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Merge pull request #3668 from plotly/px_area_fill
add pattern fills to px.area
2 parents 2b96fde + 2dedf02 commit 4bd23fe

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Diff for: CHANGELOG.md

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This project adheres to [Semantic Versioning](http://semver.org/).
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## [5.7.0] - UNRELEASED
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### Added
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- added `pattern_shape` options to `px.area()` [#3668](https://github.com/plotly/plotly.py/issues/3668)
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### Updated
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- Updated Plotly.js to from version 2.9.0 to version 2.11.1. See the [plotly.js CHANGELOG](https://github.com/plotly/plotly.js/blob/master/CHANGELOG.md#2111----2022-03-15) for more information. Notable changes include:
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- Add `fillpattern` options to `scatter` trace
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- Various JS-specific improvements such as MathJax 3.0 support
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## [5.6.0] - 2022-02-09
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### Updated

Diff for: doc/python/filled-area-plots.md

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text_representation:
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extension: .md
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format_name: markdown
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format_version: '1.2'
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jupytext_version: 1.6.0
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format_version: '1.3'
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jupytext_version: 1.13.7
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kernelspec:
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display_name: Python 3
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display_name: Python 3 (ipykernel)
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language: python
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name: python3
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language_info:
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.7.6
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version: 3.9.7
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plotly:
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description: How to make filled area plots in Python with Plotly.
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display_as: basic
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```python
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import plotly.express as px
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df = px.data.gapminder()
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fig = px.area(df, x="year", y="pop", color="continent",
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line_group="country")
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fig = px.area(df, x="year", y="pop", color="continent", line_group="country")
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fig.show()
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```
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IFrame(snippet_url + 'filled-area-plots', width='100%', height=1200)
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```
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### Pattern Fills
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*New in v5.0*
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Area charts afford the use of [patterns (also known as hatching or texture)](/python/pattern-hatching-texture/) in addition to color:
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```python
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import plotly.express as px
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df = px.data.medals_long()
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fig = px.area(df, x="medal", y="count", color="nation",
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pattern_shape="nation", pattern_shape_sequence=[".", "x", "+"])
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fig.show()
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```
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<!-- #region tags=[] -->
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### Filled area chart with plotly.graph_objects
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#### Basic Overlaid Area Chart
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<!-- #endregion -->
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```python
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```python tags=[]
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import plotly.graph_objects as go
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fig = go.Figure()

Diff for: doc/python/pattern-hatching-texture.md

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text_representation:
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extension: .md
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format_name: markdown
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format_version: '1.2'
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jupytext_version: 1.4.2
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format_version: '1.3'
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jupytext_version: 1.13.7
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kernelspec:
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display_name: Python 3
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display_name: Python 3 (ipykernel)
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language: python
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name: python3
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language_info:
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name: python
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nbconvert_exporter: python
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pygments_lexer: ipython3
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version: 3.7.7
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version: 3.9.7
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plotly:
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description: How to use patterns (also known as hatching or texture) with bar
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charts.
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*New in v5.0*
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[Bar charts](/python/bar-charts/), [histograms](/python/histograms/) and [polar bar charts](/python/wind-rose-charts/) have large markers which support not only a fill color, but also an optional **pattern** (also known as "hatching" or "texture"). This can be used for a variety of reasons:
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[Bar charts](/python/bar-charts/), [histograms](/python/histograms/), [polar bar charts](/python/wind-rose-charts/) and [area charts](/python/filled-area-plots/) have large markers or areas which support not only a fill color, but also an optional **pattern** (also known as "hatching" or "texture"). This can be used for a variety of reasons:
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* to double-encode variables (i.e. using both color and pattern) to improve accessibility for visually-impaired end-users
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* to encode an additional variable beyond just using color
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* to make charts that are easier to print in black and white
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### Patterned Bar Charts with Plotly Express
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### Patterned Charts with Plotly Express
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the `px.bar()`, `px.histogram()` and `px.bar_polar()` functions support the `pattern_shape` argument. In the chart below, we double-encode `nation` using color and pattern:
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the `px.bar()`, `px.histogram()`, `px.bar_polar()` and `px.area()` functions support the `pattern_shape` argument. In the chart below, we double-encode `nation` using color and pattern:
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```python
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import plotly.express as px
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fig.show()
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```
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```python
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import plotly.express as px
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df = px.data.medals_long()
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fig = px.area(df, x="medal", y="count", color="nation", pattern_shape="nation")
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fig.show()
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```
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In the chart below we use `px.histogram()` instead of `px.bar()` to aggregate multiple values together, and encode one variable (sex) using both color and x-position and another (smoker) using patterns:
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```python

Diff for: packages/python/plotly/plotly/express/_chart_types.py

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y=None,
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line_group=None,
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color=None,
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pattern_shape=None,
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symbol=None,
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hover_name=None,
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hover_data=None,
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labels=None,
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color_discrete_sequence=None,
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color_discrete_map=None,
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pattern_shape_sequence=None,
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pattern_shape_map=None,
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symbol_sequence=None,
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symbol_map=None,
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markers=False,

Diff for: packages/python/plotly/plotly/express/_core.py

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if variable == "dash":
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arg_name = "line_dash"
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vprefix = "line_dash"
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if variable == "pattern":
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if variable in ["pattern", "shape"]:
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arg_name = "pattern_shape"
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vprefix = "pattern_shape"
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if args[vprefix + "_map"] == "identity":
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grouped_attrs.append("marker.symbol")
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if "pattern_shape" in args:
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grouped_attrs.append("marker.pattern.shape")
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if constructor in [go.Scatter]:
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grouped_attrs.append("fillpattern.shape")
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else:
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grouped_attrs.append("marker.pattern.shape")
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if "orientation" in args:
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has_x = args["x"] is not None
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