Merge pull request numpy#8400 from b-carter/fix_corrcoef_cov_rowvar_p…

…aram

Fix `corrcoef` and `cov` rowvar param handling

numpy/lib/function_base.py

@@ -2842,13 +2842,13 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None,
         dtype = np.result_type(m, y, np.float64)
 
     X = array(m, ndmin=2, dtype=dtype)
-    if rowvar == 0 and X.shape[0] != 1:
+    if not rowvar and X.shape[0] != 1:
         X = X.T
     if X.shape[0] == 0:
         return np.array([]).reshape(0, 0)
     if y is not None:
         y = array(y, copy=False, ndmin=2, dtype=dtype)
-        if rowvar == 0 and y.shape[0] != 1:
+        if not rowvar and y.shape[0] != 1:
             y = y.T
         X = np.vstack((X, y))
 
@@ -2918,7 +2918,7 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None,
     return c.squeeze()
 
 
-def corrcoef(x, y=None, rowvar=1, bias=np._NoValue, ddof=np._NoValue):
+def corrcoef(x, y=None, rowvar=True, bias=np._NoValue, ddof=np._NoValue):
     """
     Return Pearson product-moment correlation coefficients.
 
@@ -2939,8 +2939,8 @@ def corrcoef(x, y=None, rowvar=1, bias=np._NoValue, ddof=np._NoValue):
     y : array_like, optional
         An additional set of variables and observations. `y` has the same
         shape as `x`.
-    rowvar : int, optional
-        If `rowvar` is non-zero (default), then each row represents a
+    rowvar : bool, optional
+        If `rowvar` is True (default), then each row represents a
         variable, with observations in the columns. Otherwise, the relationship
         is transposed: each column represents a variable, while the rows
         contain observations.