can now serialize a timedelta64[ns] dtype in a table (GH3577), See the docs. • added an is_open property to indicate if the underlying file handle is_open; a closed store will now report ‘CLOSED’ when arguments will now return a copy of the input object • TimeSeries is now an alias for Series. the property is_time_series can be used to distinguish (if desired) • Refactor of Sparse objects to use BlockManager on table writing • support for arbitrarily indexed dimensions • SparseSeries now has a density property (GH2384) • enable Series.str.strip/lstrip/rstrip methods to take an input argument to strip arbitrary

factorize(),nunique(),value_counts() are now supported on Index types as well. The Series.weekday property from is removed from Series for API consistency. Using a DatetimeIndex/PeriodIndex method on a Series (previously raised a TypeError) • Bug in cache coherence with chained indexing and slicing; add _is_view property to NDFrame to correctly predict views; mark is_copy on xs only if its an actual copy (and not a can now serialize a timedelta64[ns] dtype in a table (GH3577), See the docs. • added an is_open property to indicate if the underlying file handle is_open; a closed store will now report ‘CLOSED’ when

– The expiry parameter can now be a single date or a list-like object containing dates. – A new property expiry_dates was added, which returns all available expiry dates. Current behavior: In [17]: from factorize(),nunique(),value_counts() are now supported on Index types as well. The Series.weekday property from is removed from Series for API consistency. Using a DatetimeIndex/PeriodIndex method on a Series (previously raised a TypeError) • Bug in cache coherence with chained indexing and slicing; add _is_view property to NDFrame to correctly predict views; mark is_copy on xs only if its an actual copy (and not a

– The expiry parameter can now be a single date or a list-like object containing dates. – A new property expiry_dates was added, which returns all available expiry dates. Current behavior: In [17]: from factorize(),nunique(),value_counts() are now supported on Index types as well. The Series.weekday property from is removed from Series for API consistency. Using a DatetimeIndex/PeriodIndex method on a Series (previously raised a TypeError) • Bug in cache coherence with chained indexing and slicing; add _is_view property to NDFrame to correctly predict views; mark is_copy on xs only if its an actual copy (and not a

normalize as a dt accessor method. (GH10047) • DataFrame and Series now have _constructor_expanddim property as overridable constructor for one higher dimensionality data. This should be used only when it incompat cython version to build (GH9827) • Bug in plotting secondary_y incorrectly attaches right_ax property to secondary axes specifying itself recursively. (GH9861) • Bug in Series.quantile on empty Series sheet names as they are parsed. (GH9450) • Added days_in_month (compatibility alias daysinmonth) property to Timestamp, DatetimeIndex, Period, PeriodIndex, and Series.dt (GH9572) • Added decimal option

(GH13333) • Timestamp, Period, DatetimeIndex, PeriodIndex and .dt accessor have gained a .is_leap_year property to check whether the date belongs to a leap year. (GH13727) • astype() will now accept a dict of merge_ordered() and the original name will be removed in a future version (GH13358) • Timestamp.offset property (and named arg in the constructor), has been deprecated in favor of freq (GH12160) • pd.tseries deprecated and will be removed in a subsequent release. Datetime-likes now have a .is_leap_year property (GH13727) • Panel4D and PanelND constructors are deprecated and will be removed in a future version

(GH13333) • Timestamp, Period, DatetimeIndex, PeriodIndex and .dt accessor have gained a .is_leap_year property to check whether the date belongs to a leap year. (GH13727) • astype() will now accept a dict of merge_ordered() and the original name will be removed in a future version (GH13358) • Timestamp.offset property (and named arg in the constructor), has been deprecated in favor of freq (GH12160) • pd.tseries deprecated and will be removed in a subsequent release. Datetime-likes now have a .is_leap_year property (GH13727) • Panel4D and PanelND constructors are deprecated and will be removed in a future version

parse_dates keyword of pd.read_excel() to parse string columns as dates (GH14326) • Added .empty property to subclasses of Index. (GH15270) • Enabled floor division for Timedelta and TimedeltaIndex (GH15828) (GH13333) • Timestamp, Period, DatetimeIndex, PeriodIndex and .dt accessor have gained a . is_leap_year property to check whether the date belongs to a leap year. (GH13727) • astype() will now accept a dict of merge_ordered() and the original name will be removed in a future version (GH13358) • Timestamp.offset property (and named arg in the constructor), has been deprecated in favor of freq (GH12160) • pd.tseries

Int64Index([1, 2, 3], dtype='int64') The values have been correctly interpreted as integers. The .dtype property of a Categorical, CategoricalIndex or a Series with categorical type will now return an instance Improved the import time of pandas by about 2.25x. (GH16764) • Support for PEP 519 – Adding a file system path protocol on most readers (e.g. read_csv()) and writers (e.g. DataFrame.to_csv()) (GH13823). __fspath__ method to pd.HDFStore, pd.ExcelFile, and pd.ExcelWriter to work prop- erly with the file system path protocol (GH13823). • The validate argument for merge() now checks whether a merge is one-to-one

instead of raising TypeError (GH19369) • pandas.io.formats.style.Styler supports a number-format property when using to_excel() (GH22015) • DataFrame.corr() and Series.corr() now raise a ValueError along issues surrounding the installation and usage of the above three libraries. Note: – if you’re on a system with apt-get you can do sudo apt-get build-dep python-lxml to get the necessary dependencies for party libraries may extend NumPy’s type system to add support for custom arrays (see dtypes). To get the actual data inside a Index or Series, use the .array property In [11]: s.array Out[11]: