Merge branch 'master' into pathlib

Author: maresb

CHANGELOG.md

@@ -2,22 +2,28 @@
 All notable changes to this project will be documented in this file.
 This project adheres to [Semantic Versioning](http://semver.org/).
 
-## [4.15.0] - UNRELEASED
 
-### Added
+## [4.14.3] - 2021-01-12
 
 ### Fixed
 
-### Updated
+- `px.timeline()` now allows `hover_data` formatting of start and end times [3018](https://github.com/plotly/plotly.py/pull/3018)
+- Small change to packaging of `plotlywidget` extension for JupyterLab 3 [3021](https://github.com/plotly/plotly.py/pull/3021)
 
+## [4.14.2] - 2021-01-11
 
-## [4.14.2] - UNRELEASED
+### Updated
 
-### Added
+- JupyterLab extensions now compatible with JupyterLab 3.x [3016](https://github.com/plotly/plotly.py/pull/3016)
+- Updated Plotly.js to version 1.58.4. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/v1.58.4/CHANGELOG.md) for more information. These changes are reflected in the auto-generated `plotly.graph_objects` module. Notable changes include:
+  - fixes for rendering 3d plots on recent Safari versions
+  - fixes to inside ticklabels
+  - regression fixes
 
 ### Fixed
 
-### Updated
+- `px.histogram()` Y-axis labels now take into account `histnorm` and `barnorm` [2989](https://github.com/plotly/plotly.py/pull/2989)
+- `px.histogram()` `marginal` and `facet_*` now work correctly together [3014](https://github.com/plotly/plotly.py/pull/3014)
 
 
 ## [4.14.1] - 2020-12-09

README.md

@@ -37,9 +37,9 @@ Our recommended IDE for Plotly’s Python graphing library is Dash Enterprise’
 
 ## Quickstart
 
-`pip install plotly==4.14.1`
+`pip install plotly==4.14.3`
 
-Inside [Jupyter notebook](https://jupyter.org/install) (installable with `pip install "notebook>=5.3" "ipywidgets>=7.2"`):
+Inside [Jupyter notebook](https://jupyter.org/install) (installable with `pip install "notebook>=5.3" "ipywidgets>=7.5"`):
 
 ```python
 import plotly.graph_objects as go
@@ -86,53 +86,53 @@ Built on top of [plotly.js](https://github.com/plotly/plotly.js), `plotly.py` is
 plotly.py may be installed using pip...
 
 ```
-pip install plotly==4.14.1
+pip install plotly==4.14.3
 ```
 
 or conda.
 
 ```
-conda install -c plotly plotly=4.14.1
+conda install -c plotly plotly=4.14.3
 ```
 
 ### Jupyter Notebook Support
 
 For use in the Jupyter Notebook, install the `notebook` and `ipywidgets`
-packages using pip...
+packages using `pip`:
 
 ```
-pip install "notebook>=5.3" "ipywidgets==7.5"
+pip install "notebook>=5.3" "ipywidgets>=7.5"
 ```
 
-or conda.
+or `conda`:
 
 ```
-conda install "notebook>=5.3" "ipywidgets=7.5"
+conda install "notebook>=5.3" "ipywidgets>=7.5"
 ```
 
-### JupyterLab Support (Python 3.5+)
+### JupyterLab Support
 
 For use in JupyterLab, install the `jupyterlab` and `ipywidgets`
-packages using pip...
+packages using `pip`:
 
 ```
-pip install jupyterlab "ipywidgets==7.5"
+pip install jupyterlab "ipywidgets>=7.5"
 ```
 
-or conda.
+or `conda`:
 
 ```
-conda install jupyterlab "ipywidgets=7.5"
+conda install jupyterlab "ipywidgets>=7.5"
 ```
 
 Then run the following commands to install the required JupyterLab extensions (note that this will require [`node`](https://nodejs.org/) to be installed):
 
 ```
 # Basic JupyterLab renderer support
-jupyter labextension install jupyterlab-plotly@4.14.1
+jupyter labextension install jupyterlab-plotly@4.14.3
 
 # OPTIONAL: Jupyter widgets extension for FigureWidget support
-jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.14.1
+jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.14.3
 ```
 
 Please check out our [Troubleshooting guide](https://plotly.com/python/troubleshooting/) if you run into any problems with JupyterLab.

binder/requirements.txt

@@ -1,5 +1,5 @@
 jupytext
-plotly==4.14.1
+plotly==4.14.3
 jupyter
 notebook
 pandas==1.0.3

contributing.md

@@ -280,7 +280,7 @@ pytest  packages/python/plotly/plotly/tests/test_core/
 pytest plotly/tests/test_plotly/test_plot.py
 ```
 
-or for a specfic test function
+or for a specific test function
 
 ```bash
 pytest plotly/tests/test_plotly/test_plot.py::test_function

doc/apidoc/conf.py

@@ -28,7 +28,7 @@
 # The short X.Y version
 version = ""
 # The full version, including alpha/beta/rc tags
-release = "4.14.1"
+release = "4.14.3"
 
 
 # -- General configuration ---------------------------------------------------

doc/python/builtin-colorscales.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: A reference for the built-in named continuous (sequential, diverging
       and cylclical) color scales in Plotly.
@@ -74,6 +74,19 @@ import plotly.express as px
 print(px.colors.sequential.Plasma)
 ```
 
+### Continuous Color Scales 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 + 'builtin-colorscales', width='100%', height=630)
+```
+
 ### Built-In Sequential Color scales
 
 A collection of predefined sequential colorscales is provided in the `plotly.colors.sequential` module. Sequential color scales are appropriate for most continuous data, but in some cases it can be helpful to use a diverging or cyclical color scale (see below).

doc/python/getting-started.md

@@ -56,16 +56,16 @@ We also encourage you to join the [Plotly Community Forum](http://community.plot
 
 ### Installation
 
-`plotly` may be installed using pip...
+`plotly` may be installed using `pip`:
 
 ```
-$ pip install plotly==4.14.1
+$ pip install plotly==4.14.3
 ```
 
-or conda.
+or `conda`:
 
 ```
-$ conda install -c plotly plotly=4.14.1
+$ conda install -c plotly plotly=4.14.3
 ```
 
 This package contains everything you need to write figures to standalone HTML files.
@@ -98,16 +98,16 @@ IFrame(snippet_url + 'getting-started', width='100%', height=630)
 #### Jupyter Notebook Support
 
 For use in the classic [Jupyter Notebook](https://jupyter.org/), install the `notebook` and `ipywidgets`
-packages using pip...
+packages using `pip`:
 
 ```
-$ pip install "notebook>=5.3" "ipywidgets>=7.2"
+$ pip install "notebook>=5.3" "ipywidgets>=7.5"
 ```
 
-or conda.
+or `conda`:
 
 ```
-$ conda install "notebook>=5.3" "ipywidgets>=7.2"
+$ conda install "notebook>=5.3" "ipywidgets>=7.5"
 ```
 
 These packages contain everything you need to run a Jupyter notebook...
@@ -138,29 +138,29 @@ fig
 
 See [_Displaying Figures in Python_](/python/renderers/) for more information on the renderers framework, and see [_Plotly FigureWidget Overview_](/python/figurewidget/) for more information on using `FigureWidget`.
 
-#### JupyterLab Support (Python 3.5+)
+#### JupyterLab Support
 
 For use in [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/), install the `jupyterlab` and `ipywidgets`
-packages using pip...
+packages using `pip`:
 
 ```
 $ pip install jupyterlab "ipywidgets>=7.5"
 ```
 
-or conda.
+or `conda`:
 
 ```
-$ conda install jupyterlab "ipywidgets=7.5"
+$ conda install jupyterlab "ipywidgets>=7.5"
 ```
 
 Then run the following commands to install the required JupyterLab extensions (note that this will require [`node`](https://nodejs.org/) to be installed):
 
 ```
 # JupyterLab renderer support
-jupyter labextension install jupyterlab-plotly@4.14.1
+jupyter labextension install jupyterlab-plotly@4.14.3
 
 # OPTIONAL: Jupyter widgets extension
-jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.14.1
+jupyter labextension install @jupyter-widgets/jupyterlab-manager plotlywidget@4.14.3
 ```
 
 These packages contain everything you need to run JupyterLab...

doc/python/heatmaps.md

@@ -102,7 +102,7 @@ fig.show()
 
 ### Heatmap with Categorical Axis Labels
 
-In this example we also show how to ignore [hovertext](https://plotly.com/python/hover-text-and-formatting/) when we have [missing values](https://plotly.com/python/missing_values) in the data by setting the [hoverongaps](https://plotly.com/python/reference/heatmap/#heatmap-hoverongaps) to False.
+In this example we also show how to ignore [hovertext](https://plotly.com/python/hover-text-and-formatting/) when we have missing values in the data by setting the [hoverongaps](https://plotly.com/python/reference/heatmap/#heatmap-hoverongaps) to False.
 
 ```python
 import plotly.graph_objects as go

doc/python/horizontal-vertical-shapes.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 add annotated horizontal and vertical lines in Python.
     display_as: file_settings
@@ -67,6 +67,19 @@ fig.add_hrect(y0=0.9, y1=2.6, line_width=0, fillcolor="red", opacity=0.2)
 fig.show()
 ```
 
+#### Horizontal and vertical lines 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 + 'horizontal-vertical-shapes', width='100%', height=630)
+```
+
 #### Adding Text Annotations
 
 [Text annotations](/python/text-and-annotations) can optionally be added to an autoshape

doc/python/hover-text-and-formatting.md

@@ -34,7 +34,7 @@ jupyter:
 
 ### Hover Labels
 
-One of the most deceptively-power features of interactive visualization using Plotly is the ability for the user to reveal more information about a data point by moving their mouse cursor over the point and having a hover label appear.
+One of the most deceptively-powerful features of interactive visualization using Plotly is the ability for the user to reveal more information about a data point by moving their mouse cursor over the point and having a hover label appear.
 
 There are three hover modes available in Plotly. The default setting is `layout.hovermode='closest'`, wherein a single hover label appears for the point directly underneath the cursor.
 

doc/python/imshow.md

@@ -450,7 +450,7 @@ from skimage.data import image_fetcher
 path = image_fetcher.fetch('data/cells.tif')
 data = io.imread(path)
 img = data[25:40]
-fig = px.imshow(img, animation_frame=0, binary_string=True, labels=dict(animation_frame="yo"))
+fig = px.imshow(img, animation_frame=0, binary_string=True, labels=dict(animation_frame="slice"))
 fig.show()
 ```
 

doc/python/interactive-html-export.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: Plotly allows you to save interactive HTML versions of your figures
       to your local disk.
@@ -56,10 +56,23 @@ fig.write_html("path/to/file.html")
 By default, the resulting HTML file is a fully self-contained HTML file which can be uploaded to a web server or shared via email or other file-sharing mechanisms. The downside to this approach is that the file is very large (5Mb+) because it contains an inlined copy of the Plotly.js library required to make the figure interactive. This can be controlled via the `include_plotlyjs` argument (see below).
 
 
+### HTML 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 <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 + 'interactive-html-export', width='100%', height=630)
+```
+
 ### Full Parameter Documentation
 
 ```python
 import plotly.graph_objects as go
 
 help(go.Figure.write_html)
-```
+```