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DOC: modernize lifecycle tutorial with annotate and bar_label#31364

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manasvi-sahare wants to merge 3 commits intomatplotlib:mainfrom
manasvi-sahare:doc-lifecycle-modernize
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DOC: modernize lifecycle tutorial with annotate and bar_label#31364
manasvi-sahare wants to merge 3 commits intomatplotlib:mainfrom
manasvi-sahare:doc-lifecycle-modernize

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This PR updates the lifecycle tutorial to improve clarity and align with modern Matplotlib practices.
Changes:

@github-actions github-actions bot added the Documentation: tutorials files in galleries/tutorials label Mar 24, 2026
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Thanks for your willingness to contribute to Matplotlib.

I'm not convinced these changes improve the document, and some aspects seem questionable. I’d lean against accepting this in its current form.

I’ll mark this for autoclose for now, but happy for others to weigh in or override.

fig, ax = plt.subplots()
ax.barh(group_names, group_data)
bars = ax.barh(group_names, group_data)
ax.bar_label(bars, padding=3)
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I don't think labelling the bar is of particular use here.

There are a subsequent 6 other plots with this same barplot, so why only label the second one?

I'm not in favour of this change.

for group in [3, 5, 8]:
ax.text(145000, group, "New Company", fontsize=10,
verticalalignment="center")
ax.annotate("New Company",
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Similarly, I don't think this is an improvement.

@jklymak jklymak added the status: autoclose candidate PRs that are not yet ready for review and may be automatically closed in two weeks label Mar 28, 2026
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⏰ This pull request might be automatically closed in two weeks from now.

Thank you for your contribution to Matplotlib and for the effort you have put into this PR. This pull request does not yet meet the quality and clarity standards needed for an effective review. Project maintainers have limited time for code reviews, and our goal is to prioritize well-prepared contributions to keep Matplotlib maintainable.

Matplotlib maintainers cannot provide one-to-one guidance on this PR. However, if you ask focused, well-researched questions, a community member may be willing to help. 💬

To increase the chance of a productive review:

As the author, you are responsible for driving this PR, which entails doing necessary background research as well as presenting its context and your thought process. If you are a new contributor, or do not know how to fulfill these requirements, we recommend that you familiarize yourself with Matplotlib's development conventions or engage with the community via our Discourse or one of our meetings before submitting code.

If you substantially improve this PR within two weeks, leave a comment and a team member may remove the status: autoclose candidate label and the PR stays open. Cosmetic changes or incomplete fixes will not be sufficient. Maintainers will assess improvements on their own schedule. Please do not ping (@) maintainers.

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