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Add inner="median" option to violin plot #3733

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Add inner="median" option to violin plot #3733

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17 changes: 12 additions & 5 deletions seaborn/categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -906,7 +906,7 @@ def plot_violins(
iter_vars = [self.orient, "hue"]
value_var = {"x": "y", "y": "x"}[self.orient]

inner_options = ["box", "quart", "stick", "point", None]
inner_options = ["box", "quart", "median", "stick", "point", None]
_check_argument("inner", inner_options, inner, prefix=True)
_check_argument("density_norm", ["area", "count", "width"], density_norm)

Expand Down Expand Up @@ -1093,16 +1093,22 @@ def vars_to_key(sub_vars):
lines = mpl.collections.LineCollection(segments, **kws)
ax.add_collection(lines, autolim=False)

elif inner.startswith("quart"):
stats = np.percentile(obs, [25, 50, 75])
elif inner.startswith("quart") or inner.startswith("median"):
median_dashes = (2.5, 1)
if inner.startswith("median"):
q = [50]
dashes = [median_dashes]
else:
q = [25, 50, 75]
dashes = [(1.25, .75), median_dashes, (1.25, .75)]
stats = np.percentile(obs, q)
pos0 = np.interp(stats, data[value_var], data[self.orient] - offsets[0])
pos1 = np.interp(stats, data[value_var], data[self.orient] + offsets[1])
pos_pts = np.stack([inv_pos(pos0), inv_pos(pos1)])
val_pts = np.stack([inv_val(stats), inv_val(stats)])
segments = np.stack([pos_pts, val_pts]).transpose(2, 0, 1)
if self.orient == "y":
segments = segments[:, ::-1, :]
dashes = [(1.25, .75), (2.5, 1), (1.25, .75)]
for i, segment in enumerate(segments):
kws = {
"color": linecolor,
Expand Down Expand Up @@ -1810,11 +1816,12 @@ def violinplot(
{palette}
{saturation}
{fill}
inner : {{"box", "quart", "point", "stick", None}}
inner : {{"box", "quart", "median" "point", "stick", None}}
Representation of the data in the violin interior. One of the following:

- `"box"`: draw a miniature box-and-whisker plot
- `"quart"`: show the quartiles of the data
- `"median"`: show the median of the data
- `"point"` or `"stick"`: show each observation
split : bool
Show an un-mirrored distribution, alternating sides when using `hue`.
Expand Down