diff --git a/doc/python/animations.md b/doc/python/animations.md
index 4fc9b08e300..245f9a11b9e 100644
--- a/doc/python/animations.md
+++ b/doc/python/animations.md
@@ -5,12 +5,22 @@ 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
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: An introduction to creating animations with Plotly in Python.
display_as: animations
@@ -37,6 +47,19 @@ 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
+
+[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 + 'animations', width='100%', height=630)
+```
+
#### Animated Bar Charts with Plotly Express
Note that you should always fix the `y_range` to ensure that your data remains visible throughout the animation.
diff --git a/doc/python/candlestick-charts.md b/doc/python/candlestick-charts.md
index a343c32742a..e621394114f 100644
--- a/doc/python/candlestick-charts.md
+++ b/doc/python/candlestick-charts.md
@@ -5,8 +5,8 @@ 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
@@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.6.7
+ version: 3.7.6
plotly:
description: How to make interactive candlestick charts in Python with Plotly.
Six examples of candlestick charts with Pandas, time series, and yahoo finance
@@ -74,6 +74,19 @@ fig.update_layout(xaxis_rangeslider_visible=False)
fig.show()
```
+#### Candlestick 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 + 'candlestick-charts', width='100%', height=630)
+```
+
#### Adding Customized Text and Annotations
```python
@@ -144,4 +157,4 @@ fig.show()
```
#### Reference
-For more information on candlestick attributes, see: https://plotly.com/python/reference/candlestick/
\ No newline at end of file
+For more information on candlestick attributes, see: https://plotly.com/python/reference/candlestick/
diff --git a/doc/python/figure-structure.md b/doc/python/figure-structure.md
index f7cafe29afa..1175ce36cec 100644
--- a/doc/python/figure-structure.md
+++ b/doc/python/figure-structure.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: The structure of a figure - data, traces and layout explained.
display_as: file_settings
@@ -49,6 +49,19 @@ print(fig)
fig.show()
```
+### Accessing figure structures 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 + 'figure-structure', width='100%', height=630)
+```
+
### Figures as Trees of Attributes
Plotly.js supports inputs adhering to a well-defined schema, whose overall architecture is explained in this page and which is exhaustively documented in the [Figure Reference](/python/reference/index/) (which is itself generated from a [machine-readable JSON representation of the schema](https://raw.githubusercontent.com/plotly/plotly.js/master/dist/plot-schema.json)). Figures are represented as trees with named nodes called "attributes". The root node of the tree has three top-level attributes: `data`, `layout` and `frames` (see below).
diff --git a/doc/python/plot-data-from-csv.md b/doc/python/plot-data-from-csv.md
index 6e3c8258764..520866132f2 100644
--- a/doc/python/plot-data-from-csv.md
+++ b/doc/python/plot-data-from-csv.md
@@ -5,8 +5,8 @@ jupyter:
text_representation:
extension: .md
format_name: markdown
- format_version: "1.1"
- jupytext_version: 1.2.0
+ 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: 3.6.8
+ version: 3.7.6
plotly:
description: How to create charts from csv files with Plotly and Python
display_as: advanced_opt
@@ -56,6 +56,19 @@ fig = px.line(df, x = 'AAPL_x', y = 'AAPL_y', title='Apple Share Prices over tim
fig.show()
```
+### Plot from CSV 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 + 'plot-data-from-csv', width='100%', height=630)
+```
+
### Plot from CSV with `graph_objects`
```python
diff --git a/doc/python/sankey-diagram.md b/doc/python/sankey-diagram.md
index 5ce928345eb..9fe695f0049 100644
--- a/doc/python/sankey-diagram.md
+++ b/doc/python/sankey-diagram.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
kernel_info:
name: python2
kernelspec:
@@ -22,7 +22,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
- version: 3.6.8
+ version: 3.7.6
plotly:
description: How to make Sankey Diagrams in Python with Plotly.
display_as: basic
@@ -104,6 +104,19 @@ fig.update_layout(title_text="Energy forecast for 2050
Source: Department of
fig.show()
```
+### Sankey Diagram 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 + 'sankey-diagram', width='100%', height=630)
+```
+
### Style Sankey Diagram
This example also uses [hovermode](https://plotly.com/python/reference/layout/#layout-hovermode) to enable multiple tooltips.