Merge pull request plotly#2949 from plotly/add-dash-snipepts

Add 6 new dash snippets to python docs

Author: nicolaskruchten

doc/python/axes.md

@@ -125,6 +125,19 @@ fig = px.bar(df, x=["Apples", "Oranges"], y=[10,20], color=["Here", "There"],
 fig.show()
 ```
 
+##### Rotate 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/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with <a class="plotly-red" href="https://plotly.com/dash/">Dash Enterprise</a>.**
+
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'axes', width='100%', height=630)
+```
+
 ##### 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.

doc/python/bar-charts.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
@@ -85,6 +85,19 @@ fig.show()
 wide_df
 ```
 
+### Bar chart 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 <a class="plotly-red" href="https://plotly.com/dash/">Dash Enterprise</a>.**
+
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'bar-charts', width='100%', height=630)
+```
+
 ### Customize bar chart with Plotly Express
 
 The bar plot can be customized using keyword arguments.

doc/python/getting-started.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: 3.7.3
+    version: 3.7.7
   plotly:
     description: Getting Started with Plotly for Python.
     has_thumbnail: false
@@ -30,8 +30,8 @@ jupyter:
     page_type: u-guide
     permalink: python/getting-started/
     redirect_from:
-      - python/getting_started/
-      - /python/pytables/
+    - python/getting_started/
+    - /python/pytables/
 ---
 
 <!-- #region -->
@@ -80,6 +80,19 @@ fig = go.Figure(data=go.Bar(y=[2, 3, 1]))
 fig.write_html('first_figure.html', auto_open=True)
 ```
 
+### Plotly chart 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 <a class="plotly-red" href="https://plotly.com/dash/">Dash Enterprise</a>.**
+
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'getting-started', width='100%', height=630)
+```
+
 <!-- #region -->
 
 #### Jupyter Notebook Support

doc/python/line-and-scatter.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
@@ -67,6 +67,19 @@ fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species",
 fig.show()
 ```
 
+## Scatter plot 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 <a class="plotly-red" href="https://plotly.com/dash/">Dash Enterprise</a>.**
+
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'line-and-scatter', width='100%', height=630)
+```
+
 ## Line plot with Plotly Express
 
 ```python

doc/python/line-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: 3.7.7
   plotly:
     description: How to make line charts in Python with Plotly. Examples on creating
       and styling line charts in Python with Plotly.
@@ -69,6 +69,19 @@ fig = px.line(df, x="year", y="lifeExp", color="continent",
 fig.show()
 ```
 
+### Line chart 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 <a class="plotly-red" href="https://plotly.com/dash/">Dash Enterprise</a>.**
+
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'line-charts', width='100%', height=630)
+```
+
 ### Sparklines with Plotly Express
 
 Sparklines are scatter plots inside subplots, with gridlines, axis lines, and ticks removed.

doc/python/plotly-express.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
@@ -72,6 +72,20 @@ The Plotly Express API in general offers the following features:
 * **Trendlines**: `px.scatter` supports [built-in trendlines with accessible model output](/python/linear-fits/).
 * **Animations**: many PX functions support [simple animation support via the `animation_frame` and `animation_group` arguments](/python/animations/).
 
+
+### Plotly Express 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 <a class="plotly-red" href="https://plotly.com/dash/">Dash Enterprise</a>.**
+
+
+```python hide_code=true
+from IPython.display import IFrame
+snippet_url = 'https://dash-gallery.plotly.host/python-docs-dash-snippets/'
+IFrame(snippet_url + 'plotly-express', width='100%', height=630)
+```
+
 ### Gallery
 
 The following set of figures is just a sampling of what can be done with Plotly Express.
@@ -416,4 +430,4 @@ df = px.data.election()
 fig = px.scatter_ternary(df, a="Joly", b="Coderre", c="Bergeron", color="winner", size="total", hover_name="district",
                    size_max=15, color_discrete_map = {"Joly": "blue", "Bergeron": "green", "Coderre":"red"} )
 fig.show()
-```
+```