Hacktoberfest 2026: the issues maintainers tagged for October, open and beginner-friendly. Browse Hacktoberfest issues

Excessive white space / margins with some plots.

Open
#586 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Assessment

Difficulty
4/5
Estimated time
3-5 days
Newbie friendliness
35/100
Issue type
Bug
Clarity
Mostly clear
Activity status
Stale
Tech stack
jupyter-notebook, python

Research direction

Start by running the two provided examples with %matplotlib ipympl and %matplotlib inline, including the constrained layout and aspect settings. Compare the resulting margins and trace the ipympl figure rendering and layout behavior. Done means the ipympl example no longer produces excessive whitespace around the axes, including for larger figures.

Written by the indexing model from the issue text.

Description

With the current ipympl 0.9.6 (and probably earlier versions) I am observing excessive white space around axes in some cases when using the %matplotlib ipympl mode but not in the %matplotlib inline mode.

A small example to reproduce:

%matplotlib ipympl
from matplotlib import pyplot as plt

fig, ax = plt.subplots(figsize=(5, 3), constrained_layout=True)
ax.imshow([[1,2,3],[4,5,6],[7,8,9]])
ax.set_aspect(0.1)

This yields:

Image

And the same example in inline mode:

%matplotlib inline
from matplotlib import pyplot as plt

fig, ax = plt.subplots(figsize=(5, 3), constrained_layout=True)
ax.imshow([[1,2,3],[4,5,6],[7,8,9]])
ax.set_aspect(0.1)

Image

Especially larger figures then became unmanageable in the ipympl backend. Setting constrained_layout or using plt.tight_layout() does not seem to influence the margins. Can this behavior be influenced?

Dominant language
Jupyter Notebook
Stars
1.7k
Forks
234
PR merge metrics
No merged PRs in 30d

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

More from matplotlib/ipympl

All issues in matplotlib/ipympl

Similar issues

More Data Visualization issues

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.