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-rw-r--r--numpy/doc/basics.py6
1 files changed, 3 insertions, 3 deletions
diff --git a/numpy/doc/basics.py b/numpy/doc/basics.py
index 5e7291957..ea651bbc7 100644
--- a/numpy/doc/basics.py
+++ b/numpy/doc/basics.py
@@ -44,7 +44,7 @@ having unique characteristics. Once you have imported NumPy using
the dtypes are available as ``np.bool``, ``np.float32``, etc.
Advanced types, not listed in the table above, are explored in
-section `link_here`.
+section :ref:`structured_arrays`.
There are 5 basic numerical types representing booleans (bool), integers (int),
unsigned integers (uint) floating point (float) and complex. Those with numbers
@@ -98,8 +98,8 @@ To determine the type of an array, look at the dtype attribute::
dtype('uint8')
dtype objects also contain information about the type, such as its bit-width
-and its byte-order. See xxx for details. The data type can also be used
-indirectly to query properties of the type, such as whether it is an integer::
+and its byte-order. The data type can also be used indirectly to query
+properties of the type, such as whether it is an integer::
>>> d = np.dtype(int)
>>> d