Work around Series.agg non-aggregation EstimateAggregator (#2946)

seaborn/_statistics.py

@@ -478,7 +478,12 @@ def __init__(self, estimator, errorbar=None, **boot_kws):
     def __call__(self, data, var):
         """Aggregate over `var` column of `data` with estimate and error interval."""
         vals = data[var]
-        estimate = vals.agg(self.estimator)
+        if callable(self.estimator):
+            # You would think we could pass to vals.agg, and yet:
+            # https://github.com/mwaskom/seaborn/issues/2943
+            estimate = self.estimator(vals)
+        else:
+            estimate = vals.agg(self.estimator)
 
         # Options that produce no error bars
         if self.error_method is None:

tests/test_statistics.py

@@ -499,6 +499,15 @@ def test_name_estimator(self, long_df):
         out = agg(long_df, "x")
         assert out["x"] == long_df["x"].mean()
 
+    def test_custom_func_estimator(self, long_df):
+
+        def func(x):
+            return np.asarray(x).min()
+
+        agg = EstimateAggregator(func)
+        out = agg(long_df, "x")
+        assert out["x"] == func(long_df["x"])
+
     def test_se_errorbars(self, long_df):
 
         agg = EstimateAggregator("mean", "se")