TRAC: Stream Charts

Discover the benefits of stream charts and how to use them to gain insights from your datasets.

Hassan Elgaddal avatar
Written by Hassan Elgaddal
Updated over a week ago

Learning Outcomes:

  • Gain a deeper understanding of stream charts and how to interpret them.

  • Learn about the data types Pulsar utilises for visualisation purposes.


What is a Stream Chart?

The Stream Chart, a close relative of the Area Chart, has a unique feature that sets it apart. Unlike an Area Chart, a Stream Chart displays data around a fluctuating central baseline, offering a more dynamic visualisation.

In a Stream Chart, individual categories are depicted as coloured areas flowing along a horizontal axis representing time. At any given moment, the area of a category's stream reflects the magnitude of its value. Stacked areas of all categories form a flowing, layered visualisation, revealing overall data trends.

You can find Stream Charts within the following pages in TRAC:


What Insights Can you Gain from Stream Charts?

  • Stream Charts offer exceptional visualisations, enabling you to grasp how Topics, Keywords, Hashtags, or Entities are evolving over time within your searches.

  • By hovering over the Stream Chart on a specific date, you can identify trending keywords within your search, along with their respective volumes.

  • Stream Charts also allow you to spot any notable peaks for keywords.

πŸ’‘Top Tip: You have the option to refine data to concentrate on particular keywords, topics, hashtags, and entities that are trending in your search. This feature is beneficial if there are any data points that you wish to exclude from your Stream Chart.

In the example provided below, you can observe that the term "Overwatch" has been removed since it pertains to the name of a video game and is therefore not likely to provide us with much insight as it will always be prevalent in the online conversations related to this search. Consequently, we utilised the "edit data" function to eliminate this keyword from the visualisation.


We hope you enjoyed reading this article! πŸ“š

If you have any questions or would like to learn more, please don't hesitate to reach out to our support team via live chat. πŸš€

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