python3-pandas-doc-0.16.2-4.1>t  DH`pX̢/=„3aZ3;) Vʀ Au 8ri>R$VBV ԗsIt6gq L\%C 3_*(v}"#ПC"qG~m0A72r PD ?EC \ ջ~6ƭ&AVN~Z9_Bˆ_Pc.jY UW ¶jQ 0a;awU@ǫ1e3b6ec5b5c4155ceffd03f4da90720dd22e60b96tX̢/=„k|NN7e//6 _'$- < 8AT OeZ`9F)wZm |&۫؝s21 [6Ư !7 H<?d  A|     $ , . 08BLpx(8$9\:kFGHI X$Y,\D]L^dbc2defluvwxzCpython3-pandas-doc0.16.24.1Documentation for python3-pandasDocumentation, help files, and examples for python3-pandasX̡lamb52openSUSE Leap 42.3openSUSEBSD-3-Clausehttp://bugs.opensuse.orgDevelopment/Libraries/Pythonhttp://pandas.pydata.org/linuxx86_64AAX̡X̡rootrootrootrootpython3-pandas-0.16.2-4.1.src.rpmpython3-pandas-docpython3-pandas-doc(x86-64)   rpmlib(CompressedFileNames)rpmlib(PayloadFilesHavePrefix)rpmlib(PayloadIsLzma)3.0.4-14.0-14.4.6-14.11.2U@U@U}lU[%UQT8TT_W@TD@SSSRe@Q@toddrme2178@gmail.comtoddrme2178@gmail.comarun@gmx.detoddrme2178@gmail.comtoddrme2178@gmail.comarun@gmx.dearun@gmx.detoddrme2178@gmail.comtoddrme2178@gmail.comtoddrme2178@gmail.comtoddrme2178@gmail.comarun@gmx.detoddrme2178@gmail.comhighwaystar.ru@gmail.com- xlwt and boto are now available for python 3.- Don't require HDF5 directly, the ambiguities should be and have been fixed in the packages that require hdf5 directly, not here.- 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).- 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- 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., Series.dt. and Series.cat.. - 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- specfile: * update copyright year * fix "have choice for libhdf5" * removed modname variable- 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)- 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 ` 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`).- 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- 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 `). - Support for ignoring full line comments in the :func:`~pandas.read_csv` text parser. - New documentation section on :ref:`Options and Settings `. - Lots of bug fixes.- 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 python3-SQLAlchemy dependency- 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- 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 - Add pandas-0.12.0-objToJSON_return_fix.patch, which should be included upstream in the next release- added Recommends:python3-tables - python3 package added - 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 performancelamb52 14898058090.16.2-4.10.16.2-4.1python3-pandas-dochtml/usr/share/doc/packages//usr/share/doc/packages/python3-pandas-doc/-fmessage-length=0 -grecord-gcc-switches -O2 -Wall -D_FORTIFY_SOURCE=2 -fstack-protector -funwind-tables -fasynchronous-unwind-tables -gobs://build.opensuse.org/openSUSE:Leap:42.3/standard/1ae464041ff8918e62d632ec86f6054d-python3-pandascpiolzma5x86_64-suse-linuxdirectory{G}%Nihpython3-pandas0.16.2?@] crt:bLLD qB]b%C"KFT a6&<1ddD漚E7}^ ^>6PϷJoשᐸTgiUwsj4{O