8000 adding a diverging bar example to the horizontal bar documentation by rl-utility-man · Pull Request #4994 · plotly/plotly.py · GitHub
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adding a diverging bar example to the horizontal bar documentation #4994

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Merged
merged 12 commits into from
Apr 17, 2025
Merged

adding a diverging bar example to the horizontal bar documentation #4994

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3a3b7a8
Update horizontal-bar-charts.md
SimaRaha Jan 25, 2025
6c2426a
Rob's edits
rl-utility-man Jan 27, 2025
0bac79d
Merge branch 'master' into patch-2
rl-utility-man Feb 6, 2025
aa96405
switched from hard coded data to a df.read_csv from github
rl-utility-man Mar 16, 2025
be0a29e
separated update_xaxes from update_layout
rl-utility-man Mar 16, 2025
28aa4f3
removed the (irrelevant) neutral category
rl-utility-man Mar 26, 2025
6b70a42
removed unneeded comment
rl-utility-man Mar 26, 2025
ebece08
Update doc/python/horizontal-bar-charts.md
rl-utility-man Mar 31, 2025
a67ec54
removing extra sentence
rl-utility-man Mar 31, 2025
de7f742
Merge branch 'main' into patch-2
LiamConnors Apr 8, 2025
efc4316
Moved language from #4984 per suggestion of @LiamConnors
rl-utility-man Apr 9, 2025
be3b500
Update horizontal-bar-charts.md
rl-utility-man Apr 14, 2025
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removing extra sentence 
Co-authored-by: Liam Connors <connorsl@tcd.ie>
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@rl-utility-man @LiamConnors
rl-utility-man and LiamConnors authored Mar 31, 2025
commit a67ec5420868262498ba270856059a61355a86aa
2 changes: 1 addition & 1 deletion doc/python/horizontal-bar-charts.md
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Expand Up @@ -219,7 +219,7 @@ fig.show()

### Diverging Bar (or Butterfly) Chart

Diverging bar charts show counts of positive outcomes or sentiments to the right of zero and counts of negative outcomes to the left of zero, allowing the reader to easily spot areas of excellence and concern. Implementing presentation-ready versions of them in Plotly requires a few non standard layout and legendrank options.
Diverging bar charts show counts of positive outcomes or sentiments to the right of zero and counts of negative outcomes to the left of zero, allowing the reader to easily spot areas of excellence and concern.

```python
import plotly.graph_objects as go
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