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Nov 20, 2020
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5 new dash snippets #2919

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27 changes: 25 additions & 2 deletions doc/python/animations.md
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Expand Up @@ -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
Expand All @@ -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.
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21 changes: 17 additions & 4 deletions doc/python/candlestick-charts.md
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Expand Up @@ -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
Expand All @@ -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
Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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/
17 changes: 15 additions & 2 deletions doc/python/figure-structure.md
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Expand Up @@ -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
Expand All @@ -20,7 +20,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
version: 3.7.7
version: 3.7.6
plotly:
description: The structure of a figure - data, traces and layout explained.
display_as: file_settings
Expand Down Expand Up @@ -49,6 +49,19 @@ print(fig)
fig.show()
```

### Accessing figure structures 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 + 'figure-structure', width='100%', height=630)
```

### Figures as Trees of Attributes

Plotly.js supports inputs adhering to a well-defined schema, whose overall architecture is explained in this page and which is exhaustively documented in the [Figure Reference](/python/reference/index/) (which is itself generated from a [machine-readable JSON representation of the schema](https://raw.githubusercontent.com/plotly/plotly.js/master/dist/plot-schema.json)). Figures are represented as trees with named nodes called "attributes". The root node of the tree has three top-level attributes: `data`, `layout` and `frames` (see below).
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19 changes: 16 additions & 3 deletions doc/python/plot-data-from-csv.md
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Expand Up @@ -5,8 +5,8 @@ jupyter:
text_representation:
extension: .md
format_name: markdown
format_version: "1.1"
jupytext_version: 1.2.0
format_version: '1.2'
jupytext_version: 1.6.0
kernelspec:
display_name: Python 3
language: python
Expand All @@ -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 create charts from csv files with Plotly and Python
display_as: advanced_opt
Expand Down Expand Up @@ -56,6 +56,19 @@ fig = px.line(df, x = 'AAPL_x', y = 'AAPL_y', title='Apple Share Prices over tim
fig.show()
```

### Plot from CSV 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 + 'plot-data-from-csv', width='100%', height=630)
```

### Plot from CSV with `graph_objects`

```python
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17 changes: 15 additions & 2 deletions doc/python/sankey-diagram.md
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Expand Up @@ -6,7 +6,7 @@ jupyter:
extension: .md
format_name: markdown
format_version: '1.2'
jupytext_version: 1.3.1
jupytext_version: 1.6.0
kernel_info:
name: python2
kernelspec:
Expand All @@ -22,7 +22,7 @@ jupyter:
name: python
nbconvert_exporter: python
pygments_lexer: ipython3
version: 3.6.8
version: 3.7.6
plotly:
description: How to make Sankey Diagrams in Python with Plotly.
display_as: basic
Expand Down Expand Up @@ -104,6 +104,19 @@ fig.update_layout(title_text="Energy forecast for 2050<br>Source: Department of
fig.show()
```

### Sankey Diagram 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 + 'sankey-diagram', width='100%', height=630)
```

### Style Sankey Diagram
This example also uses [hovermode](https://plotly.com/python/reference/layout/#layout-hovermode) to enable multiple tooltips.

Expand Down