PlotJuggler
A fast, powerful, and intuitive desktop application for visualizing and analyzing time series data from files, streams, and robotics systems.
What is PlotJuggler?
PlotJuggler is a desktop application for visualizing and analyzing time series data from various sources, including files, live streams, and robotics systems. It solves the problem of efficiently exploring and transforming large time series datasets with an intuitive drag-and-drop interface and high-performance rendering.
Engineers, researchers, and developers working with time series data in fields like robotics, embedded systems, IoT, and data analysis who need a powerful, interactive visualization tool.
Developers choose PlotJuggler for its combination of ease of use, extensibility via plugins, and ability to handle massive datasets with real-time streaming support, especially in ROS and robotics ecosystems.
Overview
The Time Series Visualization Tool that you deserve.
Use Cases
Best For
- Visualizing ROS bag files and streaming ROS topics in robotics development
- Analyzing embedded system logs like PX4 ULog files from drones
- Real-time monitoring of IoT sensor data via MQTT or WebSockets
- Interactive exploration of large CSV time series datasets
- Applying mathematical transformations to time series data without coding
- Extending visualization capabilities with custom plugins for proprietary data formats
Not Ideal For
- Teams needing browser-based, collaborative dashboards for real-time team monitoring and sharing
- Data scientists requiring integrated statistical modeling or machine learning pipelines for predictive analytics
- Users seeking a simple, web-based tool for creating quick static charts without installation or heavy dependencies
Pros & Cons
Pros
Enables building complex visualizations without coding, making it accessible for engineers and researchers, as highlighted in the simple interface description.
Loads from files like CSV, ULog, and streams from MQTT, ROS, covering diverse engineering data sources, with built-in support for JSON, CBOR, and more.
Handles thousands of time series and millions of data points efficiently, crucial for real-time analysis, leveraging OpenGL for fast visualization.
Seamlessly opens ROS bags and subscribes to ROS topics for both ROS1 and ROS2, tailored for robotics development, with dedicated plugins and installation options.
Supports custom plugins for additional data sources and formats, enabling community-driven extensions, as seen in separate repositories for MQTT, LSL, and ROS.
Cons
The snap installation has noted restrictions with ROS2, requiring additional packages or source compilation for full functionality, as mentioned in the README.
Plugins are hosted in separate repositories, leading to potential integration challenges, inconsistent documentation, and added setup complexity for users.
Relies on Lua scripting for custom transforms, which may not meet advanced analytical needs without significant user effort, limiting out-of-the-box statistical functions.
Lacks web or mobile versions, limiting accessibility and collaboration for distributed teams, as it is primarily a standalone desktop tool.
Frequently Asked Questions
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kepler.glKepler.gl is a powerful open source geospatial analysis tool for large-scale data sets.
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