contributed patches to this release. People with a + by their names contributed a patch for the first time. • Felix Divo + • Jeremy Schendel • Joris Van den Bossche • MeeseeksMachine • Tom Augspurger as in an SQL table or Excel spreadsheet • Ordered and unordered (not necessarily fixed-frequency) time series data. • Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels and delimited), Excel files, databases, and saving / loading data from the ultrafast HDF5 format • Time series-specific functionality: date range generation and frequency conversion, moving window statistics

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 5.9 Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374 16 Time Series / Date functionality 377 16.1 Time Stamps vs. Time Spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 388 16.6 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . 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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 5.9 Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 15 Time Series / Date functionality 287 15.1 Time Stamps vs. Time Spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 295 15.6 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Categorical). For example, with PeriodIndex, .values generates a new ndarray of period objects each time. In [18]: idx.values Out[18]: array([Period('2000-01-01', 'D'), Period('2000-01-02', 'D'), Period('2000-01-03' methods has been updated to 'infer' (GH22004). • DataFrame.to_sql() now supports writing TIMESTAMP WITH TIME ZONE types for supported databases. For databases that don’t support timezones, datetime data will constructor (GH2193) • DatetimeIndex has gained the DatetimeIndex.timetz attribute. This returns the local time with timezone information. (GH21358) 12 Chapter 1. What’s New in 0.24.0 (January 25, 2019) pandas:

. . . . . . . . 53 1.6.1.1 merge_asof for asof-style time-series joining . . . . . . . . . . . . . . . . . . . 53 1.6.1.2 .rolling() is now time-series aware . . . . . . . . . . . . . . . . . . . . datetime64 dtype and 1.6 dependency . . . . . . . . . . . . . . . . . . . . . . . . . 350 1.28.3 Time series changes and improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . 350 1.28 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415 5.9 Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . 52 1.5.1.1 merge_asof for asof-style time-series joining . . . . . . . . . . . . . . . . . . . 52 1.5.1.2 .rolling() is now time-series aware . . . . . . . . . . . . . . . . . . . . datetime64 dtype and 1.6 dependency . . . . . . . . . . . . . . . . . . . . . . . . . 348 1.27.3 Time series changes and improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348 1.27 Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 413 5.9 Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 5.9 Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412 16 Time Series / Date functionality 413 16.1 Time Stamps vs. Time Spans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424 16.6 Time series-related instance methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 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