DOC Ensures that manhattan_distances passes numpydoc validation (#22139)

Micky774 · thomasjpfan · web-flow · commit ff09c8a579b1 · 2022-01-10T17:49:07.000-05:00
Co-authored-by: Thomas J. Fan &lt;thomasjpfan@gmail.com&gt;
diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py
@@ -804,9 +804,11 @@ def manhattan_distances(X, Y=None, *, sum_over_features=True):
     Parameters
     ----------
     X : array-like of shape (n_samples_X, n_features)
+        An array where each row is a sample and each column is a feature.
 
     Y : array-like of shape (n_samples_Y, n_features), default=None
-        If `None`, uses `Y=X`.
+        An array where each row is a sample and each column is a feature.
+        If `None`, method uses `Y=X`.
 
     sum_over_features : bool, default=True
         If True the function returns the pairwise distance matrix
diff --git a/sklearn/tests/test_docstrings.py b/sklearn/tests/test_docstrings.py
@@ -127,7 +127,6 @@
     "sklearn.metrics.pairwise.haversine_distances",
     "sklearn.metrics.pairwise.kernel_metrics",
     "sklearn.metrics.pairwise.laplacian_kernel",
-    "sklearn.metrics.pairwise.manhattan_distances",
     "sklearn.metrics.pairwise.paired_cosine_distances",
     "sklearn.metrics.pairwise.paired_distances",
     "sklearn.metrics.pairwise.paired_euclidean_distances",
