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Matplotlib: Visualization with Python

Authors: The Matplotlib Development Team;

Matplotlib: Visualization with Python

Abstract

Highlights of this release include: - Preliminary support for free-threaded CPython 3.13 - Standard getters/setters for axis inversion state - New more-accessible color cycle - Dark-mode diverging colormaps - Exception handling control - InsetIndicator artist - FillBetweenPolyCollection - Fill between 3D lines - Data in 3D plots can now be dynamically clipped to the axes view limits - Rotating 3d plots with the mouse - Increased Figure limits with Agg renderer - Subfigures no longer provisional - Subfigures are now added in row-major order

If Matplotlib contributes to a project that leads to a scientific publication, please acknowledge this fact by citing J. D. Hunter, "Matplotlib: A 2D Graphics Environment", Computing in Science & Engineering, vol. 9, no. 3, pp. 90-95, 2007.

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download
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
64
Top 1%
Top 10%
Top 1%
238
4
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