Fix documentation for DataFrame.corr and Series.corr. (#10493)

Follow-up work to fix documentation from #7141 before the 22.04 release.

Authors:
  - Bradley Dice (https://github.com/bdice)

Approvers:
  - https://github.com/brandon-b-miller

URL: #10493

python/cudf/cudf/core/dataframe.py

@@ -5664,12 +5664,20 @@ def cov(self, **kwargs):
         df._set_column_names_like(self)
         return df
 
-    def corr(self, method="pearson"):
+    def corr(self, method="pearson", min_periods=None):
         """Compute the correlation matrix of a DataFrame.
+
         Parameters
         ----------
         method : {'pearson', 'spearman'}, default 'pearson'
-            The correlation method to use, one of 'pearson' or 'spearman'.
+            Method used to compute correlation:
+
+            - pearson : Standard correlation coefficient
+            - spearman : Spearman rank correlation
+
+        min_periods : int, optional
+            Minimum number of observations required per pair of columns to
+            have a valid result.
 
         Returns
         -------
@@ -5682,6 +5690,10 @@ def corr(self, method="pearson"):
             values = self.rank().values
         else:
             raise ValueError("method must be either 'pearson', 'spearman'")
+
+        if min_periods is not None:
+            raise NotImplementedError("Unsupported argument 'min_periods'")
+
         corr = cupy.corrcoef(values, rowvar=False)
         cols = self._data.to_pandas_index()
         df = DataFrame(cupy.asfortranarray(corr)).set_index(cols)
@@ -5692,6 +5704,7 @@ def corr(self, method="pearson"):
     def to_struct(self, name=None):
         """
         Return a struct Series composed of the columns of the DataFrame.
+
         Parameters
         ----------
         name: optional

python/cudf/cudf/core/series.py

@@ -2413,6 +2413,19 @@ def corr(self, other, method="pearson", min_periods=None):
         """Calculates the sample correlation between two Series,
         excluding missing values.
 
+        Parameters
+        ----------
+        other : Series
+            Series with which to compute the correlation.
+        method : {'pearson', 'spearman'}, default 'pearson'
+            Method used to compute correlation:
+
+            - pearson : Standard correlation coefficient
+            - spearman : Spearman rank correlation
+
+        min_periods : int, optional
+            Minimum number of observations needed to have a valid result.
+
         Examples
         --------
         >>> import cudf
@@ -2427,7 +2440,7 @@ def corr(self, other, method="pearson", min_periods=None):
         if method not in {"pearson", "spearman"}:
             raise ValueError(f"Unknown method {method}")
 
-        if min_periods not in (None,):
+        if min_periods is not None:
             raise NotImplementedError("Unsupported argument 'min_periods'")
 
         if self.empty or other.empty: