Performance Improvements 3 1.1.2 Bug Fixes 3 1.2 v0.19.0 (October 2, 2016) 4 1.2.1 New features 6 merge_asof for asof-style time-series joining 6 .rolling() is now time-series aware 8 read_csv has improved number of bug fixes. We recommend that all users upgrade to this version. Highlights include: • merge_asof() for asof-style time-series joining, see here • .rolling() is now time-series aware, see here Improvements - Bug Fixes ## New features ## merge_asof for asof-style time-series joining A long-time requested feature has been added through the merge_asof() function, to support asof style joining of

Development Team Oct 02,2016 ## What’s New 3 1.1 v0.19.0 (October 2, 2016) 3 1.1.1 New features 5 merge_asof for asof-style time-series joining 5 .rolling() is now time-series aware 7 read_csv has number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * merge_asof() for asof-style time-series joining, see here - .rolling() is now time-series aware, see here silence numpy ufunc warnings upon import, see here. ## What's new in v0.19.0 - New features - merge_asof for asof-style time-series joining - . rolling() is now time-series aware - read_csv has improved

Improvements 48 1.4.2 Bug Fixes 49 1.5 v0.19.0 (October 2, 2016) 50 1.5.1 New features 52 1.5.1.1 merge_asof for asof-style time-series joining 52 1.5.1.2 .rolling() is now time-series aware 54 1.5.1.3 number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * merge_asof() for asof-style time-series joining, see here - .rolling() is now time-series aware, see here silence numpy ufunc warnings upon import, see here. ## What's new in v0.19.0 - New features - merge_asof for asof-style time-series joining - . rolling() is now time-series aware - read_csv has improved

pivot_table() not returning correct type float when margins=True and aggfunc='mean' (GH24893) • Bug merge_asof() could not use datetime.timedelta for tolerance kwarg (GH28098) • Bug in merge(), did not append qcut() and cut() now handle boolean input (GH20303) • Fix to ensure all int dtypes can be used in merge_asof() when using a tolerance value. Previously every non-int64 type would raise an erroneous MergeError preserved when transposing a DataFrame where each column is the same extension dtype (GH30091) • Bug in merge_asof() merging on a tz-aware left_index and right_on a tz-aware column (GH29864) • Improved error message

0 8 K2 3.0 c 2.0 9 K4 3.0 c 3.0 10 K1 NaN d 1.0 11 K2 4.0 d 2.0 12 K4 4.0 d 3.0 Merging asof A merge_asof() is similar to an ordered left-join except that we match on nearest key rather than equal keys merge_ordered(left, right[, on, left_on, ...]) Perform merge with optional filling/interpolation. merge_asof(left, right[, on, left_on, ...]) Perform an asof merge. concat(objs[, axis, join, ignore_index DataFrame of the two merged objects. See also: merge_ordered Merge with optional filling/interpolation. merge_asof Merge on nearest keys. DataFrame.join Similar method using indices. 1064 Chapter 3. API reference

Chapter 2. User Guide pandas: powerful Python data analysis toolkit, Release 1.3.3 Merging asof A merge_asof() is similar to an ordered left-join except that we match on nearest key rather than equal keys merge_ordered(left, right[, on, left_on, ...]) Perform merge with optional filling/interpolation. merge_asof(left, right[, on, left_on, ...]) Perform an asof merge. concat(objs[, axis, join, ignore_index DataFrame of the two merged objects. See also: merge_ordered Merge with optional filling/interpolation. merge_asof Merge on nearest keys. DataFrame.join Similar method using indices. Notes Support for specifying

0 8 K2 3.0 c 2.0 9 K4 3.0 c 3.0 10 K1 NaN d 1.0 11 K2 4.0 d 2.0 12 K4 4.0 d 3.0 Merging asof A merge_asof() is similar to an ordered left-join except that we match on nearest key rather than equal keys merge_ordered(left, right[, on, left_on, ...]) Perform merge with optional filling/interpolation. merge_asof(left, right[, on, left_on, ...]) Perform an asof merge. concat(objs[, axis, join, ignore_index DataFrame of the two merged objects. See also: merge_ordered Merge with optional filling/interpolation. merge_asof Merge on nearest keys. DataFrame.join Similar method using indices. Notes Support for specifying

0 8 K2 3.0 c 2.0 9 K4 3.0 c 3.0 10 K1 NaN d 1.0 11 K2 4.0 d 2.0 12 K4 4.0 d 3.0 Merging asof A merge_asof() is similar to an ordered left-join except that we match on nearest key rather than equal keys right[, on, left_on, ...]) Perform a merge for ordered data with optional fill- ing/interpolation. merge_asof(left, right[, on, left_on, ...]) Perform a merge by key distance. concat(objs[, axis, join, ignore_index DataFrame of the two merged objects. See also: merge_ordered Merge with optional filling/interpolation. merge_asof Merge on nearest keys. DataFrame.join Similar method using indices. 3.2. General functions 1129

0 8 K2 3.0 c 2.0 9 K4 3.0 c 3.0 10 K1 NaN d 1.0 11 K2 4.0 d 2.0 12 K4 4.0 d 3.0 Merging asof A merge_asof() is similar to an ordered left-join except that we match on nearest key rather than equal keys merge_ordered(left, right[, on, left_on, ...]) Perform merge with optional filling/interpolation. merge_asof(left, right[, on, left_on, ...]) Perform an asof merge. concat(objs, ForwardRef]], ...[, axis, DataFrame of the two merged objects. See also: merge_ordered Merge with optional filling/interpolation. merge_asof Merge on nearest keys. DataFrame.join Similar method using indices. Notes Support for specifying

0 8 K2 3.0 c 2.0 9 K4 3.0 c 3.0 10 K1 NaN d 1.0 11 K2 4.0 d 2.0 12 K4 4.0 d 3.0 Merging asof A merge_asof() is similar to an ordered left-join except that we match on nearest key rather than equal keys merge_ordered(left, right[, on, left_on, ...]) Perform merge with optional filling/interpolation. merge_asof(left, right[, on, left_on, ...]) Perform an asof merge. concat(objs, ForwardRef]], ...[, axis, DataFrame of the two merged objects. See also: merge_ordered Merge with optional filling/interpolation. merge_asof Merge on nearest keys. DataFrame.join Similar method using indices. 4.2. General functions 953