Add properties for DatetimeIndex

databricks/koalas/indexes/datetimes.py

@@ -136,3 +136,298 @@ def __getattr__(self, item: str) -> Any:
             else:
                 return partial(property_or_func, self)
         raise AttributeError("'DatetimeIndex' object has no attribute '{}'".format(item))
+
+    # Properties
+    @property
+    def year(self) -> Index:
+        """
+        The year of the datetime.
+        """
+        return Index(self.to_series().dt.year)
+
+    @property
+    def month(self) -> Index:
+        """
+        The month of the timestamp as January = 1 December = 12.
+        """
+        return Index(self.to_series().dt.month)
+
+    @property
+    def day(self) -> Index:
+        """
+        The days of the datetime.
+        """
+        return Index(self.to_series().dt.day)
+
+    @property
+    def hour(self) -> Index:
+        """
+        The hours of the datetime.
+        """
+        return Index(self.to_series().dt.hour)
+
+    @property
+    def minute(self) -> Index:
+        """
+        The minutes of the datetime.
+        """
+        return Index(self.to_series().dt.minute)
+
+    @property
+    def second(self) -> Index:
+        """
+        The seconds of the datetime.
+        """
+        return Index(self.to_series().dt.second)
+
+    @property
+    def microsecond(self) -> Index:
+        """
+        The microseconds of the datetime.
+        """
+        return Index(self.to_series().dt.microsecond)
+
+    @property
+    def week(self) -> Index:
+        """
+        The week ordinal of the year.
+        """
+        return Index(self.to_series().dt.week)
+
+    @property
+    def weekofyear(self) -> Index:
+        return Index(self.to_series().dt.weekofyear)
+
+    weekofyear.__doc__ = week.__doc__
+
+    @property
+    def dayofweek(self) -> Index:
+        """
+        The day of the week with Monday=0, Sunday=6.
+        Return the day of the week. It is assumed the week starts on
+        Monday, which is denoted by 0 and ends on Sunday which is denoted
+        by 6. This method is available on both Series with datetime
+        values (using the `dt` accessor) or DatetimeIndex.
+
+        Returns
+        -------
+        Series or Index
+            Containing integers indicating the day number.
+
+        See Also
+        --------
+        Series.dt.dayofweek : Alias.
+        Series.dt.weekday : Alias.
+        Series.dt.day_name : Returns the name of the day of the week.
+
+        Examples
+        --------
+        >>> idx = ks.from_pandas(pd.date_range('2016-12-31', '2017-01-08', freq='D'))
+        >>> idx.dayofweek
+        Int64Index([5, 6, 0, 1, 2, 3, 4, 5, 6], dtype='int64')
+        """
+        return Index(self.to_series().dt.dayofweek)
+
+    @property
+    def day_of_week(self) -> Index:
+        return self.dayofweek
+
+    day_of_week.__doc__ = dayofweek.__doc__
+
+    @property
+    def weekday(self) -> Index:
+        return Index(self.to_series().dt.weekday)
+
+    weekday.__doc__ = dayofweek.__doc__
+
+    @property
+    def dayofyear(self) -> Index:
+        """
+        The ordinal day of the year.
+        """
+        return Index(self.to_series().dt.dayofyear)
+
+    @property
+    def day_of_year(self) -> Index:
+        return self.dayofyear
+
+    day_of_year.__doc__ = dayofyear.__doc__
+
+    @property
+    def quarter(self) -> Index:
+        """
+        The quarter of the date.
+        """
+        return Index(self.to_series().dt.quarter)
+
+    @property
+    def is_month_start(self) -> Index:
+        """
+        Indicates whether the date is the first day of the month.
+
+        Returns
+        -------
+        Index
+            Returns a Index with boolean values
+
+        See Also
+        --------
+        is_month_end : Return a boolean indicating whether the date
+            is the last day of the month.
+
+        Examples
+        --------
+        >>> idx = ks.from_pandas(pd.date_range("2018-02-27", periods=3))
+        >>> idx.is_month_start
+        Index([False, False, True], dtype='object')
+        """
+        return Index(self.to_series().dt.is_month_start)
+
+    @property
+    def is_month_end(self) -> Index:
+        """
+        Indicates whether the date is the last day of the month.
+
+        Returns
+        -------
+        Index
+            Returns a Index with boolean values.
+
+        See Also
+        --------
+        is_month_start : Return a boolean indicating whether the date
+            is the first day of the month.
+
+        Examples
+        --------
+        >>> idx = ks.from_pandas(pd.date_range("2018-02-27", periods=3))
+        >>> idx.is_month_end
+        Index([False, True, False], dtype='object')
+        """
+        return Index(self.to_series().dt.is_month_end)
+
+    @property
+    def is_quarter_start(self) -> Index:
+        """
+        Indicator for whether the date is the first day of a quarter.
+
+        Returns
+        -------
+        is_quarter_start : Index
+            Returns an Index with boolean values.
+
+        See Also
+        --------
+        quarter : Return the quarter of the date.
+        is_quarter_end : Similar property for indicating the quarter start.
+
+        Examples
+        --------
+        >>> idx = ks.from_pandas(pd.date_range('2017-03-30', periods=4))
+        >>> idx.is_quarter_start
+        Index([False, False, True, False], dtype='object')
+        """
+        return Index(self.to_series().dt.is_quarter_start)
+
+    @property
+    def is_quarter_end(self) -> Index:
+        """
+        Indicator for whether the date is the last day of a quarter.
+
+        Returns
+        -------
+        is_quarter_end : Index
+            Returns an Index with boolean values.
+
+        See Also
+        --------
+        quarter : Return the quarter of the date.
+        is_quarter_start : Similar property indicating the quarter start.
+
+        Examples
+        --------
+        >>> idx = ks.from_pandas(pd.date_range('2017-03-30', periods=4))
+        >>> idx.is_quarter_end
+        Index([False, True, False, False], dtype='object')
+        """
+        return Index(self.to_series().dt.is_quarter_end)
+
+    @property
+    def is_year_start(self) -> Index:
+        """
+        Indicate whether the date is the first day of a year.
+
+        Returns
+        -------
+        Index
+            Returns an Index with boolean values.
+
+        See Also
+        --------
+        is_year_end : Similar property indicating the last day of the year.
+
+        Examples
+        --------
+        >>> idx = ks.from_pandas(pd.date_range("2017-12-30", periods=3))
+        >>> idx.is_year_start
+        Index([False, False, True], dtype='object')
+        """
+        return Index(self.to_series().dt.is_year_start)
+
+    @property
+    def is_year_end(self) -> Index:
+        """
+        Indicate whether the date is the last day of the year.
+
+        Returns
+        -------
+        Index
+            Returns an Index with boolean values.
+
+        See Also
+        --------
+        is_year_start : Similar property indicating the start of the year.
+
+        Examples
+        --------
+        >>> idx = ks.from_pandas(pd.date_range("2017-12-30", periods=3))
+        >>> idx.is_year_end
+        Index([False, True, False], dtype='object')
+        """
+        return Index(self.to_series().dt.is_year_end)
+
+    @property
+    def is_leap_year(self) -> Index:
+        """
+        Boolean indicator if the date belongs to a leap year.
+
+        A leap year is a year, which has 366 days (instead of 365) including
+        29th of February as an intercalary day.
+        Leap years are years which are multiples of four with the exception
+        of years divisible by 100 but not by 400.
+
+        Returns
+        -------
+        Index
+             Booleans indicating if dates belong to a leap year.
+
+        Examples
+        --------
+        >>> idx = ks.from_pandas(pd.date_range("2012-01-01", "2015-01-01", freq="Y"))
+        >>> idx.is_leap_year
+        Index([True, False, False], dtype='object')
+        """
+        return Index(self.to_series().dt.is_leap_year)
+
+    @property
+    def daysinmonth(self) -> Index:
+        """
+        The number of days in the month.
+        """
+        return Index(self.to_series().dt.daysinmonth)
+
+    @property
+    def days_in_month(self) -> Index:
+        return Index(self.to_series().dt.days_in_month)
+
+    days_in_month.__doc__ = daysinmonth.__doc__

databricks/koalas/missing/indexes.py

@@ -100,35 +100,13 @@ class MissingPandasLikeIndex(object):
 class MissingPandasLikeDatetimeIndex(MissingPandasLikeIndex):
 
     # Properties
-    year = _unsupported_property("year", cls="DatetimeIndex")
-    month = _unsupported_property("month", cls="DatetimeIndex")
-    day = _unsupported_property("day", cls="DatetimeIndex")
-    hour = _unsupported_property("hour", cls="DatetimeIndex")
-    minute = _unsupported_property("minute", cls="DatetimeIndex")
-    second = _unsupported_property("second", cls="DatetimeIndex")
-    microsecond = _unsupported_property("microsecond", cls="DatetimeIndex")
     nanosecond = _unsupported_property("nanosecond", cls="DatetimeIndex")
     date = _unsupported_property("date", cls="DatetimeIndex")
     time = _unsupported_property("time", cls="DatetimeIndex")
     timetz = _unsupported_property("timetz", cls="DatetimeIndex")
-    dayofyear = _unsupported_property("dayofyear", cls="DatetimeIndex")
-    day_of_year = _unsupported_property("day_of_year", cls="DatetimeIndex")
-    weekofyear = _unsupported_property("weekofyear", cls="DatetimeIndex")
-    week = _unsupported_property("week", cls="DatetimeIndex")
-    dayofweek = _unsupported_property("dayofweek", cls="DatetimeIndex")
-    day_of_week = _unsupported_property("day_of_week", cls="DatetimeIndex")
-    weekday = _unsupported_property("weekday", cls="DatetimeIndex")
-    quarter = _unsupported_property("quarter", cls="DatetimeIndex")
     tz = _unsupported_property("tz", cls="DatetimeIndex")
     freq = _unsupported_property("freq", cls="DatetimeIndex")
     freqstr = _unsupported_property("freqstr", cls="DatetimeIndex")
-    is_month_start = _unsupported_property("is_month_start", cls="DatetimeIndex")
-    is_month_end = _unsupported_property("is_month_end", cls="DatetimeIndex")
-    is_quarter_start = _unsupported_property("is_quarter_start", cls="DatetimeIndex")
-    is_quarter_end = _unsupported_property("is_quarter_end", cls="DatetimeIndex")
-    is_year_start = _unsupported_property("is_year_start", cls="DatetimeIndex")
-    is_year_end = _unsupported_property("is_year_end", cls="DatetimeIndex")
-    is_leap_year = _unsupported_property("is_leap_year", cls="DatetimeIndex")
     inferred_freq = _unsupported_property("inferred_freq", cls="DatetimeIndex")
 
     # Functions

databricks/koalas/tests/test_indexes.py

@@ -370,6 +370,44 @@ def test_index_unique(self):
         with self.assertRaisesRegex(KeyError, "Requested level (hi)*"):
             kidx.unique(level="hi")
 
+    def test_datetime_index_properties(self):
+        pids = [
+            pd.DatetimeIndex([0]),
+            pd.DatetimeIndex(["2004-01-01", "2002-12-31", "2000-04-01"]),
+        ] + [
+            pd.date_range("2000-01-01", periods=3, freq=unit)
+            for unit in ["ns", "us", "ms", "s", "m", "h", "D"]
+        ]
+
+        for pid in pids:
+            kid = ks.from_pandas(pid)
+            self.assert_eq(kid.year, pid.year)
+            self.assert_eq(kid.month, pid.month)
+            self.assert_eq(kid.day, pid.day)
+            self.assert_eq(kid.hour, pid.hour)
+            self.assert_eq(kid.minute, pid.minute)
+            self.assert_eq(kid.second, pid.second)
+            self.assert_eq(kid.microsecond, pid.microsecond)
+            self.assert_eq(kid.week, pid.week)
+            self.assert_eq(kid.weekofyear, pid.weekofyear)
+            self.assert_eq(kid.dayofweek, pid.dayofweek)
+            self.assert_eq(kid.weekday, pid.weekday)
+            self.assert_eq(kid.dayofyear, pid.dayofyear)
+            self.assert_eq(kid.quarter, pid.quarter)
+            self.assert_eq(kid.daysinmonth, pid.daysinmonth)
+            self.assert_eq(kid.days_in_month, pid.days_in_month)
+            self.assert_eq(kid.is_month_start, ks.Index(pid.is_month_start))
+            self.assert_eq(kid.is_month_end, ks.Index(pid.is_month_end))
+            self.assert_eq(kid.is_quarter_start, ks.Index(pid.is_quarter_start))
+            self.assert_eq(kid.is_quarter_end, ks.Index(pid.is_quarter_end))
+            self.assert_eq(kid.is_year_start, ks.Index(pid.is_year_start))
+            self.assert_eq(kid.is_year_end, ks.Index(pid.is_year_end))
+            self.assert_eq(kid.is_leap_year, ks.Index(pid.is_leap_year))
+
+            if LooseVersion(pd.__version__) >= LooseVersion("1.2.0"):
+                self.assert_eq(kid.day_of_year, pid.day_of_year)
+                self.assert_eq(kid.day_of_week, pid.day_of_week)
+
     def test_multi_index_copy(self):
         arrays = [[1, 1, 2, 2], ["red", "blue", "red", "blue"]]
         idx = pd.MultiIndex.from_arrays(arrays, names=("number", "color"))