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-rw-r--r--doc/neps/missing-data.rst2
-rw-r--r--doc/source/reference/arrays.classes.rst2
2 files changed, 2 insertions, 2 deletions
diff --git a/doc/neps/missing-data.rst b/doc/neps/missing-data.rst
index 6f124890b..338a8da96 100644
--- a/doc/neps/missing-data.rst
+++ b/doc/neps/missing-data.rst
@@ -320,7 +320,7 @@ A manual loop through a masked array like::
>>> a[3] = np.NA
>>> a
array([ 0., 1., 2., NA, 4.], maskna=True)
- >>> for i in xrange(len(a)):
+ >>> for i in range(len(a)):
... a[i] = np.log(a[i])
...
__main__:2: RuntimeWarning: divide by zero encountered in log
diff --git a/doc/source/reference/arrays.classes.rst b/doc/source/reference/arrays.classes.rst
index b35e36545..5cdadd40e 100644
--- a/doc/source/reference/arrays.classes.rst
+++ b/doc/source/reference/arrays.classes.rst
@@ -340,7 +340,7 @@ The default iterator of an ndarray object is the default Python
iterator of a sequence type. Thus, when the array object itself is
used as an iterator. The default behavior is equivalent to::
- for i in xrange(arr.shape[0]):
+ for i in range(arr.shape[0]):
val = arr[i]
This default iterator selects a sub-array of dimension :math:`N-1`