DOC: add missing parameters to DateOffset classes: Milli, Micro and Nano

pandas/_libs/tslibs/offsets.pyx

@@ -1194,20 +1194,107 @@ cdef class Second(Tick):
 
 
 cdef class Milli(Tick):
+    """
+    Offset ``n`` milliseconds.
+
+    Parameters
+    ----------
+    n : int, default 1
+        The number of milliseconds represented.
+
+    See Also
+    --------
+    :class:`~pandas.tseries.offsets.DateOffset` : Standard kind of date increment.
+
+    Examples
+    --------
+    You can use the parameter ``n`` to represent a shift of n milliseconds.
+
+    >>> from pandas.tseries.offsets import Milli
+    >>> ts = pd.Timestamp(2022, 12, 9, 15)
+    >>> ts
+    Timestamp('2022-12-09 15:00:00')
+
+    >>> ts + Milli(n=10)
+    Timestamp('2022-12-09 15:00:00.010000')
+    >>> ts - Milli(n=10)
+    Timestamp('2022-12-09 14:59:59.990000')
+
+    >>> ts + Milli(n=-10)
+    Timestamp('2022-12-09 14:59:59.990000')
+    """
     _nanos_inc = 1_000_000
     _prefix = "ms"
     _period_dtype_code = PeriodDtypeCode.L
     _creso = NPY_DATETIMEUNIT.NPY_FR_ms
 
 
 cdef class Micro(Tick):
+    """
+    Offset ``n`` microseconds.
+
+    Parameters
+    ----------
+    n : int, default 1
+        The number of microseconds represented.
+
+    See Also
+    --------
+    :class:`~pandas.tseries.offsets.DateOffset` : Standard kind of date increment.
+
+    Examples
+    --------
+    You can use the parameter ``n`` to represent a shift of n microseconds.
+
+    >>> from pandas.tseries.offsets import Micro
+    >>> ts = pd.Timestamp(2022, 12, 9, 15)
+    >>> ts
+    Timestamp('2022-12-09 15:00:00')
+
+    >>> ts + Micro(n=1000)
+    Timestamp('2022-12-09 15:00:00.001000')
+    >>> ts - Micro(n=1000)
+    Timestamp('2022-12-09 14:59:59.999000')
+
+    >>> ts + Micro(n=-1000)
+    Timestamp('2022-12-09 14:59:59.999000')
+    """
     _nanos_inc = 1000
     _prefix = "us"
     _period_dtype_code = PeriodDtypeCode.U
     _creso = NPY_DATETIMEUNIT.NPY_FR_us
 
 
 cdef class Nano(Tick):
+    """
+    Offset ``n`` nanoseconds.
+
+    Parameters
+    ----------
+    n : int, default 1
+        The number of nanoseconds represented.
+
+    See Also
+    --------
+    :class:`~pandas.tseries.offsets.DateOffset` : Standard kind of date increment.
+
+    Examples
+    --------
+    You can use the parameter ``n`` to represent a shift of n nanoseconds.
+
+    >>> from pandas.tseries.offsets import Nano
+    >>> ts = pd.Timestamp(2022, 12, 9, 15)
+    >>> ts
+    Timestamp('2022-12-09 15:00:00')
+
+    >>> ts + Nano(n=1000)
+    Timestamp('2022-12-09 15:00:00.000001')
+    >>> ts - Nano(n=1000)
+    Timestamp('2022-12-09 14:59:59.999999')
+
+    >>> ts + Nano(n=-1000)
+    Timestamp('2022-12-09 14:59:59.999999')
+    """
     _nanos_inc = 1
     _prefix = "ns"
     _period_dtype_code = PeriodDtypeCode.N
@@ -3073,9 +3160,12 @@ cdef class SemiMonthEnd(SemiMonthOffset):
 
     Parameters
     ----------
-    n : int
+    n : int, default 1
+        The number of months represented.
     normalize : bool, default False
+        Normalize start/end dates to midnight before generating date range.
     day_of_month : int, {1, 3,...,27}, default 15
+        A specific integer for the day of the month.
 
     Examples
     --------
@@ -3113,9 +3203,12 @@ cdef class SemiMonthBegin(SemiMonthOffset):
 
     Parameters
     ----------
-    n : int
+    n : int, default 1
+        The number of months represented.
     normalize : bool, default False
-    day_of_month : int, {2, 3,...,27}, default 15
+        Normalize start/end dates to midnight before generating date range.
+    day_of_month : int, {1, 3,...,27}, default 15
+        A specific integer for the day of the month.
 
     Examples
     --------