Choose a Visualization Type

Choosing the right visualization type is one part science and one part art. If you found Superchart, it's likely this isn't your first data visualization rodeo. You probably already know the aspects of the visualization you'd like to create.

If not, here are some loose recommendations to consider.

  • if your data is in a time series trying to show trends over time, start with a line or column chart; 
  • if your data is in categories, try a column or bar chart; 
  • Use tables and pivot tables to show raw data sets and data summaries, but keep them small.

Here are the five visualization types in Superchart and an embedded example of each:


When you just need to show raw data or a subset of raw data, nothing beats a well-formatted table. Tables can be easy to scan when comparing values. They can also add detail when paired with other, more visual charts and graphs.

Pivot Table

Pivot tables are key to any quick data analysis. Pivot tables can be useful in summarizing data for an audience, especially when categories and sub-categories provide greater detail or insight. Pivot tables are very friendly and descriptive for the information consumer.

Line Chart

Line graphs are popular among data analysts. They show how values change over time and how trends emerge or decline, making it easier to identify patterns within the data set. Line graphs are especially useful when tracking multiple values that may be related to one another in some way, such as inventory levels versus customer purchases.

Bar Chart

The most commonly used type of graph is the bar chart (or its sibling, the column chart), which is used to compare categories or groups within a data set. Bar charts are often used to track how different variables interact with one another, such as changes in sales over time. A bar chart has the data shown as bars that go side-to-side (horizontal).


A column chart has the data shown as columns that go up and down (vertical). Column charts provide many of the same benefits as bar charts, making it easy to understand categories visually and how those categories interact with another variable.

More visualization types to come. For details on configuring visualizations, check out additional articles in the knowledge center.

Last Updated
March 6, 2023