Polychart2.js is an easy-to-use yet powerful JavaScript graphing library. It takes many ideas from the Grammar of Graphics and the R library ggplot2, and adds interactive elements to take full advantage of the web.
Charts are defined in Polychart2 by providing a combinations of
- one or more layers, defining the "mark" or "chart type" to be used
- one or more aesthetic mappings, defining which data columns will map to which visible features like position or color (these are known as aesthetics)
- scales, definining how data columns will map to aesthetics (e.g. linear or log scale? what numeric values map to which colour?)
- coordinates, defining which coordinate sytem to plot the chart in (typically cartesian or polar)
The full list of supported layers, aesthetics, scales and coordinates and how they are specified can be found in the documentations.
The Polychart2 library can perform simple statistical calculations based on
existing data. For example, it is possible to plot the total number of sales
per region by assigning the x-mapping to region and y-mapping to
sum(sales).
These statistical calculations can happen in the front-end, right in the browser, can be done in the backend with a server that can communicate with the front end.
The full list of supported operations and integration details are provided in the documentations.
Charts created by Polychart2 is interactive by nature, and uses an event-based model for interaction. Events are thrown when the underlying data changes, or when a user interacts with the chart. Charts can be modified as a response to events. See the documentations for more details.
- polychart2.js - The full version of Polychart2.js
- polychart2.min.js - The minified version of Polychart2.js
- polychart2.standalone.js - The minified version, including dependencies
Polychart2.js uses the following libraries internally.
Other libraries in the lib/ directory are included for the test and example scripts.
When developing locally, note that your browser may enforce strict permissions for reading files out of the local file system. Additionally for testing backend data processing functionalities, server database querying functionalities are used. For those examples, a tornado server and a sqlite3 database is included. To run the server run:
python server.py
Once this is running, go to http://localhost:8888/.
MIT