diff --git a/.circleci/config.yml b/.circleci/config.yml
index 3b36cc4802..14b14a0230 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -61,9 +61,9 @@ commands:
cd js
npm ci
npm run build
-
+
- when:
- condition:
+ condition:
not:
equal:
- <<parameters.pandas_version>>
@@ -315,6 +315,8 @@ jobs:
name: Install dependencies
command: |
cd doc
+ sudo apt-get update
+ sudo apt-get install rename
curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv
source .venv/bin/activate
diff --git a/doc/python/3d-axes.md b/doc/python/3d-axes.md
index b6ec1d8d3e..e6ea841403 100644
--- a/doc/python/3d-axes.md
+++ b/doc/python/3d-axes.md
@@ -6,7 +6,7 @@ jupyter:
extension: .md
format_name: markdown
format_version: '1.3'
- jupytext_version: 1.15.1
+ jupytext_version: 1.16.4
kernelspec:
display_name: Python 3 (ipykernel)
language: python
@@ -114,7 +114,7 @@ fig = make_subplots(rows=2, cols=2,
print_grid=False)
for i in [1,2]:
for j in [1,2]:
- fig.append_trace(
+ fig.add_trace(
go.Mesh3d(
x=(60*np.random.randn(N)),
y=(25*np.random.randn(N)),
diff --git a/doc/python/bar-charts.md b/doc/python/bar-charts.md
index f16955a93b..543b1563e3 100644
--- a/doc/python/bar-charts.md
+++ b/doc/python/bar-charts.md
@@ -124,7 +124,7 @@ import plotly.express as px
df = px.data.gapminder().query("continent == 'Oceania'")
fig = px.bar(df, x='year', y='pop',
hover_data=['lifeExp', 'gdpPercap'], color='country',
- labels={'pop':'population of Canada'}, height=400)
+ labels={'pop':'population of Oceania'}, height=400)
fig.show()
```
diff --git a/doc/python/histograms.md b/doc/python/histograms.md
index 78eab47193..aca2c25b3d 100644
--- a/doc/python/histograms.md
+++ b/doc/python/histograms.md
@@ -6,9 +6,9 @@ jupyter:
extension: .md
format_name: markdown
format_version: '1.3'
- jupytext_version: 1.14.1
+ jupytext_version: 1.16.4
kernelspec:
- display_name: Python 3
+ display_name: Python 3 (ipykernel)
language: python
name: python3
language_info:
@@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.8.8
+ version: 3.11.10
plotly:
description: How to make Histograms in Python with Plotly.
display_as: statistical
@@ -438,12 +438,12 @@ trace5 = go.Histogram(x=x,
autobinx = False
)
-fig.append_trace(trace0, 1, 1)
-fig.append_trace(trace1, 1, 2)
-fig.append_trace(trace2, 2, 1)
-fig.append_trace(trace3, 2, 2)
-fig.append_trace(trace4, 3, 1)
-fig.append_trace(trace5, 3, 2)
+fig.add_trace(trace0, 1, 1)
+fig.add_trace(trace1, 1, 2)
+fig.add_trace(trace2, 2, 1)
+fig.add_trace(trace3, 2, 2)
+fig.add_trace(trace4, 3, 1)
+fig.add_trace(trace5, 3, 2)
fig.show()
```
diff --git a/doc/python/horizontal-bar-charts.md b/doc/python/horizontal-bar-charts.md
index ae9b02e3d3..3a5070f9bc 100644
--- a/doc/python/horizontal-bar-charts.md
+++ b/doc/python/horizontal-bar-charts.md
@@ -5,10 +5,10 @@ jupyter:
text_representation:
extension: .md
format_name: markdown
- format_version: '1.1'
- jupytext_version: 1.1.1
+ format_version: '1.3'
+ jupytext_version: 1.16.4
kernelspec:
- display_name: Python 3
+ display_name: Python 3 (ipykernel)
language: python
name: python3
language_info:
@@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.6.7
+ version: 3.11.10
plotly:
description: How to make horizontal bar charts in Python with Plotly.
display_as: basic
@@ -217,6 +217,77 @@ fig.update_layout(annotations=annotations)
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. This example allows the reader of the graph to infer the number of people offering a neutral response because the neutral category, which is left implicit, would make the responses add to 100%.
+
+```python
+import plotly.graph_objects as go
+import pandas as pd
+
+
+df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/refs/heads/master/gss_2002_5_pt_likert.csv')
+
+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 positive, red and orange for negative
+color_by_category={
+ "Strongly Agree":'darkblue',
+ "Agree":'lightblue',
+ "Disagree":'orange',
+ "Strongly Disagree":'red',
+}
+
+
+# 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,
+}
+# Add bars for each category
+for col in ["Disagree","Strongly Disagree","Agree","Strongly Agree"]:
+ 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]
+ ))
+
+fig.update_layout(
+ title="Reactions to statements from the 2002 General Social Survey:",
+ yaxis_title = "",
+ barmode='relative', # Allows bars to diverge from the center
+ plot_bgcolor="white",
+)
+
+fig.update_xaxes(
+ title="Percent of Responses",
+ zeroline=True, # Ensure there's a zero line for divergence
+ zerolinecolor="black",
+ # use array tick mode to show that the counts to the left of zero are still positive.
+ # this is hard coded; generalize this if you plan to create a function that takes unknown or widely varying data
+ tickmode = 'array',
+ tickvals = [-50, 0, 50, 100],
+ ticktext = [50, 0, 50, 100]
+)
+
+fig.show()
+
+```
+
+
### Bar Chart with Line Plot
```python
@@ -239,7 +310,7 @@ x = ['Japan', 'United Kingdom', 'Canada', 'Netherlands',
fig = make_subplots(rows=1, cols=2, specs=[[{}, {}]], shared_xaxes=True,
shared_yaxes=False, vertical_spacing=0.001)
-fig.append_trace(go.Bar(
+fig.add_trace(go.Bar(
x=y_saving,
y=x,
marker=dict(
@@ -252,7 +323,7 @@ fig.append_trace(go.Bar(
orientation='h',
), 1, 1)
-fig.append_trace(go.Scatter(
+fig.add_trace(go.Scatter(
x=y_net_worth, y=x,
mode='lines+markers',
line_color='rgb(128, 0, 128)',
@@ -335,4 +406,4 @@ fig.show()
### Reference
-See more examples of bar charts and styling options [here](https://plotly.com/python/bar-charts/).<br> 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/).<br> See https://plotly.com/python/reference/bar/ for more information and chart attribute options!
diff --git a/doc/python/subplots.md b/doc/python/subplots.md
index 6842a650b5..b5711ee5de 100644
--- a/doc/python/subplots.md
+++ b/doc/python/subplots.md
@@ -6,9 +6,9 @@ jupyter:
extension: .md
format_name: markdown
format_version: '1.3'
- jupytext_version: 1.14.1
+ jupytext_version: 1.16.4
kernelspec:
- display_name: Python 3
+ display_name: Python 3 (ipykernel)
language: python
name: python3
language_info:
@@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.8.8
+ version: 3.11.10
plotly:
description: How to make subplots in with Plotly's Python graphing library. Examples
of stacked, custom-sized, gridded, and annotated subplots.
@@ -80,17 +80,17 @@ import plotly.graph_objects as go
fig = make_subplots(rows=3, cols=1)
-fig.append_trace(go.Scatter(
+fig.add_trace(go.Scatter(
x=[3, 4, 5],
y=[1000, 1100, 1200],
), row=1, col=1)
-fig.append_trace(go.Scatter(
+fig.add_trace(go.Scatter(
x=[2, 3, 4],
y=[100, 110, 120],
), row=2, col=1)
-fig.append_trace(go.Scatter(
+fig.add_trace(go.Scatter(
x=[0, 1, 2],
y=[10, 11, 12]
), row=3, col=1)
diff --git a/doc/python/supported-colors.md b/doc/python/supported-colors.md
new file mode 100644
index 0000000000..53fd7b3aec
--- /dev/null
+++ b/doc/python/supported-colors.md
@@ -0,0 +1,142 @@
+---
+jupyter:
+ jupytext:
+ notebook_metadata_filter: all
+ text_representation:
+ extension: .md
+ format_name: markdown
+ format_version: '1.3'
+ jupytext_version: 1.17.0
+ kernelspec:
+ display_name: Python 3 (ipykernel)
+ language: python
+ name: python3
+ language_info:
+ codemirror_mode:
+ name: ipython
+ version: 3
+ file_extension: .py
+ mimetype: text/x-python
+ name: python
+ nbconvert_exporter: python
+ pygments_lexer: ipython3
+ version: 3.13.2
+ plotly:
+ description: A list of supported named CSS Colors
+ display_as: file_settings
+ language: python
+ layout: base
+ name: Supported CSS Colors
+ order: 40
+ page_type: example_index
+ permalink: python/css-colors/
+ thumbnail: thumbnail/shape.jpg
+---
+
+# Supported CSS Colors
+
+Many properties in Plotly.py for configuring colors support named CSS colors. For example, marker colors:
+
+```python
+import plotly.graph_objects as go
+
+fig = go.Figure([
+ go.Bar(
+ x=['Jan', 'Feb', 'Mar', 'Apr'],
+ y=[20, 14, 25, 16],
+ name='Primary Product',
+ # Named CSS color
+ marker_color='royalblue'
+ )
+])
+
+fig.show()
+```
+
+These colors are supported in Plotly.py when a property accepts a [named CSS color](https://developer.mozilla.org/en-US/docs/Web/CSS/named-color).
+
+```python hide_code=true
+import plotly.graph_objects as go
+import pandas as pd
+
+supported_colors = ["aliceblue", "antiquewhite", "aqua", "aquamarine", "azure",
+ "beige", "bisque", "black", "blanchedalmond", "blue",
+ "blueviolet", "brown", "burlywood", "cadetblue",
+ "chartreuse", "chocolate", "coral", "cornflowerblue",
+ "cornsilk", "crimson", "cyan", "darkblue", "darkcyan",
+ "darkgoldenrod", "darkgray", "darkgrey", "darkgreen",
+ "darkkhaki", "darkmagenta", "darkolivegreen", "darkorange",
+ "darkorchid", "darkred", "darksalmon", "darkseagreen",
+ "darkslateblue", "darkslategray", "darkslategrey",
+ "darkturquoise", "darkviolet", "deeppink", "deepskyblue",
+ "dimgray", "dimgrey", "dodgerblue", "firebrick",
+ "floralwhite", "forestgreen", "fuchsia", "gainsboro",
+ "ghostwhite", "gold", "goldenrod", "gray", "grey", "green",
+ "greenyellow", "honeydew", "hotpink", "indianred", "indigo",
+ "ivory", "khaki", "lavender", "lavenderblush", "lawngreen",
+ "lemonchiffon", "lightblue", "lightcoral", "lightcyan",
+ "lightgoldenrodyellow", "lightgray", "lightgrey",
+ "lightgreen", "lightpink", "lightsalmon", "lightseagreen",
+ "lightskyblue", "lightslategray", "lightslategrey",
+ "lightsteelblue", "lightyellow", "lime", "limegreen",
+ "linen", "magenta", "maroon", "mediumaquamarine",
+ "mediumblue", "mediumorchid", "mediumpurple",
+ "mediumseagreen", "mediumslateblue", "mediumspringgreen",
+ "mediumturquoise", "mediumvioletred", "midnightblue",
+ "mintcream", "mistyrose", "moccasin", "navajowhite", "navy",
+ "oldlace", "olive", "olivedrab", "orange", "orangered",
+ "orchid", "palegoldenrod", "palegreen", "paleturquoise",
+ "palevioletred", "papayawhip", "peachpuff", "peru", "pink",
+ "plum", "powderblue", "purple", "red", "rosybrown",
+ "royalblue", "rebeccapurple", "saddlebrown", "salmon",
+ "sandybrown", "seagreen", "seashell", "sienna", "silver",
+ "skyblue", "slateblue", "slategray", "slategrey", "snow",
+ "springgreen", "steelblue", "tan", "teal", "thistle", "tomato",
+ "turquoise", "violet", "wheat", "white", "whitesmoke",
+ "yellow", "yellowgreen"]
+
+fig = go.Figure(layout=dict(title="Supported Named CSS Colors"))
+
+for i, color in enumerate(supported_colors):
+ row, col = i // 5, i % 5
+ x0, y0 = col * 1.2, -row * 1.2
+
+ fig.add_shape(
+ type="rect",
+ x0=x0, y0=y0,
+ x1=x0+1, y1=y0+1,
+ fillcolor=color,
+ line=dict(color="black", width=0.2),
+ )
+
+ fig.add_annotation(
+ x=x0+0.5, y=y0-0.1,
+ text=color,
+ showarrow=False,
+ font=dict(size=10)
+ )
+
+fig.update_layout(
+ height=((len(supported_colors) // 5) + (1 if len(supported_colors) % 5 else 0)) * 120,
+ width=800,
+ showlegend=False,
+ plot_bgcolor='rgba(0,0,0,0)',
+ margin=dict(l=50, r=50, t=50, b=50),
+ xaxis=dict(
+ showgrid=False,
+ zeroline=False,
+ showticklabels=False,
+ range=[-0.5, 6]
+ ),
+ yaxis=dict(
+ showgrid=False,
+ zeroline=False,
+ showticklabels=False,
+ scaleanchor="x",
+ scaleratio=1,
+ range=[-((len(supported_colors) // 5) + 1) * 1.2, 1.5]
+ )
+)
+
+fig.show()
+```