Python library for hive plot visualizations of networks.

Joined September 2022
Hiveplotlib version 0.28 streamlined NetworkX integration plus easy access to graph metrics for drawing hive plots. Now we're excited to be part of the NetworkX documentation with their 3.7 release!
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For more on how we sped up hive plot construction and visualization, check out our blog post: hiveplotlib.readthedocs.io/s…
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For more on how Hive Plot Matrices support network exploration, check out our new tutorial: hiveplotlib.readthedocs.io/s…
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Hiveplotlib 0.27.0 is here! This release supports Hive Plot Matrices for network exploration, plus major speedups via @numba_jit and parallelization. Check out the thread below for more info.
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If you’re struggling to make your hive plot, but can’t find what you’re looking for in our docs, let us know! DM us on X or make an issue in our Gitlab repository here: gitlab.com/geomdata/hiveplot…
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From 1970-1972, Wayne W. Zachary observed a karate club split into two factions. Did they split based on friendships? With a hive plot visualization, we can quickly see that people talked more within factions, but also that the factions were not completely isolated.
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Interested in visualizing your network data with hive plots? Is your network data in a @networkx_team Graph? Check out our Creating Hive Plots from Networkx page at the link below
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Interested in visualizing your network data with hive plots? Is your network data in @pandas_dev DataFrames? Check out our Creating Hive Plots from Pandas page at the link below
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Hiveplotlib supports visualization using multiple python viz libraries, but using each plotting tool is a bit different in practice. To help users out, we added docs for each of our supported viz back ends, check it out at the link below
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Whether you want to use the default matplotlib back end, an interactive back end to explore your hive plot with hover tools, or the datashader back end for large networks, Hiveplotlib v0.26 makes the switch easy! Check out our Changing Viz Back Ends page at the link below
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