A simple JavaScript library for drawing line, bar, area, and donut charts with a focus on time-series data.
Morris.js is a JavaScript charting library that enables developers to create pretty, interactive line, bar, area, and donut charts for time-series data. It solves the problem of quickly embedding functional, aesthetically pleasing graphs into web applications without requiring extensive configuration or heavy dependencies.
Frontend developers and web designers who need to integrate simple, interactive charts into websites or applications, particularly those working with time-based data visualization.
Developers choose Morris.js for its dead-simple API, lightweight footprint, and attractive default styling, making it an ideal choice for projects that require straightforward charting without the complexity of larger libraries like D3.js.
Pretty time-series line graphs
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The API is minimal and easy to use, allowing developers to create charts quickly with just a few lines of code, as highlighted in the project's philosophy prioritizing simplicity.
Charts are visually appealing out-of-the-box with interactive hover details, making them engaging without requiring extensive customization, a key feature mentioned in the description.
Optimized for chronological data with automatic date handling, simplifying the visualization of trends like website traffic or sales, as noted in the Key Features.
Includes a setData method to update charts with new data without full redraws, improving performance for live data scenarios, which is explicitly listed in the features.
The library hasn't been updated since 2014, with the author noting in the README that they are not actively supporting it, leading to potential bugs and lack of modern features.
Requires jQuery and Raphael.js, adding significant overhead and compatibility issues for projects using modern, lightweight frameworks or vanilla JavaScript.
Only supports line, bar, area, and donut charts, lacking common options like pie, scatter, or radar charts, which restricts its usefulness for diverse data visualization needs.