Qgrid is an IPython extension which uses SlickGrid to render pandas DataFrames within an IPython notebook. It's being developed for use in Quantopian's hosted research environment, and this repository holds the latest source code.

• SlickGrid is an an advanced javascript grid which allows users to scroll, sort, and filter hundreds of thousands of rows with extreme responsiveness.
• Pandas is a powerful data analysis / manipulation library for Python, and DataFrames are the primary way of storing and manipulating two-dimensional data in pandas.

Qgrid renders pandas DataFrames as SlickGrids, which enables users to explore the entire contents of a DataFrame using intuitive sorting and filtering controls. It's designed to be used within IPython notebook, but it's also fully functional when rendered in nbviewer.

See the demo by viewing qgrid_demo.ipynb in nbviewer.

Installation instruction can be found in the same notebook as the demo, qgrid_demo.ipynb.

Read the full API documentation on readthedocs.

IPython notebook has a standard way of implementing purely client-side extensions, which involves placing the extension in the nbextensions folder and configuring IPython notebook to load it. These "nbextensions" are able to respond to Javascript events that they're given access to through IPython notebook's Javascript API, and the examples I've seen tend to run some javascript once when the notebook is initialized. For example, I've seen nbextensions that add a button to the notebook toolbar or create a floating table of contents.

Initially I was expecting that qgrid would be an nbextension because it's basically just a Javascript grid. That turned out to mostly incorrect, and qgrid ended up being implemented as a python package that contains an nbextension.

• Qgrid needs to run Javascript at the time of cell execution rather than notebook startup.
  • In particular, when show_grid gets called from a cell in an IPython notebook, qgrid needs to be able to inject HTML and Javascript into the DOM.
• Qgrids are generated through a python API (i.e. the show_grid function), so there has to be some python code in the extension, for the purpose of providing that API.

• Qgrid includes a bunch of Javascript/CSS files and %install_ext was designed for the case of installing an extension that consists of a single python file.
  • pip is more well suited for the task of distributing a package with dependencies.
• Qgrid's API is a python module, so it makes sense for it to be distributed with pip, like any other python module.

• The qgrid python package can be installed using pip, and the qgrid module can be imported using import qgrid
• The qgrid module includes an nbinstall function for installing qgrid's Javascript/CSS dependencies. When nbinstall is run, the qgrid module copies it's Javascript/CSS folder into the nbextensions folder, effectively deploying it as an nbextension.
• The qgrid module also contains show_grid, which is the function that actually generates a qgrid from a DataFrame. The show_grid function generates the qgrid by returning a custom object with its _ipython_display_ function overridden. I learned about this strategy from the "Custom Display Logic" sample notebook provided with the IPython git repository, found here on GitHub.