diff --git a/doc/python/colorscales.md b/doc/python/colorscales.md
index 32711054fc2..bf974769e59 100644
--- a/doc/python/colorscales.md
+++ b/doc/python/colorscales.md
@@ -6,7 +6,7 @@ jupyter:
extension: .md
format_name: markdown
format_version: '1.2'
- jupytext_version: 1.3.1
+ jupytext_version: 1.6.0
kernelspec:
display_name: Python 3
language: python
@@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.6.8
+ version: 3.7.6
plotly:
description: How to set, create and control continous color scales and color bars
in scatter, bar, map and heatmap figures.
@@ -90,6 +90,19 @@ fig = px.scatter(df, x="total_bill", y="tip", color="size",
fig.show()
```
+### Colorscales 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/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with Dash Enterprise.**
+
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'colorscales', width='100%', height=630)
+```
+
### Color Scales in Plotly Express
By default, [Plotly Express](/python/plotly-express/) will use the color scale from the active [template](/python/templates/)'s `layout.colorscales.sequential` attribute, and the default active template is `plotly` which uses the `Plasma` color scale. You can choose any of the [built-in color scales](/python/builtin-colorscales/), however, or define your own.
@@ -557,4 +570,4 @@ fig.show()
### Reference
-See https://plotly.com/python/reference/ for more information and chart attribute options!
\ No newline at end of file
+See https://plotly.com/python/reference/ for more information and chart attribute options!
diff --git a/doc/python/marker-style.md b/doc/python/marker-style.md
index f5b305b96d7..ea73d05cd24 100644
--- a/doc/python/marker-style.md
+++ b/doc/python/marker-style.md
@@ -6,7 +6,7 @@ jupyter:
extension: .md
format_name: markdown
format_version: '1.2'
- jupytext_version: 1.4.2
+ jupytext_version: 1.6.0
kernelspec:
display_name: Python 3
language: python
@@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.7.7
+ version: 3.7.6
plotly:
description: How to style markers in Python with Plotly.
display_as: file_settings
@@ -107,6 +107,19 @@ fig.show()
Fully opaque, the default setting, is useful for non-overlapping markers. When many points overlap it can be hard to observe density.
+
+### Control Marker Border with 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/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with Dash Enterprise.**
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'marker-style', width='100%', height=630)
+```
+
### Opacity
Setting opacity outside the marker will set the opacity of the trace. Thus, it will allow greater visbility of additional traces but like fully opaque it is hard to distinguish density.
diff --git a/doc/python/setting-graph-size.md b/doc/python/setting-graph-size.md
index c6a65f1a4fa..37f1bb7bb7b 100644
--- a/doc/python/setting-graph-size.md
+++ b/doc/python/setting-graph-size.md
@@ -6,7 +6,7 @@ jupyter:
extension: .md
format_name: markdown
format_version: '1.2'
- jupytext_version: 1.3.2
+ jupytext_version: 1.6.0
kernelspec:
display_name: Python 3
language: python
@@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.7.3
+ version: 3.7.6
plotly:
description: How to manipulate the graph size, margins and background color.
display_as: file_settings
@@ -51,6 +51,18 @@ fig.update_layout(
fig.show()
```
+### Adjusting graph size with 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/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with Dash Enterprise.**
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'setting-graph-size', width='100%', height=630)
+```
+
### Adjusting Height, Width, & Margins With Graph Objects
[Graph objects](/python/graph-objects/) are the low-level building blocks of figures which you can use instead of Plotly Express for greater control.
@@ -117,4 +129,4 @@ fig.show()
#### Reference
-See https://plotly.com/python/reference/layout/ for more information and chart attribute options!
\ No newline at end of file
+See https://plotly.com/python/reference/layout/ for more information and chart attribute options!
diff --git a/doc/python/static-image-export.md b/doc/python/static-image-export.md
index c4f23a0aa49..9ed085d33e7 100644
--- a/doc/python/static-image-export.md
+++ b/doc/python/static-image-export.md
@@ -5,8 +5,8 @@ jupyter:
text_representation:
extension: .md
format_name: markdown
- format_version: '1.1'
- jupytext_version: 1.1.6
+ format_version: '1.2'
+ jupytext_version: 1.6.0
kernelspec:
display_name: Python 3
language: python
@@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.7.3
+ version: 3.7.6
plotly:
description: Plotly allows you to save static images of your plots. Save the image
to your local computer, or embed it inside your Jupyter notebooks as a static
@@ -148,6 +148,20 @@ fig.write_image("images/fig1.eps")
**Note:** It is important to note that any figures containing WebGL traces (i.e. of type `scattergl`, `heatmapgl`, `contourgl`, `scatter3d`, `surface`, `mesh3d`, `scatterpolargl`, `cone`, `streamtube`, `splom`, or `parcoords`) that are exported in a vector format will include encapsulated rasters, instead of vectors, for some parts of the image.
+
+### Image Export 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/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with Dash Enterprise.**
+
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'static-image-export', width='100%', height=630)
+```
+
### Get Image as Bytes
The `plotly.io.to_image` function is used to return an image as a bytes object. You can also use the `.to_image` graph object figure method.
@@ -221,4 +235,4 @@ Here is a complete listing of the available image export settings:
See the [Orca Management](/python/orca-management/) section for information on how to specify image export settings when using orca.
### Summary
-In summary, to export high-quality static images from plotly.py, all you need to do is install the `kaleido` package and then use the `plotly.io.write_image` and `plotly.io.to_image` functions (or the `.write_image` and `.to_image` graph object figure methods).
\ No newline at end of file
+In summary, to export high-quality static images from plotly.py, all you need to do is install the `kaleido` package and then use the `plotly.io.write_image` and `plotly.io.to_image` functions (or the `.write_image` and `.to_image` graph object figure methods).
diff --git a/doc/python/table.md b/doc/python/table.md
index 378c91297f5..928a5b53ea8 100644
--- a/doc/python/table.md
+++ b/doc/python/table.md
@@ -5,12 +5,22 @@ jupyter:
text_representation:
extension: .md
format_name: markdown
- format_version: '1.1'
- jupytext_version: 1.1.1
+ format_version: '1.2'
+ jupytext_version: 1.6.0
kernelspec:
display_name: Python 3
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: 3.7.6
plotly:
description: How to make tables in Python with Plotly.
display_as: basic
@@ -80,6 +90,18 @@ fig = go.Figure(data=[go.Table(
fig.show()
```
+#### Tables 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/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with Dash Enterprise.**
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'table', width='100%', height=630)
+```
+
#### Changing Row and Column Size
```python
@@ -211,4 +233,4 @@ fig.show()
```
#### Reference
-For more information on tables and table attributes see: https://plotly.com/python/reference/table/.
\ No newline at end of file
+For more information on tables and table attributes see: https://plotly.com/python/reference/table/.