Percent Stacked Column ChartĮach column is of equal length and totals 100%.

Further, we can also explore which part has the largest proportion, and how each part changes. If a column graph can help us observe the 'total', then the stacked bar chart can reflect the 'total' and 'structure' at the same time. Moreover, each of its values is divided into multiple sub-categories, and these sub-categories are generally referred to by different colors.

It is often used to compare values of different categories. Grouped column graphs are often used to compare data between different groups, which all contain the same category of data. The columns in each group use different colors or the same color with different transparency to distinguish each category. Similar to a column chart, the height of the columns is used to map and compare data values. When users need to display different groups under each category on the same axis, they need to use a grouped column chart. Grouped Column ChartĪ grouped column chart is also called an aggregated column graph. Fit to show the proportion of each variable in the same category. Compare the difference between the variables of the same category and the sum of variables of different categories.Ģ) Percent stacked column chart. Limitation: Too many categories cannot display data characteristics.ġ) Stacked column chart. Show data changes for multiple categories and comparisons between variables in the same category.Column charts are useful for comparing discrete data or showing trends over time. Used to compare the relationship of two or more variables. It is represented by a series of vertical stripes of varying heights that represent the distribution of data. Column ChartĪ column chart is a statistical graph that expresses a graph with the length of a rectangle as a variable. This article will introduce 20 commonly used graph types in turn, analyze their characteristics, applicable scenarios, and limitations, so as to help you convey the information expressed through charts more intuitively. Therefore, it is very important to use appropriate graphs to visualize data. However, the dense data is less readable and pointless.ĭata visualization can make data changes more intuitive and meaningful and can help people understand and accept data. With the development of the times, more and more data volume accumulates.

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