The first important step one can take to make a great visualization is to decide what is the goal behind the effort. Apart from it, it is also very important to know who the audience is and how this will help them.
Once the answers to these questions are known, and the purpose of visualization is well understood, the next challenge is to choose the right method to present it. The most commonly used types of visualization could further be categorized into five and summarized in the Table 2:
Table 2 different charts for data visualization. (Last update: Jun 21, 2022)
Sometimes, we need to use more than one type of graph to represent the trend and pattern of data. Though there is no standard rule of how to combine graphs into one figure, we present some examples below for some inspiration. Readers need to be first familiar with basic visualization graphs or discuss with a data scientist/specialist about the possibility of visualizing your data.
Example I: Combination of scatter plot and boxplot/violin/histogram
The original figure, with a bit messy and overlapping sample points
The revised figure, with the addition of boxplots for y-axis.
The revised figure, with the addition of violin plot for y-axis and histogram for x-axis. Besides, 3 classes are selected and shown by controlling the (interactive) legend on the right hand.