doc-prod merge

Author: nicolaskruchten

doc/Makefile

@@ -23,15 +23,15 @@ all: $(HTML_FILES) $(V3_REDIR_FILES) $(NEXT_REDIR_FILES)
 
 $(IPYNB_DIR)/.mapbox_token: $(MD_DIR)/.mapbox_token
 	@mkdir -p $(IPYNB_DIR)
-	cd $(IPYNB_DIR) && ln -s ../../$<
+	@echo "[symlink]    .mapbox_token"
+	@cd $(IPYNB_DIR) && ln -s ../../$<
 
 $(IPYNB_FILES): $(IPYNB_DIR)/.mapbox_token
 
 $(IPYNB_DIR)/%.ipynb: $(MD_DIR)/%.md
 	@mkdir -p $(IPYNB_DIR)
 	@echo "[jupytext]   $<"
-	@cat what_about_dash.md >> $<
-	@jupytext $< --to notebook --quiet --output $@
+	@cat $< what_about_dash.md | jupytext  --to notebook --quiet --output $@
 
 $(HTML_DIR)/2019-07-03-%.html: $(IPYNB_DIR)/%.ipynb
 	@mkdir -p $(HTML_DIR)

doc/nb.tpl

@@ -11,6 +11,11 @@
 
 {%- endblock header-%}
 
+{% block input_group %}
+    {%- if not cell.metadata.get('hide_code', False) -%}
+        {{ super() }}
+    {%- endif -%}
+{% endblock input_group %}
 
 {%- block footer %}
 {{ super() }}

doc/python/3d-mesh.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.2'
-      jupytext_version: 1.3.0
+      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 make 3D Mesh Plots
     display_as: 3d_charts
@@ -68,6 +68,19 @@ fig = go.Figure(data=[go.Mesh3d(x=x, y=y, z=z,
 fig.show()
 ```
 
+### 3D Mesh 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 style="color: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 + '3d-mesh', width='100%', height=630)
+```
+
 ### Mesh Tetrahedron
 
 In this example we use the `ì`, `j` and `k` parameters to specify manually the geometry of the triangles of the mesh.
@@ -163,4 +176,4 @@ fig.show()
 ```
 
 ## Reference
-See https://plotly.com/python/reference/mesh3d/ for more information and chart attribute options!
+See https://plotly.com/python/reference/mesh3d/ for more information and chart attribute options!

doc/python/3d-scatter-plots.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: 3.6.8
+    version: 3.7.6
   plotly:
     description: How to make 3D scatter plots in Python with Plotly.
     display_as: 3d_charts
@@ -72,6 +72,19 @@ fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
 fig.update_layout(margin=dict(l=0, r=0, b=0, t=0))
 ```
 
+#### 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/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with <a style="color: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 + '3d-scatter-plots', width='100%', height=630)
+```
+
 ### 3D Scatter Plot with go.Scatter3d
 
 #### Basic 3D Scatter Plot

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 <a style="color: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 + '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.

doc/python/box-plots.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 make Box Plots in Python with Plotly.
     display_as: statistical
@@ -60,6 +60,18 @@ fig = px.box(df, x="time", y="total_bill")
 fig.show()
 ```
 
+### Box 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/) & [deploy](https://plotly.com/dash/app-manager/) apps like this with <a style="color: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 + 'box-plots', width='100%', height=630)
+```
+
 ### Display the underlying data
 
 With the `points` argument, display underlying data points with either all points (`all`), outliers only (`outliers`, default), or none of them (`False`).

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 <a style="color: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 + '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/
+For more information on candlestick attributes, see: https://plotly.com/python/reference/candlestick/

doc/python/choropleth-maps.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 make choropleth maps in Python with Plotly.
     display_as: maps
@@ -143,6 +143,18 @@ fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
 fig.show()
 ```
 
+### Choropleth maps 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 style="color: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 + 'choropleth-maps', width='100%', height=630)
+```
+
 ### Discrete Colors
 
 In addition to [continuous colors](/python/colorscales/), we can [discretely-color](/python/discrete-color/) our choropleth maps by setting `color` to a non-numerical column, like the name of the winner of an election.

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 <a style="color: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 + '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!
+See https://plotly.com/python/reference/ for more information and chart attribute options!

doc/python/discrete-color.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 use and configure discrete color sequences, also known as
       categorical or qualitative color scales.
@@ -99,6 +99,18 @@ fig = px.scatter(df, x="total_bill", y="tip", color="size",
 fig.show()
 ```
 
+### Discrete Colors 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 style="color: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 + 'discrete-color', width='100%', height=630)
+```
+
 ### Color Sequences in Plotly Express
 
 By default, Plotly Express will use the color sequence from the active [template](/python/templates/)'s `layout.colorway` attribute, and the default active template is `plotly` which uses the `plotly` color sequence. You can choose any of the following built-in qualitative color sequences from the `px.colors.qualitative` module, however, or define your own.
@@ -240,4 +252,4 @@ This works because just like in `px.colors.qualitative`, all [built-in continuou
 import plotly.express as px
 
 print(px.colors.sequential.Plasma)
-```
+```