal axis of the bar chart is the time dimension, and users habitually believe that there is a time trend. If the horizontal axis is not a time dimension, it is recommended to distinguish each column by color.
Advantages: Line charts are used to reflect trends over time. This graph is often used when we need to describe the change of things with time dimension. Line charts are great for data comparing.
Ramification – Area Chart
Fill the shadow below the line chart to form an area chart. If there are two or more line charts, fill in the shades of different colors below the respective line to form a stacked area chart to facilitate understanding the relative proportion of the line chart.
Note: The pie chart is a chart that should be avoided because the naked eye is not sensitive to the size of the area. But when it reflects a specific gravity, it will have a better effect if it is matched with a specific value.
When you need to compare data, especially when comparing more than two whole components, be sure to use a bar chart or a column chart. Do not ask the person who reads the picture to convert the fan shape into data and compare them in the pie charts. Cause the human eye is insensitive to the size of the area, it may cause misreading of the data.
In addition, in order to maximize the effect of the pie chart, it should generally not exceed 6 parts in use. If you need to express more than 6 parts, please also use a bar chart. It will be clearer.
By the way, you may have seen the following chart – rose chart, it is beautiful while it is perhaps the most confusing chart, you should know that most data can’t be made into a beautiful rose chart, data often needs to be indexed to form a more beautiful rose chart.
The data of the scatter plot is three-dimensional data. Two sets of data are used to form multiple coordinate points. The distribution of the coordinate points is analyzed to determine the association or distribution trend between the two variables.
The series can be distinguished by color, or the third dimension can be determined by the size of the scatter point, which leads to the bubble chart.
The bubble chart is a derivative of the scatter chart. The third dimension is measured by the area of each point. It is suitable for the comparison of three-dimensional data, and the third dimension needs to be emphasized. It is not applicable if it exceeds three dimensions.
The radar chart is suitable for multi-dimensional data (more than four dimensions), and each dimension must be sortable. There are usually about 6 data points. If there are too many data points, it is difficult to distinguish them.
Word Cloud Chart
The word cloud chart mainly displays text information, and visually highlights “keywords” that appear frequently, and is often used to compare the frequency of text occurrences. Such as user portrait tags, search keyword frequency, news keyword frequency.
Geographic maps can be used for all analyses related to spatial attributes. For example, the sales volume in various regions, or the density of shops in a commercial area. The color depth or bubble size is generally used to show the numerical value of the area. For example, population density, sales volume by region, or store density in a commercial area.
Maps are very attractive data visualization in these charts.
It is often used to analyze the path of user churn and is a very practical chart.
Four Basic Principles of Data Visualization
Finally, if you wanna make a dashboard, you should know the 4 basic principles of design.
Although it’s very basic, follow them and I am sure you can make beautiful data visualization. Just like this
You can roughly understand how to choose the appropriate chart according to your data from this article. Only the data visualization with practical significance can really bring out the value of the data.
All charts in this article come from FineReport, the personal version is completely free.