If data visualizations are central to understanding data analysis, choosing the type of chart is even more important. The various options display information in different ways, with advantages and disadvantages.

When it comes to data visualization, graphics are a central point. The first thing to take into account before choosing the visual tool is the objective: What story is that data trying to tell? Looking for trends? Compare variables? This is the first premise the graphic must be in tune with the storytelling. 

The second point is to be clear to whom those results will be shown. It is not the same to show data to a general public than to a public specialized in the subject in question or to people trained in statistics or data. 

data size it will also significantly affect the chart type, since some of them are not intended for use with big data sets. For example, pie charts work best with a small number of data sets; however, if you are using a significant number of them, it will make more sense to use scatterplot-style graphics.

There is various types of data, which also conditions the choice. For example, if you have continuous data, a bar chart might not be the best choice, but a line chart might. Similarly, if the data is categorical, then using a bar chart or pie chart may be more convenient.

The other point is How the different data elements are related. Are there variables such as time, size, type? Are they a time series? Is it a distribution? 

One of the most common uses when it comes to data visualization is show the change in value of a variable over time. These graphs usually have time on the horizontal axis, moving from left to right, with the values of the variable of interest on the vertical axis. In these cases, bar charts or line charts are usually the most appropriate.

Other times, what is sought is understand how a whole is made up. In these cases, the pie chart and donut chart or a stacked bar or stacked area chart can be very useful because the components are in the foreground.

If what you are looking for is compare values between different data sets, again a bar chart or a line chart works, as well as a dot plot or a clustered bar chart.

If the goal is understand the relationship between data features to observe trends and patterns among them, scatterplots are the standard way to show the relationship between two variables. If there are additional variables, bubble charts can represent them well.

It is important to be able to experiment with different types of graphs and see how the data is displayed in each case and in relation to the storytelling that you want to tell. It's also important to note that you don't need to display everything on one chart. Often, it is best to keep each individual graph as simple and clear as possible, and in any case, use multiple graphs to make comparisons, show trends, and demonstrate relationships between multiple variables.

Julio Cesar Blanco – August 22, 2022