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File python-pandas.changes of Package python-pandas
------------------------------------------------------------------- Thu Jan 11 11:18:48 UTC 2018 - tchvatal@suse.com - Drop commented code to allow us py3 only build ------------------------------------------------------------------- Wed Jan 3 22:41:40 UTC 2018 - arun@gmx.de - specfile: * update copyright year - update to version 0.22.0: * Pandas 0.22.0 changes the handling of empty and all-NA sums and products. The summary is that + The sum of an empty or all-NA Series is now 0 + The product of an empty or all-NA Series is now 1 + We’ve added a min_count parameter to .sum() and .prod() controlling the minimum number of valid values for the result to be valid. If fewer than min_count non-NA values are present, the result is NA. The default is 0. To return NaN, the 0.21 behavior, use min_count=1. ------------------------------------------------------------------- Sat Dec 16 23:04:54 UTC 2017 - arun@gmx.de - update to version 0.21.1: * Highlights include: + Temporarily restore matplotlib datetime plotting functionality. This should resolve issues for users who implicitly relied on pandas to plot datetimes with matplotlib. See here. + Improvements to the Parquet IO functions introduced in 0.21.0. See here. * Improvements to the Parquet IO functionality + DataFrame.to_parquet() will now write non-default indexes when the underlying engine supports it. The indexes will be preserved when reading back in with read_parquet() (GH18581). + read_parquet() now allows to specify the columns to read from a parquet file (GH18154) + read_parquet() now allows to specify kwargs which are passed to the respective engine (GH18216) * Other Enhancements + Timestamp.timestamp() is now available in Python 2.7. (GH17329) + Grouper and TimeGrouper now have a friendly repr output (GH18203). * Deprecations + pandas.tseries.register has been renamed to pandas.plotting.register_matplotlib_converters`() (GH18301) * Performance Improvements + Improved performance of plotting large series/dataframes (GH18236). * Conversion + Bug in TimedeltaIndex subtraction could incorrectly overflow when NaT is present (GH17791) + Bug in DatetimeIndex subtracting datetimelike from DatetimeIndex could fail to overflow (GH18020) + Bug in IntervalIndex.copy() when copying and IntervalIndex with non-default closed (GH18339) + Bug in DataFrame.to_dict() where columns of datetime that are tz-aware were not converted to required arrays when used with orient='records', raising"TypeError` (GH18372) + Bug in DateTimeIndex and date_range() where mismatching tz-aware start and end timezones would not raise an err if end.tzinfo is None (GH18431) + Bug in Series.fillna() which raised when passed a long integer on Python 2 (GH18159). * Indexing + Bug in a boolean comparison of a datetime.datetime and a datetime64[ns] dtype Series (GH17965) + Bug where a MultiIndex with more than a million records was not raising AttributeError when trying to access a missing attribute (GH18165) + Bug in IntervalIndex constructor when a list of intervals is passed with non-default closed (GH18334) + Bug in Index.putmask when an invalid mask passed (GH18368) + Bug in masked assignment of a timedelta64[ns] dtype Series, incorrectly coerced to float (GH18493) * I/O + Bug in class:~pandas.io.stata.StataReader not converting date/time columns with display formatting addressed (GH17990). Previously columns with display formatting were normally left as ordinal numbers and not converted to datetime objects. + Bug in read_csv() when reading a compressed UTF-16 encoded file (GH18071) + Bug in read_csv() for handling null values in index columns when specifying na_filter=False (GH5239) + Bug in read_csv() when reading numeric category fields with high cardinality (GH18186) + Bug in DataFrame.to_csv() when the table had MultiIndex columns, and a list of strings was passed in for header (GH5539) + Bug in parsing integer datetime-like columns with specified format in read_sql (GH17855). + Bug in DataFrame.to_msgpack() when serializing data of the numpy.bool_ datatype (GH18390) + Bug in read_json() not decoding when reading line deliminted JSON from S3 (GH17200) + Bug in pandas.io.json.json_normalize() to avoid modification of meta (GH18610) + Bug in to_latex() where repeated multi-index values were not printed even though a higher level index differed from the previous row (GH14484) + Bug when reading NaN-only categorical columns in HDFStore (GH18413) + Bug in DataFrame.to_latex() with longtable=True where a latex multicolumn always spanned over three columns (GH17959) * Plotting + Bug in DataFrame.plot() and Series.plot() with DatetimeIndex where a figure generated by them is not pickleable in Python 3 (GH18439) * Groupby/Resample/Rolling + Bug in DataFrame.resample(...).apply(...) when there is a callable that returns different columns (GH15169) + Bug in DataFrame.resample(...) when there is a time change (DST) and resampling frequecy is 12h or higher (GH15549) + Bug in pd.DataFrameGroupBy.count() when counting over a datetimelike column (GH13393) + Bug in rolling.var where calculation is inaccurate with a zero-valued array (GH18430) * Reshaping + Error message in pd.merge_asof() for key datatype mismatch now includes datatype of left and right key (GH18068) + Bug in pd.concat when empty and non-empty DataFrames or Series are concatenated (GH18178 GH18187) + Bug in DataFrame.filter(...) when unicode is passed as a condition in Python 2 (GH13101) + Bug when merging empty DataFrames when np.seterr(divide='raise') is set (GH17776) * Numeric + Bug in pd.Series.rolling.skew() and rolling.kurt() with all equal values has floating issue (GH18044) + Bug in TimedeltaIndex subtraction could incorrectly overflow when NaT is present (GH17791) + Bug in DatetimeIndex subtracting datetimelike from DatetimeIndex could fail to overflow (GH18020) * Categorical + Bug in DataFrame.astype() where casting to ‘category’ on an empty DataFrame causes a segmentation fault (GH18004) + Error messages in the testing module have been improved when items have different CategoricalDtype (GH18069) + CategoricalIndex can now correctly take a pd.api.types.CategoricalDtype as its dtype (GH18116) + Bug in Categorical.unique() returning read-only codes array when all categories were NaN (GH18051) + Bug in DataFrame.groupby(axis=1) with a CategoricalIndex (GH18432) * String + Series.str.split() will now propogate NaN values across all expanded columns instead of None (GH18450) ------------------------------------------------------------------- Mon Oct 30 06:05:48 UTC 2017 - arun@gmx.de - specfile: * updated minimum numpy version to 1.9.0 (see setup.py) - update to version 0.21.0: * Highlights include: + Integration with Apache Parquet, including a new top-level read_parquet() function and DataFrame.to_parquet() method, see here. + New user-facing pandas.api.types.CategoricalDtype for specifying categoricals independent of the data, see here. + The behavior of sum and prod on all-NaN Series/DataFrames is now consistent and no longer depends on whether bottleneck is installed, see here. + Compatibility fixes for pypy, see here. + Additions to the drop, reindex and rename API to make them more consistent, see here. + Addition of the new methods DataFrame.infer_objects (see here) and GroupBy.pipe (see here). + Indexing with a list of labels, where one or more of the labels is missing, is deprecated and will raise a KeyError in a future version, see here. * full list at http://pandas.pydata.org/pandas-docs/stable/whatsnew.html ------------------------------------------------------------------- Sat Sep 23 21:12:48 UTC 2017 - arun@gmx.de - update to version 0.20.3: * bug fix release, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-20-3-july-7-2017 for complete changelog - changes from version 0.20.2: * bug fix release, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-20-2-june-4-2017 for complete changelog ------------------------------------------------------------------- Thu May 18 01:07:08 UTC 2017 - toddrme2178@gmail.com - Update to version 0.20.1 Highlights include: * New ``.agg()`` API for Series/DataFrame similar to the groupby-rolling-resample API's * Integration with the ``feather-format``, including a new top-level ``pd.read_feather()`` and ``DataFrame.to_feather()`` method * The ``.ix`` indexer has been deprecated * ``Panel`` has been deprecated * Addition of an ``IntervalIndex`` and ``Interval`` scalar type * Improved user API when grouping by index levels in ``.groupby()`` * Improved support for ``UInt64`` dtypes * A new orient for JSON serialization, ``orient='table'``, that uses the Table Schema spec and that gives the possibility for a more interactive repr in the Jupyter Notebook * Experimental support for exporting styled DataFrames (``DataFrame.style``) to Excel * Window binary corr/cov operations now return a MultiIndexed ``DataFrame`` rather than a ``Panel``, as ``Panel`` is now deprecated * Support for S3 handling now uses ``s3fs`` * Google BigQuery support now uses the ``pandas-gbq`` library ------------------------------------------------------------------- Mon May 8 03:37:27 UTC 2017 - toddrme2178@gmail.com - Fix dateutil dependency ------------------------------------------------------------------- Tue Apr 25 18:39:03 UTC 2017 - toddrme2178@gmail.com - Implement single-spec version. ------------------------------------------------------------------- Thu Mar 30 15:00:41 UTC 2017 - toddrme2178@gmail.com - update to version 0.19.2: * Enhancements The pd.merge_asof(), added in 0.19.0, gained some improvements: + pd.merge_asof() gained left_index/right_index and left_by/right_by arguments (GH14253) + pd.merge_asof() can take multiple columns in by parameter and has specialized dtypes for better performace (GH13936) * Performance Improvements + Performance regression with PeriodIndex (GH14822) + Performance regression in indexing with getitem (GH14930) + Improved performance of .replace() (GH12745) + Improved performance Series creation with a datetime index and dictionary data (GH14894) * Bug Fixes + Compat with python 3.6 for pickling of some offsets (GH14685) + Compat with python 3.6 for some indexing exception types (GH14684, GH14689) + Compat with python 3.6 for deprecation warnings in the test suite (GH14681) + Compat with python 3.6 for Timestamp pickles (GH14689) + Compat with dateutil==2.6.0; segfault reported in the testing suite (GH14621) + Allow nanoseconds in Timestamp.replace as a kwarg (GH14621) + Bug in pd.read_csv in which aliasing was being done for na_values when passed in as a dictionary (GH14203) + Bug in pd.read_csv in which column indices for a dict-like na_values were not being respected (GH14203) + Bug in pd.read_csv where reading files fails, if the number of headers is equal to the number of lines in the file (GH14515) + Bug in pd.read_csv for the Python engine in which an unhelpful error message was being raised when multi-char delimiters were not being respected with quotes (GH14582) + Fix bugs (GH14734, GH13654) in pd.read_sas and pandas.io.sas.sas7bdat.SAS7BDATReader that caused problems when reading a SAS file incrementally. + Bug in pd.read_csv for the Python engine in which an unhelpful error message was being raised when skipfooter was not being respected by Python’s CSV library (GH13879) + Bug in .fillna() in which timezone aware datetime64 values were incorrectly rounded (GH14872) + Bug in .groupby(..., sort=True) of a non-lexsorted MultiIndex when grouping with multiple levels (GH14776) + Bug in pd.cut with negative values and a single bin (GH14652) + Bug in pd.to_numeric where a 0 was not unsigned on a downcast='unsigned' argument (GH14401) + Bug in plotting regular and irregular timeseries using shared axes (sharex=True or ax.twinx()) (GH13341, GH14322). + Bug in not propogating exceptions in parsing invalid datetimes, noted in python 3.6 (GH14561) + Bug in resampling a DatetimeIndex in local TZ, covering a DST change, which would raise AmbiguousTimeError (GH14682) + Bug in indexing that transformed RecursionError into KeyError or IndexingError (GH14554) + Bug in HDFStore when writing a MultiIndex when using data_columns=True (GH14435) + Bug in HDFStore.append() when writing a Series and passing a min_itemsize argument containing a value for the index (GH11412) + Bug when writing to a HDFStore in table format with a min_itemsize value for the index and without asking to append (GH10381) + Bug in Series.groupby.nunique() raising an IndexError for an empty Series (GH12553) + Bug in DataFrame.nlargest and DataFrame.nsmallest when the index had duplicate values (GH13412) + Bug in clipboard functions on linux with python2 with unicode and separators (GH13747) + Bug in clipboard functions on Windows 10 and python 3 (GH14362, GH12807) + Bug in .to_clipboard() and Excel compat (GH12529) + Bug in DataFrame.combine_first() for integer columns (GH14687). + Bug in pd.read_csv() in which the dtype parameter was not being respected for empty data (GH14712) + Bug in pd.read_csv() in which the nrows parameter was not being respected for large input when using the C engine for parsing (GH7626) + Bug in pd.merge_asof() could not handle timezone-aware DatetimeIndex when a tolerance was specified (GH14844) + Explicit check in to_stata and StataWriter for out-of-range values when writing doubles (GH14618) + Bug in .plot(kind='kde') which did not drop missing values to generate the KDE Plot, instead generating an empty plot. (GH14821) + Bug in unstack() if called with a list of column(s) as an argument, regardless of the dtypes of all columns, they get coerced to object (GH11847) - update to version 0.19.1: * Performance Improvements + Fixed performance regression in factorization of Period data (GH14338) + Fixed performance regression in Series.asof(where) when where is a scalar (GH14461) + Improved performance in DataFrame.asof(where) when where is a scalar (GH14461) + Improved performance in .to_json() when lines=True (GH14408) + Improved performance in certain types of loc indexing with a MultiIndex (GH14551). * Bug Fixes + Source installs from PyPI will now again work without cython installed, as in previous versions (GH14204) + Compat with Cython 0.25 for building (GH14496) + Fixed regression where user-provided file handles were closed in read_csv (c engine) (GH14418). + Fixed regression in DataFrame.quantile when missing values where present in some columns (GH14357). + Fixed regression in Index.difference where the freq of a DatetimeIndex was incorrectly set (GH14323) + Added back pandas.core.common.array_equivalent with a deprecation warning (GH14555). + Bug in pd.read_csv for the C engine in which quotation marks were improperly parsed in skipped rows (GH14459) + Bug in pd.read_csv for Python 2.x in which Unicode quote characters were no longer being respected (GH14477) + Fixed regression in Index.append when categorical indices were appended (GH14545). + Fixed regression in pd.DataFrame where constructor fails when given dict with None value (GH14381) + Fixed regression in DatetimeIndex._maybe_cast_slice_bound when index is empty (GH14354). + Bug in localizing an ambiguous timezone when a boolean is passed (GH14402) + Bug in TimedeltaIndex addition with a Datetime-like object where addition overflow in the negative direction was not being caught (GH14068, GH14453) + Bug in string indexing against data with object Index may raise AttributeError (GH14424) + Corrrecly raise ValueError on empty input to pd.eval() and df.query() (GH13139) + Bug in RangeIndex.intersection when result is a empty set (GH14364). + Bug in groupby-transform broadcasting that could cause incorrect dtype coercion (GH14457) + Bug in Series.__setitem__ which allowed mutating read-only arrays (GH14359). + Bug in DataFrame.insert where multiple calls with duplicate columns can fail (GH14291) + pd.merge() will raise ValueError with non-boolean parameters in passed boolean type arguments (GH14434) + Bug in Timestamp where dates very near the minimum (1677-09) could underflow on creation (GH14415) + Bug in pd.concat where names of the keys were not propagated to the resulting MultiIndex (GH14252) + Bug in pd.concat where axis cannot take string parameters 'rows' or 'columns' (GH14369) + Bug in pd.concat with dataframes heterogeneous in length and tuple keys (GH14438) + Bug in MultiIndex.set_levels where illegal level values were still set after raising an error (GH13754) + Bug in DataFrame.to_json where lines=True and a value contained a } character (GH14391) + Bug in df.groupby causing an AttributeError when grouping a single index frame by a column and the index level (:issue`14327`) + Bug in df.groupby where TypeError raised when pd.Grouper(key=...) is passed in a list (GH14334) + Bug in pd.pivot_table may raise TypeError or ValueError when index or columns is not scalar and values is not specified (GH14380) ------------------------------------------------------------------- Sun Oct 23 01:32:23 UTC 2016 - toddrme2178@gmail.com - update to version 0.19.0: (long changelog, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-19-0-october-2-2016) * Highlights include: + merge_asof() for asof-style time-series joining + .rolling() is now time-series aware + read_csv() now supports parsing Categorical data + A function union_categorical() has been added for combining categoricals + PeriodIndex now has its own period dtype, and changed to be more consistent with other Index classes + Sparse data structures gained enhanced support of int and bool dtypes + Comparison operations with Series no longer ignores the index, see here for an overview of the API changes. + Introduction of a pandas development API for utility functions + Deprecation of Panel4D and PanelND. We recommend to represent these types of n-dimensional data with the xarray package. + Removal of the previously deprecated modules pandas.io.data, pandas.io.wb, pandas.tools.rplot. - specfile: * require python3-Cython * Split documentation into own subpackage to speed up build. * Remove buildrequires for optional dependencies to speed up build. - Remove unneeded patches: * 0001_disable_experimental_msgpack_big_endian.patch ^ * 0001_respect_byteorder_in_statareader.patch ------------------------------------------------------------------- Tue Jul 12 16:44:48 UTC 2016 - antoine.belvire@laposte.net - Update to 0.8.1: * .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group. * pd.to_datetime() has gained the ability to assemble dates from a DataFrame. * Method chaining improvements. * Custom business hour offset. * Many bug fixes in the handling of sparse. * Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsb (GH13045). - Changes from 0.8.0: * Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby. * Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings. * API breaking change to the .resample method to make it more .groupby like. * Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError. * The .to_xarray() function has been added for compatibility with the xarray package. * The read_sas function has been enhanced to read sas7bdat files. * Addition of the .str.extractall() method, and API changes to the .str.extract() method and .str.cat() method. * pd.test() top-level nose test runner is available (GH4327). ------------------------------------------------------------------- Fri Feb 26 13:13:58 UTC 2016 - tbechtold@suse.com - Require python-python-dateutil. package was renamed ------------------------------------------------------------------- Tue Feb 9 17:01:02 UTC 2016 - aplanas@suse.com - Add 0001_respect_byteorder_in_statareader.patch Fix StataReader in big endian architectures https://github.com/pydata/pandas/issues/11282 - Add 0001_disable_experimental_msgpack_big_endian.patch Skip experimental msgpack test in big endian systems ------------------------------------------------------------------- Wed Feb 3 15:27:31 UTC 2016 - aplanas@suse.com - Remove non-needed BuildRequires - Update Requires from documentation - Update Recommends from documentation - Add tests in %check section ------------------------------------------------------------------- Mon Nov 30 09:56:31 UTC 2015 - toddrme2178@gmail.com - update to version 0.17.1: (for full changelog see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-17-1-november-21-2015) Highlights include: * Support for Conditional HTML Formatting, see here * Releasing the GIL on the csv reader & other ops, see here * Fixed regression in DataFrame.drop_duplicates from 0.16.2, causing incorrect results on integer values (GH11376) ------------------------------------------------------------------- Mon Oct 12 09:28:25 UTC 2015 - toddrme2178@gmail.com - update to version 0.17.0: (for full changelog see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-17-0-october-9-2015) Highlights: * Release the Global Interpreter Lock (GIL) on some cython operations, see here * Plotting methods are now available as attributes of the .plot accessor, see here * The sorting API has been revamped to remove some long-time inconsistencies, see here * Support for a datetime64[ns] with timezones as a first-class dtype, see here * The default for to_datetime will now be to raise when presented with unparseable formats, previously this would return the original input. 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 accessor (dt) now supports Series.dt.strftime to generate formatted strings for datetime-likes, and Series.dt.total_seconds to ge nerate each duration of the timedelta in seconds. See here * Period and PeriodIndex can handle multiplied freq like 3D, which corresponding to 3 days span. See here * Development installed versions of pandas will now have PEP440 compliant version strings (GH9518) * Development support for benchmarking with the Air Speed Velocity library (GH8361) * Support for reading SAS xport files, see here * Documentation comparing SAS to pandas, see here * Removal of the automatic TimeSeries broadcasting, deprecated since 0.8.0, see here * Display format with plain text can optionally align with Unicode East Asian Width, see here * Compatibility with Python 3.5 (GH11097) * Compatibility with matplotlib 1.5.0 (GH11111) ------------------------------------------------------------------- Mon Jun 29 11:06:30 UTC 2015 - toddrme2178@gmail.com - update to version 0.16.2: (see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-16-2-june-12-2015) * Highlights + A new pipe method + Documentation on how to use numba with pandas * Enhancements + Added rsplit to Index/Series StringMethods (GH10303) + Removed the hard-coded size limits on the DataFrame HTML representation in the IPython notebook, and leave this to IPython itself (only for IPython v3.0 or greater). This eliminates the duplicate scroll bars that appeared in the notebook with large frames (GH10231). Note that the notebook has a toggle output scrolling feature to limit the display of very large frames (by clicking left of the output). You can also configure the way DataFrames are displayed using the pandas options, see here here. + axis parameter of DataFrame.quantile now accepts also index and column. (GH9543) * API Changes + Holiday now raises NotImplementedError if both offset and observance are used in the constructor instead of returning an incorrect result (GH10217). * Performance Improvements + Improved Series.resample performance with dtype=datetime64[ns] (GH7754) + Increase performance of str.split when expand=True (GH10081) * Bug Fixes + Bug in Series.hist raises an error when a one row Series was given (GH10214) + Bug where HDFStore.select modifies the passed columns list (GH7212) + Bug in Categorical repr with display.width of None in Python 3 (GH10087) + Bug in to_json with certain orients and a CategoricalIndex would segfault (GH10317) + Bug where some of the nan funcs do not have consistent return dtypes (GH10251) + Bug in DataFrame.quantile on checking that a valid axis was passed (GH9543) + Bug in groupby.apply aggregation for Categorical not preserving categories (GH10138) + Bug in to_csv where date_format is ignored if the datetime is fractional (GH10209) + Bug in DataFrame.to_json with mixed data types (GH10289) + Bug in cache updating when consolidating (GH10264) + Bug in mean() where integer dtypes can overflow (GH10172) + Bug where Panel.from_dict does not set dtype when specified (GH10058) + Bug in Index.union raises AttributeError when passing array-likes. (GH10149) + Bug in Timestamp‘s’ microsecond, quarter, dayofyear, week and daysinmonth properties return np.int type, not built-in int. (GH10050) + Bug in NaT raises AttributeError when accessing to daysinmonth, dayofweek properties. (GH10096) + Bug in Index repr when using the max_seq_items=None setting (GH10182). + Bug in getting timezone data with dateutil on various platforms ( GH9059, GH8639, GH9663, GH10121) + Bug in displaying datetimes with mixed frequencies; display ‘ms’ datetimes to the proper precision. (GH10170) + Bug in setitem where type promotion is applied to the entire block (GH10280) + Bug in Series arithmetic methods may incorrectly hold names (GH10068) + Bug in GroupBy.get_group when grouping on multiple keys, one of which is categorical. (GH10132) + Bug in DatetimeIndex and TimedeltaIndex names are lost after timedelta arithmetics ( GH9926) + Bug in DataFrame construction from nested dict with datetime64 (GH10160) + Bug in Series construction from dict with datetime64 keys (GH9456) + Bug in Series.plot(label="LABEL") not correctly setting the label (GH10119) + Bug in plot not defaulting to matplotlib axes.grid setting (GH9792) + Bug causing strings containing an exponent, but no decimal to be parsed as int instead of float in engine='python' for the read_csv parser (GH9565) + Bug in Series.align resets name when fill_value is specified (GH10067) + Bug in read_csv causing index name not to be set on an empty DataFrame (GH10184) + Bug in SparseSeries.abs resets name (GH10241) + Bug in TimedeltaIndex slicing may reset freq (GH10292) + Bug in GroupBy.get_group raises ValueError when group key contains NaT (GH6992) + Bug in SparseSeries constructor ignores input data name (GH10258) + Bug in Categorical.remove_categories causing a ValueError when removing the NaN category if underlying dtype is floating-point (GH10156) + Bug where infer_freq infers timerule (WOM-5XXX) unsupported by to_offset (GH9425) + Bug in DataFrame.to_hdf() where table format would raise a seemingly unrelated error for invalid (non-string) column names. This is now explicitly forbidden. (GH9057) + Bug to handle masking empty DataFrame (GH10126). + Bug where MySQL interface could not handle numeric table/column names (GH10255) + Bug in read_csv with a date_parser that returned a datetime64 array of other time resolution than [ns] (GH10245) + Bug in Panel.apply when the result has ndim=0 (GH10332) + Bug in read_hdf where auto_close could not be passed (GH9327). + Bug in read_hdf where open stores could not be used (GH10330). + Bug in adding empty DataFrame``s, now results in a ``DataFrame that .equals an empty DataFrame (GH10181). + Bug in to_hdf and HDFStore which did not check that complib choices were valid (GH4582, GH8874). ------------------------------------------------------------------- Tue May 19 09:18:50 UTC 2015 - toddrme2178@gmail.com - Update to version 0.16.1 * Highlights - Support for a ``CategoricalIndex``, a category based index - New section on how-to-contribute to pandas - Revised "Merge, join, and concatenate" documentation, including graphical examples to make it easier to understand each operations - New method sample for drawing random samples from Series, DataFrames and Panels. - The default Index printing has changed to a more uniform format - BusinessHour datetime-offset is now supported * Enhancements - BusinessHour`offset is now supported, which represents business hours starting from 09:00 - 17:00 on BusinessDay by default. - DataFrame.diff now takes an axis parameter that determines the direction of differencing - Allow clip, clip_lower, and clip_upper to accept array-like arguments as thresholds (This is a regression from 0.11.0). These methods now have an axis parameter which determines how the Series or DataFrame will be aligned with the threshold(s). - DataFrame.mask() and Series.mask() now support same keywords as where - drop function can now accept errors keyword to suppress ValueError raised when any of label does not exist in the target data. - Allow conversion of values with dtype datetime64 or timedelta64 to strings using astype(str) - get_dummies function now accepts sparse keyword. If set to True, the return DataFrame is sparse, e.g. SparseDataFrame. - Period now accepts datetime64 as value input. - Allow timedelta string conversion when leading zero is missing from time definition, ie 0:00:00 vs 00:00:00. - Allow Panel.shift with axis='items' - Trying to write an excel file now raises NotImplementedError if the DataFrame has a MultiIndex instead of writing a broken Excel file. - Allow Categorical.add_categories to accept Series or np.array. - Add/delete str/dt/cat accessors dynamically from __dir__. - Add normalize as a dt accessor method. - DataFrame and Series now have _constructor_expanddim property as overridable constructor for one higher dimensionality data. This should be used only when it is really needed - pd.lib.infer_dtype now returns 'bytes' in Python 3 where appropriate. - We introduce a CategoricalIndex, a new type of index object that is useful for supporting indexing with duplicates. This is a container around a Categorical (introduced in v0.15.0) and allows efficient indexing and storage of an index with a large number of duplicated elements. Prior to 0.16.1, setting the index of a DataFrame/Series with a category dtype would convert this to regular object-based Index. - Series, DataFrames, and Panels now have a new method: pandas.DataFrame.sample. The method accepts a specific number of rows or columns to return, or a fraction of the total number or rows or columns. It also has options for sampling with or without replacement, for passing in a column for weights for non-uniform sampling, and for setting seed values to facilitate replication. - The following new methods are accesible via .str accessor to apply the function to each values. + capitalize() + swapcase() + normalize() + partition() + rpartition() + index() + rindex() + translate() - Added StringMethods (.str accessor) to Index - split now takes expand keyword to specify whether to expand dimensionality. return_type is deprecated. * API changes - When passing in an ax to df.plot( ..., ax=ax), the sharex kwarg will now default to False. - Add support for separating years and quarters using dashes, for example 2014-Q1. - pandas.DataFrame.assign now inserts new columns in alphabetical order. Previously the order was arbitrary. - By default, read_csv and read_table will now try to infer the compression type based on the file extension. Set compression=None to restore the previous behavior (no decompression). - The string representation of Index and its sub-classes have now been unified. These will show a single-line display if there are few values; a wrapped multi-line display for a lot of values (but less than display.max_seq_items; if lots of items > display.max_seq_items) will show a truncated display (the head and tail of the data). The formatting for MultiIndex is unchanges (a multi-line wrapped display). The display width responds to the option display.max_seq_items, which is defaulted to 100. * Deprecations - Series.str.split's return_type keyword was removed in favor of expand * Performance Improvements - Improved csv write performance with mixed dtypes, including datetimes by up to 5x - Improved csv write performance generally by 2x - Improved the performance of pd.lib.max_len_string_array by 5-7x * Bug Fixes - Bug where labels did not appear properly in the legend of DataFrame.plot(), passing label= arguments works, and Series indices are no longer mutated. - Bug in json serialization causing a segfault when a frame had zero length. - Bug in read_csv where missing trailing delimiters would cause segfault. - Bug in retaining index name on appending - Bug in scatter_matrix draws unexpected axis ticklabels - Fixed bug in StataWriter resulting in changes to input DataFrame upon save. - Bug in transform causing length mismatch when null entries were present and a fast aggregator was being used - Bug in equals causing false negatives when block order differed - Bug in grouping with multiple pd.Grouper where one is non-time based - Bug in read_sql_table error when reading postgres table with timezone - Bug in DataFrame slicing may not retain metadata - Bug where TimdeltaIndex were not properly serialized in fixed HDFStore - Bug with TimedeltaIndex constructor ignoring name when given another TimedeltaIndex as data. - Bug in DataFrameFormatter._get_formatted_index with not applying max_colwidth to the DataFrame index - Bug in .loc with a read-only ndarray data source - Bug in groupby.apply() that would raise if a passed user defined function either returned only None (for all input). - Always use temporary files in pytables tests - Bug in plotting continuously using secondary_y may not show legend properly. - Bug in DataFrame.plot(kind="hist") results in TypeError when DataFrame contains non-numeric columns - Bug where repeated plotting of DataFrame with a DatetimeIndex may raise TypeError - Bug in setup.py that would allow an incompat cython version to build - Bug in plotting secondary_y incorrectly attaches right_ax property to secondary axes specifying itself recursively. - Bug in Series.quantile on empty Series of type Datetime or Timedelta - Bug in where causing incorrect results when upcasting was required - Bug in FloatArrayFormatter where decision boundary for displaying "small" floats in decimal format is off by one order of magnitude for a given display.precision - Fixed bug where DataFrame.plot() raised an error when both color and style keywords were passed and there was no color symbol in the style strings - Not showing a DeprecationWarning on combining list-likes with an Index - Bug in read_csv and read_table when using skip_rows parameter if blank lines are present. - Bug in read_csv() interprets index_col=True as 1 - Bug in index equality comparisons using == failing on Index/MultiIndex type incompatibility - Bug in which SparseDataFrame could not take nan as a column name - Bug in to_msgpack and read_msgpack zlib and blosc compression support - Bug GroupBy.size doesn't attach index name properly if grouped by TimeGrouper - Bug causing an exception in slice assignments because length_of_indexer returns wrong results - Bug in csv parser causing lines with initial whitespace plus one non-space character to be skipped. - Bug in C csv parser causing spurious NaNs when data started with newline followed by whitespace. - Bug causing elements with a null group to spill into the final group when grouping by a Categorical - Bug where .iloc and .loc behavior is not consistent on empty dataframes - Bug in invalid attribute access on a TimedeltaIndex incorrectly raised ValueError instead of AttributeError - Bug in unequal comparisons between categorical data and a scalar, which was not in the categories (e.g. Series(Categorical(list("abc"), ordered=True)) > "d". This returned False for all elements, but now raises a TypeError. Equality comparisons also now return False for == and True for !=. - Bug in DataFrame __setitem__ when right hand side is a dictionary - Bug in where when dtype is datetime64/timedelta64, but dtype of other is not - Bug in MultiIndex.sortlevel() results in unicode level name breaks - Bug in which groupby.transform incorrectly enforced output dtypes to match input dtypes. - Bug in DataFrame constructor when columns parameter is set, and data is an empty list - Bug in bar plot with log=True raises TypeError if all values are less than 1 - Bug in horizontal bar plot ignores log=True - Bug in PyTables queries that did not return proper results using the index - Bug where dividing a dataframe containing values of type Decimal by another Decimal would raise. - Bug where using DataFrames asfreq would remove the name of the index. - Bug causing extra index point when resample BM/BQ - Changed caching in AbstractHolidayCalendar to be at the instance level rather than at the class level as the latter can result in unexpected behaviour. - Fixed latex output for multi-indexed dataframes - Bug causing an exception when setting an empty range using DataFrame.loc - Bug in hiding ticklabels with subplots and shared axes when adding a new plot to an existing grid of axes - Bug in transform and filter when grouping on a categorical variable - Bug in transform when groups are equal in number and dtype to the input index - Google BigQuery connector now imports dependencies on a per-method basis. - Updated BigQuery connector to no longer use deprecated oauth2client.tools.run() - Bug in subclassed DataFrame. It may not return the correct class, when slicing or subsetting it. - Bug in .median() where non-float null values are not handled correctly - Bug in Series.fillna() where it raises if a numerically convertible string is given ------------------------------------------------------------------- Tue Mar 24 12:44:20 UTC 2015 - toddrme2178@gmail.com - update to version 0.16.0: * Highlights: - DataFrame.assign method - Series.to_coo/from_coo methods to interact with scipy.sparse - Backwards incompatible change to Timedelta to conform the .seconds attribute with datetime.timedelta - Changes to the .loc slicing API to conform with the behavior of .ix - Changes to the default for ordering in the Categorical constructor - Enhancement to the .str accessor to make string operations easier - The pandas.tools.rplot, pandas.sandbox.qtpandas and pandas.rpy modules are deprecated. We refer users to external packages like seaborn, pandas-qt and rpy2 for similar or equivalent functionality * New features - Inspired by dplyr's mutate verb, DataFrame has a new assign method. - Added SparseSeries.to_coo and SparseSeries.from_coo methods for converting to and from scipy.sparse.coo_matrix instances. - Following new methods are accesible via .str accessor to apply the function to each values. This is intended to make it more consistent with standard methods on strings: isalnum(), isalpha(), isdigit(), isdigit(), isspace(), islower(), isupper(), istitle(), isnumeric(), isdecimal(), find(), rfind(), ljust(), rjust(), zfill() - Reindex now supports method='nearest' for frames or series with a monotonic increasing or decreasing index. - The read_excel() function's sheetname argument now accepts a list and None, to get multiple or all sheets respectively. If more than one sheet is specified, a dictionary is returned. - Allow Stata files to be read incrementally with an iterator; support for long strings in Stata files. - Paths beginning with ~ will now be expanded to begin with the user's home directory. - Added time interval selection in get_data_yahoo. - Added Timestamp.to_datetime64() to complement Timedelta.to_timedelta64(). - tseries.frequencies.to_offset() now accepts Timedelta as input. - Lag parameter was added to the autocorrelation method of Series, defaults to lag-1 autocorrelation. - Timedelta will now accept nanoseconds keyword in constructor. - SQL code now safely escapes table and column names. - Added auto-complete for Series.str.<tab>, Series.dt.<tab> and Series.cat.<tab>. - Index.get_indexer now supports method='pad' and method='backfill' even for any target array, not just monotonic targets. - Index.asof now works on all index types. - A verbose argument has been augmented in io.read_excel(), defaults to False. Set to True to print sheet names as they are parsed. - Added days_in_month (compatibility alias daysinmonth) property to Timestamp, DatetimeIndex, Period, PeriodIndex, and Series.dt. - Added decimal option in to_csv to provide formatting for non-'.' decimal separators - Added normalize option for Timestamp to normalized to midnight - Added example for DataFrame import to R using HDF5 file and rhdf5 library. * Backwards incompatible API changes - In v0.16.0, we are restoring the API to match that of datetime.timedelta. Further, the component values are still available through the .components accessor. This affects the .seconds and .microseconds accessors, and removes the .hours, .minutes, .milliseconds accessors. These changes affect TimedeltaIndex and the Series .dt accessor as well. - The behavior of a small sub-set of edge cases for using .loc have changed. Furthermore we have improved the content of the error messages that are raised: + Slicing with .loc where the start and/or stop bound is not found in the index is now allowed; this previously would raise a KeyError. This makes the behavior the same as .ix in this case. This change is only for slicing, not when indexing with a single label. + Allow slicing with float-like values on an integer index for .ix. Previously this was only enabled for .loc: + Provide a useful exception for indexing with an invalid type for that index when using .loc. For example trying to use .loc on an index of type DatetimeIndex or PeriodIndex or TimedeltaIndex, with an integer (or a float). - In prior versions, Categoricals that had an unspecified ordering (meaning no ordered keyword was passed) were defaulted as ordered Categoricals. Going forward, the ordered keyword in the Categorical constructor will default to False. Ordering must now be explicit. Furthermore, previously you *could* change the ordered attribute of a Categorical by just setting the attribute, e.g. cat.ordered=True; This is now deprecated and you should use cat.as_ordered() or cat.as_unordered(). These will by default return a **new** object and not modify the existing object. - Index.duplicated now returns np.array(dtype=bool) rather than Index(dtype=object) containing bool values. - DataFrame.to_json now returns accurate type serialisation for each column for frames of mixed dtype - DatetimeIndex, PeriodIndex and TimedeltaIndex.summary now output the same format. - TimedeltaIndex.freqstr now output the same string format as DatetimeIndex. - Bar and horizontal bar plots no longer add a dashed line along the info axis. The prior style can be achieved with matplotlib's axhline or axvline methods. - Series accessors .dt, .cat and .str now raise AttributeError instead of TypeError if the series does not contain the appropriate type of data. This follows Python's built-in exception hierarchy more closely and ensures that tests like hasattr(s, 'cat') are consistent on both Python 2 and 3. - Series now supports bitwise operation for integral types. Previously even if the input dtypes were integral, the output dtype was coerced to bool. - During division involving a Series or DataFrame, 0/0 and 0//0 now give np.nan instead of np.inf. - Series.values_counts and Series.describe for categorical data will now put NaN entries at the end. - Series.describe for categorical data will now give counts and frequencies of 0, not NaN, for unused categories - Due to a bug fix, looking up a partial string label with DatetimeIndex.asof now includes values that match the string, even if they are after the start of the partial string label. Old behavior: * Deprecations - The rplot trellis plotting interface is deprecated and will be removed in a future version. We refer to external packages like seaborn for similar but more refined functionality. - The pandas.sandbox.qtpandas interface is deprecated and will be removed in a future version. We refer users to the external package pandas-qt. - The pandas.rpy interface is deprecated and will be removed in a future version. Similar functionaility can be accessed thru the rpy2 project - Adding DatetimeIndex/PeriodIndex to another DatetimeIndex/PeriodIndex is being deprecated as a set-operation. This will be changed to a TypeError in a future version. .union() should be used for the union set operation. - Subtracting DatetimeIndex/PeriodIndex from another DatetimeIndex/PeriodIndex is being deprecated as a set-operation. This will be changed to an actual numeric subtraction yielding a TimeDeltaIndex in a future version. .difference() should be used for the differencing set operation. * Removal of prior version deprecations/changes - DataFrame.pivot_table and crosstab's rows and cols keyword arguments were removed in favor of index and columns - DataFrame.to_excel and DataFrame.to_csv cols keyword argument was removed in favor of columns - Removed convert_dummies in favor of get_dummies - Removed value_range in favor of describe * Performance Improvements - Fixed a performance regression for .loc indexing with an array or list-like. - DataFrame.to_json 30x performance improvement for mixed dtype frames. - Performance improvements in MultiIndex.duplicated by working with labels instead of values - Improved the speed of nunique by calling unique instead of value_counts - Performance improvement of up to 10x in DataFrame.count and DataFrame.dropna by taking advantage of homogeneous/heterogeneous dtypes appropriately - Performance improvement of up to 20x in DataFrame.count when using a MultiIndex and the level keyword argument - Performance and memory usage improvements in merge when key space exceeds int64 bounds - Performance improvements in multi-key groupby - Performance improvements in MultiIndex.sortlevel - Performance and memory usage improvements in DataFrame.duplicated - Cythonized Period - Decreased memory usage on to_hdf * Bug Fixes - Changed .to_html to remove leading/trailing spaces in table body - Fixed issue using read_csv on s3 with Python 3 - Fixed compatibility issue in DatetimeIndex affecting architectures where numpy.int_ defaults to numpy.int32 - Bug in Panel indexing with an object-like - Bug in the returned Series.dt.components index was reset to the default index - Bug in Categorical.__getitem__/__setitem__ with listlike input getting incorrect results from indexer coercion - Bug in partial setting with a DatetimeIndex - Bug in groupby for integer and datetime64 columns when applying an aggregator that caused the value to be changed when the number was sufficiently large - Fixed bug in to_sql when mapping a Timestamp object column (datetime column with timezone info) to the appropriate sqlalchemy type. - Fixed bug in to_sql dtype argument not accepting an instantiated SQLAlchemy type. - Bug in .loc partial setting with a np.datetime64 - Incorrect dtypes inferred on datetimelike looking Series & on .xs slices - Items in Categorical.unique() (and s.unique() if s is of dtype category) now appear in the order in which they are originally found, not in sorted order. This is now consistent with the behavior for other dtypes in pandas. - Fixed bug on big endian platforms which produced incorrect results in StataReader. - Bug in MultiIndex.has_duplicates when having many levels causes an indexer overflow - Bug in pivot and unstack where nan values would break index alignment - Bug in left join on multi-index with sort=True or null values. - Bug in MultiIndex where inserting new keys would fail. - Bug in groupby when key space exceeds int64 bounds. - Bug in unstack with TimedeltaIndex or DatetimeIndex and nulls. - Bug in rank where comparing floats with tolerance will cause inconsistent behaviour. - Fixed character encoding bug in read_stata and StataReader when loading data from a URL. - Bug in adding offsets.Nano to other offets raises TypeError - Bug in DatetimeIndex iteration, related to, fixed in - Bugs in resample around DST transitions. This required fixing offset classes so they behave correctly on DST transitions. - Bug in binary operator method (eg .mul()) alignment with integer levels. - Bug in boxplot, scatter and hexbin plot may show an unnecessary warning - Bug in subplot with layout kw may show unnecessary warning - Bug in using grouper functions that need passed thru arguments (e.g. axis), when using wrapped function (e.g. fillna), - DataFrame now properly supports simultaneous copy and dtype arguments in constructor - Bug in read_csv when using skiprows on a file with CR line endings with the c engine. - isnull now detects NaT in PeriodIndex - Bug in groupby .nth() with a multiple column groupby - Bug in DataFrame.where and Series.where coerce numerics to string incorrectly - Bug in DataFrame.where and Series.where raise ValueError when string list-like is passed. - Accessing Series.str methods on with non-string values now raises TypeError instead of producing incorrect results - Bug in DatetimeIndex.__contains__ when index has duplicates and is not monotonic increasing - Fixed division by zero error for Series.kurt() when all values are equal - Fixed issue in the xlsxwriter engine where it added a default 'General' format to cells if no other format wass applied. This prevented other row or column formatting being applied. - Fixes issue with index_col=False when usecols is also specified in read_csv. - Bug where wide_to_long would modify the input stubnames list - Bug in to_sql not storing float64 values using double precision. - SparseSeries and SparsePanel now accept zero argument constructors (same as their non-sparse counterparts). - Regression in merging Categorical and object dtypes - Bug in read_csv with buffer overflows with certain malformed input files - Bug in groupby MultiIndex with missing pair - Fixed bug in Series.groupby where grouping on MultiIndex levels would ignore the sort argument - Fix bug in DataFrame.Groupby where sort=False is ignored in the case of Categorical columns. - Fixed bug with reading CSV files from Amazon S3 on python 3 raising a TypeError - Bug in the Google BigQuery reader where the 'jobComplete' key may be present but False in the query results - Bug in Series.values_counts with excluding NaN for categorical type Series with dropna=True - Fixed mising numeric_only option for DataFrame.std/var/sem - Support constructing Panel or Panel4D with scalar data - Series text representation disconnected from `max_rows`/`max_columns`. - Series number formatting inconsistent when truncated. - A Spurious SettingWithCopy Warning was generated when setting a new item in a frame in some cases ------------------------------------------------------------------- Mon Jan 12 13:46:26 UTC 2015 - toddrme2178@gmail.com - update to version 0.15.2: * API changes: - Indexing in MultiIndex beyond lex-sort depth is now supported, though a lexically sorted index will have a better performance. (GH2646) - Bug in unique of Series with category dtype, which returned all categories regardless whether they were "used" or not (see GH8559 for the discussion). Previous behaviour was to return all categories. - Series.all and Series.any now support the level and skipna parameters. Series.all, Series.any, Index.all, and Index.any no longer support the out and keepdims parameters, which existed for compatibility with ndarray. Various index types no longer support the all and any aggregation functions and will now raise TypeError. (GH8302). - Allow equality comparisons of Series with a categorical dtype and object dtype; previously these would raise TypeError (GH8938) - Bug in NDFrame: conflicting attribute/column names now behave consistently between getting and setting. Previously, when both a column and attribute named y existed, data.y would return the attribute, while data.y = z would update the column (GH8994) - Timestamp('now') is now equivalent to Timestamp.now() in that it returns the local time rather than UTC. Also, Timestamp('today') is now equivalent to Timestamp.today() and both have tz as a possible argument. (GH9000) - Fix negative step support for label-based slices (GH8753) * Enhancements: - Added ability to export Categorical data to Stata (GH8633). See here for limitations of categorical variables exported to Stata data files. - Added flag order_categoricals to StataReader and read_stata to select whether to order imported categorical data (GH8836). See here for more information on importing categorical variables from Stata data files. - Added ability to export Categorical data to to/from HDF5 (GH7621). Queries work the same as if it was an object array. However, the category dtyped data is stored in a more efficient manner. See here for an example and caveats w.r.t. prior versions of pandas. - Added support for searchsorted() on Categorical class (GH8420). - Added the ability to specify the SQL type of columns when writing a DataFrame to a database (GH8778). For example, specifying to use the sqlalchemy String type instead of the default Text type for string columns. - Series.all and Series.any now support the level and skipna parameters (GH8302). - Panel now supports the all and any aggregation functions. (GH8302). - Added support for utcfromtimestamp(), fromtimestamp(), and combine() on Timestamp class (GH5351). - Added Google Analytics (pandas.io.ga) basic documentation (GH8835). - Timedelta arithmetic returns NotImplemented in unknown cases, allowing extensions by custom classes (GH8813). - Timedelta now supports arithemtic with numpy.ndarray objects of the appropriate dtype (numpy 1.8 or newer only) (GH8884). - Added Timedelta.to_timedelta64() method to the public API (GH8884). - Added gbq.generate_bq_schema() function to the gbq module (GH8325). - 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 require an exact match for a provided format string (if its False). exact defaults to True (meaning that exact matching is still the default) (GH8904) - Added axvlines boolean option to parallel_coordinates plot function, determines whether vertical lines will be printed, default is True - Added ability to read table footers to read_html (GH8552). - to_sql now infers datatypes of non-NA values for columns that contain NA values and have dtype object (GH8778). * Performance: - Reduce memory usage when skiprows is an integer in read_csv (GH8681) - Performance boost for to_datetime conversions with a passed format=, and the exact=False (GH8904) * Bug fixes: - Bug in concat of Series with category dtype which were coercing to object. (GH8641) - Bug in Timestamp-Timestamp not returning a Timedelta type and datelike-datelike ops with timezones (GH8865) - Made consistent a timezone mismatch exception (either tz operated with None or incompatible timezone), will now return TypeError rather than ValueError (a couple of edge cases only), (GH8865) - Bug in using a pd.Grouper(key=...) with no level/axis or level only (GH8795, GH8866) - Report a TypeError when invalid/no paramaters are passed in a groupby (GH8015) - Bug in packaging pandas with py2app/cx_Freeze (GH8602, GH8831) - Bug in groupby signatures that didn’t include *args or **kwargs (GH8733). - io.data.Options now raises RemoteDataError when no expiry dates are available from Yahoo and when it receives no data from Yahoo (GH8761), (GH8783). - Unclear error message in csv parsing when passing dtype and names and the parsed data is a different data type (GH8833) - Bug in slicing a multi-index with an empty list and at least one boolean indexer (GH8781) - io.data.Options now raises RemoteDataError when no expiry dates are available from Yahoo (GH8761). - Timedelta kwargs may now be numpy ints and floats (GH8757). - Fixed several outstanding bugs for Timedelta arithmetic and comparisons (GH8813, GH5963, GH5436). - sql_schema now generates dialect appropriate CREATE TABLE statements (GH8697) - slice string method now takes step into account (GH8754) - Bug in BlockManager where setting values with different type would break block integrity (GH8850) - Bug in DatetimeIndex when using time object as key (GH8667) - Bug in merge where how='left' and sort=False would not preserve left frame order (GH7331) - Bug in MultiIndex.reindex where reindexing at level would not reorder labels (GH4088) - Bug in certain operations with dateutil timezones, manifesting with dateutil 2.3 (GH8639) - Regression in DatetimeIndex iteration with a Fixed/Local offset timezone (GH8890) - Bug in to_datetime when parsing a nanoseconds using the %f format (GH8989) - io.data.Options now raises RemoteDataError when no expiry dates are available from Yahoo and when it receives no data from Yahoo (GH8761), (GH8783). - Fix: The font size was only set on x axis if vertical or the y axis if horizontal. (GH8765) - Fixed division by 0 when reading big csv files in python 3 (GH8621) - Bug in outputing a Multindex with to_html,index=False which would add an extra column (GH8452) - Imported categorical variables from Stata files retain the ordinal information in the underlying data (GH8836). - Defined .size attribute across NDFrame objects to provide compat with numpy >= 1.9.1; buggy with np.array_split (GH8846) - Skip testing of histogram plots for matplotlib <= 1.2 (GH8648). - Bug where get_data_google returned object dtypes (GH3995) - Bug in DataFrame.stack(..., dropna=False) when the DataFrame’s columns is a MultiIndex whose labels do not reference all its levels. (GH8844) - Bug in that Option context applied on __enter__ (GH8514) - Bug in resample that causes a ValueError when resampling across multiple days and the last offset is not calculated from the start of the range (GH8683) - Bug where DataFrame.plot(kind='scatter') fails when checking if an np.array is in the DataFrame (GH8852) - Bug in pd.infer_freq/DataFrame.inferred_freq that prevented proper sub-daily frequency inference when the index contained DST days (GH8772). - Bug where index name was still used when plotting a series with use_index=False (GH8558). - Bugs when trying to stack multiple columns, when some (or all) of the level names are numbers (GH8584). - Bug in MultiIndex where __contains__ returns wrong result if index is not lexically sorted or unique (GH7724) - BUG CSV: fix problem with trailing whitespace in skipped rows, (GH8679), (GH8661), (GH8983) - Regression in Timestamp does not parse ‘Z’ zone designator for UTC (GH8771) - Bug in StataWriter the produces writes strings with 244 characters irrespective of actual size (GH8969) - Fixed ValueError raised by cummin/cummax when datetime64 Series contains NaT. (GH8965) - Bug in Datareader returns object dtype if there are missing values (GH8980) - Bug in plotting if sharex was enabled and index was a timeseries, would show labels on multiple axes (GH3964). - Bug where passing a unit to the TimedeltaIndex constructor applied the to nano-second conversion twice. (GH9011). - Bug in plotting of a period-like array (GH9012) - Update copyright year ------------------------------------------------------------------- Sun Nov 9 15:40:36 UTC 2014 - toddrme2178@gmail.com - Updated to version 0.15.1: + API changes - Represent ``MultiIndex`` labels with a dtype that utilizes memory based on the level size. - ``groupby`` with ``as_index=False`` will not add erroneous extra columns to result (:issue:`8582`): - ``groupby`` will not erroneously exclude columns if the column name conflics with the grouper name (:issue:`8112`): - ``concat`` permits a wider variety of iterables of pandas objects to be passed as the first parameter (:issue:`8645`): - ``s.dt.hour`` and other ``.dt`` accessors will now return ``np.nan`` for missing values (rather than previously -1), (:issue:`8689`) - support for slicing with monotonic decreasing indexes, even if ``start`` or ``stop`` is not found in the index (:issue:`7860`): - added Index properties `is_monotonic_increasing` and `is_monotonic_decreasing` (:issue:`8680`). - pandas now also registers the ``datetime64`` dtype in matplotlib's units registry to plot such values as datetimes. + Enhancements - Added option to select columns when importing Stata files (:issue:`7935`) - Qualify memory usage in ``DataFrame.info()`` by adding ``+`` if it is a lower bound (:issue:`8578`) - Raise errors in certain aggregation cases where an argument such as ``numeric_only`` is not handled (:issue:`8592`). - Added support for 3-character ISO and non-standard country codes in :func:``io.wb.download()`` (:issue:`8482`) - :ref:`World Bank data requests <remote_data.wb>` now will warn/raise based on an ``errors`` argument, as well as a list of hard-coded country codes and the World Bank's JSON response. - Added option to ``Series.str.split()`` to return a ``DataFrame`` rather than a ``Series`` (:issue:`8428`) - Added option to ``df.info(null_counts=None|True|False)`` to override the default display options and force showing of the null-counts (:issue:`8701`) + Bug Fixes - Bug in unpickling of a ``CustomBusinessDay`` object (:issue:`8591`) - Bug in coercing ``Categorical`` to a records array, e.g. ``df.to_records()`` (:issue:`8626`) - Bug in ``Categorical`` not created properly with ``Series.to_frame()`` (:issue:`8626`) - Bug in coercing in astype of a ``Categorical`` of a passed ``pd.Categorical`` (this now raises ``TypeError`` correctly), (:issue:`8626`) - Bug in ``cut``/``qcut`` when using ``Series`` and ``retbins=True`` (:issue:`8589`) - Bug in writing Categorical columns to an SQL database with ``to_sql`` (:issue:`8624`). - Bug in comparing ``Categorical`` of datetime raising when being compared to a scalar datetime (:issue:`8687`) - Bug in selecting from a ``Categorical`` with ``.iloc`` (:issue:`8623`) - Bug in groupby-transform with a Categorical (:issue:`8623`) - Bug in duplicated/drop_duplicates with a Categorical (:issue:`8623`) - Bug in ``Categorical`` reflected comparison operator raising if the first argument was a numpy array scalar (e.g. np.int64) (:issue:`8658`) - Bug in Panel indexing with a list-like (:issue:`8710`) - Compat issue is ``DataFrame.dtypes`` when ``options.mode.use_inf_as_null`` is True (:issue:`8722`) - Bug in ``read_csv``, ``dialect`` parameter would not take a string (:issue: `8703`) - Bug in slicing a multi-index level with an empty-list (:issue:`8737`) - Bug in numeric index operations of add/sub with Float/Index Index with numpy arrays (:issue:`8608`) - Bug in setitem with empty indexer and unwanted coercion of dtypes (:issue:`8669`) - Bug in ix/loc block splitting on setitem (manifests with integer-like dtypes, e.g. datetime64) (:issue:`8607`) - Bug when doing label based indexing with integers not found in the index for non-unique but monotonic indexes (:issue:`8680`). - Bug when indexing a Float64Index with ``np.nan`` on numpy 1.7 (:issue:`8980`). - Fix ``shape`` attribute for ``MultiIndex`` (:issue:`8609`) - Bug in ``GroupBy`` where a name conflict between the grouper and columns would break ``groupby`` operations (:issue:`7115`, :issue:`8112`) - Fixed a bug where plotting a column ``y`` and specifying a label would mutate the index name of the original DataFrame (:issue:`8494`) - Fix regression in plotting of a DatetimeIndex directly with matplotlib (:issue:`8614`). - Bug in ``date_range`` where partially-specified dates would incorporate current date (:issue:`6961`) - Bug in Setting by indexer to a scalar value with a mixed-dtype `Panel4d` was failing (:issue:`8702`) - Bug where ``DataReader``'s would fail if one of the symbols passed was invalid. Now returns data for valid symbols and np.nan for invalid (:issue:`8494`) - Bug in ``get_quote_yahoo`` that wouldn't allow non-float return values (:issue:`5229`). ------------------------------------------------------------------- Mon Oct 20 10:42:30 UTC 2014 - toddrme2178@gmail.com - Update to 0.15.0, highlights: - Drop support for numpy < 1.7.0 - The Categorical type was integrated as a first-class pandas type - New scalar type Timedelta, and a new index type TimedeltaIndex - New DataFrame default display for df.info() to include memory usage - New datetimelike properties accessor .dt for Series - Split indexing documentation into Indexing and Selecting Data and MultiIndex / Advanced Indexing - Split out string methods documentation into Working with Text Data - read_csv will now by default ignore blank lines when parsing - API change in using Indexes in set operations - Internal refactoring of the Index class to no longer sub-class ndarray - dropping support for PyTables less than version 3.0.0, and numexpr less than version 2.1 - Update minimum dependency versions of python-numpy, python-tables, and python-numexpr ------------------------------------------------------------------- Tue Jul 15 12:31:13 UTC 2014 - toddrme2178@gmail.com - Update to 0.14.1, highlights: - New methods :meth:`~pandas.DataFrame.select_dtypes` to select columns based on the dtype and :meth:`~pandas.Series.sem` to calculate the standard error of the mean. - Support for dateutil timezones (see :ref:`docs <timeseries.timezone>`). - Support for ignoring full line comments in the :func:`~pandas.read_csv` text parser. - New documentation section on :ref:`Options and Settings <options>`. - Lots of bug fixes. ------------------------------------------------------------------- Sun Jun 1 07:41:11 UTC 2014 - toddrme2178@gmail.com - Update to 0.14.0, highlights: * Officially support Python 3.4 * SQL interfaces updated to use sqlalchemy * Display interface changes * MultiIndexing Using Slicers * Ability to join a singly-indexed DataFrame with a multi-indexed DataFrame * More consistency in groupby results and more flexible groupby specifications * Holiday calendars are now supported in CustomBusinessDay * Several improvements in plotting functions, including: hexbin, area and pie plots * Performance doc section on I/O operations, See Here - Added python-SQLAlchemy dependency ------------------------------------------------------------------- Fri Mar 7 04:11:36 UTC 2014 - arun@gmx.de - updated to 0.13.1 500 lines worth of Changelog entries, so too long:) For a complete list see: http://pandas.pydata.org/pandas-docs/dev/release.html ------------------------------------------------------------------- Mon Oct 21 21:59:47 UTC 2013 - toddrme2178@gmail.com - Update to 0.12.0 * Integrated JSON reading and writing with the read_json functions and methods like DataFrame.to_json. * New HTML table reading function read_html which will use either lxml or BeautifulSoup under the hood. * Support for reading and writing STATA format files. - Add all optional dependencies as Recommends - Build and install documentation ------------------------------------------------------------------- Mon May 6 06:01:46 UTC 2013 - highwaystar.ru@gmail.com - added Recommends: python-tables - update to 0.11.0 * New precision indexing fields loc, iloc, at, and iat, to reduce occasional ambiguity in the catch-all hitherto ix method. * Expanded support for NumPy data types in DataFrame * NumExpr integration to accelerate various operator evaluation * New Cookbook and 10 minutes to pandas pages in the documentation by Jeff Reback * Improved DataFrame to CSV exporting performance ------------------------------------------------------------------- Tue Jun 19 20:29:31 UTC 2012 - scorot@free.fr - remove unneeded python-Pygments and python-Sphinx from build requirements ------------------------------------------------------------------- Tue Jun 19 20:23:50 UTC 2012 - scorot@free.fr - remove duplicates - fix bytecode inconsistent mtime ------------------------------------------------------------------- Wed Jun 13 20:45:39 UTC 2012 - scorot@free.fr - use proper commands instead of deprecated macro - remove unneeded -01 and --skip-build flags from the install command line - set install prefix with %%{_prefix} instead of hard coded path ------------------------------------------------------------------- Wed Jun 13 18:41:46 UTC 2012 - scorot@free.fr - add %%py_compile macro in order to fix byte code mtime inconsistency ------------------------------------------------------------------- Tue Jun 12 21:03:07 UTC 2012 - scorot@free.fr - spec file reformating ------------------------------------------------------------------- Tue Jun 12 20:46:31 UTC 2012 - scorot@free.fr - first package
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