diff --git a/numpy/lib/format.py b/numpy/lib/format.py
index 1e508f3e5dda..042d3235c1a3 100644
--- a/numpy/lib/format.py
+++ b/numpy/lib/format.py
@@ -468,7 +468,7 @@ def read_array(fp):
 
 
 def open_memmap(filename, mode='r+', dtype=None, shape=None,
-                fortran_order=False, version=(1,0)):
+                fortran_order=False, version=(1,0), offset=0):
     """
     Open a .npy file as a memory-mapped array.
 
@@ -489,8 +489,9 @@ def open_memmap(filename, mode='r+', dtype=None, shape=None,
         which results in a data-type of `float64`.
     shape : tuple of int
         The shape of the array if we are creating a new file in "write"
-        mode, in which case this parameter is required.  Otherwise, this
-        parameter is ignored and is thus optional.
+        mode, in which case this parameter is required. If opening an 
+        existing file, `shape` may specify a (contiguous) slice to open.
+        Otherwise, this parameter is ignored.
     fortran_order : bool, optional
         Whether the array should be Fortran-contiguous (True) or
         C-contiguous (False, the default) if we are creating a new file
@@ -498,6 +499,8 @@ def open_memmap(filename, mode='r+', dtype=None, shape=None,
     version : tuple of int (major, minor)
         If the mode is a "write" mode, then this is the version of the file
         format used to create the file.  Default: (1,0)
+    offset : int, optional
+        Number of elements to skip along the first dimension.
 
     Returns
     -------
@@ -521,6 +524,7 @@ def open_memmap(filename, mode='r+', dtype=None, shape=None,
                          " existing file handles.")
 
     if 'w' in mode:
+        assert offset == 0, "Cannot specify offset when creating memmap"
         # We are creating the file, not reading it.
         # Check if we ought to create the file.
         if version != (1, 0):
@@ -553,11 +557,17 @@ def open_memmap(filename, mode='r+', dtype=None, shape=None,
             if version != (1, 0):
                 msg = "only support version (1,0) of file format, not %r"
                 raise ValueError(msg % (version,))
-            shape, fortran_order, dtype = read_array_header_1_0(fp)
+            fullshape, fortran_order, dtype = read_array_header_1_0(fp)
+            if shape is None:
+                shape = fullshape
+                if offset:
+                    shape = list(fullshape)
+                    shape[0] = shape[0] - offset
+                    shape = tuple(shape)
             if dtype.hasobject:
                 msg = "Array can't be memory-mapped: Python objects in dtype."
                 raise ValueError(msg)
-            offset = fp.tell()
+            offset = fp.tell() + offset * dtype.itemsize
         finally:
             fp.close()
 
@@ -575,3 +585,4 @@ def open_memmap(filename, mode='r+', dtype=None, shape=None,
         mode=mode, offset=offset)
 
     return marray
+
diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py
index 3f4db4593816..1218ad3e9cc8 100644
--- a/numpy/lib/npyio.py
+++ b/numpy/lib/npyio.py
@@ -262,7 +262,7 @@ def __contains__(self, key):
         return self.files.__contains__(key)
 
 
-def load(file, mmap_mode=None):
+def load(file, mmap_mode=None, offset=0, shape=None):
     """
     Load a pickled, ``.npy``, or ``.npz`` binary file.
 
@@ -324,6 +324,9 @@ def load(file, mmap_mode=None):
     """
     import gzip
 
+    if (not mmap_mode) and (offset or shape):
+        raise ValueError("Offset and shape should be used only with mmap_mode")
+
     own_fid = False
     if isinstance(file, basestring):
         fid = open(file, "rb")
@@ -345,7 +348,7 @@ def load(file, mmap_mode=None):
             return NpzFile(fid, own_fid=True)
         elif magic == format.MAGIC_PREFIX: # .npy file
             if mmap_mode:
-                return format.open_memmap(file, mode=mmap_mode)
+            return open_memmap(file, mode=mmap_mode, shape=shape, offset=offset)
             else:
                 return format.read_array(fid)
         else:  # Try a pickle
@@ -1740,3 +1743,4 @@ def recfromcsv(fname, **kwargs):
     else:
         output = output.view(np.recarray)
     return output
+