Skip to main content

A package for organizing matplotlib plots.

Project description


PyPI version Build Status Documentation Status codecov

Grid-strategy is a python package that enables the user organize matplotlib plots using different grid strategies.


This package would add a mechanism for creating a grid of subplots based on the number of axes to be plotted and a strategy for how they should be arranged, with some sensible strategy as the default.

Detailed Description

It is often the case that you have some number of plots to display (and this number may be unknown ahead of time), and want some sensible arrangement of the plots so that they are all roughly equally aligned. However, the subplots and gridspec methods for creating subplots require both an x and a y dimension for creation and population of a grid. This package would allow users to specify a strategy for the creation of a grid, and then specify how many axes they want to plot, and they would get back a collection of axes arranged according to their strategy.

A proof of concept was implemented for the 'squarish' strategy, which arranges plots in alternating rows of x and x-1 objects. Some examples featuring this technique:

n=6 n=7

n=8 n=17

This makes use of a GridStrategy object, which populates a GridSpec. In general, this concept can likely be implemented as a layer of abstraction above gridspec.GridSpec.

Some basic strategies that will be included in the first release:

  • "Squarish" (name subject to change) - As implemented in the demo code above - currently this is centered, but the base SquarishStrategy object could have options like justification which could include:
    • 'center' (default), 'left', 'right' - empty spaces either center the plots or leave them ragged-left or ragged-right
    • 'fill-space' and fill-grow' (names subject to change) - These would fill every column as "fully-justified", with fill-space increasing the interstitial space and fill-grow modifying the width of the plots themselves to fill the row.
  • "Rectangular" - Similar to "Squarish", this would find the largest pair of factors of the number of plots and use that to populate a rectangular grid - so 6 would return a 3x2 grid, 7 would return a 7x1 grid, and 10 would return a 5x2 grid.

Since many of these grid strategies would likely have at least some asymmetries, a mechanism for transposing any grid structure should be implemented in the base GridStrategy object.

Higher dimensions

Currently the package is limited to 2-dimensional grid arrangements, but a "nice-to-have" might be a higher-order API for GridStrategy that also allows for the proliferation of additional figures (e.g. "if I have more than 10 axes to plot, split them up as evenly as possible among n / 10 different figures"). This would be no harder to implement in terms of the creation of such strategies, but may be harder to work with since it would necessarily spawn axes across multiple figures.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

grid-strategy-0.0.1.tar.gz (17.2 kB view hashes)

Uploaded source

Built Distribution

grid_strategy-0.0.1-py3-none-any.whl (11.2 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page