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Prefer scatterplot over plt.scatter in examples and plotters #2069

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merged 2 commits into from
Aug 20, 2020
Merged

Prefer scatterplot over plt.scatter in examples and plotters #2069

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2478956
use scatterplot instead of plt.scatter
MaozGelbart May 11, 2020
92a394e
Merge branch 'master' into jointplot_scatter
mwaskom Aug 18, 2020
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46 changes: 25 additions & 21 deletions seaborn/axisgrid.py
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Original file line number Diff line number Diff line change
Expand Up @@ -543,15 +543,15 @@ def __init__(
:context: close-figs

>>> g = sns.FacetGrid(tips, col="time", row="smoker")
>>> g = g.map(plt.scatter, "total_bill", "tip", edgecolor="w")
>>> g = g.map(sns.scatterplot, "total_bill", "tip")

Assign one of the variables to the color of the plot elements:

.. plot::
:context: close-figs

>>> g = sns.FacetGrid(tips, col="time", hue="smoker")
>>> g = (g.map(plt.scatter, "total_bill", "tip", edgecolor="w")
>>> g = (g.map(sns.scatterplot, "total_bill", "tip")
... .add_legend())

Change the height and aspect ratio of each facet:
Expand All @@ -575,10 +575,10 @@ def __init__(
.. plot::
:context: close-figs

>>> kws = dict(s=50, linewidth=.5, edgecolor="w")
>>> kws = dict(s=50, linewidth=.5)
>>> g = sns.FacetGrid(tips, col="sex", hue="time", palette="Set1",
... hue_order=["Dinner", "Lunch"])
>>> g = (g.map(plt.scatter, "total_bill", "tip", **kws)
>>> g = (g.map(sns.scatterplot, "total_bill", "tip", **kws)
... .add_legend())

Use a dictionary mapping hue levels to colors:
Expand All @@ -589,7 +589,7 @@ def __init__(
>>> pal = dict(Lunch="seagreen", Dinner="gray")
>>> g = sns.FacetGrid(tips, col="sex", hue="time", palette=pal,
... hue_order=["Dinner", "Lunch"])
>>> g = (g.map(plt.scatter, "total_bill", "tip", **kws)
>>> g = (g.map(sns.scatterplot, "total_bill", "tip", **kws)
... .add_legend())

Additionally use a different marker for the hue levels:
Expand All @@ -600,7 +600,7 @@ def __init__(
>>> g = sns.FacetGrid(tips, col="sex", hue="time", palette=pal,
... hue_order=["Dinner", "Lunch"],
... hue_kws=dict(marker=["^", "v"]))
>>> g = (g.map(plt.scatter, "total_bill", "tip", **kws)
>>> g = (g.map(sns.scatterplot, "total_bill", "tip", **kws)
... .add_legend())

"Wrap" a column variable with many levels into the rows:
Expand Down Expand Up @@ -652,7 +652,8 @@ def __init__(
:context: close-figs

>>> g = sns.FacetGrid(tips, col="smoker", row="sex")
>>> g = (g.map(plt.scatter, "total_bill", "tip", color="g", **kws)
>>> g = (g.map(sns.scatterplot, "total_bill", "tip",
... color="g", **kws)
... .set_axis_labels("Total bill (US Dollars)", "Tip"))

Set other attributes that are shared across the facetes:
Expand All @@ -661,7 +662,8 @@ def __init__(
:context: close-figs

>>> g = sns.FacetGrid(tips, col="smoker", row="sex")
>>> g = (g.map(plt.scatter, "total_bill", "tip", color="r", **kws)
>>> g = (g.map(sns.scatterplot, "total_bill", "tip",
... color="r", **kws)
... .set(xlim=(0, 60), ylim=(0, 12),
... xticks=[10, 30, 50], yticks=[2, 6, 10]))

Expand All @@ -681,7 +683,8 @@ def __init__(

>>> g = sns.FacetGrid(tips, col="smoker", row="sex",
... margin_titles=True)
>>> g = (g.map(plt.scatter, "total_bill", "tip", color="m", **kws)
>>> g = (g.map(sns.scatterplot, "total_bill", "tip",
... color="m", **kws)
... .set(xlim=(0, 60), ylim=(0, 12),
... xticks=[10, 30, 50], yticks=[2, 6, 10])
... .fig.subplots_adjust(wspace=.05, hspace=.05))
Expand Down Expand Up @@ -1242,7 +1245,7 @@ def __init__(
>>> import seaborn as sns; sns.set()
>>> iris = sns.load_dataset("iris")
>>> g = sns.PairGrid(iris)
>>> g = g.map(plt.scatter)
>>> g = g.map(sns.scatterplot)

Show a univariate distribution on the diagonal:

Expand All @@ -1251,7 +1254,7 @@ def __init__(

>>> g = sns.PairGrid(iris)
>>> g = g.map_diag(plt.hist)
>>> g = g.map_offdiag(plt.scatter)
>>> g = g.map_offdiag(sns.scatterplot)

(It's not actually necessary to catch the return value every time,
as it is the same object, but it makes it easier to deal with the
Expand All @@ -1264,7 +1267,7 @@ def __init__(

>>> g = sns.PairGrid(iris, hue="species")
>>> g = g.map_diag(plt.hist)
>>> g = g.map_offdiag(plt.scatter)
>>> g = g.map_offdiag(sns.scatterplot)
>>> g = g.add_legend()

Use a different style to show multiple histograms:
Expand All @@ -1274,7 +1277,7 @@ def __init__(

>>> g = sns.PairGrid(iris, hue="species")
>>> g = g.map_diag(plt.hist, histtype="step", linewidth=3)
>>> g = g.map_offdiag(plt.scatter)
>>> g = g.map_offdiag(sns.scatterplot)
>>> g = g.add_legend()

Plot a subset of variables
Expand All @@ -1283,7 +1286,7 @@ def __init__(
:context: close-figs

>>> g = sns.PairGrid(iris, vars=["sepal_length", "sepal_width"])
>>> g = g.map(plt.scatter)
>>> g = g.map(sns.scatterplot)

Pass additional keyword arguments to the functions

Expand All @@ -1292,7 +1295,7 @@ def __init__(

>>> g = sns.PairGrid(iris)
>>> g = g.map_diag(plt.hist, edgecolor="w")
>>> g = g.map_offdiag(plt.scatter, edgecolor="w", s=40)
>>> g = g.map_offdiag(sns.scatterplot)

Use different variables for the rows and columns:

Expand All @@ -1302,7 +1305,7 @@ def __init__(
>>> g = sns.PairGrid(iris,
... x_vars=["sepal_length", "sepal_width"],
... y_vars=["petal_length", "petal_width"])
>>> g = g.map(plt.scatter)
>>> g = g.map(sns.scatterplot)

Use different functions on the upper and lower triangles:

Expand All @@ -1321,7 +1324,7 @@ def __init__(

>>> g = sns.PairGrid(iris, hue="species", palette="Set2",
... hue_kws={"marker": ["o", "s", "D"]})
>>> g = g.map(sns.scatterplot, linewidths=1, edgecolor="w", s=40)
>>> g = g.map(sns.scatterplot)
>>> g = g.add_legend()

"""
Expand Down Expand Up @@ -2362,9 +2365,8 @@ def jointplot(
:context: close-figs

>>> g = sns.jointplot(x="petal_length", y="sepal_length", data=iris,
... marginal_kws=dict(bins=15),
... annot_kws=dict(stat="r"),
... s=40, edgecolor="w", linewidth=1)
... marginal_kws=dict(bins=15, rug=True),
... marker="+")

"""
# Avoid circular import
Expand Down Expand Up @@ -2401,8 +2403,10 @@ def jointplot(
# Plot the data using the grid
if kind == "scatter":

from .relational import scatterplot # Avoid circular import

joint_kws.setdefault("color", color)
grid.plot_joint(plt.scatter, **joint_kws)
grid.plot_joint(scatterplot, **joint_kws)

marginal_kws.setdefault("kde", False)
marginal_kws.setdefault("color", color)
Expand Down