Figure does not show without explicit plt.show()

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Under some circumstances when using ipympl the figure does not show up in the output area unless plt.show() is explicitly called.

At the moment the reproduction is a bit finicky. As a minimal example these cells, when executed once show a nice empty plot:

%matplotlib widget

from matplotlib import pyplot as plt
import pandas as pd
from io import StringIO

fig, axes = plt.subplots(figsize=(6, 5.5))

s = """1,2,3
1,2,3"""
csv = StringIO(s)
df = pd.read_csv(csv)

# with this it always works:
# plt.show()

When changing the line to read a more complex dataset df = pd.read_csv(file_with_1MB) the empty figure sometimes does not show up anymore. If I add an explicit plt.show() at the end the figure always appears as normal.

It is not directly tied to the larger data file though, even the example above sometimes shows the same behavior after the second cell is re-executed several times. When using %matplotlib inline no issues or errors occur.

I am somewhat certain that this behavior is a regression, as it was not occurring in earlier versions of the Jupyterlab/ipympl ecosystem (with Jupyterlab/ipympl older than approximately six months ago).

Any hints how to debug this a bit better would be appreciated.

Versions

This issues occurs with a recent jupyterlab / ipympl installation (and using Chrome 142.0.7444.60). Here, this is on Windows 11 but the issue also occurs on Linux systems.

 3.13.9 | packaged by conda-forge | (main, Oct 22 2025, 23:12:41) [MSC v.1944 64 bit (AMD64)]
ipympl version: 0.9.8

Selected Jupyter core packages...
IPython          : 9.7.0
ipykernel        : 7.1.0
ipywidgets       : 8.1.8
jupyter_client   : 8.6.3
jupyter_core     : 5.9.1
jupyter_server   : 2.17.0
jupyterlab       : 4.4.10
nbclient         : 0.10.2
nbconvert        : 7.16.6
nbformat         : 5.10.4
notebook         : 7.4.4
qtconsole        : not installed
traitlets        : 5.14.3

C:\tools\miniconda3\Library\envs\jupyter\share\jupyter\labextensions
        jupyter-matplotlib v0.11.8 enabled ok
        jupyterlab_pygments v0.3.0 enabled ok (python, jupyterlab_pygments)
        @jupyter-notebook/lab-extension v7.4.7 enabled ok
        @jupyter-widgets/jupyterlab-manager v5.0.15 enabled ok (python, jupyterlab_widgets)
        @mbektas/notebook-intelligence v1.1.2 enabled ok (python, notebook_intelligence)

まず、%matplotlib widget を使った2つのノートブックセルを、レポートに記載されたより大きなCSVと繰り返し実行を含めて再現し、%matplotlib inline と比較します。ペイロードにはリポジトリのファイル名やテストの記載がありません。明示的な plt.show() の呼び出しなしにインタラクティブな図が確実に表示されれば完了です。