VChart 1.12.11
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VChart Story Teller

Not only an out-of-the-box multi-terminal chart library, but also a vivid and flexible data storyteller.

VTable Checkered Artist

Not only a high-performance multi-dimensional data analysis form, but also a grid artist created between rows and columns.

VGrammar Data Magician

It is not only a visual grammar that generates thousands of charts, but also a data magician who turns boring into magic.

VRender Visual Rendering

Not only a visual rendering engine with rich functions, but also a handy pen.

VMind Smart Visualization Suit

Not just automatic, but also fantastic.

VStory Relationship Explorer plus

It is not only a fully functional graph visualization library, but also an explorer of data relationships.

!!!###!!!title=Social Media Seuqnce Chart——VisActor/VChart demo!!!###!!!!!!###!!!description=The high complexity of time-series data makes it difficult for analysts to manually explore and find patterns, leading to an increasing need for visualization techniques to aid analysis in order to extract and communicate insights from event sequence datasets. For social media information, it is often necessary to show the different behaviors of different users at different times in the form of nodes and edges in the evolution of linear time, and in order to better discover the user's behavior preferences, it is also necessary to use histograms. The form of behavioral statistics is displayed. Time series diagrams based on linear time maps can show data in this scenario.!!!###!!!

Social Media Seuqnce Chart

Name
Sequence Chart
Target
Comparison
Shape
Line
Scatter
Rectangle
Component
Data Zoom

mobile

The high complexity of time-series data makes it difficult for analysts to manually explore and find patterns, leading to an increasing need for visualization techniques to aid analysis in order to extract and communicate insights from event sequence datasets. For social media information, it is often necessary to show the different behaviors of different users at different times in the form of nodes and edges in the evolution of linear time, and in order to better discover the user's behavior preferences, it is also necessary to use histograms. The form of behavioral statistics is displayed. Time series diagrams based on linear time maps can show data in this scenario.

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