@@ -1777,7 +1777,44 @@ def freq(self, value):
17771777 is_quarter_start = _field_accessor (
17781778 'is_quarter_start' ,
17791779 'is_quarter_start' ,
1780- "Logical indicating if first day of quarter (defined by frequency)" )
1780+ """
1781+ Indicator for whether the date is the first day of a quarter.
1782+
1783+ Returns
1784+ -------
1785+ is_quarter_start : Series or DatetimeIndex
1786+ The same type as the original data with boolean values. Series will
1787+ have the same name and index. DatetimeIndex will have the same
1788+ name.
1789+
1790+ See Also
1791+ --------
1792+ quarter : Return the quarter of the date.
1793+ is_quarter_end : Similar method for indicating the start of a quarter.
1794+
1795+ Examples
1796+ --------
1797+ This method is available on Series with datetime values under
1798+ the ``.dt`` accessor, and directly on DatetimeIndex.
1799+
1800+ >>> df = pd.DataFrame({'dates': pd.date_range("2017-03-30",
1801+ ... periods=4)})
1802+ >>> df.assign(quarter=df.dates.dt.quarter,
1803+ ... is_quarter_start=df.dates.dt.is_quarter_start)
1804+ dates quarter is_quarter_start
1805+ 0 2017-03-30 1 False
1806+ 1 2017-03-31 1 False
1807+ 2 2017-04-01 2 True
1808+ 3 2017-04-02 2 False
1809+
1810+ >>> idx = pd.date_range('2017-03-30', periods=4)
1811+ >>> idx
1812+ DatetimeIndex(['2017-03-30', '2017-03-31', '2017-04-01', '2017-04-02'],
1813+ dtype='datetime64[ns]', freq='D')
1814+
1815+ >>> idx.is_quarter_start
1816+ array([False, False, True, False])
1817+ """ )
17811818 is_quarter_end = _field_accessor (
17821819 'is_quarter_end' ,
17831820 'is_quarter_end' ,
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