merging doc-prod to master

Author: nicolaskruchten

.circleci/create_conda_optional_env.sh

@@ -19,5 +19,9 @@ if [ ! -d $HOME/miniconda/envs/circle_optional ]; then
 requests nbformat six retrying psutil pandas decorator pytest mock nose poppler xarray scikit-image ipython jupyter ipykernel ipywidgets
 
     # Install orca into environment
+<<<<<<< HEAD
     $HOME/miniconda/bin/conda install --yes -n circle_optional -c plotly plotly-orca==1.3.1
+=======
+    $HOME/miniconda/bin/conda install --yes -n circle_optional -c plotly plotly-orca==1.2.1
+>>>>>>> doc-prod
 fi

binder/requirements.txt

@@ -14,3 +14,4 @@ networkx
 scikit-image
 datashader
 pyarrow
+cufflinks==0.17.3

doc/Makefile

@@ -30,6 +30,7 @@ $(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 $@
 
 $(HTML_DIR)/2019-07-03-%.html: $(IPYNB_DIR)/%.ipynb

doc/python/2D-Histogram.md

@@ -71,7 +71,7 @@ fig = go.Figure(go.Histogram2d(x=x, y=y, histnorm='probability',
 fig.show()
 ```
 ### Sharing bin settings between 2D Histograms
-This example shows how to use [bingroup](https://plot.ly/python/reference/#histogram-bingroup) attribute to have a compatible bin settings for both histograms. To define `start`, `end` and `size` value of x-axis and y-axis seperatly, set [ybins](https://plot.ly/python/reference/#histogram2dcontour-ybins) and `xbins`.
+This example shows how to use [bingroup](https://plotly.com/python/reference/#histogram-bingroup) attribute to have a compatible bin settings for both histograms. To define `start`, `end` and `size` value of x-axis and y-axis seperatly, set [ybins](https://plotly.com/python/reference/#histogram2dcontour-ybins) and `xbins`.
 
 ```python
 import plotly.graph_objects as go
@@ -170,4 +170,4 @@ fig.show()
 ```
 
 #### Reference
-See https://plot.ly/python/reference/#histogram2d for more information and chart attribute options!
+See https://plotly.com/python/reference/#histogram2d for more information and chart attribute options!

doc/python/2d-histogram-contour.md

@@ -185,4 +185,4 @@ fig.show()
 ```
 
 #### Reference
-See https://plot.ly/python/reference/#histogram2dcontour for more information and chart attribute options!
+See https://plotly.com/python/reference/#histogram2dcontour for more information and chart attribute options!

doc/python/3d-axes.md

@@ -39,7 +39,7 @@ jupyter:
 attributes such as `xaxis`, `yaxis` and `zaxis` parameters, in order to
 set the range, title, ticks, color etc. of the axes.
 
-For creating 3D charts, see [this page](https://plot.ly/python/3d-charts/).
+For creating 3D charts, see [this page](https://plotly.com/python/3d-charts/).
 
 ```python
 import plotly.graph_objects as go
@@ -141,7 +141,7 @@ fig.show()
 import plotly.graph_objects as go
 import numpy as np
 
-# Define random surface
+# Define random surface
 N = 50
 fig = go.Figure(data=[go.Mesh3d(x=(60*np.random.randn(N)),
                    y=(25*np.random.randn(N)),
@@ -150,7 +150,7 @@ fig = go.Figure(data=[go.Mesh3d(x=(60*np.random.randn(N)),
                    color='rgba(100,22,200,0.5)'
                   )])
 
-# Different types of customized ticks
+# Different types of customized ticks
 fig.update_layout(scene = dict(
                     xaxis = dict(
                         ticktext= ['TICKS','MESH','PLOTLY','PYTHON'],
@@ -184,7 +184,7 @@ fig = go.Figure(data=[go.Mesh3d(x=(30*np.random.randn(N)),
                    opacity=0.5,)])
 
 
-# xaxis.backgroundcolor is used to set background color
+# xaxis.backgroundcolor is used to set background color
 fig.update_layout(scene = dict(
                     xaxis = dict(
                          backgroundcolor="rgb(200, 200, 230)",

doc/python/3d-bubble-charts.md

@@ -108,7 +108,7 @@ fig = go.Figure(data=go.Scatter3d(
     mode = 'markers',
     marker = dict(
         sizemode = 'diameter',
-        sizeref = 750, # info on sizeref: https://plot.ly/python/reference/#scatter-marker-sizeref
+        sizeref = 750, # info on sizeref: https://plotly.com/python/reference/#scatter-marker-sizeref
         size = planet_diameter,
         color = planet_colors,
         )
@@ -147,7 +147,7 @@ fig = go.Figure(go.Scatter3d(
     mode = 'markers',
     marker = dict(
         sizemode = 'diameter',
-        sizeref = 750, # info on sizeref: https://plot.ly/python/reference/#scatter-marker-sizeref
+        sizeref = 750, # info on sizeref: https://plotly.com/python/reference/#scatter-marker-sizeref
         size = planet_diameter,
         color = temperatures,
         colorbar_title = 'Mean<br>Temperature',
@@ -167,4 +167,4 @@ fig.show()
 
 #### Reference
 
-See https://plot.ly/python/reference/#scatter3d and https://plot.ly/python/reference/#scatter-marker-sizeref <br>for more information and chart attribute options!
+See https://plotly.com/python/reference/#scatter3d and https://plotly.com/python/reference/#scatter-marker-sizeref <br>for more information and chart attribute options!

doc/python/3d-camera-controls.md

@@ -290,4 +290,4 @@ fig.show()
 #### Reference
 
 
-See https://plot.ly/python/reference/#layout-scene-camera for more information and chart attribute options!
+See https://plotly.com/python/reference/#layout-scene-camera for more information and chart attribute options!

doc/python/3d-isosurface-plots.md

@@ -235,5 +235,5 @@ fig.show()
 ```
 
 #### Reference
-See https://plot.ly/python/reference/#isosurface for more information and chart attribute options!
+See https://plotly.com/python/reference/#isosurface for more information and chart attribute options!
 

doc/python/3d-line-plots.md

@@ -120,4 +120,4 @@ fig.show()
 
 #### Reference
 
-See https://plot.ly/python/reference/#scatter3d-marker-line for more information and chart attribute options!
+See https://plotly.com/python/reference/#scatter3d-marker-line for more information and chart attribute options!