numpy · ahaldane · Nov 28, 2017 · Nov 28, 2017 · Nov 28, 2017
diff --git a/doc/source/reference/routines.datetime.rst b/doc/source/reference/routines.datetime.rst
@@ -5,6 +5,13 @@ Datetime Support Functions
 
 .. currentmodule:: numpy
 
+.. autosummary::
+   :toctree: generated/
+
+   datetime_as_string
+   datetime_data
+
+
 Business Day Functions
 ======================
 

diff --git a/numpy/add_newdocs.py b/numpy/add_newdocs.py
@@ -6862,6 +6862,104 @@ def luf(lamdaexpr, *args, **kwargs):
     AxisError: axes_arg: axis -4 is out of bounds for array of dimension 3
     """)
 
+add_newdoc('numpy.core.multiarray', 'datetime_as_string',
+    """
+    datetime_as_string(arr, unit=None, timezone='naive', casting='same_kind')
+
+    Convert an array of datetimes into an array of strings.
+
+    Parameters
+    ----------
+    arr : array_like of datetime64
+        The array of UTC timestamps to format.
+    unit : str
+        One of None, 'auto', or a datetime unit.
+    timezone : {'naive', 'UTC', 'local'} or tzinfo
+        Timezone information to use when displaying the datetime. If 'UTC', end
+        with a Z to indicate UTC time. If 'local', convert to the local timezone
+        first, and suffix with a +-#### timezone offset. If a tzinfo object,
+        then do as with 'local', but use the specified timezone.
+    casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}
+        Casting to allow when changing between datetime units.
+
+    Returns
+    -------
+    str_arr : ndarray
+        An array of strings the same shape as `arr`.
+
+    Examples
+    --------
+    >>> d = np.arange('2002-10-27T04:30', 4*60, 60, dtype='M8[m]')
+    >>> d
+    array(['2002-10-27T04:30', '2002-10-27T05:30', '2002-10-27T06:30',
+           '2002-10-27T07:30'], dtype='datetime64[m]')
+
+    Setting the timezone to UTC shows the same information, but with a Z suffix
+
+    >>> np.datetime_as_string(d, timezone='UTC')
+    array(['2002-10-27T04:30Z', '2002-10-27T05:30Z', '2002-10-27T06:30Z',
+           '2002-10-27T07:30Z'], dtype='<U35')
+
+    Note that we picked datetimes that cross a DST boundary. Passing in a
+    ``pytz`` timezone object will print the appropriate offset::
+
+    >>> np.datetime_as_string(d, timezone=pytz.timezone('US/Eastern'))
+    array(['2002-10-27T00:30-0400', '2002-10-27T01:30-0400',
+           '2002-10-27T01:30-0500', '2002-10-27T02:30-0500'], dtype='<U39')
+
+    Passing in a unit will change the precision::
+
+    >>> np.datetime_as_string(d, unit='h')
+    array(['2002-10-27T04', '2002-10-27T05', '2002-10-27T06', '2002-10-27T07'],
+          dtype='<U32')
+    >>> np.datetime_as_string(d, unit='s')
+    array(['2002-10-27T04:30:00', '2002-10-27T05:30:00', '2002-10-27T06:30:00',
+           '2002-10-27T07:30:00'], dtype='<U38')
+
+    But can be made to not lose precision::
+
+    >>> np.datetime_as_string(d, unit='h', casting='safe')
+    TypeError: Cannot create a datetime string as units 'h' from a NumPy
+    datetime with units 'm' according to the rule 'safe'
+    """)
+
+add_newdoc('numpy.core.multiarray', 'datetime_data',
+    """
+    datetime_data(dtype, /)
+
+    Get information about the step size of a date or time type.
+
+    The returned tuple can be passed as the second argument of `datetime64` and
+    `timedelta64`.
+
+    Parameters
+    ----------
+    dtype : dtype
+        The dtype object, which must be a `datetime64` or `timedelta64` type.
+
+    Returns
+    -------
+    unit : str
+        The :ref:`datetime unit <arrays.dtypes.dateunits>` on which this dtype
+        is based.
+    count : int
+        The number of base units in a step.
+
+    Examples
+    --------
+    >>> dt_25s = np.dtype('timedelta64[25s]')
+    >>> np.datetime_data(dt_25s)
+    ('s', 25)
+    >>> np.array(10, dt_25s).astype('timedelta64[s]')
+    array(250, dtype='timedelta64[s]')
+
+    The result can be used to construct a datetime that uses the same units
+    as a timedelta::
+
+    >>> np.datetime64('2010', np.datetime_data(dt_25s))
+    numpy.datetime64('2010-01-01T00:00:00','25s')
+    """)
+
 ##############################################################################
 #
 # nd_grid instances