diff --git a/doc/python/3d-mesh.md b/doc/python/3d-mesh.md
index f444affa15..a543b9cd02 100644
--- a/doc/python/3d-mesh.md
+++ b/doc/python/3d-mesh.md
@@ -33,7 +33,7 @@ jupyter:
thumbnail: thumbnail/3d-mesh.jpg
---
-### Simple 3D Mesh example ###
+### Simple 3D Mesh Example
`go.Mesh3d` draws a 3D set of triangles with vertices given by `x`, `y` and `z`. If only coordinates are given, an algorithm such as [Delaunay triangulation](https://en.wikipedia.org/wiki/Delaunay_triangulation) is used to draw the triangles. Otherwise the triangles can be given using the `i`, `j` and `k` parameters (see examples below).
@@ -49,7 +49,7 @@ fig = go.Figure(data=[go.Mesh3d(x=x, y=y, z=z, color='lightpink', opacity=0.50)]
fig.show()
```
-### 3D Mesh example with Alphahull
+### 3D Mesh Example with Alphahull
The `alphahull` parameter sets the shape of the mesh. If the value is -1 (default value) then [Delaunay triangulation](https://en.wikipedia.org/wiki/Delaunay_triangulation) is used. If >0 then the [alpha-shape algorithm](https://en.wikipedia.org/wiki/Alpha_shape) is used. If 0, the [convex hull](https://en.wikipedia.org/wiki/Convex_hull) is represented (resulting in a convex body).
@@ -72,7 +72,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
@@ -146,7 +146,7 @@ fig = go.Figure(data=[
fig.show()
```
-### Intensity values defined on vertices or cells
+### Intensity Values Defined on Vertices or Cells
The `intensitymode` attribute of `go.Mesh3d` can be set to `vertex` (default mode, in which case intensity values are interpolated between values defined on vertices), or to `cell` (value of the whole cell, no interpolation). Note that the `intensity` parameter should have the same length as the number of vertices or cells, depending on the `intensitymode`.
diff --git a/doc/python/3d-scatter-plots.md b/doc/python/3d-scatter-plots.md
index b913bc8f56..edf729fa3f 100644
--- a/doc/python/3d-scatter-plots.md
+++ b/doc/python/3d-scatter-plots.md
@@ -33,7 +33,7 @@ jupyter:
thumbnail: thumbnail/3d-scatter.jpg
---
-## 3D scatter plot with Plotly Express
+## 3D Scatter Plot with Plotly Express
[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on a variety of types of data](/python/px-arguments/) and produces [easy-to-style figures](/python/styling-plotly-express/).
@@ -57,7 +57,7 @@ fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
fig.show()
```
-#### Style 3d scatter plot
+#### Style 3D Scatter Plot
It is possible to customize the style of the figure through the parameters of `px.scatter_3d` for some options, or by updating the traces or the layout of the figure through `fig.update`.
@@ -73,11 +73,11 @@ fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
fig.show()
```
-#### 3d scatter plots in Dash
+#### 3D Scatter Plots in Dash
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/animations.md b/doc/python/animations.md
index af22e349af..f600ddee0f 100644
--- a/doc/python/animations.md
+++ b/doc/python/animations.md
@@ -34,7 +34,7 @@ jupyter:
thumbnail: thumbnail/animations.gif
---
-#### Animated figures with Plotly Express
+#### Animated Figures with Plotly Express
Several [Plotly Express](/python/plotly-express/) functions support the creation of animated figures through the `animation_frame` and `animation_group` arguments.
@@ -48,11 +48,11 @@ px.scatter(df, x="gdpPercap", y="lifeExp", animation_frame="year", animation_gro
log_x=True, size_max=55, range_x=[100,100000], range_y=[25,90])
```
-#### Animated figures in Dash
+#### Animated Figures in Dash
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
@@ -81,7 +81,7 @@ fig.show()
* Although Plotly Express supports animation for many chart and map types, smooth inter-frame transitions are today *only* possible for `scatter` and `bar`
* Plotly Express will *not* automatically compute the union of all x/y/color ranges, so these must be specified manually to avoid scale jumps across frames
-#### Animated figures with Graph Objects
+#### Animated Figures with Graph Objects
The remainder of this section describes the low-level [graph objects](/python/graph-objects/) API for constructing animated figures manually.
diff --git a/doc/python/axes.md b/doc/python/axes.md
index 9d5f154e10..33a9b68703 100644
--- a/doc/python/axes.md
+++ b/doc/python/axes.md
@@ -64,7 +64,7 @@ The axis type is auto-detected by looking at data from the first [trace](/python
* Both of these test an evenly-spaced sample of at most 1000 values
-### Forcing an axis to be categorical
+### Forcing an Axis to be Categorical
It is possible to force the axis type by setting explicitly `xaxis_type`. In the example below the automatic X axis type would be `linear` (because there are not more than twice as many unique strings as unique numbers) but we force it to be `category`.
@@ -91,7 +91,7 @@ The examples on this page apply to axes of any type, but extra attributes are av
#### Set and Style Axes Title Labels
-##### Set axis title text with Plotly Express
+##### Set Axis Title Text with Plotly Express
Axis titles are automatically set to the column names when [using Plotly Express with a data frame as input](/python/px-arguments/).
@@ -124,11 +124,11 @@ fig = px.bar(x=["Apples", "Oranges"], y=[10,20], color=["Here", "There"],
fig.show()
```
-##### Rotating tick labels in Dash
+##### Rotating Tick Labels in Dash
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
@@ -173,7 +173,7 @@ fig.update_xaxes(labelalias=dict(Sat="Saturday", Sun="Sunday"))
fig.show()
```
-##### Set axis title text with Graph Objects
+##### Set Axis Title Text with Graph Objects
Axis titles are set using the nested `title.text` property of the x or y axis. Here is an example of creating a new figure and using `update_xaxes` and `update_yaxes`, with magic underscore notation, to set the axis titles.
@@ -188,7 +188,7 @@ fig.update_yaxes(title_text='Value A')
fig.show()
```
-### Set axis title position
+### Set Axis Title Position
This example sets `standoff` attribute to cartesian axes to determine the distance between the tick labels and the axis title. Note that the axis title position is always constrained within the margins, so the actual standoff distance is always less than the set or default value. By default [automargin](https://plotly.com/python/setting-graph-size/#automatically-adjust-margins) is `True` in Plotly template for the cartesian axis, so the margins will be pushed to fit the axis title at given standoff distance.
@@ -213,7 +213,7 @@ fig.update_yaxes(
fig.show()
```
-##### Set axis title font
+##### Set Axis Title Font
Here is an example that configures the font family, size, and color for the axis titles in a figure created using Plotly Express.
@@ -230,7 +230,7 @@ fig.show()
#### Tick Placement, Color, and Style
-##### Toggling axis tick marks
+##### Toggling Axis Tick Marks
Axis tick marks are disabled by default for the default `plotly` theme, but they can easily be turned on by setting the `ticks` axis property to `"inside"` (to place ticks inside plotting area) or `"outside"` (to place ticks outside the plotting area).
@@ -247,7 +247,7 @@ fig.update_yaxes(ticks="inside", col=1)
fig.show()
```
-##### Set number of tick marks (and grid lines)
+##### Set Number of Tick Marks (and Grid Lines)
The approximate number of ticks displayed for an axis can be specified using the `nticks` axis property.
@@ -263,7 +263,7 @@ fig.update_yaxes(nticks=20)
fig.show()
```
-##### Set start position and distance between ticks
+##### Set Start Position and Distance Between Ticks
The `tick0` and `dtick` axis properties can be used to control to placement of axis ticks as follows: If specified, a tick will fall exactly on the location of `tick0` and additional ticks will be added in both directions at intervals of `dtick`.
@@ -279,7 +279,7 @@ fig.update_yaxes(tick0=0.25, dtick=0.5)
fig.show()
```
-##### Set exact location of axis ticks
+##### Set Exact Location of Axis Ticks
It is possible to configure an axis to display ticks at a set of predefined locations by setting the `tickvals` property to an array of positions.
@@ -295,7 +295,7 @@ fig.update_yaxes(tickvals=[5.1, 5.9, 6.3, 7.5])
fig.show()
```
-##### Style tick marks
+##### Style Tick Marks
As discussed above, tick marks are disabled by default in the default `plotly` theme, but they can be enabled by setting the `ticks` axis property to `"inside"` (to place ticks inside plotting area) or `"outside"` (to place ticks outside the plotting area).
@@ -314,7 +314,7 @@ fig.update_yaxes(ticks="outside", tickwidth=2, tickcolor='crimson', ticklen=10,
fig.show()
```
-##### Step for tick labels
+##### Step for Tick Labels
*New in v5.6*
@@ -330,7 +330,7 @@ fig.update_yaxes(ticklabelstep=2)
fig.show()
```
-##### Toggling axis labels
+##### Toggling Axis Labels
The axis tick mark labels can be disabled by setting the `showticklabels` axis property to `False`.
@@ -347,7 +347,7 @@ fig.update_yaxes(showticklabels=False)
fig.show()
```
-##### Set axis label rotation and font
+##### Set Axis Label Rotation and Font
The orientation of the axis tick mark labels is configured using the `tickangle` axis property. The value of `tickangle` is the angle of rotation, in the clockwise direction, of the labels from vertical in units of degrees. The font family, size, and color for the tick labels are stored under the `tickfont` axis property.
@@ -426,7 +426,7 @@ fig.update_layout(title_text="Apple Stock Price")
fig.show()
```
-#### Adding minor ticks
+#### Adding Minor Ticks
_new in 5.8_
@@ -506,9 +506,9 @@ fig.update_layout(
fig.show()
```
-### Axis lines: grid and zerolines
+### Axis Lines: Grid and Zero Lines
-##### Toggling Axis grid lines
+##### Toggling Axis Grid Lines
Axis grid lines can be disabled by setting the `showgrid` property to `False` for the x and/or y axis.
@@ -523,7 +523,7 @@ fig.update_yaxes(showgrid=False)
fig.show()
```
-##### Toggling Axis zero lines
+##### Toggling Axis Zero Lines
The lines passing through zero can be disabled as well by setting the `zeroline` axis property to `False`
@@ -537,9 +537,9 @@ fig.update_yaxes(showgrid=False, zeroline=False)
fig.show()
```
-#### Styling and Coloring Axes and the Zero-Line
+#### Styling and Coloring Axes and the Zero Line
-##### Styling axis lines
+##### Styling Axis Lines
The `showline` axis property controls the visibility of the axis line, and the `linecolor` and `linewidth` axis properties control the color and width of the axis line.
@@ -556,7 +556,7 @@ fig.update_yaxes(showline=True, linewidth=2, linecolor='black')
fig.show()
```
-##### Mirroring axis lines
+##### Mirroring Axis Lines
Axis lines can be mirrored to the opposite side of the plotting area by setting the `mirror` axis property to `True`.
@@ -573,7 +573,7 @@ fig.update_yaxes(showline=True, linewidth=2, linecolor='black', mirror=True)
fig.show()
```
-##### Styling grid lines
+##### Styling Grid Lines
The width and color of axis grid lines are controlled by the `gridwidth` and `gridcolor` axis properties.
@@ -604,7 +604,7 @@ fig.update_xaxes(gridcolor='black', griddash='dash', minor_griddash="dot")
fig.show()
```
-##### Styling zero lines
+##### Styling Zero Lines
The width and color of axis zero lines are controlled by the `zerolinewidth` and `zerolinecolor` axis properties.
@@ -689,7 +689,7 @@ fig.update_xaxes(insiderange=['2018-10-01', '2019-01-01'], title=dict(text="Date
fig.show()
```
-#### Setting only a Lower or Upper Bound for Range
+#### Setting Only a Lower or Upper Bound for Range
*New in 5.17*
@@ -767,7 +767,7 @@ fig.update_yaxes(
fig.show()
```
-### Fixed Ratio Axes with Compressed domain
+### Fixed Ratio Axes with Compressed Domain
If an axis needs to be compressed (either due to its own `scaleanchor` and `scaleratio` or those of the other axis), `constrain` determines how that happens: by increasing the "range" (default), or by decreasing the "domain".
@@ -794,7 +794,7 @@ fig.update_yaxes(
fig.show()
```
-##### Decreasing the domain spanned by an axis
+##### Decreasing the Domain Spanned by an Axis
In the example below, the x and y axis are anchored together, and the range of the `xaxis` is set manually. By default, plotly extends the range of the axis (overriding the `range` parameter) to fit in the figure `domain`. You can restrict the `domain` to force the axis to span only the set range, by setting `constrain='domain'` as below.
@@ -842,7 +842,7 @@ fig.update_yaxes(autorange="reversed")
fig.show()
```
-#### Reversed Axes with Range ( Min/Max ) Specified
+#### Reversed Axes with Range (Min/Max) Specified
The direction of an axis can be reversed when manually setting the range extents by specifying a list containing the upper bound followed by the lower bound (rather that the lower followed by the upper) as the `range` axis property.
@@ -888,7 +888,7 @@ fig.update_yaxes(range=[None, 3], autorange="max reversed")
fig.show()
```
-### Axis range for log axis type
+### Axis Range for Log Axis Type
If you are using a `log` type of axis and you want to set the range of the axis, you have to give the `log10` value of the bounds when using `fig.update_xaxes` or `fig.update_layout`. However, with `plotly.express` functions you pass directly the values of the range bounds (`plotly.express` then computes the appropriate values to pass to the figure layout).
@@ -928,7 +928,7 @@ fig.update_yaxes(domain=(0.25, 0.75))
fig.show()
```
-#### Synchronizing axes in subplots with `matches`
+#### Synchronizing Axes in Subplots with `matches`
Using `facet_col` from `plotly.express` let [zoom](https://help.plotly.com/zoom-pan-hover-controls/#step-3-zoom-in-and-zoom-out-autoscale-the-plot) and [pan](https://help.plotly.com/zoom-pan-hover-controls/#step-6-pan-along-axes) each facet to the same range implicitly. However, if the subplots are created with `make_subplots`, the axis needs to be updated with `matches` parameter to update all the subplots accordingly.
@@ -1008,7 +1008,7 @@ fig.update_xaxes(autorangeoptions=dict(clipmax=4))
fig.show()
```
-##### Specify Values to be Included
+##### Specify Values to Be Included
Use `autorangeoptions.include` to specify a value that should always be included within the calculated autorange. In this example, we specify that for the autorange calculated on the x-axis, 5 should be included.
diff --git a/doc/python/bar-charts.md b/doc/python/bar-charts.md
index 7a340c7090..24ec27bd49 100644
--- a/doc/python/bar-charts.md
+++ b/doc/python/bar-charts.md
@@ -33,7 +33,7 @@ jupyter:
thumbnail: thumbnail/bar.jpg
---
-### Bar chart with Plotly Express
+### Bar Charts with Plotly Express
[Plotly Express](/python/plotly-express/) is the easy-to-use, high-level interface to Plotly, which [operates on a variety of types of data](/python/px-arguments/) and produces [easy-to-style figures](/python/styling-plotly-express/).
@@ -49,7 +49,7 @@ fig.show()
```
-#### Bar charts with Long Format Data
+#### Bar Charts with Long Format Data
Long-form data has one row per observation, and one column per variable. This is suitable for storing and displaying multivariate data i.e. with dimension greater than 2. This format is sometimes called "tidy".
@@ -71,7 +71,7 @@ fig.show()
long_df
```
-#### Bar charts with Wide Format Data
+#### Bar Charts with Wide Format Data
Wide-form data has one row per value of one of the first variable, and one column per value of the second variable. This is suitable for storing and displaying 2-dimensional data.
```python
@@ -87,11 +87,11 @@ fig.show()
wide_df
```
-### Bar charts in Dash
+### Bar Charts in Dash
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
@@ -246,7 +246,7 @@ fig = px.bar(df, x="medal", y="count", color="nation",
fig.show()
```
-### Facetted subplots
+### Facetted Subplots
Use the keyword arguments `facet_row` (resp. `facet_col`) to create facetted subplots, where different rows (resp. columns) correspond to different values of the dataframe column specified in `facet_row`.
@@ -467,7 +467,7 @@ fig = go.Figure(data=[go.Bar(
fig.show()
```
-### Controlling text fontsize with uniformtext
+### Controlling Text Font Size with uniformtext
If you want all the text labels to have the same size, you can use the `uniformtext` layout parameter. The `minsize` attribute sets the font size, and the `mode` attribute sets what happens for labels which cannot fit with the desired fontsize: either `hide` them or `show` them with overflow. In the example below we also force the text to be outside of bars with `textposition`.
@@ -589,9 +589,9 @@ fig.update_layout(
)
```
-### Using a scatterplot to wrap long bars into multiple columns
+### Using a Scatter Plot to Wrap Long Bars into Multiple Columns
-This bar-style pictogram allows readers to focus on the relative sizes of smaller entities by wrapping the bar for largest entries into multiple columns. You could make it even more of a pictogram by using fontawesome to replace the square markers we use below with icons like mortar boards for students.
+This bar-style pictogram allows readers to focus on the relative sizes of smaller entities by wrapping the bar for largest entries into multiple columns. You could make it even more of a pictogram by using fontawesome to replace the square markers we use below with icons like mortar boards for students.
```python
import plotly.graph_objects as go
diff --git a/doc/python/box-plots.md b/doc/python/box-plots.md
index 0dff5c64ed..06782e6319 100644
--- a/doc/python/box-plots.md
+++ b/doc/python/box-plots.md
@@ -69,7 +69,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
from IPython.display import IFrame
diff --git a/doc/python/builtin-colorscales.md b/doc/python/builtin-colorscales.md
index 01fc9ec8e1..0f387c00ee 100644
--- a/doc/python/builtin-colorscales.md
+++ b/doc/python/builtin-colorscales.md
@@ -78,7 +78,7 @@ print(px.colors.sequential.Plasma)
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/candlestick-charts.md b/doc/python/candlestick-charts.md
index 36712d47d3..bd79575d89 100644
--- a/doc/python/candlestick-charts.md
+++ b/doc/python/candlestick-charts.md
@@ -78,7 +78,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/choropleth-maps.md b/doc/python/choropleth-maps.md
index 0919535c26..c1772091f5 100644
--- a/doc/python/choropleth-maps.md
+++ b/doc/python/choropleth-maps.md
@@ -147,7 +147,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
from IPython.display import IFrame
diff --git a/doc/python/colorscales.md b/doc/python/colorscales.md
index aadef07600..b47fbb5f1c 100644
--- a/doc/python/colorscales.md
+++ b/doc/python/colorscales.md
@@ -94,7 +94,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
@@ -157,7 +157,7 @@ fig.show()
### Explicitly Constructing a Color scale
-The Plotly Express `color_continuous_scale` argument accepts explicitly-constructed color scales as well.
+The Plotly Express `color_continuous_scale` argument accepts explicitly-constructed color scales as well.
The Graph Objects `colorscale` parameter also accepts an explicitly-constructed color scale, as shown in the example [below](#custom-heatmap-color-scale-with-graph-objects).
diff --git a/doc/python/creating-and-updating-figures.md b/doc/python/creating-and-updating-figures.md
index 170fa4d64f..24ed6755a2 100644
--- a/doc/python/creating-and-updating-figures.md
+++ b/doc/python/creating-and-updating-figures.md
@@ -131,7 +131,7 @@ print("\n\n")
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/discrete-color.md b/doc/python/discrete-color.md
index fd4de49201..6f0696a592 100644
--- a/doc/python/discrete-color.md
+++ b/doc/python/discrete-color.md
@@ -103,7 +103,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
from IPython.display import IFrame
diff --git a/doc/python/distplot.md b/doc/python/distplot.md
index 33335248c4..1c36503d3e 100644
--- a/doc/python/distplot.md
+++ b/doc/python/distplot.md
@@ -60,7 +60,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/figure-labels.md b/doc/python/figure-labels.md
index 1374188910..cf32e706d2 100644
--- a/doc/python/figure-labels.md
+++ b/doc/python/figure-labels.md
@@ -110,7 +110,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash dash-daq`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
from IPython.display import IFrame
diff --git a/doc/python/figure-structure.md b/doc/python/figure-structure.md
index 9102b110a3..1f26bb61eb 100644
--- a/doc/python/figure-structure.md
+++ b/doc/python/figure-structure.md
@@ -53,7 +53,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/filled-area-plots.md b/doc/python/filled-area-plots.md
index d475049204..1416d51431 100644
--- a/doc/python/filled-area-plots.md
+++ b/doc/python/filled-area-plots.md
@@ -52,7 +52,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/getting-started.md b/doc/python/getting-started.md
index cb68c6a010..332a0e5e16 100644
--- a/doc/python/getting-started.md
+++ b/doc/python/getting-started.md
@@ -79,7 +79,7 @@ You'll also need to install a [supported dataframe library](/python/px-arguments
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/heatmaps.md b/doc/python/heatmaps.md
index cbbc73fa81..fa83ace853 100644
--- a/doc/python/heatmaps.md
+++ b/doc/python/heatmaps.md
@@ -97,7 +97,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/histograms.md b/doc/python/histograms.md
index 004dff0aee..143b2fbd5f 100644
--- a/doc/python/histograms.md
+++ b/doc/python/histograms.md
@@ -104,7 +104,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/horizontal-vertical-shapes.md b/doc/python/horizontal-vertical-shapes.md
index d533904aac..6692671483 100644
--- a/doc/python/horizontal-vertical-shapes.md
+++ b/doc/python/horizontal-vertical-shapes.md
@@ -71,7 +71,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/hover-text-and-formatting.md b/doc/python/hover-text-and-formatting.md
index ccfefc85a7..0567cc2f29 100644
--- a/doc/python/hover-text-and-formatting.md
+++ b/doc/python/hover-text-and-formatting.md
@@ -156,7 +156,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
Change the hover mode below and try hovering over the points:
diff --git a/doc/python/interactive-html-export.md b/doc/python/interactive-html-export.md
index 49871e5cb4..a81437e5a3 100644
--- a/doc/python/interactive-html-export.md
+++ b/doc/python/interactive-html-export.md
@@ -132,7 +132,7 @@ with open(output_html_path, "w", encoding="utf-8") as output_file:
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/legend.md b/doc/python/legend.md
index d75ce2f5d2..d9709527fe 100644
--- a/doc/python/legend.md
+++ b/doc/python/legend.md
@@ -213,7 +213,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/line-and-scatter.md b/doc/python/line-and-scatter.md
index b82312afcc..5aa37b85e3 100644
--- a/doc/python/line-and-scatter.md
+++ b/doc/python/line-and-scatter.md
@@ -89,7 +89,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/line-charts.md b/doc/python/line-charts.md
index ad355e0af4..99d47995a0 100644
--- a/doc/python/line-charts.md
+++ b/doc/python/line-charts.md
@@ -62,7 +62,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true tags=[]
diff --git a/doc/python/marker-style.md b/doc/python/marker-style.md
index 6a75ccbd48..9e1eb88e11 100644
--- a/doc/python/marker-style.md
+++ b/doc/python/marker-style.md
@@ -155,7 +155,7 @@ The `marker.line.dash` attribute is available on `go.Scatter`, `go.Scatterpolar`
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
from IPython.display import IFrame
diff --git a/doc/python/ml-knn.md b/doc/python/ml-knn.md
index cd09c9589f..6885e12670 100644
--- a/doc/python/ml-knn.md
+++ b/doc/python/ml-knn.md
@@ -240,7 +240,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/ml-regression.md b/doc/python/ml-regression.md
index f2783dd892..e24a743749 100644
--- a/doc/python/ml-regression.md
+++ b/doc/python/ml-regression.md
@@ -95,7 +95,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/ml-roc-pr.md b/doc/python/ml-roc-pr.md
index 71cc38389e..f9b36575f0 100644
--- a/doc/python/ml-roc-pr.md
+++ b/doc/python/ml-roc-pr.md
@@ -123,7 +123,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/multiple-axes.md b/doc/python/multiple-axes.md
index 96e2f19b16..46e9f9635c 100644
--- a/doc/python/multiple-axes.md
+++ b/doc/python/multiple-axes.md
@@ -75,11 +75,11 @@ fig.update_yaxes(title_text="secondary yaxis title", secondary_y=True)
fig.show()
```
-### Multiple axes in Dash
+### Multiple Axes in Dash
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/network-graphs.md b/doc/python/network-graphs.md
index f28a697c32..de25fee55c 100644
--- a/doc/python/network-graphs.md
+++ b/doc/python/network-graphs.md
@@ -43,7 +43,7 @@ Install the Python library `networkx` with `pip install networkx`.
-### Create random graph
+### Create Random Graph
```python
import plotly.graph_objects as go
@@ -54,7 +54,7 @@ G = nx.random_geometric_graph(200, 0.125)
```
#### Create Edges
-Add edges as disconnected lines in a single trace and nodes as a scatter trace
+Add edges as disconnected lines in a single trace and nodes as a scatter trace:
```python
edge_x = []
@@ -153,11 +153,11 @@ fig.show()
```
-### Network graphs in Dash
+### Network Graphs in Dash
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash dash-cytoscape`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/pie-charts.md b/doc/python/pie-charts.md
index 7636a09987..f6f3ec4eb0 100644
--- a/doc/python/pie-charts.md
+++ b/doc/python/pie-charts.md
@@ -68,7 +68,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
from IPython.display import IFrame
diff --git a/doc/python/plot-data-from-csv.md b/doc/python/plot-data-from-csv.md
index b257aea9de..5986489b26 100644
--- a/doc/python/plot-data-from-csv.md
+++ b/doc/python/plot-data-from-csv.md
@@ -60,7 +60,7 @@ fig.show()
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/plotly-express.md b/doc/python/plotly-express.md
index 73f402df5e..90b5c81d25 100644
--- a/doc/python/plotly-express.md
+++ b/doc/python/plotly-express.md
@@ -89,7 +89,7 @@ The Plotly Express API in general offers the following features:
[Dash](https://plotly.com/dash/) is the best way to build analytical apps in Python using Plotly figures. To run the app below, run `pip install dash`, click "Download" to get the code and run `python app.py`.
-Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
+Get started with [the official Dash docs](https://dash.plotly.com/installation) and **learn how to effortlessly [style](https://plotly.com/dash/design-kit/) & publish apps like this with Dash Enterprise or Plotly Cloud.**
```python hide_code=true
diff --git a/doc/python/renderers.md b/doc/python/renderers.md
index 9fbcc0f4b2..3eb3a97331 100644
--- a/doc/python/renderers.md
+++ b/doc/python/renderers.md
@@ -233,7 +233,7 @@ fig.show(renderer="png", width=800, height=300)
### Displaying figures in Plotly Studio
-Use [Plotly Studio](https://plotly.com/studio?utm_medium=graphing_libraries&utm_content=python_renderers) to build data apps with Plotly figures using natural language and AI. Describe the charts you want to Plotly Studio, which generates them within a [Dash](https://plotly.com/dash/?utm_medium=graphing_libraries&utm_content=python_renderers) app that you can publish to [Plotly Cloud](https://plotly.com/cloud/?utm_medium=graphing_libraries&utm_content=python_renderers) or [Dash Enterprise](https://plotly.com/dash/?utm_medium=graphing_libraries&utm_content=python_renderers).
+Use [Plotly Studio](https://plotly.com/studio?utm_medium=graphing_libraries&utm_content=python_renderers) to build data apps with Plotly figures using natural language and AI. Describe the charts you want to Plotly Studio, which generates them within a [Dash](https://plotly.com/dash/?utm_medium=graphing_libraries&utm_content=python_renderers) app that you can publish to [Plotly Cloud](https://plotly.com/cloud/?utm_medium=graphing_libraries&utm_content=python_renderers) or [Dash Enterprise](https://plotly.com/dash-enterprise/?utm_medium=graphing_libraries&utm_content=python_renderers).
```python hide_code=true
from IPython.display import HTML
@@ -244,7 +244,7 @@ HTML('