diff --git a/doc/python/horizontal-bar-charts.md b/doc/python/horizontal-bar-charts.md
index 25aa9d4f7d..52cd62f0ae 100644
--- a/doc/python/horizontal-bar-charts.md
+++ b/doc/python/horizontal-bar-charts.md
@@ -214,6 +214,107 @@ for yd, xd in zip(y_data, x_data):
fig.update_layout(annotations=annotations)
+fig.show()
+```
+### Diverging Bar (or Butterfly) Chart with Neutral Column
+
+Diverging bar charts offer two imperfect options for responses that are neither positive nor negative: omit them, leaving them implicit when the categories add to 100%, as we did above or put them in a separate column, as we do in this example. Jonathan Schwabish discusses this on page 92-97 of _Better Data Visualizations_.
+
+```
+import pandas as pd
+import plotly.graph_objects as go
+
+
+df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/refs/heads/master/gss_2002_5_pt_likert.csv')
+#data source details are in this CSV file
+df.rename(columns={'Unnamed: 0':"Category"}, inplace=True)
+
+
+#achieve the diverging effect by putting a negative sign on the "disagree" answers
+for v in ["Disagree","Strongly Disagree"]:
+ df[v]=df[v]*-1
+
+fig = go.Figure()
+# this color palette conveys meaning: blues for negative, reds for positive, gray for Neither Agree nor Disagree
+color_by_category={
+ "Strongly Agree":'darkblue',
+ "Agree":'lightblue',
+ "Disagree":'orange',
+ "Strongly Disagree":'red',
+ "Neither Agree nor Disagree":'gray',
+}
+
+
+# We want the legend to be ordered in the same order that the categories appear, left to right --
+# which is different from the order in which we have to add the traces to the figure.
+# since we need to create the "somewhat" traces before the "strongly" traces to display
+# the segments in the desired order
+
+legend_rank_by_category={
+ "Strongly Disagree":1,
+ "Disagree":2,
+ "Agree":3,
+ "Strongly Agree":4,
+ "Neither Agree nor Disagree":5
+}
+
+# Add bars
+for col in df[["Disagree","Strongly Disagree","Agree","Strongly Agree","Neither Agree nor Disagree"]]:
+ fig.add_trace(go.Bar(
+ y=df["Category"],
+ x=df[col],
+ name=col,
+ orientation='h',
+ marker=dict(color=color_by_category[col]),
+ legendrank=legend_rank_by_category[col],
+ xaxis=f"x{1+(col=="Neither Agree nor Disagree")}", # in this context, putting "Neither Agree nor Disagree" on a secondary x-axis on a different domain
+ # yields results equivalent to subplots with far less code
+ )
+)
+
+# make calculations to split the plot into two columns with a shared x axis scale
+# by setting the domain and range of the x axes appropriately
+
+# Find the maximum width of the bars to the left and right sides of the origin; remember that the width of
+# the plot is the sum of the longest negative bar and the longest positive bar even if they are on separate rows
+max_left = min(df[["Disagree","Strongly Disagree"]].sum(axis=1))
+max_right = max(df[["Agree","Strongly Agree"]].sum(axis=1))
+
+# we are working in percent, but coded the negative reactions as negative numbers; so we need to take the absolute value
+max_width_signed = abs(max_left)+max_right
+max_width_neither = max(df["Neither Agree nor Disagree"])
+
+fig.update_layout(
+
+ title="Reactions to statements from the 2002 General Social Survey:",
+ plot_bgcolor="white",
+ barmode='relative', # Allows bars to diverge from the center
+ )
+fig.update_xaxes(
+ zeroline=True, #the zero line distinguishes between positive and negative segments
+ zerolinecolor="black",
+ #starting here, we set domain and range to create a shared x-axis scale
+ # multiply by .98 to add space between the two columns
+ range=[max_left, max_right],
+ domain=[0, 0.98*(max_width_signed/(max_width_signed+max_width_neither))]
+)
+fig.update_layout(
+ xaxis2=dict(
+ range=[0, max_width_neither],
+ domain=[(1-.98*(1-max_width_signed/(max_width_signed+max_width_neither))), 1.0],
+ )
+)
+fig.update_legends(
+ orientation="h", # a horizontal legend matches the horizontal bars
+ yref="container",
+ yanchor="bottom",
+ y=0.02,
+ xanchor="center",
+ x=0.5
+)
+
+fig.update_yaxes(title="")
+
fig.show()
```
@@ -260,7 +361,7 @@ fig.append_trace(go.Scatter(
), 1, 2)
fig.update_layout(
- title='Household savings & net worth for eight OECD countries',
+ title=dict(text='Household savings & net worth for eight OECD countries'),
yaxis=dict(
showgrid=False,
showline=False,
@@ -335,4 +436,4 @@ fig.show()
### Reference
-See more examples of bar charts and styling options [here](https://plotly.com/python/bar-charts/).
See https://plotly.com/python/reference/bar/ for more information and chart attribute options!
\ No newline at end of file
+See more examples of bar charts and styling options [here](https://plotly.com/python/bar-charts/).
See https://plotly.com/python/reference/bar/ for more information and chart attribute options!