. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 2.1.9 Time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Exponentially Weighted window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 837 2.20 Time series / date functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 841 2.20.2 Timestamps vs. time spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 842 2.20.3 Converting

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 2.1.9 Time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Exponentially Weighted window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 837 2.20 Time series / date functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 841 2.20.2 Timestamps vs. time spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 842 2.20.3 Converting

. . . . . . . . . . . . . . . 827 2.2.19 Time series / date functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 844 2.2.20 Time deltas . . . . . . . . . . . . . . . . . . Combining / comparing / joining / merging . . . . . . . . . . . . . . . . . . . . . . . . . . 1475 3.3.12 Time Series-related . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1476 Combining / comparing / joining / merging . . . . . . . . . . . . . . . . . . . . . . . . . . 2009 3.4.12 Time Series-related . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2009

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 2.1.9 Time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Exponentially Weighted window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 832 2.20 Time series / date functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 836 2.20.2 Timestamps vs. time spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 837 2.20.3 Converting

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 2.1.9 Time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 Exponentially Weighted window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 831 2.20 Time series / date functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 835 2.20.2 Timestamps vs. time spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 836 2.20.3 Converting

allow “M”, “y”, or “Y” for the “unit” argument (GH23264) • Removed the previously deprecated keyword “time_rule” from (non-public) offsets.generate_range, which has been moved to core.arrays._ranges.generate_range() toolkit, Release 1.0.0 • Bug in DataFrame.rolling() not allowing rolling on monotonic decreasing time indexes (GH19248). • Bug in DataFrame.groupby() not offering selection by column name when axis=1 contributed patches to this release. People with a “+” by their names contributed a patch for the first time. • Aaditya Panikath + • Abdullah ˙Ihsan Seçer • Abhijeet Krishnan + • Adam J. Stewart • Adam

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 2.1.9 Time series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Exponentially Weighted window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 798 2.20 Time series / date functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 802 2.20.2 Timestamps vs. time spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 803 2.20.3 Converting

argument to disambiguate DST transition times (GH25017) • DataFrame.at_time() and Series.at_time() now support datetime.time objects with time- zones (GH24043) • DataFrame.pivot_table() now accepts an observed (GH2936, GH2656, GH7739, GH10519, GH12155, GH20084, GH21417) Now every group is evaluated only a single time. In [20]: df = pd.DataFrame({"a": ["x", "y"], "b": [1, 2]}) In [21]: df Out[21]: a b 0 x 1 (continues ValueError (GH27063) • Series.to_excel() and DataFrame.to_excel() will now raise a ValueError when saving time- zone aware data. (GH27008, GH7056) • ExtensionArray.argsort() places NA values at the end of the

argument to disambiguate DST transition times (GH25017) • DataFrame.at_time() and Series.at_time() now support datetime.time objects with time- zones (GH24043) • DataFrame.pivot_table() now accepts an observed (GH2936, GH2656, GH7739, GH10519, GH12155, GH20084, GH21417) Now every group is evaluated only a single time. In [20]: df = pd.DataFrame({"a": ["x", "y"], "b": [1, 2]}) In [21]: df Out[21]: a b 0 x 1 (continues ValueError (GH27063) • Series.to_excel() and DataFrame.to_excel() will now raise a ValueError when saving time- zone aware data. (GH27008, GH7056) • ExtensionArray.argsort() places NA values at the end of the

. . . . . . . . 82 1.8.1.1 merge_asof for asof-style time-series joining . . . . . . . . . . . . . . . . . . . 82 1.8.1.2 .rolling() is now time-series aware . . . . . . . . . . . . . . . . . . . . datetime64 dtype and 1.6 dependency . . . . . . . . . . . . . . . . . . . . . . . . . 378 1.30.3 Time series changes and improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378 1.30 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443 5.9 Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .