Highlights include: • support for a new index type Float64Index, and other Indexing enhancements • HDFStore has a new string based syntax for query specification • support for new methods of interpolation 13.0 (January 3, 2014) 17 pandas: powerful Python data analysis toolkit, Release 0.13.1 1.2.6 HDFStore API Changes • Query Format Changes. A much more string-like query format is now supported. See the ’df_fixed’) In [49]: with get_store(path) as store: ....: print(store) ....: HDFStore’> File path: test.h5 /df_fixed frame (shape->[10,2]) /df_table frame_table (typ->appendable,nrows->10

files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular R2C0 R2C1 R2C2 R_10_g3 R_11_g3 R3C0 R3C1 R3C2 R_10_g4 R_11_g4 R4C0 R4C1 R4C2 • Support for HDFStore (via PyTables 3.0.0) on Python3 - Iterator support via read_hdf that automatically opens and closes other strings with the same length 'w' is the only non-null string in the yielded Series. • HDFStore – will retain index attributes (freq,tz,name) on recreation (GH3499) – will warn with a AttributeConflictWarning

Formatting 28 1.2.2.12 Window Binary Corr/Cov operations return a MultiIndex DataFrame 29 1.2.2.13 HDFStore where string comparison 30 1.2.2.14 Index.intersection and inner join now preserve the order of 3 Changes to Index Comparisons 158 1.9.2.4 Changes to Boolean Comparisons vs. None 158 1.9.2.5 HDFStore dropna behavior 159 1.9.2.6 Changes to display.precision option 160 1.9.2.7 Changes to Categorical 3 Deprecations 283 1.19.4 Indexing API Changes 283 1.19.5 Float64Index API Change 285 1.19.6 HDFStore API Changes 286 1.19.7 DataFrame repr Changes 289 1.19.8 Enhancements 289 1.19.9 Experimental

because it doesn’t make sense NotImplementedError: operator ’/’ not implemented for bool dtypes • In HDFStore, select_as_multiple will always raise a KeyError, when a key or the selector is not found (GH6177) nanRep keyword from DataFrame.to_csv() and DataFrame.to_string() (GH275) • Remove unique keyword from HDFStore.select_column() (GH3256) • Remove inferTimeRule keyword from Timestamp.offset() (GH391) • Remove when index doesn’t match data (GH6532) • Prevent segfault due to MultiIndex not being supported in HDFStore table format (GH1848) • Bug in pd.DataFrame.sort_index where mergesort wasn’t stable when ascending=False

to_timedelta 110 Changes to Index Comparisons 111 Changes to Boolean Comparisons vs. None 112 HDFStore dropna behavior 113 Changes to display.precision option 114 Changes to Categorical.unique 114 3 Deprecations 236 1.15.4 Indexing API Changes 236 1.15.5 Float64Index API Change 238 1.15.6 HDFStore API Changes 240 1.15.7 DataFrame repr Changes 243 1.15.8 Enhancements 243 1.15.9 Experimental 274 1.18 v0.10.1 (January 22, 2013) 276 1.18.1 API changes 276 1.18.2 New features 277 1.18.3 HDFStore 277 1.19 v0.10.0 (December 17, 2012) 282 1.19.1 File parsing new features 282 1.19.2 API changes

Series now works with map objects the same way as generators (GH8909). • Added context manager to HDFStore for automatic closing (GH8791). • to_datetime gains an exact keyword to allow for a format to not in DataFrame.as_matrix() with mixed datetime64[ns] and timedelta64[ns] dtypes (GH7778) • Bug in HDFStore.select_column() not preserving UTC timezone info when selecting a DatetimeIndex (GH7777) • Bug in PeriodIndex into a Series would convert to int64 dtype, rather than object of Periods (GH7932) • Bug in HDFStore iteration when passing a where (GH8014) • Bug in DataFrameGroupby.transform when transforming with

Also, date parse functions now return consistent results. See here • The default for dropna in HDFStore has changed to False, to store by default all rows even if they are all NaN, see here • Datetime * Consistent Parsing – Changes to Index Comparisons – Changes to Boolean Comparisons vs. None – HDFStore dropna behavior – Changes to display.precision option – Changes to Categorical.unique – Changes [76]: None == None Out[76]: True In [77]: np.nan == np.nan Out[77]: False HDFStore dropna behavior The default behavior for HDFStore write functions with format=’table’ is now to keep rows that are all missing

2.12 Window Binary Corr/Cov operations return a MultiIndex DataFrame . . . . . . . . 31 1.3.2.13 HDFStore where string comparison . . . . . . . . . . . . . . . . . . . . . . . . . . 32 1.3.2.14 Index.intersection 4 Changes to Boolean Comparisons vs. None . . . . . . . . . . . . . . . . . . . . . 160 1.10.2.5 HDFStore dropna behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 1.10.2.6 Changes Float64Index API Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287 1.20.6 HDFStore API Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288 1.20.7 DataFrame

in DataFrame.as_matrix() with mixed datetime64[ns] and timedelta64[ns] dtypes (GH7778) • Bug in HDFStore.select_column() not preserving UTC timezone info when selecting a DatetimeIndex (GH7777) • Bug PeriodIndex into a Series would convert to int64 dtype, rather than object of Periods (GH7932) • Bug in HDFStore iteration when passing a where (GH8014) • Bug in DataFrameGroupby.transform when transforming with doesn't make sense NotImplementedError: operator '//' not implemented for bool dtypes • In HDFStore, select_as_multiple will always raise a KeyError, when a key or the selector is not found (GH6177)

2.12 Window Binary Corr/Cov operations return a MultiIndex DataFrame . . . . . . . . 60 1.5.2.13 HDFStore where string comparison . . . . . . . . . . . . . . . . . . . . . . . . . . 61 1.5.2.14 Index.intersection 4 Changes to Boolean Comparisons vs. None . . . . . . . . . . . . . . . . . . . . . 189 1.12.2.5 HDFStore dropna behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 190 v 1.12.2.6 Changes Float64Index API Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 316 1.22.6 HDFStore API Changes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 1.22.7 DataFrame