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Unverified Commit 77961b43 authored by Alistair Miles's avatar Alistair Miles Committed by GitHub
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Add note about plotly and dollarmath incompatibility (#1674)


Co-authored-by: default avatarChris Holdgraf <choldgraf@gmail.com>
Co-authored-by: default avatarChris Holdgraf <choldgraf@berkeley.edu>
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%% Cell type:markdown id: tags:
# Interactive data visualizations
Jupyter Notebook has support for many kinds of interactive outputs, including
the ipywidgets ecosystem as well as many interactive visualization libraries.
These are supported in Jupyter Book, with the right configuration.
This page has a few common examples.
First off, we'll download a little bit of data
and show its structure:
%% Cell type:code id: tags:
``` python
import plotly.express as px
data = px.data.iris()
data.head()
```
%% Cell type:markdown id: tags:
## Altair
Interactive outputs will work under the assumption that the outputs they produce have
self-contained HTML that works without requiring any external dependencies to load.
See the [`Altair` installation instructions](https://altair-viz.github.io/getting_started/installation.html#installation)
to get set up with Altair. Below is some example output.
%% Cell type:code id: tags:
``` python
import altair as alt
alt.Chart(data=data).mark_point().encode(
x="sepal_width",
y="sepal_length",
color="species",
size='sepal_length'
)
```
%% Cell type:markdown id: tags:
## Plotly
Plotly is another interactive plotting library that provides a high-level API for
visualization. See the [Plotly JupyterLab documentation](https://plotly.com/python/getting-started/#JupyterLab-Support-(Python-3.5+))
to get started with Plotly in the notebook.
```{margin}
Plotly uses [renderers to output different kinds of information](https://plotly.com/python/renderers/)
when you display a plot. Experiment with renderers to get the output you want.
```
Below is some example output.
:::{important}
For these plots to show, it may be necessary to load `require.js`, in your `_config.yml`:
```yaml
sphinx:
config:
html_js_files:
- https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js
```
:::
:::{important}
Including plotly plots in a Jupyter Book page is [currently not compatible](https://github.com/executablebooks/jupyter-book/issues/1528) with the dollarmath syntax extension (mathematical notation written between two "$" characters). If you are trying to include both plotly plots and mathematical notation within the same page, and finding that plotly plots are not being rendered, this may be the cause. Try removing all use of the dollarmath syntax within the page and rebuilding the book.
:::
%% Cell type:code id: tags:
``` python
import plotly.io as pio
import plotly.express as px
import plotly.offline as py
df = px.data.iris()
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species", size="sepal_length")
fig
```
%% Cell type:markdown id: tags:
## Bokeh
Bokeh provides several options for interactive visualizations, and is part of the PyViz ecosystem. See
[the Bokeh with Jupyter documentation](https://docs.bokeh.org/en/latest/docs/user_guide/jupyter.html#userguide-jupyter) to
get started.
Below is some example output. First we'll initialized Bokeh with `output_notebook()`.
This needs to be in a separate cell to give the JavaScript time to load.
%% Cell type:code id: tags:
``` python
from bokeh.plotting import figure, show, output_notebook
output_notebook()
```
%% Cell type:markdown id: tags:
Now we'll make our plot.
%% Cell type:code id: tags:
``` python
p = figure()
p.circle(data["sepal_width"], data["sepal_length"], fill_color=data["species"], size=data["sepal_length"])
show(p)
```
%% Cell type:markdown id: tags:
## ipywidgets
You may also run code for Jupyter Widgets in your document, and the interactive HTML
outputs will embed themselves in your site. See [the ipywidgets documentation](https://ipywidgets.readthedocs.io/en/latest/user_install.html)
for how to get set up in your own environment.
```{admonition} Widgets often need a kernel
Note that `ipywidgets` tend to behave differently from other interactive visualization libraries. They
interact both with Javascript, and with Python. Some functionality in `ipywidgets` may not
work in default Jupyter Book pages (because no Python kernel is running). You may be able to
get around this with [tools for remote kernels, like thebe](https://thebelab.readthedocs.org).
```
Here are some simple widget elements rendered below.
%% Cell type:code id: tags:
``` python
import ipywidgets as widgets
widgets.IntSlider(
value=7,
min=0,
max=10,
step=1,
description='Test:',
disabled=False,
continuous_update=False,
orientation='horizontal',
readout=True,
readout_format='d'
)
```
%% Cell type:code id: tags:
``` python
tab_contents = ['P0', 'P1', 'P2', 'P3', 'P4']
children = [widgets.Text(description=name) for name in tab_contents]
tab = widgets.Tab()
tab.children = children
for ii in range(len(children)):
tab.set_title(ii, f"tab_{ii}")
tab
```
%% Cell type:markdown id: tags:
You can find [a list of existing Jupyter Widgets](https://ipywidgets.readthedocs.io/en/latest/examples/Widget%20List.html)
in the jupyter-widgets documentation.
......
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