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Rework docs about scatter plots #7169

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Oct 17, 2022
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Rework docs about scatter plots #7169

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e783df3
Rework docs about scatter
Illviljan Oct 16, 2022
21b3493
Update plotting.rst
Illviljan Oct 16, 2022
03a189d
Update plotting.rst
Illviljan Oct 16, 2022
a63a0f1
Show that dataarray scatter also exists.
Illviljan Oct 16, 2022
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55 changes: 45 additions & 10 deletions doc/user-guide/plotting.rst
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Expand Up @@ -756,14 +756,32 @@ Consider this dataset

.. ipython:: python

ds = xr.tutorial.scatter_example_dataset()
ds = xr.tutorial.scatter_example_dataset(seed=42)
ds


Scatter
~~~~~~~

Suppose we want to scatter ``A`` against ``B``
Let's plot the ``A`` DataArray as a function of the ``y`` coord

.. ipython:: python
:okwarning:

ds.A

@savefig da_A_y.png
ds.A.plot.scatter(x="y")

Same plot can be displayed using the dataset:

.. ipython:: python
:okwarning:

@savefig ds_A_y.png
ds.plot.scatter(x="y", y="A")

Now suppose we want to scatter the ``A`` DataArray against the ``B`` DataArray

.. ipython:: python
:okwarning:
Expand All @@ -779,17 +797,19 @@ The ``hue`` kwarg lets you vary the color by variable value
@savefig ds_hue_scatter.png
ds.plot.scatter(x="A", y="B", hue="w")

When ``hue`` is specified, a colorbar is added for numeric ``hue`` DataArrays by
default and a legend is added for non-numeric ``hue`` DataArrays (as above).
You can force a legend instead of a colorbar by setting ``hue_style='discrete'``.
Additionally, the boolean kwarg ``add_guide`` can be used to prevent the display of a legend or colorbar (as appropriate).
You can force a legend instead of a colorbar by setting ``add_legend=True, add_colorbar=False``.

.. ipython:: python
:okwarning:

ds = ds.assign(w=[1, 2, 3, 5])
@savefig ds_discrete_legend_hue_scatter.png
ds.plot.scatter(x="A", y="B", hue="w", hue_style="discrete")
ds.plot.scatter(x="A", y="B", hue="w", add_legend=True, add_colorbar=False)

.. ipython:: python
:okwarning:

@savefig ds_discrete_colorbar_hue_scatter.png
ds.plot.scatter(x="A", y="B", hue="w", add_legend=False, add_colorbar=True)

The ``markersize`` kwarg lets you vary the point's size by variable value.
You can additionally pass ``size_norm`` to control how the variable's values are mapped to point sizes.
Expand All @@ -798,16 +818,31 @@ You can additionally pass ``size_norm`` to control how the variable's values are
:okwarning:

@savefig ds_hue_size_scatter.png
ds.plot.scatter(x="A", y="B", hue="z", hue_style="discrete", markersize="z")
ds.plot.scatter(x="A", y="B", hue="y", markersize="z")

The ``z`` kwarg lets you plot the data along the z-axis as well.

.. ipython:: python
:okwarning:

@savefig ds_hue_size_scatter_z.png
ds.plot.scatter(x="A", y="B", z="z", hue="y", markersize="x")

Faceting is also possible

.. ipython:: python
:okwarning:

@savefig ds_facet_scatter.png
ds.plot.scatter(x="A", y="B", col="x", row="z", hue="w", hue_style="discrete")
ds.plot.scatter(x="A", y="B", hue="y", markersize="x", row="x", col="w")

And adding the z-axis

.. ipython:: python
:okwarning:

@savefig ds_facet_scatter_z.png
ds.plot.scatter(x="A", y="B", z="z", hue="y", markersize="x", row="x", col="w")

For more advanced scatter plots, we recommend converting the relevant data variables
to a pandas DataFrame and using the extensive plotting capabilities of ``seaborn``.
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