Python binding for quarters

python/cudf/cudf/_lib/cpp/datetime.pxd

@@ -18,3 +18,4 @@ cdef extern from "cudf/datetime.hpp" namespace "cudf::datetime" nogil:
     ) except +
     cdef unique_ptr[column] day_of_year(const column_view& column) except +
     cdef unique_ptr[column] is_leap_year(const column_view& column) except +
+    cdef unique_ptr[column] extract_quarter(const column_view& column) except +

python/cudf/cudf/_lib/datetime.pyx

@@ -67,3 +67,17 @@ def is_leap_year(Column col):
         c_result = move(libcudf_datetime.is_leap_year(col_view))
 
     return Column.from_unique_ptr(move(c_result))
+
+
+def extract_quarter(Column col):
+    """
+    Returns a column which contains the corresponding quarter of the year
+    for every timestamp inside the input column.
+    """
+    cdef unique_ptr[column] c_result
+    cdef column_view col_view = col.view()
+
+    with nogil:
+        c_result = move(libcudf_datetime.extract_quarter(col_view))
+
+    return Column.from_unique_ptr(move(c_result))

python/cudf/cudf/core/index.py

@@ -13,7 +13,7 @@
 from pandas._config import get_option
 
 import cudf
-from cudf._lib.datetime import is_leap_year
+from cudf._lib.datetime import extract_quarter, is_leap_year
 from cudf._lib.filling import sequence
 from cudf._lib.search import search_sorted
 from cudf._lib.table import Table
@@ -2357,6 +2357,31 @@ def is_leap_year(self):
         res = is_leap_year(self._values).fillna(False)
         return cupy.asarray(res)
 
+    @property
+    def quarter(self):
+        """
+        Integer indicator for which quarter of the year the date belongs in.
+
+        There are 4 quarters in a year. With the first quarter being from
+        January - March, second quarter being April - June, third quarter
+        being July - September and fourth quarter being October - December.
+
+        Returns
+        -------
+        Int64Index
+        Integer indicating which quarter the date belongs to.
+
+        Examples
+        --------
+        >>> import cudf
+        >>> gIndex = cudf.DatetimeIndex(["2020-05-31 08:00:00",
+        ...    "1999-12-31 18:40:00"])
+        >>> gIndex.quarter
+        Int64Index([2, 4], dtype='int64')
+        """
+        res = extract_quarter(self._values)
+        return Int64Index(res, dtype="int64")
+
     def to_pandas(self):
         nanos = self._values.astype("datetime64[ns]")
         return pd.DatetimeIndex(nanos.to_pandas(), name=self.name)

python/cudf/cudf/core/series.py

@@ -6447,13 +6447,39 @@ def is_leap_year(self):
         )
 
     @property
-    def is_month_start(self):
+    def quarter(self):
         """
-        Boolean indicator if the date is the first day of the month.
+        Integer indicator for which quarter of the year the date belongs in.
+
+        There are 4 quarters in a year. With the first quarter being from
+        January - March, second quarter being April - June, third quarter
+        being July - September and fourth quarter being October - December.
 
         Returns
         -------
         Series
+        Integer indicating which quarter the date belongs to.
+
+        Examples
+        -------
+        >>> import cudf
+        >>> s = cudf.Series(["2020-05-31 08:00:00","1999-12-31 18:40:00"],
+        ...     dtype="datetime64[ms]")
+        >>> s.dt.quarter
+        0    2
+        1    4
+        dtype: int16
+        """
+        res = libcudf.datetime.extract_quarter(self.series._column)
+        return Series._from_data(
+            ColumnAccessor({None: res}),
+            index=self.series._index,
+            name=self.series.name,
+        )
+
+    @property
+    def is_month_start(self):
+        """
         Booleans indicating if dates are the first day of the month.
         """
         return (self.day == 1).fillna(False)

python/cudf/cudf/tests/test_datetime.py

@@ -1299,6 +1299,38 @@ def test_is_leap_year():
     assert_eq(expect2, got2)
 
 
+def test_quarter():
+    data = [
+        "2020-05-31 08:00:00",
+        "1999-12-31 18:40:00",
+        "2000-12-31 04:00:00",
+        "1900-02-28 07:00:00",
+        "1800-03-14 07:30:00",
+        "2100-03-14 07:30:00",
+        "1970-01-01 00:00:00",
+        "1969-12-31 12:59:00",
+    ]
+    dtype = "datetime64[s]"
+
+    # Series
+    ps = pd.Series(data, dtype=dtype)
+    gs = cudf.from_pandas(ps)
+
+    expect = ps.dt.quarter
+    got = gs.dt.quarter.astype(np.int64)
+
+    assert_eq(expect, got)
+
+    # DatetimeIndex
+    pIndex = pd.DatetimeIndex(data)
+    gIndex = cudf.from_pandas(pIndex)
+
+    expect2 = pIndex.quarter
+    got2 = gIndex.quarter
+
+    assert_eq(expect2, got2)
+
+
 @pytest.mark.parametrize(
     "data",
     [