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py-pandas: updated to 0.21.1 v0.21.1: Restore Matplotlib datetime Converter Registration New features - Improvements to the Parquet IO functionality - Other Enhancements Deprecations Performance Improvements Bug Fixes - Conversion - Indexing - I/O - Plotting - Groupby/Resample/Rolling - Reshaping - Numeric - Categorical - String
2017-12-14 14:37:59 +01:00
@comment $NetBSD: PLIST,v 1.14 2017/12/14 13:37:59 adam Exp $
Prefer egg.mk to distutils.mk. Clean up. Add missing dependency on py-sqlite3. Add missing test dependency on py-nose. Add comments with links to bug reports about test failures. Bump PKGREVISION for dependency change.
2016-08-19 09:57:26 +02:00
${PYSITELIB}/${EGG_INFODIR}/PKG-INFO
${PYSITELIB}/${EGG_INFODIR}/SOURCES.txt
${PYSITELIB}/${EGG_INFODIR}/dependency_links.txt
${PYSITELIB}/${EGG_INFODIR}/not-zip-safe
${PYSITELIB}/${EGG_INFODIR}/requires.txt
${PYSITELIB}/${EGG_INFODIR}/top_level.txt
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/__init__.py
${PYSITELIB}/pandas/__init__.pyc
${PYSITELIB}/pandas/__init__.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/_libs/__init__.py
${PYSITELIB}/pandas/_libs/__init__.pyc
${PYSITELIB}/pandas/_libs/__init__.pyo
${PYSITELIB}/pandas/_libs/algos.so
${PYSITELIB}/pandas/_libs/groupby.so
${PYSITELIB}/pandas/_libs/hashing.so
${PYSITELIB}/pandas/_libs/hashtable.so
${PYSITELIB}/pandas/_libs/index.so
${PYSITELIB}/pandas/_libs/interval.so
${PYSITELIB}/pandas/_libs/join.so
${PYSITELIB}/pandas/_libs/json.so
${PYSITELIB}/pandas/_libs/lib.so
${PYSITELIB}/pandas/_libs/parsers.so
${PYSITELIB}/pandas/_libs/period.so
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/_libs/properties.so
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/_libs/reshape.so
${PYSITELIB}/pandas/_libs/sparse.so
${PYSITELIB}/pandas/_libs/testing.so
${PYSITELIB}/pandas/_libs/tslib.so
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/_libs/tslibs/__init__.py
${PYSITELIB}/pandas/_libs/tslibs/__init__.pyc
${PYSITELIB}/pandas/_libs/tslibs/__init__.pyo
${PYSITELIB}/pandas/_libs/tslibs/fields.so
${PYSITELIB}/pandas/_libs/tslibs/frequencies.so
${PYSITELIB}/pandas/_libs/tslibs/parsing.so
${PYSITELIB}/pandas/_libs/tslibs/strptime.so
${PYSITELIB}/pandas/_libs/tslibs/timedeltas.so
${PYSITELIB}/pandas/_libs/tslibs/timezones.so
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/_libs/window.so
Update py-pandas to 0.17.1. 0.17.1 This is a minor bug-fix release from 0.17.0 and includes a large number of bug fixes along several new features, enhancements, and performance improvements. We recommend that all users upgrade to this version. 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) 0.17.0 This is a major release from 0.16.2 and includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: 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 generate 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)
2015-12-28 15:35:02 +01:00
${PYSITELIB}/pandas/_version.py
${PYSITELIB}/pandas/_version.pyc
${PYSITELIB}/pandas/_version.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/api/__init__.py
${PYSITELIB}/pandas/api/__init__.pyc
${PYSITELIB}/pandas/api/__init__.pyo
${PYSITELIB}/pandas/api/types/__init__.py
${PYSITELIB}/pandas/api/types/__init__.pyc
${PYSITELIB}/pandas/api/types/__init__.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/compat/__init__.py
${PYSITELIB}/pandas/compat/__init__.pyc
${PYSITELIB}/pandas/compat/__init__.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/compat/chainmap.py
${PYSITELIB}/pandas/compat/chainmap.pyc
${PYSITELIB}/pandas/compat/chainmap.pyo
${PYSITELIB}/pandas/compat/chainmap_impl.py
${PYSITELIB}/pandas/compat/chainmap_impl.pyc
${PYSITELIB}/pandas/compat/chainmap_impl.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/compat/numpy/__init__.py
${PYSITELIB}/pandas/compat/numpy/__init__.pyc
${PYSITELIB}/pandas/compat/numpy/__init__.pyo
${PYSITELIB}/pandas/compat/numpy/function.py
${PYSITELIB}/pandas/compat/numpy/function.pyc
${PYSITELIB}/pandas/compat/numpy/function.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/compat/openpyxl_compat.py
${PYSITELIB}/pandas/compat/openpyxl_compat.pyc
${PYSITELIB}/pandas/compat/openpyxl_compat.pyo
${PYSITELIB}/pandas/compat/pickle_compat.py
${PYSITELIB}/pandas/compat/pickle_compat.pyc
${PYSITELIB}/pandas/compat/pickle_compat.pyo
${PYSITELIB}/pandas/computation/__init__.py
${PYSITELIB}/pandas/computation/__init__.pyc
${PYSITELIB}/pandas/computation/__init__.pyo
${PYSITELIB}/pandas/computation/expressions.py
${PYSITELIB}/pandas/computation/expressions.pyc
${PYSITELIB}/pandas/computation/expressions.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/conftest.py
${PYSITELIB}/pandas/conftest.pyc
${PYSITELIB}/pandas/conftest.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/__init__.py
${PYSITELIB}/pandas/core/__init__.pyc
${PYSITELIB}/pandas/core/__init__.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/core/accessor.py
${PYSITELIB}/pandas/core/accessor.pyc
${PYSITELIB}/pandas/core/accessor.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/algorithms.py
${PYSITELIB}/pandas/core/algorithms.pyc
${PYSITELIB}/pandas/core/algorithms.pyo
${PYSITELIB}/pandas/core/api.py
${PYSITELIB}/pandas/core/api.pyc
${PYSITELIB}/pandas/core/api.pyo
Update pandas to 0.12.0. This is a major release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular expressions. For detailed changes see: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2013-12-10 14:00:30 +01:00
${PYSITELIB}/pandas/core/base.py
${PYSITELIB}/pandas/core/base.pyc
${PYSITELIB}/pandas/core/base.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/categorical.py
${PYSITELIB}/pandas/core/categorical.pyc
${PYSITELIB}/pandas/core/categorical.pyo
${PYSITELIB}/pandas/core/common.py
${PYSITELIB}/pandas/core/common.pyc
${PYSITELIB}/pandas/core/common.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/core/computation/__init__.py
${PYSITELIB}/pandas/core/computation/__init__.pyc
${PYSITELIB}/pandas/core/computation/__init__.pyo
${PYSITELIB}/pandas/core/computation/align.py
${PYSITELIB}/pandas/core/computation/align.pyc
${PYSITELIB}/pandas/core/computation/align.pyo
${PYSITELIB}/pandas/core/computation/api.py
${PYSITELIB}/pandas/core/computation/api.pyc
${PYSITELIB}/pandas/core/computation/api.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/core/computation/check.py
${PYSITELIB}/pandas/core/computation/check.pyc
${PYSITELIB}/pandas/core/computation/check.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/core/computation/common.py
${PYSITELIB}/pandas/core/computation/common.pyc
${PYSITELIB}/pandas/core/computation/common.pyo
${PYSITELIB}/pandas/core/computation/engines.py
${PYSITELIB}/pandas/core/computation/engines.pyc
${PYSITELIB}/pandas/core/computation/engines.pyo
${PYSITELIB}/pandas/core/computation/eval.py
${PYSITELIB}/pandas/core/computation/eval.pyc
${PYSITELIB}/pandas/core/computation/eval.pyo
${PYSITELIB}/pandas/core/computation/expr.py
${PYSITELIB}/pandas/core/computation/expr.pyc
${PYSITELIB}/pandas/core/computation/expr.pyo
${PYSITELIB}/pandas/core/computation/expressions.py
${PYSITELIB}/pandas/core/computation/expressions.pyc
${PYSITELIB}/pandas/core/computation/expressions.pyo
${PYSITELIB}/pandas/core/computation/ops.py
${PYSITELIB}/pandas/core/computation/ops.pyc
${PYSITELIB}/pandas/core/computation/ops.pyo
${PYSITELIB}/pandas/core/computation/pytables.py
${PYSITELIB}/pandas/core/computation/pytables.pyc
${PYSITELIB}/pandas/core/computation/pytables.pyo
${PYSITELIB}/pandas/core/computation/scope.py
${PYSITELIB}/pandas/core/computation/scope.pyc
${PYSITELIB}/pandas/core/computation/scope.pyo
Update pandas to 0.10.0. pkgsrc change: depend on math/py-pytables. Changes since 0.9.1: * Delimited file parsing engine rewritten to use a fraction of memory while being 40%+ faster. - Much-improved Unicode handling via the encoding option. - Column filtering (usecols) - Dtype specification (dtype argument) - Ability to specify strings to be recognized as True/False - Ability to yield NumPy record arrays (as_recarray) - High performance delim_whitespace option - Decimal format (e.g. European format) specification - Easier CSV dialect options: escapechar, lineterminator, quotechar, etc. - More robust handling of many exceptional kinds of files observed in the wild * API changes - Deprecated DataFrame BINOP TimeSeries special case behavior - Altered resample default behavior - Infinity and negative infinity are no longer treated as NA by isnull and notnull. - Methods with the inplace option now all return None instead of the calling object. - pandas.merge no longer sorts the group keys (sort=False) by default. - The default column names for a file with no header have been changed. - Values like 'Yes' and 'No' are not interpreted as boolean by default. - The file parsers will not recognize non-string values arising from a converter function as NA. - Calling fillna on Series or DataFrame with no arguments is no longer valid code. - Series.apply will now operate on a returned value from the applied function. - New API functions for working with pandas options. * New features - Wide DataFrame Printing. - Updated PyTables Support. * Enhancements - added ability to hierarchical keys. - added mixed-dtype support! - performance improvments on table writing. - support for arbitrarily indexed dimensions. - SparseSeries now has a density property. * Bug fixes - added Term method of specifying where conditions. - del store['df'] now call store.remove('df') for store deletion. - deleting of consecutive rows is much faster than before. - in_itemsize parameter can be specified in table creation to force a minimum size for indexing columns. - indexing support via create_table_index (requires PyTables >= 2.3) - appending on a store would fail if the table was not first created via put. - fixed issue with missing attributes after loading a pickled dataframe. - minor change to select and remove: require a table ONLY if where is also provided. * Compatibility - 0.10 of HDFStore is backwards compatible for reading tables created in a prior version of pandas, however, query terms using the prior (undocumented) methodology are unsupported. * N Dimensional Panels (Experimental)
2013-01-08 00:18:35 +01:00
${PYSITELIB}/pandas/core/config.py
${PYSITELIB}/pandas/core/config.pyc
${PYSITELIB}/pandas/core/config.pyo
${PYSITELIB}/pandas/core/config_init.py
${PYSITELIB}/pandas/core/config_init.pyc
${PYSITELIB}/pandas/core/config_init.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/datetools.py
${PYSITELIB}/pandas/core/datetools.pyc
${PYSITELIB}/pandas/core/datetools.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/core/dtypes/__init__.py
${PYSITELIB}/pandas/core/dtypes/__init__.pyc
${PYSITELIB}/pandas/core/dtypes/__init__.pyo
${PYSITELIB}/pandas/core/dtypes/api.py
${PYSITELIB}/pandas/core/dtypes/api.pyc
${PYSITELIB}/pandas/core/dtypes/api.pyo
${PYSITELIB}/pandas/core/dtypes/cast.py
${PYSITELIB}/pandas/core/dtypes/cast.pyc
${PYSITELIB}/pandas/core/dtypes/cast.pyo
${PYSITELIB}/pandas/core/dtypes/common.py
${PYSITELIB}/pandas/core/dtypes/common.pyc
${PYSITELIB}/pandas/core/dtypes/common.pyo
${PYSITELIB}/pandas/core/dtypes/concat.py
${PYSITELIB}/pandas/core/dtypes/concat.pyc
${PYSITELIB}/pandas/core/dtypes/concat.pyo
${PYSITELIB}/pandas/core/dtypes/dtypes.py
${PYSITELIB}/pandas/core/dtypes/dtypes.pyc
${PYSITELIB}/pandas/core/dtypes/dtypes.pyo
${PYSITELIB}/pandas/core/dtypes/generic.py
${PYSITELIB}/pandas/core/dtypes/generic.pyc
${PYSITELIB}/pandas/core/dtypes/generic.pyo
${PYSITELIB}/pandas/core/dtypes/inference.py
${PYSITELIB}/pandas/core/dtypes/inference.pyc
${PYSITELIB}/pandas/core/dtypes/inference.pyo
${PYSITELIB}/pandas/core/dtypes/missing.py
${PYSITELIB}/pandas/core/dtypes/missing.pyc
${PYSITELIB}/pandas/core/dtypes/missing.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/frame.py
${PYSITELIB}/pandas/core/frame.pyc
${PYSITELIB}/pandas/core/frame.pyo
${PYSITELIB}/pandas/core/generic.py
${PYSITELIB}/pandas/core/generic.pyc
${PYSITELIB}/pandas/core/generic.pyo
${PYSITELIB}/pandas/core/groupby.py
${PYSITELIB}/pandas/core/groupby.pyc
${PYSITELIB}/pandas/core/groupby.pyo
${PYSITELIB}/pandas/core/index.py
${PYSITELIB}/pandas/core/index.pyc
${PYSITELIB}/pandas/core/index.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/core/indexes/__init__.py
${PYSITELIB}/pandas/core/indexes/__init__.pyc
${PYSITELIB}/pandas/core/indexes/__init__.pyo
${PYSITELIB}/pandas/core/indexes/accessors.py
${PYSITELIB}/pandas/core/indexes/accessors.pyc
${PYSITELIB}/pandas/core/indexes/accessors.pyo
${PYSITELIB}/pandas/core/indexes/api.py
${PYSITELIB}/pandas/core/indexes/api.pyc
${PYSITELIB}/pandas/core/indexes/api.pyo
${PYSITELIB}/pandas/core/indexes/base.py
${PYSITELIB}/pandas/core/indexes/base.pyc
${PYSITELIB}/pandas/core/indexes/base.pyo
${PYSITELIB}/pandas/core/indexes/category.py
${PYSITELIB}/pandas/core/indexes/category.pyc
${PYSITELIB}/pandas/core/indexes/category.pyo
${PYSITELIB}/pandas/core/indexes/datetimelike.py
${PYSITELIB}/pandas/core/indexes/datetimelike.pyc
${PYSITELIB}/pandas/core/indexes/datetimelike.pyo
${PYSITELIB}/pandas/core/indexes/datetimes.py
${PYSITELIB}/pandas/core/indexes/datetimes.pyc
${PYSITELIB}/pandas/core/indexes/datetimes.pyo
${PYSITELIB}/pandas/core/indexes/frozen.py
${PYSITELIB}/pandas/core/indexes/frozen.pyc
${PYSITELIB}/pandas/core/indexes/frozen.pyo
${PYSITELIB}/pandas/core/indexes/interval.py
${PYSITELIB}/pandas/core/indexes/interval.pyc
${PYSITELIB}/pandas/core/indexes/interval.pyo
${PYSITELIB}/pandas/core/indexes/multi.py
${PYSITELIB}/pandas/core/indexes/multi.pyc
${PYSITELIB}/pandas/core/indexes/multi.pyo
${PYSITELIB}/pandas/core/indexes/numeric.py
${PYSITELIB}/pandas/core/indexes/numeric.pyc
${PYSITELIB}/pandas/core/indexes/numeric.pyo
${PYSITELIB}/pandas/core/indexes/period.py
${PYSITELIB}/pandas/core/indexes/period.pyc
${PYSITELIB}/pandas/core/indexes/period.pyo
${PYSITELIB}/pandas/core/indexes/range.py
${PYSITELIB}/pandas/core/indexes/range.pyc
${PYSITELIB}/pandas/core/indexes/range.pyo
${PYSITELIB}/pandas/core/indexes/timedeltas.py
${PYSITELIB}/pandas/core/indexes/timedeltas.pyc
${PYSITELIB}/pandas/core/indexes/timedeltas.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/indexing.py
${PYSITELIB}/pandas/core/indexing.pyc
${PYSITELIB}/pandas/core/indexing.pyo
${PYSITELIB}/pandas/core/internals.py
${PYSITELIB}/pandas/core/internals.pyc
${PYSITELIB}/pandas/core/internals.pyo
Update py-pandas to 0.17.1. 0.17.1 This is a minor bug-fix release from 0.17.0 and includes a large number of bug fixes along several new features, enhancements, and performance improvements. We recommend that all users upgrade to this version. 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) 0.17.0 This is a major release from 0.16.2 and includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: 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 generate 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)
2015-12-28 15:35:02 +01:00
${PYSITELIB}/pandas/core/missing.py
${PYSITELIB}/pandas/core/missing.pyc
${PYSITELIB}/pandas/core/missing.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/nanops.py
${PYSITELIB}/pandas/core/nanops.pyc
${PYSITELIB}/pandas/core/nanops.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/core/ops.py
${PYSITELIB}/pandas/core/ops.pyc
${PYSITELIB}/pandas/core/ops.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/panel.py
${PYSITELIB}/pandas/core/panel.pyc
${PYSITELIB}/pandas/core/panel.pyo
Update pandas to 0.10.0. pkgsrc change: depend on math/py-pytables. Changes since 0.9.1: * Delimited file parsing engine rewritten to use a fraction of memory while being 40%+ faster. - Much-improved Unicode handling via the encoding option. - Column filtering (usecols) - Dtype specification (dtype argument) - Ability to specify strings to be recognized as True/False - Ability to yield NumPy record arrays (as_recarray) - High performance delim_whitespace option - Decimal format (e.g. European format) specification - Easier CSV dialect options: escapechar, lineterminator, quotechar, etc. - More robust handling of many exceptional kinds of files observed in the wild * API changes - Deprecated DataFrame BINOP TimeSeries special case behavior - Altered resample default behavior - Infinity and negative infinity are no longer treated as NA by isnull and notnull. - Methods with the inplace option now all return None instead of the calling object. - pandas.merge no longer sorts the group keys (sort=False) by default. - The default column names for a file with no header have been changed. - Values like 'Yes' and 'No' are not interpreted as boolean by default. - The file parsers will not recognize non-string values arising from a converter function as NA. - Calling fillna on Series or DataFrame with no arguments is no longer valid code. - Series.apply will now operate on a returned value from the applied function. - New API functions for working with pandas options. * New features - Wide DataFrame Printing. - Updated PyTables Support. * Enhancements - added ability to hierarchical keys. - added mixed-dtype support! - performance improvments on table writing. - support for arbitrarily indexed dimensions. - SparseSeries now has a density property. * Bug fixes - added Term method of specifying where conditions. - del store['df'] now call store.remove('df') for store deletion. - deleting of consecutive rows is much faster than before. - in_itemsize parameter can be specified in table creation to force a minimum size for indexing columns. - indexing support via create_table_index (requires PyTables >= 2.3) - appending on a store would fail if the table was not first created via put. - fixed issue with missing attributes after loading a pickled dataframe. - minor change to select and remove: require a table ONLY if where is also provided. * Compatibility - 0.10 of HDFStore is backwards compatible for reading tables created in a prior version of pandas, however, query terms using the prior (undocumented) methodology are unsupported. * N Dimensional Panels (Experimental)
2013-01-08 00:18:35 +01:00
${PYSITELIB}/pandas/core/panel4d.py
${PYSITELIB}/pandas/core/panel4d.pyc
${PYSITELIB}/pandas/core/panel4d.pyo
${PYSITELIB}/pandas/core/panelnd.py
${PYSITELIB}/pandas/core/panelnd.pyc
${PYSITELIB}/pandas/core/panelnd.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/core/resample.py
${PYSITELIB}/pandas/core/resample.pyc
${PYSITELIB}/pandas/core/resample.pyo
${PYSITELIB}/pandas/core/reshape/__init__.py
${PYSITELIB}/pandas/core/reshape/__init__.pyc
${PYSITELIB}/pandas/core/reshape/__init__.pyo
${PYSITELIB}/pandas/core/reshape/api.py
${PYSITELIB}/pandas/core/reshape/api.pyc
${PYSITELIB}/pandas/core/reshape/api.pyo
${PYSITELIB}/pandas/core/reshape/concat.py
${PYSITELIB}/pandas/core/reshape/concat.pyc
${PYSITELIB}/pandas/core/reshape/concat.pyo
${PYSITELIB}/pandas/core/reshape/merge.py
${PYSITELIB}/pandas/core/reshape/merge.pyc
${PYSITELIB}/pandas/core/reshape/merge.pyo
${PYSITELIB}/pandas/core/reshape/pivot.py
${PYSITELIB}/pandas/core/reshape/pivot.pyc
${PYSITELIB}/pandas/core/reshape/pivot.pyo
${PYSITELIB}/pandas/core/reshape/reshape.py
${PYSITELIB}/pandas/core/reshape/reshape.pyc
${PYSITELIB}/pandas/core/reshape/reshape.pyo
${PYSITELIB}/pandas/core/reshape/tile.py
${PYSITELIB}/pandas/core/reshape/tile.pyc
${PYSITELIB}/pandas/core/reshape/tile.pyo
${PYSITELIB}/pandas/core/reshape/util.py
${PYSITELIB}/pandas/core/reshape/util.pyc
${PYSITELIB}/pandas/core/reshape/util.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/series.py
${PYSITELIB}/pandas/core/series.pyc
${PYSITELIB}/pandas/core/series.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/core/sorting.py
${PYSITELIB}/pandas/core/sorting.pyc
${PYSITELIB}/pandas/core/sorting.pyo
${PYSITELIB}/pandas/core/sparse/__init__.py
${PYSITELIB}/pandas/core/sparse/__init__.pyc
${PYSITELIB}/pandas/core/sparse/__init__.pyo
${PYSITELIB}/pandas/core/sparse/api.py
${PYSITELIB}/pandas/core/sparse/api.pyc
${PYSITELIB}/pandas/core/sparse/api.pyo
${PYSITELIB}/pandas/core/sparse/array.py
${PYSITELIB}/pandas/core/sparse/array.pyc
${PYSITELIB}/pandas/core/sparse/array.pyo
${PYSITELIB}/pandas/core/sparse/frame.py
${PYSITELIB}/pandas/core/sparse/frame.pyc
${PYSITELIB}/pandas/core/sparse/frame.pyo
${PYSITELIB}/pandas/core/sparse/list.py
${PYSITELIB}/pandas/core/sparse/list.pyc
${PYSITELIB}/pandas/core/sparse/list.pyo
${PYSITELIB}/pandas/core/sparse/scipy_sparse.py
${PYSITELIB}/pandas/core/sparse/scipy_sparse.pyc
${PYSITELIB}/pandas/core/sparse/scipy_sparse.pyo
${PYSITELIB}/pandas/core/sparse/series.py
${PYSITELIB}/pandas/core/sparse/series.pyc
${PYSITELIB}/pandas/core/sparse/series.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/core/strings.py
${PYSITELIB}/pandas/core/strings.pyc
${PYSITELIB}/pandas/core/strings.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/core/tools/__init__.py
${PYSITELIB}/pandas/core/tools/__init__.pyc
${PYSITELIB}/pandas/core/tools/__init__.pyo
${PYSITELIB}/pandas/core/tools/datetimes.py
${PYSITELIB}/pandas/core/tools/datetimes.pyc
${PYSITELIB}/pandas/core/tools/datetimes.pyo
${PYSITELIB}/pandas/core/tools/numeric.py
${PYSITELIB}/pandas/core/tools/numeric.pyc
${PYSITELIB}/pandas/core/tools/numeric.pyo
${PYSITELIB}/pandas/core/tools/timedeltas.py
${PYSITELIB}/pandas/core/tools/timedeltas.pyc
${PYSITELIB}/pandas/core/tools/timedeltas.pyo
${PYSITELIB}/pandas/core/util/__init__.py
${PYSITELIB}/pandas/core/util/__init__.pyc
${PYSITELIB}/pandas/core/util/__init__.pyo
${PYSITELIB}/pandas/core/util/hashing.py
${PYSITELIB}/pandas/core/util/hashing.pyc
${PYSITELIB}/pandas/core/util/hashing.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/core/window.py
${PYSITELIB}/pandas/core/window.pyc
${PYSITELIB}/pandas/core/window.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/errors/__init__.py
${PYSITELIB}/pandas/errors/__init__.pyc
${PYSITELIB}/pandas/errors/__init__.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/formats/__init__.py
${PYSITELIB}/pandas/formats/__init__.pyc
${PYSITELIB}/pandas/formats/__init__.pyo
${PYSITELIB}/pandas/formats/style.py
${PYSITELIB}/pandas/formats/style.pyc
${PYSITELIB}/pandas/formats/style.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/io/__init__.py
${PYSITELIB}/pandas/io/__init__.pyc
${PYSITELIB}/pandas/io/__init__.pyo
Update pandas to 0.12.0. This is a major release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular expressions. For detailed changes see: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2013-12-10 14:00:30 +01:00
${PYSITELIB}/pandas/io/api.py
${PYSITELIB}/pandas/io/api.pyc
${PYSITELIB}/pandas/io/api.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/io/clipboard/__init__.py
${PYSITELIB}/pandas/io/clipboard/__init__.pyc
${PYSITELIB}/pandas/io/clipboard/__init__.pyo
${PYSITELIB}/pandas/io/clipboard/clipboards.py
${PYSITELIB}/pandas/io/clipboard/clipboards.pyc
${PYSITELIB}/pandas/io/clipboard/clipboards.pyo
${PYSITELIB}/pandas/io/clipboard/exceptions.py
${PYSITELIB}/pandas/io/clipboard/exceptions.pyc
${PYSITELIB}/pandas/io/clipboard/exceptions.pyo
${PYSITELIB}/pandas/io/clipboard/windows.py
${PYSITELIB}/pandas/io/clipboard/windows.pyc
${PYSITELIB}/pandas/io/clipboard/windows.pyo
v0.20.2: This is a minor bug-fix release in the 0.20.x series and includes some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version.
2017-06-07 10:13:56 +02:00
${PYSITELIB}/pandas/io/clipboards.py
${PYSITELIB}/pandas/io/clipboards.pyc
${PYSITELIB}/pandas/io/clipboards.pyo
Update pandas to 0.12.0. This is a major release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular expressions. For detailed changes see: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2013-12-10 14:00:30 +01:00
${PYSITELIB}/pandas/io/common.py
${PYSITELIB}/pandas/io/common.pyc
${PYSITELIB}/pandas/io/common.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/io/data.py
${PYSITELIB}/pandas/io/data.pyc
${PYSITELIB}/pandas/io/data.pyo
${PYSITELIB}/pandas/io/date_converters.py
${PYSITELIB}/pandas/io/date_converters.pyc
${PYSITELIB}/pandas/io/date_converters.pyo
Update pandas to 0.12.0. This is a major release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular expressions. For detailed changes see: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2013-12-10 14:00:30 +01:00
${PYSITELIB}/pandas/io/excel.py
${PYSITELIB}/pandas/io/excel.pyc
${PYSITELIB}/pandas/io/excel.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/io/feather_format.py
${PYSITELIB}/pandas/io/feather_format.pyc
${PYSITELIB}/pandas/io/feather_format.pyo
${PYSITELIB}/pandas/io/formats/__init__.py
${PYSITELIB}/pandas/io/formats/__init__.pyc
${PYSITELIB}/pandas/io/formats/__init__.pyo
${PYSITELIB}/pandas/io/formats/common.py
${PYSITELIB}/pandas/io/formats/common.pyc
${PYSITELIB}/pandas/io/formats/common.pyo
${PYSITELIB}/pandas/io/formats/console.py
${PYSITELIB}/pandas/io/formats/console.pyc
${PYSITELIB}/pandas/io/formats/console.pyo
${PYSITELIB}/pandas/io/formats/css.py
${PYSITELIB}/pandas/io/formats/css.pyc
${PYSITELIB}/pandas/io/formats/css.pyo
${PYSITELIB}/pandas/io/formats/excel.py
${PYSITELIB}/pandas/io/formats/excel.pyc
${PYSITELIB}/pandas/io/formats/excel.pyo
${PYSITELIB}/pandas/io/formats/format.py
${PYSITELIB}/pandas/io/formats/format.pyc
${PYSITELIB}/pandas/io/formats/format.pyo
${PYSITELIB}/pandas/io/formats/printing.py
${PYSITELIB}/pandas/io/formats/printing.pyc
${PYSITELIB}/pandas/io/formats/printing.pyo
${PYSITELIB}/pandas/io/formats/style.py
${PYSITELIB}/pandas/io/formats/style.pyc
${PYSITELIB}/pandas/io/formats/style.pyo
${PYSITELIB}/pandas/io/formats/templates/html.tpl
${PYSITELIB}/pandas/io/formats/terminal.py
${PYSITELIB}/pandas/io/formats/terminal.pyc
${PYSITELIB}/pandas/io/formats/terminal.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/io/gbq.py
${PYSITELIB}/pandas/io/gbq.pyc
${PYSITELIB}/pandas/io/gbq.pyo
Update pandas to 0.12.0. This is a major release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular expressions. For detailed changes see: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2013-12-10 14:00:30 +01:00
${PYSITELIB}/pandas/io/html.py
${PYSITELIB}/pandas/io/html.pyc
${PYSITELIB}/pandas/io/html.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/io/json/__init__.py
${PYSITELIB}/pandas/io/json/__init__.pyc
${PYSITELIB}/pandas/io/json/__init__.pyo
${PYSITELIB}/pandas/io/json/json.py
${PYSITELIB}/pandas/io/json/json.pyc
${PYSITELIB}/pandas/io/json/json.pyo
${PYSITELIB}/pandas/io/json/normalize.py
${PYSITELIB}/pandas/io/json/normalize.pyc
${PYSITELIB}/pandas/io/json/normalize.pyo
${PYSITELIB}/pandas/io/json/table_schema.py
${PYSITELIB}/pandas/io/json/table_schema.pyc
${PYSITELIB}/pandas/io/json/table_schema.pyo
${PYSITELIB}/pandas/io/msgpack/__init__.py
${PYSITELIB}/pandas/io/msgpack/__init__.pyc
${PYSITELIB}/pandas/io/msgpack/__init__.pyo
${PYSITELIB}/pandas/io/msgpack/_packer.so
${PYSITELIB}/pandas/io/msgpack/_unpacker.so
${PYSITELIB}/pandas/io/msgpack/_version.py
${PYSITELIB}/pandas/io/msgpack/_version.pyc
${PYSITELIB}/pandas/io/msgpack/_version.pyo
${PYSITELIB}/pandas/io/msgpack/exceptions.py
${PYSITELIB}/pandas/io/msgpack/exceptions.pyc
${PYSITELIB}/pandas/io/msgpack/exceptions.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/io/packers.py
${PYSITELIB}/pandas/io/packers.pyc
${PYSITELIB}/pandas/io/packers.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/io/parquet.py
${PYSITELIB}/pandas/io/parquet.pyc
${PYSITELIB}/pandas/io/parquet.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/io/parsers.py
${PYSITELIB}/pandas/io/parsers.pyc
${PYSITELIB}/pandas/io/parsers.pyo
Update pandas to 0.12.0. This is a major release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular expressions. For detailed changes see: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2013-12-10 14:00:30 +01:00
${PYSITELIB}/pandas/io/pickle.py
${PYSITELIB}/pandas/io/pickle.pyc
${PYSITELIB}/pandas/io/pickle.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/io/pytables.py
${PYSITELIB}/pandas/io/pytables.pyc
${PYSITELIB}/pandas/io/pytables.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/io/s3.py
${PYSITELIB}/pandas/io/s3.pyc
${PYSITELIB}/pandas/io/s3.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/io/sas/__init__.py
${PYSITELIB}/pandas/io/sas/__init__.pyc
${PYSITELIB}/pandas/io/sas/__init__.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/io/sas/_sas.so
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/io/sas/sas7bdat.py
${PYSITELIB}/pandas/io/sas/sas7bdat.pyc
${PYSITELIB}/pandas/io/sas/sas7bdat.pyo
${PYSITELIB}/pandas/io/sas/sas_constants.py
${PYSITELIB}/pandas/io/sas/sas_constants.pyc
${PYSITELIB}/pandas/io/sas/sas_constants.pyo
${PYSITELIB}/pandas/io/sas/sas_xport.py
${PYSITELIB}/pandas/io/sas/sas_xport.pyc
${PYSITELIB}/pandas/io/sas/sas_xport.pyo
${PYSITELIB}/pandas/io/sas/sasreader.py
${PYSITELIB}/pandas/io/sas/sasreader.pyc
${PYSITELIB}/pandas/io/sas/sasreader.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/io/sql.py
${PYSITELIB}/pandas/io/sql.pyc
${PYSITELIB}/pandas/io/sql.pyo
Update pandas to 0.12.0. This is a major release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular expressions. For detailed changes see: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2013-12-10 14:00:30 +01:00
${PYSITELIB}/pandas/io/stata.py
${PYSITELIB}/pandas/io/stata.pyc
${PYSITELIB}/pandas/io/stata.pyo
Update py-pandas to 0.11.0. Summary of changes since 0.10.1: This is a major release from 0.10.1 and includes many new features and enhancements along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time pandas users should pay close attention to. * 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. * Improved DataFrame to CSV exporting performance. For a full list refer to the "what's new" page. Also fixes PLIST errors introduced in last update.
2013-05-17 01:10:16 +02:00
${PYSITELIB}/pandas/io/wb.py
${PYSITELIB}/pandas/io/wb.pyc
${PYSITELIB}/pandas/io/wb.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/json.py
${PYSITELIB}/pandas/json.pyc
${PYSITELIB}/pandas/json.pyo
${PYSITELIB}/pandas/lib.py
${PYSITELIB}/pandas/lib.pyc
${PYSITELIB}/pandas/lib.pyo
${PYSITELIB}/pandas/parser.py
${PYSITELIB}/pandas/parser.pyc
${PYSITELIB}/pandas/parser.pyo
${PYSITELIB}/pandas/plotting/__init__.py
${PYSITELIB}/pandas/plotting/__init__.pyc
${PYSITELIB}/pandas/plotting/__init__.pyo
${PYSITELIB}/pandas/plotting/_compat.py
${PYSITELIB}/pandas/plotting/_compat.pyc
${PYSITELIB}/pandas/plotting/_compat.pyo
${PYSITELIB}/pandas/plotting/_converter.py
${PYSITELIB}/pandas/plotting/_converter.pyc
${PYSITELIB}/pandas/plotting/_converter.pyo
${PYSITELIB}/pandas/plotting/_core.py
${PYSITELIB}/pandas/plotting/_core.pyc
${PYSITELIB}/pandas/plotting/_core.pyo
${PYSITELIB}/pandas/plotting/_misc.py
${PYSITELIB}/pandas/plotting/_misc.pyc
${PYSITELIB}/pandas/plotting/_misc.pyo
${PYSITELIB}/pandas/plotting/_style.py
${PYSITELIB}/pandas/plotting/_style.pyc
${PYSITELIB}/pandas/plotting/_style.pyo
${PYSITELIB}/pandas/plotting/_timeseries.py
${PYSITELIB}/pandas/plotting/_timeseries.pyc
${PYSITELIB}/pandas/plotting/_timeseries.pyo
${PYSITELIB}/pandas/plotting/_tools.py
${PYSITELIB}/pandas/plotting/_tools.pyc
${PYSITELIB}/pandas/plotting/_tools.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/stats/__init__.py
${PYSITELIB}/pandas/stats/__init__.pyc
${PYSITELIB}/pandas/stats/__init__.pyo
${PYSITELIB}/pandas/stats/api.py
${PYSITELIB}/pandas/stats/api.pyc
${PYSITELIB}/pandas/stats/api.pyo
${PYSITELIB}/pandas/stats/moments.py
${PYSITELIB}/pandas/stats/moments.pyc
${PYSITELIB}/pandas/stats/moments.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/testing.py
${PYSITELIB}/pandas/testing.pyc
${PYSITELIB}/pandas/testing.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tests/__init__.py
${PYSITELIB}/pandas/tests/__init__.pyc
${PYSITELIB}/pandas/tests/__init__.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/api/__init__.py
${PYSITELIB}/pandas/tests/api/__init__.pyc
${PYSITELIB}/pandas/tests/api/__init__.pyo
${PYSITELIB}/pandas/tests/api/test_api.py
${PYSITELIB}/pandas/tests/api/test_api.pyc
${PYSITELIB}/pandas/tests/api/test_api.pyo
${PYSITELIB}/pandas/tests/api/test_types.py
${PYSITELIB}/pandas/tests/api/test_types.pyc
${PYSITELIB}/pandas/tests/api/test_types.pyo
${PYSITELIB}/pandas/tests/computation/__init__.py
${PYSITELIB}/pandas/tests/computation/__init__.pyc
${PYSITELIB}/pandas/tests/computation/__init__.pyo
${PYSITELIB}/pandas/tests/computation/test_compat.py
${PYSITELIB}/pandas/tests/computation/test_compat.pyc
${PYSITELIB}/pandas/tests/computation/test_compat.pyo
${PYSITELIB}/pandas/tests/computation/test_eval.py
${PYSITELIB}/pandas/tests/computation/test_eval.pyc
${PYSITELIB}/pandas/tests/computation/test_eval.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tests/data/iris.csv
Update py-pandas to 0.11.0. Summary of changes since 0.10.1: This is a major release from 0.10.1 and includes many new features and enhancements along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time pandas users should pay close attention to. * 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. * Improved DataFrame to CSV exporting performance. For a full list refer to the "what's new" page. Also fixes PLIST errors introduced in last update.
2013-05-17 01:10:16 +02:00
${PYSITELIB}/pandas/tests/data/tips.csv
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/dtypes/__init__.py
${PYSITELIB}/pandas/tests/dtypes/__init__.pyc
${PYSITELIB}/pandas/tests/dtypes/__init__.pyo
${PYSITELIB}/pandas/tests/dtypes/test_cast.py
${PYSITELIB}/pandas/tests/dtypes/test_cast.pyc
${PYSITELIB}/pandas/tests/dtypes/test_cast.pyo
${PYSITELIB}/pandas/tests/dtypes/test_common.py
${PYSITELIB}/pandas/tests/dtypes/test_common.pyc
${PYSITELIB}/pandas/tests/dtypes/test_common.pyo
${PYSITELIB}/pandas/tests/dtypes/test_concat.py
${PYSITELIB}/pandas/tests/dtypes/test_concat.pyc
${PYSITELIB}/pandas/tests/dtypes/test_concat.pyo
${PYSITELIB}/pandas/tests/dtypes/test_dtypes.py
${PYSITELIB}/pandas/tests/dtypes/test_dtypes.pyc
${PYSITELIB}/pandas/tests/dtypes/test_dtypes.pyo
${PYSITELIB}/pandas/tests/dtypes/test_generic.py
${PYSITELIB}/pandas/tests/dtypes/test_generic.pyc
${PYSITELIB}/pandas/tests/dtypes/test_generic.pyo
${PYSITELIB}/pandas/tests/dtypes/test_inference.py
${PYSITELIB}/pandas/tests/dtypes/test_inference.pyc
${PYSITELIB}/pandas/tests/dtypes/test_inference.pyo
${PYSITELIB}/pandas/tests/dtypes/test_io.py
${PYSITELIB}/pandas/tests/dtypes/test_io.pyc
${PYSITELIB}/pandas/tests/dtypes/test_io.pyo
${PYSITELIB}/pandas/tests/dtypes/test_missing.py
${PYSITELIB}/pandas/tests/dtypes/test_missing.pyc
${PYSITELIB}/pandas/tests/dtypes/test_missing.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/frame/__init__.py
${PYSITELIB}/pandas/tests/frame/__init__.pyc
${PYSITELIB}/pandas/tests/frame/__init__.pyo
${PYSITELIB}/pandas/tests/frame/common.py
${PYSITELIB}/pandas/tests/frame/common.pyc
${PYSITELIB}/pandas/tests/frame/common.pyo
${PYSITELIB}/pandas/tests/frame/test_alter_axes.py
${PYSITELIB}/pandas/tests/frame/test_alter_axes.pyc
${PYSITELIB}/pandas/tests/frame/test_alter_axes.pyo
${PYSITELIB}/pandas/tests/frame/test_analytics.py
${PYSITELIB}/pandas/tests/frame/test_analytics.pyc
${PYSITELIB}/pandas/tests/frame/test_analytics.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/frame/test_api.py
${PYSITELIB}/pandas/tests/frame/test_api.pyc
${PYSITELIB}/pandas/tests/frame/test_api.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/frame/test_apply.py
${PYSITELIB}/pandas/tests/frame/test_apply.pyc
${PYSITELIB}/pandas/tests/frame/test_apply.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/frame/test_asof.py
${PYSITELIB}/pandas/tests/frame/test_asof.pyc
${PYSITELIB}/pandas/tests/frame/test_asof.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/frame/test_axis_select_reindex.py
${PYSITELIB}/pandas/tests/frame/test_axis_select_reindex.pyc
${PYSITELIB}/pandas/tests/frame/test_axis_select_reindex.pyo
${PYSITELIB}/pandas/tests/frame/test_block_internals.py
${PYSITELIB}/pandas/tests/frame/test_block_internals.pyc
${PYSITELIB}/pandas/tests/frame/test_block_internals.pyo
${PYSITELIB}/pandas/tests/frame/test_combine_concat.py
${PYSITELIB}/pandas/tests/frame/test_combine_concat.pyc
${PYSITELIB}/pandas/tests/frame/test_combine_concat.pyo
${PYSITELIB}/pandas/tests/frame/test_constructors.py
${PYSITELIB}/pandas/tests/frame/test_constructors.pyc
${PYSITELIB}/pandas/tests/frame/test_constructors.pyo
${PYSITELIB}/pandas/tests/frame/test_convert_to.py
${PYSITELIB}/pandas/tests/frame/test_convert_to.pyc
${PYSITELIB}/pandas/tests/frame/test_convert_to.pyo
${PYSITELIB}/pandas/tests/frame/test_dtypes.py
${PYSITELIB}/pandas/tests/frame/test_dtypes.pyc
${PYSITELIB}/pandas/tests/frame/test_dtypes.pyo
${PYSITELIB}/pandas/tests/frame/test_indexing.py
${PYSITELIB}/pandas/tests/frame/test_indexing.pyc
${PYSITELIB}/pandas/tests/frame/test_indexing.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/frame/test_join.py
${PYSITELIB}/pandas/tests/frame/test_join.pyc
${PYSITELIB}/pandas/tests/frame/test_join.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/frame/test_missing.py
${PYSITELIB}/pandas/tests/frame/test_missing.pyc
${PYSITELIB}/pandas/tests/frame/test_missing.pyo
${PYSITELIB}/pandas/tests/frame/test_mutate_columns.py
${PYSITELIB}/pandas/tests/frame/test_mutate_columns.pyc
${PYSITELIB}/pandas/tests/frame/test_mutate_columns.pyo
${PYSITELIB}/pandas/tests/frame/test_nonunique_indexes.py
${PYSITELIB}/pandas/tests/frame/test_nonunique_indexes.pyc
${PYSITELIB}/pandas/tests/frame/test_nonunique_indexes.pyo
${PYSITELIB}/pandas/tests/frame/test_operators.py
${PYSITELIB}/pandas/tests/frame/test_operators.pyc
${PYSITELIB}/pandas/tests/frame/test_operators.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/frame/test_period.py
${PYSITELIB}/pandas/tests/frame/test_period.pyc
${PYSITELIB}/pandas/tests/frame/test_period.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/frame/test_quantile.py
${PYSITELIB}/pandas/tests/frame/test_quantile.pyc
${PYSITELIB}/pandas/tests/frame/test_quantile.pyo
${PYSITELIB}/pandas/tests/frame/test_query_eval.py
${PYSITELIB}/pandas/tests/frame/test_query_eval.pyc
${PYSITELIB}/pandas/tests/frame/test_query_eval.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/frame/test_rank.py
${PYSITELIB}/pandas/tests/frame/test_rank.pyc
${PYSITELIB}/pandas/tests/frame/test_rank.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/frame/test_replace.py
${PYSITELIB}/pandas/tests/frame/test_replace.pyc
${PYSITELIB}/pandas/tests/frame/test_replace.pyo
${PYSITELIB}/pandas/tests/frame/test_repr_info.py
${PYSITELIB}/pandas/tests/frame/test_repr_info.pyc
${PYSITELIB}/pandas/tests/frame/test_repr_info.pyo
${PYSITELIB}/pandas/tests/frame/test_reshape.py
${PYSITELIB}/pandas/tests/frame/test_reshape.pyc
${PYSITELIB}/pandas/tests/frame/test_reshape.pyo
${PYSITELIB}/pandas/tests/frame/test_sorting.py
${PYSITELIB}/pandas/tests/frame/test_sorting.pyc
${PYSITELIB}/pandas/tests/frame/test_sorting.pyo
${PYSITELIB}/pandas/tests/frame/test_subclass.py
${PYSITELIB}/pandas/tests/frame/test_subclass.pyc
${PYSITELIB}/pandas/tests/frame/test_subclass.pyo
${PYSITELIB}/pandas/tests/frame/test_timeseries.py
${PYSITELIB}/pandas/tests/frame/test_timeseries.pyc
${PYSITELIB}/pandas/tests/frame/test_timeseries.pyo
${PYSITELIB}/pandas/tests/frame/test_to_csv.py
${PYSITELIB}/pandas/tests/frame/test_to_csv.pyc
${PYSITELIB}/pandas/tests/frame/test_to_csv.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/frame/test_validate.py
${PYSITELIB}/pandas/tests/frame/test_validate.pyc
${PYSITELIB}/pandas/tests/frame/test_validate.pyo
${PYSITELIB}/pandas/tests/groupby/__init__.py
${PYSITELIB}/pandas/tests/groupby/__init__.pyc
${PYSITELIB}/pandas/tests/groupby/__init__.pyo
${PYSITELIB}/pandas/tests/groupby/common.py
${PYSITELIB}/pandas/tests/groupby/common.pyc
${PYSITELIB}/pandas/tests/groupby/common.pyo
${PYSITELIB}/pandas/tests/groupby/test_aggregate.py
${PYSITELIB}/pandas/tests/groupby/test_aggregate.pyc
${PYSITELIB}/pandas/tests/groupby/test_aggregate.pyo
${PYSITELIB}/pandas/tests/groupby/test_bin_groupby.py
${PYSITELIB}/pandas/tests/groupby/test_bin_groupby.pyc
${PYSITELIB}/pandas/tests/groupby/test_bin_groupby.pyo
${PYSITELIB}/pandas/tests/groupby/test_categorical.py
${PYSITELIB}/pandas/tests/groupby/test_categorical.pyc
${PYSITELIB}/pandas/tests/groupby/test_categorical.pyo
v0.20.2: This is a minor bug-fix release in the 0.20.x series and includes some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version.
2017-06-07 10:13:56 +02:00
${PYSITELIB}/pandas/tests/groupby/test_counting.py
${PYSITELIB}/pandas/tests/groupby/test_counting.pyc
${PYSITELIB}/pandas/tests/groupby/test_counting.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/groupby/test_filters.py
${PYSITELIB}/pandas/tests/groupby/test_filters.pyc
${PYSITELIB}/pandas/tests/groupby/test_filters.pyo
${PYSITELIB}/pandas/tests/groupby/test_groupby.py
${PYSITELIB}/pandas/tests/groupby/test_groupby.pyc
${PYSITELIB}/pandas/tests/groupby/test_groupby.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/groupby/test_index_as_string.py
${PYSITELIB}/pandas/tests/groupby/test_index_as_string.pyc
${PYSITELIB}/pandas/tests/groupby/test_index_as_string.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/groupby/test_nth.py
${PYSITELIB}/pandas/tests/groupby/test_nth.pyc
${PYSITELIB}/pandas/tests/groupby/test_nth.pyo
${PYSITELIB}/pandas/tests/groupby/test_timegrouper.py
${PYSITELIB}/pandas/tests/groupby/test_timegrouper.pyc
${PYSITELIB}/pandas/tests/groupby/test_timegrouper.pyo
${PYSITELIB}/pandas/tests/groupby/test_transform.py
${PYSITELIB}/pandas/tests/groupby/test_transform.pyc
${PYSITELIB}/pandas/tests/groupby/test_transform.pyo
${PYSITELIB}/pandas/tests/groupby/test_value_counts.py
${PYSITELIB}/pandas/tests/groupby/test_value_counts.pyc
${PYSITELIB}/pandas/tests/groupby/test_value_counts.pyo
${PYSITELIB}/pandas/tests/groupby/test_whitelist.py
${PYSITELIB}/pandas/tests/groupby/test_whitelist.pyc
${PYSITELIB}/pandas/tests/groupby/test_whitelist.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/indexes/__init__.py
${PYSITELIB}/pandas/tests/indexes/__init__.pyc
${PYSITELIB}/pandas/tests/indexes/__init__.pyo
${PYSITELIB}/pandas/tests/indexes/common.py
${PYSITELIB}/pandas/tests/indexes/common.pyc
${PYSITELIB}/pandas/tests/indexes/common.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/indexes/conftest.py
${PYSITELIB}/pandas/tests/indexes/conftest.pyc
${PYSITELIB}/pandas/tests/indexes/conftest.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/indexes/data/mindex_073.pickle
${PYSITELIB}/pandas/tests/indexes/data/multiindex_v1.pickle
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/indexes/datetimelike.py
${PYSITELIB}/pandas/tests/indexes/datetimelike.pyc
${PYSITELIB}/pandas/tests/indexes/datetimelike.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/__init__.py
${PYSITELIB}/pandas/tests/indexes/datetimes/__init__.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/__init__.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_astype.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_astype.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_astype.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_construction.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_construction.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_construction.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_date_range.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_date_range.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_date_range.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_datetime.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_datetime.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_datetime.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_datetimelike.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_datetimelike.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_datetimelike.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_formats.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_formats.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_formats.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_indexing.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_indexing.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_indexing.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_misc.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_misc.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_misc.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_missing.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_missing.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_missing.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_ops.py
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${PYSITELIB}/pandas/tests/indexes/datetimes/test_ops.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_partial_slicing.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_partial_slicing.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_partial_slicing.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_setops.py
${PYSITELIB}/pandas/tests/indexes/datetimes/test_setops.pyc
${PYSITELIB}/pandas/tests/indexes/datetimes/test_setops.pyo
${PYSITELIB}/pandas/tests/indexes/datetimes/test_tools.py
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${PYSITELIB}/pandas/tests/indexes/datetimes/test_tools.pyo
${PYSITELIB}/pandas/tests/indexes/period/__init__.py
${PYSITELIB}/pandas/tests/indexes/period/__init__.pyc
${PYSITELIB}/pandas/tests/indexes/period/__init__.pyo
${PYSITELIB}/pandas/tests/indexes/period/test_asfreq.py
${PYSITELIB}/pandas/tests/indexes/period/test_asfreq.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_asfreq.pyo
${PYSITELIB}/pandas/tests/indexes/period/test_construction.py
${PYSITELIB}/pandas/tests/indexes/period/test_construction.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_construction.pyo
${PYSITELIB}/pandas/tests/indexes/period/test_formats.py
${PYSITELIB}/pandas/tests/indexes/period/test_formats.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_formats.pyo
${PYSITELIB}/pandas/tests/indexes/period/test_indexing.py
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${PYSITELIB}/pandas/tests/indexes/period/test_indexing.pyo
${PYSITELIB}/pandas/tests/indexes/period/test_ops.py
${PYSITELIB}/pandas/tests/indexes/period/test_ops.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_ops.pyo
${PYSITELIB}/pandas/tests/indexes/period/test_partial_slicing.py
${PYSITELIB}/pandas/tests/indexes/period/test_partial_slicing.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_partial_slicing.pyo
${PYSITELIB}/pandas/tests/indexes/period/test_period.py
${PYSITELIB}/pandas/tests/indexes/period/test_period.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_period.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/indexes/period/test_period_range.py
${PYSITELIB}/pandas/tests/indexes/period/test_period_range.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_period_range.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/indexes/period/test_setops.py
${PYSITELIB}/pandas/tests/indexes/period/test_setops.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_setops.pyo
${PYSITELIB}/pandas/tests/indexes/period/test_tools.py
${PYSITELIB}/pandas/tests/indexes/period/test_tools.pyc
${PYSITELIB}/pandas/tests/indexes/period/test_tools.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/indexes/test_base.py
${PYSITELIB}/pandas/tests/indexes/test_base.pyc
${PYSITELIB}/pandas/tests/indexes/test_base.pyo
${PYSITELIB}/pandas/tests/indexes/test_category.py
${PYSITELIB}/pandas/tests/indexes/test_category.pyc
${PYSITELIB}/pandas/tests/indexes/test_category.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/indexes/test_frozen.py
${PYSITELIB}/pandas/tests/indexes/test_frozen.pyc
${PYSITELIB}/pandas/tests/indexes/test_frozen.pyo
${PYSITELIB}/pandas/tests/indexes/test_interval.py
${PYSITELIB}/pandas/tests/indexes/test_interval.pyc
${PYSITELIB}/pandas/tests/indexes/test_interval.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/indexes/test_multi.py
${PYSITELIB}/pandas/tests/indexes/test_multi.pyc
${PYSITELIB}/pandas/tests/indexes/test_multi.pyo
${PYSITELIB}/pandas/tests/indexes/test_numeric.py
${PYSITELIB}/pandas/tests/indexes/test_numeric.pyc
${PYSITELIB}/pandas/tests/indexes/test_numeric.pyo
${PYSITELIB}/pandas/tests/indexes/test_range.py
${PYSITELIB}/pandas/tests/indexes/test_range.pyc
${PYSITELIB}/pandas/tests/indexes/test_range.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/indexes/timedeltas/__init__.py
${PYSITELIB}/pandas/tests/indexes/timedeltas/__init__.pyc
${PYSITELIB}/pandas/tests/indexes/timedeltas/__init__.pyo
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_astype.py
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_astype.pyc
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_astype.pyo
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_construction.py
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_construction.pyc
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_construction.pyo
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_indexing.py
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_indexing.pyc
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_indexing.pyo
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_ops.py
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_ops.pyc
${PYSITELIB}/pandas/tests/indexes/timedeltas/test_ops.pyo
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${PYSITELIB}/pandas/tests/indexes/timedeltas/test_tools.py
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py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/indexing/__init__.py
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${PYSITELIB}/pandas/tests/indexing/test_timedelta.py
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${PYSITELIB}/pandas/tests/internals/__init__.py
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${PYSITELIB}/pandas/tests/internals/test_external_block.py
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Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/__init__.py
${PYSITELIB}/pandas/tests/io/__init__.pyc
${PYSITELIB}/pandas/tests/io/__init__.pyo
py-pandas: updated to 0.21.1 v0.21.1: Restore Matplotlib datetime Converter Registration New features - Improvements to the Parquet IO functionality - Other Enhancements Deprecations Performance Improvements Bug Fixes - Conversion - Indexing - I/O - Plotting - Groupby/Resample/Rolling - Reshaping - Numeric - Categorical - String
2017-12-14 14:37:59 +01:00
${PYSITELIB}/pandas/tests/io/conftest.py
${PYSITELIB}/pandas/tests/io/conftest.pyc
${PYSITELIB}/pandas/tests/io/conftest.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/data/S4_EDUC1.dta
${PYSITELIB}/pandas/tests/io/data/banklist.csv
${PYSITELIB}/pandas/tests/io/data/banklist.html
${PYSITELIB}/pandas/tests/io/data/blank.xls
${PYSITELIB}/pandas/tests/io/data/blank.xlsm
${PYSITELIB}/pandas/tests/io/data/blank.xlsx
${PYSITELIB}/pandas/tests/io/data/blank_with_header.xls
${PYSITELIB}/pandas/tests/io/data/blank_with_header.xlsm
${PYSITELIB}/pandas/tests/io/data/blank_with_header.xlsx
${PYSITELIB}/pandas/tests/io/data/categorical_0_14_1.pickle
${PYSITELIB}/pandas/tests/io/data/categorical_0_15_2.pickle
${PYSITELIB}/pandas/tests/io/data/computer_sales_page.html
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/data/fixed_width_format.txt
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/data/gbq_fake_job.txt
${PYSITELIB}/pandas/tests/io/data/html_encoding/chinese_utf-16.html
${PYSITELIB}/pandas/tests/io/data/html_encoding/chinese_utf-32.html
${PYSITELIB}/pandas/tests/io/data/html_encoding/chinese_utf-8.html
${PYSITELIB}/pandas/tests/io/data/html_encoding/letz_latin1.html
${PYSITELIB}/pandas/tests/io/data/iris.csv
${PYSITELIB}/pandas/tests/io/data/legacy_hdf/datetimetz_object.h5
${PYSITELIB}/pandas/tests/io/data/legacy_hdf/legacy_table.h5
0.20.3 Bug Fixes * Fixed a bug in failing to compute rolling computations of a column-MultiIndexed DataFrame * Fixed a pytest marker failing downstream packages’ tests suites Conversion * Bug in pickle compat prior to the v0.20.x series, when UTC is a timezone in a Series/DataFrame/Index * Bug in Series construction when passing a Series with dtype='category'. * Bug in DataFrame.astype() when passing a Series as the dtype kwarg.. Indexing * Bug in Float64Index causing an empty array instead of None to be returned from .get(np.nan) on a Series whose index did not contain any NaN s * Bug in MultiIndex.isin causing an error when passing an empty iterable * Fixed a bug in a slicing DataFrame/Series that have a TimedeltaIndex I/O * Bug in read_csv() in which files weren’t opened as binary files by the C engine on Windows, causing EOF characters mid-field, which would fail * Bug in read_hdf() in which reading a Series saved to an HDF file in ‘fixed’ format fails when an explicit mode='r' argument is supplied * Bug in DataFrame.to_latex() where bold_rows was wrongly specified to be True by default, whereas in reality row labels remained non-bold whatever parameter provided. * Fixed an issue with DataFrame.style() where generated element ids were not unique * Fixed loading a DataFrame with a PeriodIndex, from a format='fixed' HDFStore, in Python 3, that was written in Python 2 Plotting * Fixed regression that prevented RGB and RGBA tuples from being used as color arguments * Fixed an issue with DataFrame.plot.scatter() that incorrectly raised a KeyError when categorical data is used for plotting Reshaping * PeriodIndex / TimedeltaIndex.join was missing the sort= kwarg * Bug in joining on a MultiIndex with a category dtype for a level. * Bug in merge() when merging/joining with multiple categorical columns Categorical * Bug in DataFrame.sort_values not respecting the kind parameter with categorical data
2017-07-14 12:17:02 +02:00
${PYSITELIB}/pandas/tests/io/data/legacy_hdf/periodindex_0.20.1_x86_64_darwin_2.7.13.h5
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/data/legacy_hdf/pytables_native.h5
${PYSITELIB}/pandas/tests/io/data/legacy_hdf/pytables_native2.h5
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${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.17.0/0.17.0_x86_64_darwin_3.4.4.pickle
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.17.0/0.17.0_x86_64_darwin_3.5.3.pickle
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.17.0/0.17.0_x86_64_linux_2.7.11.pickle
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.17.0/0.17.0_x86_64_linux_3.4.4.pickle
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.17.0/0.17.1_AMD64_windows_2.7.11.pickle
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.17.1/0.17.1_AMD64_windows_2.7.11.pickle
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.17.1/0.17.1_x86_64_darwin_2.7.11.pickle
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.18.0/0.18.0_AMD64_windows_2.7.11.pickle
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.18.0/0.18.0_AMD64_windows_3.5.1.pickle
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.18.0/0.18.0_x86_64_darwin_2.7.11.pickle
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${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.19.2/0.19.2_x86_64_darwin_2.7.12.pickle
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.19.2/0.19.2_x86_64_darwin_2.7.14.pickle
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.19.2/0.19.2_x86_64_darwin_3.6.1.pickle
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/data/legacy_pickle/0.20.3/0.20.3_x86_64_darwin_2.7.14.pickle
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/data/macau.html
${PYSITELIB}/pandas/tests/io/data/nyse_wsj.html
${PYSITELIB}/pandas/tests/io/data/spam.html
${PYSITELIB}/pandas/tests/io/data/stata10_115.dta
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py-pandas: updated to 0.21.1 v0.21.1: Restore Matplotlib datetime Converter Registration New features - Improvements to the Parquet IO functionality - Other Enhancements Deprecations Performance Improvements Bug Fixes - Conversion - Indexing - I/O - Plotting - Groupby/Resample/Rolling - Reshaping - Numeric - Categorical - String
2017-12-14 14:37:59 +01:00
${PYSITELIB}/pandas/tests/io/data/stata13_dates.dta
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here A new orient for JSON serialization, orient='table', that uses the Table Schema spec and that gives the possibility for a more interactive repr in the Jupyter Notebook, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
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${PYSITELIB}/pandas/tests/io/json/data/tsframe_iso_v012.json
${PYSITELIB}/pandas/tests/io/json/data/tsframe_v012.json
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/json/data/tsframe_v012.json.zip
${PYSITELIB}/pandas/tests/io/json/test_compression.py
${PYSITELIB}/pandas/tests/io/json/test_compression.pyc
${PYSITELIB}/pandas/tests/io/json/test_compression.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/json/test_json_table_schema.py
${PYSITELIB}/pandas/tests/io/json/test_json_table_schema.pyc
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${PYSITELIB}/pandas/tests/io/json/test_pandas.pyc
${PYSITELIB}/pandas/tests/io/json/test_pandas.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/json/test_readlines.py
${PYSITELIB}/pandas/tests/io/json/test_readlines.pyc
${PYSITELIB}/pandas/tests/io/json/test_readlines.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/json/test_ujson.py
${PYSITELIB}/pandas/tests/io/json/test_ujson.pyc
${PYSITELIB}/pandas/tests/io/json/test_ujson.pyo
${PYSITELIB}/pandas/tests/io/msgpack/__init__.py
${PYSITELIB}/pandas/tests/io/msgpack/__init__.pyc
${PYSITELIB}/pandas/tests/io/msgpack/__init__.pyo
${PYSITELIB}/pandas/tests/io/msgpack/common.py
${PYSITELIB}/pandas/tests/io/msgpack/common.pyc
${PYSITELIB}/pandas/tests/io/msgpack/common.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/msgpack/data/frame.mp
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/msgpack/test_buffer.py
${PYSITELIB}/pandas/tests/io/msgpack/test_buffer.pyc
${PYSITELIB}/pandas/tests/io/msgpack/test_buffer.pyo
${PYSITELIB}/pandas/tests/io/msgpack/test_case.py
${PYSITELIB}/pandas/tests/io/msgpack/test_case.pyc
${PYSITELIB}/pandas/tests/io/msgpack/test_case.pyo
${PYSITELIB}/pandas/tests/io/msgpack/test_except.py
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${PYSITELIB}/pandas/tests/io/parser/data/iris.csv
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${PYSITELIB}/pandas/tests/io/parser/data/salaries.csv.gz
py-pandas: updated to 0.21.1 v0.21.1: Restore Matplotlib datetime Converter Registration New features - Improvements to the Parquet IO functionality - Other Enhancements Deprecations Performance Improvements Bug Fixes - Conversion - Indexing - I/O - Plotting - Groupby/Resample/Rolling - Reshaping - Numeric - Categorical - String
2017-12-14 14:37:59 +01:00
${PYSITELIB}/pandas/tests/io/parser/data/salaries.csv.zip
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/parser/data/sauron.SHIFT_JIS.csv
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/parser/data/sub_char.csv
v0.20.2: This is a minor bug-fix release in the 0.20.x series and includes some small regression fixes, bug fixes and performance improvements. We recommend that all users upgrade to this version.
2017-06-07 10:13:56 +02:00
${PYSITELIB}/pandas/tests/io/parser/data/tar_csv.tar
${PYSITELIB}/pandas/tests/io/parser/data/tar_csv.tar.gz
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/parser/data/test1.csv
${PYSITELIB}/pandas/tests/io/parser/data/test1.csv.bz2
${PYSITELIB}/pandas/tests/io/parser/data/test1.csv.gz
${PYSITELIB}/pandas/tests/io/parser/data/test2.csv
${PYSITELIB}/pandas/tests/io/parser/data/test_mmap.csv
${PYSITELIB}/pandas/tests/io/parser/data/tips.csv
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/parser/data/tips.csv.bz2
${PYSITELIB}/pandas/tests/io/parser/data/tips.csv.gz
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/parser/data/unicode_series.csv
${PYSITELIB}/pandas/tests/io/parser/data/utf16_ex.txt
py-pandas: updated to 0.21.1 v0.21.1: Restore Matplotlib datetime Converter Registration New features - Improvements to the Parquet IO functionality - Other Enhancements Deprecations Performance Improvements Bug Fixes - Conversion - Indexing - I/O - Plotting - Groupby/Resample/Rolling - Reshaping - Numeric - Categorical - String
2017-12-14 14:37:59 +01:00
${PYSITELIB}/pandas/tests/io/parser/data/utf16_ex_small.zip
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/parser/dialect.py
${PYSITELIB}/pandas/tests/io/parser/dialect.pyc
${PYSITELIB}/pandas/tests/io/parser/dialect.pyo
${PYSITELIB}/pandas/tests/io/parser/dtypes.py
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${PYSITELIB}/pandas/tests/io/parser/header.py
${PYSITELIB}/pandas/tests/io/parser/header.pyc
${PYSITELIB}/pandas/tests/io/parser/header.pyo
${PYSITELIB}/pandas/tests/io/parser/index_col.py
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${PYSITELIB}/pandas/tests/io/parser/index_col.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/parser/mangle_dupes.py
${PYSITELIB}/pandas/tests/io/parser/mangle_dupes.pyc
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Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/parser/multithread.py
${PYSITELIB}/pandas/tests/io/parser/multithread.pyc
${PYSITELIB}/pandas/tests/io/parser/multithread.pyo
${PYSITELIB}/pandas/tests/io/parser/na_values.py
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py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/sas/data/datetime.csv
${PYSITELIB}/pandas/tests/io/sas/data/datetime.sas7bdat
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/sas/data/paxraw_d_short.csv
${PYSITELIB}/pandas/tests/io/sas/data/paxraw_d_short.xpt
${PYSITELIB}/pandas/tests/io/sas/data/productsales.csv
${PYSITELIB}/pandas/tests/io/sas/data/productsales.sas7bdat
${PYSITELIB}/pandas/tests/io/sas/data/test1.sas7bdat
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${PYSITELIB}/pandas/tests/io/sas/data/test12.sas7bdat
${PYSITELIB}/pandas/tests/io/sas/data/test13.sas7bdat
${PYSITELIB}/pandas/tests/io/sas/data/test14.sas7bdat
${PYSITELIB}/pandas/tests/io/sas/data/test15.sas7bdat
${PYSITELIB}/pandas/tests/io/sas/data/test16.sas7bdat
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${PYSITELIB}/pandas/tests/io/sas/data/test_12659.sas7bdat
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${PYSITELIB}/pandas/tests/io/test_excel.py
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${PYSITELIB}/pandas/tests/io/test_html.py
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${PYSITELIB}/pandas/tests/io/test_packers.py
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py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/io/test_parquet.py
${PYSITELIB}/pandas/tests/io/test_parquet.pyc
${PYSITELIB}/pandas/tests/io/test_parquet.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/io/test_pickle.py
${PYSITELIB}/pandas/tests/io/test_pickle.pyc
${PYSITELIB}/pandas/tests/io/test_pickle.pyo
${PYSITELIB}/pandas/tests/io/test_pytables.py
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${PYSITELIB}/pandas/tests/io/test_pytables.pyo
${PYSITELIB}/pandas/tests/io/test_s3.py
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${PYSITELIB}/pandas/tests/io/test_s3.pyo
${PYSITELIB}/pandas/tests/io/test_sql.py
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${PYSITELIB}/pandas/tests/io/test_sql.pyo
${PYSITELIB}/pandas/tests/io/test_stata.py
${PYSITELIB}/pandas/tests/io/test_stata.pyc
${PYSITELIB}/pandas/tests/io/test_stata.pyo
${PYSITELIB}/pandas/tests/plotting/__init__.py
${PYSITELIB}/pandas/tests/plotting/__init__.pyc
${PYSITELIB}/pandas/tests/plotting/__init__.pyo
${PYSITELIB}/pandas/tests/plotting/common.py
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${PYSITELIB}/pandas/tests/plotting/test_boxplot_method.pyo
${PYSITELIB}/pandas/tests/plotting/test_converter.py
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${PYSITELIB}/pandas/tests/plotting/test_datetimelike.py
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${PYSITELIB}/pandas/tests/plotting/test_misc.pyo
${PYSITELIB}/pandas/tests/plotting/test_series.py
${PYSITELIB}/pandas/tests/plotting/test_series.pyc
${PYSITELIB}/pandas/tests/plotting/test_series.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/reshape/__init__.py
${PYSITELIB}/pandas/tests/reshape/__init__.pyc
${PYSITELIB}/pandas/tests/reshape/__init__.pyo
${PYSITELIB}/pandas/tests/reshape/data/allow_exact_matches.csv
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${PYSITELIB}/pandas/tests/reshape/data/quotes.csv
${PYSITELIB}/pandas/tests/reshape/data/quotes2.csv
${PYSITELIB}/pandas/tests/reshape/data/tolerance.csv
${PYSITELIB}/pandas/tests/reshape/data/trades.csv
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${PYSITELIB}/pandas/tests/reshape/test_concat.py
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${PYSITELIB}/pandas/tests/reshape/test_tile.py
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${PYSITELIB}/pandas/tests/reshape/test_union_categoricals.py
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${PYSITELIB}/pandas/tests/reshape/test_union_categoricals.pyo
${PYSITELIB}/pandas/tests/reshape/test_util.py
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Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/scalar/__init__.py
${PYSITELIB}/pandas/tests/scalar/__init__.pyc
${PYSITELIB}/pandas/tests/scalar/__init__.pyo
${PYSITELIB}/pandas/tests/scalar/test_interval.py
${PYSITELIB}/pandas/tests/scalar/test_interval.pyc
${PYSITELIB}/pandas/tests/scalar/test_interval.pyo
${PYSITELIB}/pandas/tests/scalar/test_nat.py
${PYSITELIB}/pandas/tests/scalar/test_nat.pyc
${PYSITELIB}/pandas/tests/scalar/test_nat.pyo
${PYSITELIB}/pandas/tests/scalar/test_period.py
${PYSITELIB}/pandas/tests/scalar/test_period.pyc
${PYSITELIB}/pandas/tests/scalar/test_period.pyo
${PYSITELIB}/pandas/tests/scalar/test_period_asfreq.py
${PYSITELIB}/pandas/tests/scalar/test_period_asfreq.pyc
${PYSITELIB}/pandas/tests/scalar/test_period_asfreq.pyo
${PYSITELIB}/pandas/tests/scalar/test_timedelta.py
${PYSITELIB}/pandas/tests/scalar/test_timedelta.pyc
${PYSITELIB}/pandas/tests/scalar/test_timedelta.pyo
${PYSITELIB}/pandas/tests/scalar/test_timestamp.py
${PYSITELIB}/pandas/tests/scalar/test_timestamp.pyc
${PYSITELIB}/pandas/tests/scalar/test_timestamp.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/series/__init__.py
${PYSITELIB}/pandas/tests/series/__init__.pyc
${PYSITELIB}/pandas/tests/series/__init__.pyo
${PYSITELIB}/pandas/tests/series/common.py
${PYSITELIB}/pandas/tests/series/common.pyc
${PYSITELIB}/pandas/tests/series/common.pyo
${PYSITELIB}/pandas/tests/series/test_alter_axes.py
${PYSITELIB}/pandas/tests/series/test_alter_axes.pyc
${PYSITELIB}/pandas/tests/series/test_alter_axes.pyo
${PYSITELIB}/pandas/tests/series/test_analytics.py
${PYSITELIB}/pandas/tests/series/test_analytics.pyc
${PYSITELIB}/pandas/tests/series/test_analytics.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/series/test_api.py
${PYSITELIB}/pandas/tests/series/test_api.pyc
${PYSITELIB}/pandas/tests/series/test_api.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/series/test_apply.py
${PYSITELIB}/pandas/tests/series/test_apply.pyc
${PYSITELIB}/pandas/tests/series/test_apply.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/series/test_asof.py
${PYSITELIB}/pandas/tests/series/test_asof.pyc
${PYSITELIB}/pandas/tests/series/test_asof.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/series/test_combine_concat.py
${PYSITELIB}/pandas/tests/series/test_combine_concat.pyc
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${PYSITELIB}/pandas/tests/series/test_constructors.py
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${PYSITELIB}/pandas/tests/series/test_datetime_values.py
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${PYSITELIB}/pandas/tests/series/test_dtypes.py
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${PYSITELIB}/pandas/tests/series/test_internals.pyc
${PYSITELIB}/pandas/tests/series/test_internals.pyo
${PYSITELIB}/pandas/tests/series/test_io.py
${PYSITELIB}/pandas/tests/series/test_io.pyc
${PYSITELIB}/pandas/tests/series/test_io.pyo
${PYSITELIB}/pandas/tests/series/test_missing.py
${PYSITELIB}/pandas/tests/series/test_missing.pyc
${PYSITELIB}/pandas/tests/series/test_missing.pyo
${PYSITELIB}/pandas/tests/series/test_operators.py
${PYSITELIB}/pandas/tests/series/test_operators.pyc
${PYSITELIB}/pandas/tests/series/test_operators.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/series/test_period.py
${PYSITELIB}/pandas/tests/series/test_period.pyc
${PYSITELIB}/pandas/tests/series/test_period.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/series/test_quantile.py
${PYSITELIB}/pandas/tests/series/test_quantile.pyc
${PYSITELIB}/pandas/tests/series/test_quantile.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/series/test_rank.py
${PYSITELIB}/pandas/tests/series/test_rank.pyc
${PYSITELIB}/pandas/tests/series/test_rank.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/series/test_replace.py
${PYSITELIB}/pandas/tests/series/test_replace.pyc
${PYSITELIB}/pandas/tests/series/test_replace.pyo
${PYSITELIB}/pandas/tests/series/test_repr.py
${PYSITELIB}/pandas/tests/series/test_repr.pyc
${PYSITELIB}/pandas/tests/series/test_repr.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/series/test_sorting.py
${PYSITELIB}/pandas/tests/series/test_sorting.pyc
${PYSITELIB}/pandas/tests/series/test_sorting.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/series/test_subclass.py
${PYSITELIB}/pandas/tests/series/test_subclass.pyc
${PYSITELIB}/pandas/tests/series/test_subclass.pyo
${PYSITELIB}/pandas/tests/series/test_timeseries.py
${PYSITELIB}/pandas/tests/series/test_timeseries.pyc
${PYSITELIB}/pandas/tests/series/test_timeseries.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/series/test_validate.py
${PYSITELIB}/pandas/tests/series/test_validate.pyc
${PYSITELIB}/pandas/tests/series/test_validate.pyo
${PYSITELIB}/pandas/tests/sparse/__init__.py
${PYSITELIB}/pandas/tests/sparse/__init__.pyc
${PYSITELIB}/pandas/tests/sparse/__init__.pyo
${PYSITELIB}/pandas/tests/sparse/common.py
${PYSITELIB}/pandas/tests/sparse/common.pyc
${PYSITELIB}/pandas/tests/sparse/common.pyo
${PYSITELIB}/pandas/tests/sparse/test_arithmetics.py
${PYSITELIB}/pandas/tests/sparse/test_arithmetics.pyc
${PYSITELIB}/pandas/tests/sparse/test_arithmetics.pyo
${PYSITELIB}/pandas/tests/sparse/test_array.py
${PYSITELIB}/pandas/tests/sparse/test_array.pyc
${PYSITELIB}/pandas/tests/sparse/test_array.pyo
${PYSITELIB}/pandas/tests/sparse/test_combine_concat.py
${PYSITELIB}/pandas/tests/sparse/test_combine_concat.pyc
${PYSITELIB}/pandas/tests/sparse/test_combine_concat.pyo
${PYSITELIB}/pandas/tests/sparse/test_format.py
${PYSITELIB}/pandas/tests/sparse/test_format.pyc
${PYSITELIB}/pandas/tests/sparse/test_format.pyo
${PYSITELIB}/pandas/tests/sparse/test_frame.py
${PYSITELIB}/pandas/tests/sparse/test_frame.pyc
${PYSITELIB}/pandas/tests/sparse/test_frame.pyo
${PYSITELIB}/pandas/tests/sparse/test_groupby.py
${PYSITELIB}/pandas/tests/sparse/test_groupby.pyc
${PYSITELIB}/pandas/tests/sparse/test_groupby.pyo
${PYSITELIB}/pandas/tests/sparse/test_indexing.py
${PYSITELIB}/pandas/tests/sparse/test_indexing.pyc
${PYSITELIB}/pandas/tests/sparse/test_indexing.pyo
${PYSITELIB}/pandas/tests/sparse/test_libsparse.py
${PYSITELIB}/pandas/tests/sparse/test_libsparse.pyc
${PYSITELIB}/pandas/tests/sparse/test_libsparse.pyo
${PYSITELIB}/pandas/tests/sparse/test_list.py
${PYSITELIB}/pandas/tests/sparse/test_list.pyc
${PYSITELIB}/pandas/tests/sparse/test_list.pyo
${PYSITELIB}/pandas/tests/sparse/test_pivot.py
${PYSITELIB}/pandas/tests/sparse/test_pivot.pyc
${PYSITELIB}/pandas/tests/sparse/test_pivot.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/sparse/test_reshape.py
${PYSITELIB}/pandas/tests/sparse/test_reshape.pyc
${PYSITELIB}/pandas/tests/sparse/test_reshape.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/sparse/test_series.py
${PYSITELIB}/pandas/tests/sparse/test_series.pyc
${PYSITELIB}/pandas/tests/sparse/test_series.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tests/test_algos.py
${PYSITELIB}/pandas/tests/test_algos.pyc
${PYSITELIB}/pandas/tests/test_algos.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/tests/test_base.py
${PYSITELIB}/pandas/tests/test_base.pyc
${PYSITELIB}/pandas/tests/test_base.pyo
Update pandas to 0.12.0. This is a major release from 0.11.0 and includes several new features and enhancements along with a large number of bug fixes. Highlites include a consistent I/O API naming scheme, routines to read html, write multi-indexes to csv files, read & write STATA data files, read & write JSON format files, Python 3 support for HDFStore, filtering of groupby expressions via filter, and a revamped replace routine that accepts regular expressions. For detailed changes see: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2013-12-10 14:00:30 +01:00
${PYSITELIB}/pandas/tests/test_categorical.py
${PYSITELIB}/pandas/tests/test_categorical.pyc
${PYSITELIB}/pandas/tests/test_categorical.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tests/test_common.py
${PYSITELIB}/pandas/tests/test_common.pyc
${PYSITELIB}/pandas/tests/test_common.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/tests/test_compat.py
${PYSITELIB}/pandas/tests/test_compat.pyc
${PYSITELIB}/pandas/tests/test_compat.pyo
Update pandas to 0.10.0. pkgsrc change: depend on math/py-pytables. Changes since 0.9.1: * Delimited file parsing engine rewritten to use a fraction of memory while being 40%+ faster. - Much-improved Unicode handling via the encoding option. - Column filtering (usecols) - Dtype specification (dtype argument) - Ability to specify strings to be recognized as True/False - Ability to yield NumPy record arrays (as_recarray) - High performance delim_whitespace option - Decimal format (e.g. European format) specification - Easier CSV dialect options: escapechar, lineterminator, quotechar, etc. - More robust handling of many exceptional kinds of files observed in the wild * API changes - Deprecated DataFrame BINOP TimeSeries special case behavior - Altered resample default behavior - Infinity and negative infinity are no longer treated as NA by isnull and notnull. - Methods with the inplace option now all return None instead of the calling object. - pandas.merge no longer sorts the group keys (sort=False) by default. - The default column names for a file with no header have been changed. - Values like 'Yes' and 'No' are not interpreted as boolean by default. - The file parsers will not recognize non-string values arising from a converter function as NA. - Calling fillna on Series or DataFrame with no arguments is no longer valid code. - Series.apply will now operate on a returned value from the applied function. - New API functions for working with pandas options. * New features - Wide DataFrame Printing. - Updated PyTables Support. * Enhancements - added ability to hierarchical keys. - added mixed-dtype support! - performance improvments on table writing. - support for arbitrarily indexed dimensions. - SparseSeries now has a density property. * Bug fixes - added Term method of specifying where conditions. - del store['df'] now call store.remove('df') for store deletion. - deleting of consecutive rows is much faster than before. - in_itemsize parameter can be specified in table creation to force a minimum size for indexing columns. - indexing support via create_table_index (requires PyTables >= 2.3) - appending on a store would fail if the table was not first created via put. - fixed issue with missing attributes after loading a pickled dataframe. - minor change to select and remove: require a table ONLY if where is also provided. * Compatibility - 0.10 of HDFStore is backwards compatible for reading tables created in a prior version of pandas, however, query terms using the prior (undocumented) methodology are unsupported. * N Dimensional Panels (Experimental)
2013-01-08 00:18:35 +01:00
${PYSITELIB}/pandas/tests/test_config.py
${PYSITELIB}/pandas/tests/test_config.pyc
${PYSITELIB}/pandas/tests/test_config.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/test_downstream.py
${PYSITELIB}/pandas/tests/test_downstream.pyc
${PYSITELIB}/pandas/tests/test_downstream.pyo
${PYSITELIB}/pandas/tests/test_errors.py
${PYSITELIB}/pandas/tests/test_errors.pyc
${PYSITELIB}/pandas/tests/test_errors.pyo
Update py-pandas to 0.11.0. Summary of changes since 0.10.1: This is a major release from 0.10.1 and includes many new features and enhancements along with a large number of bug fixes. The methods of Selecting Data have had quite a number of additions, and Dtype support is now full-fledged. There are also a number of important API changes that long-time pandas users should pay close attention to. * 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. * Improved DataFrame to CSV exporting performance. For a full list refer to the "what's new" page. Also fixes PLIST errors introduced in last update.
2013-05-17 01:10:16 +02:00
${PYSITELIB}/pandas/tests/test_expressions.py
${PYSITELIB}/pandas/tests/test_expressions.pyc
${PYSITELIB}/pandas/tests/test_expressions.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/test_join.py
${PYSITELIB}/pandas/tests/test_join.pyc
${PYSITELIB}/pandas/tests/test_join.pyo
Update py-pandas to 0.16.2. Closes PR pkg/49958 by matthewd. Changes since 0.14.1 for a full list see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html: v 0.16.2 This is a minor bug-fix release from 0.16.1 and includes a a large number of bug fixes along some new features (pipe() method), enhancements, and performance improvements. We recommend that all users upgrade to this version. Highlights include: A new pipe method Documentation on how to use numba with pandas, v 0.16.1 This is a minor bug-fix release from 0.16.0 and includes a a large number of bug fixes along several new features, enhancements, and performance improvements. We recommend that all users upgrade to this version. Highlights include: 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 Further enhancement to the .str accessor to make string operations easier v0.16.0 (March 22, 2015) This is a major release from 0.15.2 and includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: 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, see here v0.15.0 (October 18, 2014) This is a major release from 0.14.1 and includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Warning pandas >= 0.15.0 will no longer support compatibility with NumPy versions < 1.7.0. If you want to use the latest versions of pandas, please upgrade to NumPy >= 1.7.0 (GH7711) Highlights include: The Categorical type was integrated as a first-class pandas type New scalar type Timedelta, and a new index type TimedeltaIndex New datetimelike properties accessor .dt for Series, see Datetimelike Properties New DataFrame default display for df.info() to include memory usage, see Memory Usage read_csv will now by default ignore blank lines when parsing API change in using Indexes in set operations Enhancements in the handling of timezones A lot of improvements to the rolling and expanding moment funtions Internal refactoring of the Index class to no longer sub-class ndarray, see Internal Refactoring dropping support for PyTables less than version 3.0.0, and numexpr less than version 2.1 (GH7990) Split indexing documentation into Indexing and Selecting Data and MultiIndex / Advanced Indexing Split out string methods documentation into Working with Text Data
2015-07-21 21:44:45 +02:00
${PYSITELIB}/pandas/tests/test_lib.py
${PYSITELIB}/pandas/tests/test_lib.pyc
${PYSITELIB}/pandas/tests/test_lib.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tests/test_multilevel.py
${PYSITELIB}/pandas/tests/test_multilevel.pyc
${PYSITELIB}/pandas/tests/test_multilevel.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/tests/test_nanops.py
${PYSITELIB}/pandas/tests/test_nanops.pyc
${PYSITELIB}/pandas/tests/test_nanops.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tests/test_panel.py
${PYSITELIB}/pandas/tests/test_panel.pyc
${PYSITELIB}/pandas/tests/test_panel.pyo
Update pandas to 0.10.0. pkgsrc change: depend on math/py-pytables. Changes since 0.9.1: * Delimited file parsing engine rewritten to use a fraction of memory while being 40%+ faster. - Much-improved Unicode handling via the encoding option. - Column filtering (usecols) - Dtype specification (dtype argument) - Ability to specify strings to be recognized as True/False - Ability to yield NumPy record arrays (as_recarray) - High performance delim_whitespace option - Decimal format (e.g. European format) specification - Easier CSV dialect options: escapechar, lineterminator, quotechar, etc. - More robust handling of many exceptional kinds of files observed in the wild * API changes - Deprecated DataFrame BINOP TimeSeries special case behavior - Altered resample default behavior - Infinity and negative infinity are no longer treated as NA by isnull and notnull. - Methods with the inplace option now all return None instead of the calling object. - pandas.merge no longer sorts the group keys (sort=False) by default. - The default column names for a file with no header have been changed. - Values like 'Yes' and 'No' are not interpreted as boolean by default. - The file parsers will not recognize non-string values arising from a converter function as NA. - Calling fillna on Series or DataFrame with no arguments is no longer valid code. - Series.apply will now operate on a returned value from the applied function. - New API functions for working with pandas options. * New features - Wide DataFrame Printing. - Updated PyTables Support. * Enhancements - added ability to hierarchical keys. - added mixed-dtype support! - performance improvments on table writing. - support for arbitrarily indexed dimensions. - SparseSeries now has a density property. * Bug fixes - added Term method of specifying where conditions. - del store['df'] now call store.remove('df') for store deletion. - deleting of consecutive rows is much faster than before. - in_itemsize parameter can be specified in table creation to force a minimum size for indexing columns. - indexing support via create_table_index (requires PyTables >= 2.3) - appending on a store would fail if the table was not first created via put. - fixed issue with missing attributes after loading a pickled dataframe. - minor change to select and remove: require a table ONLY if where is also provided. * Compatibility - 0.10 of HDFStore is backwards compatible for reading tables created in a prior version of pandas, however, query terms using the prior (undocumented) methodology are unsupported. * N Dimensional Panels (Experimental)
2013-01-08 00:18:35 +01:00
${PYSITELIB}/pandas/tests/test_panel4d.py
${PYSITELIB}/pandas/tests/test_panel4d.pyc
${PYSITELIB}/pandas/tests/test_panel4d.pyo
${PYSITELIB}/pandas/tests/test_panelnd.py
${PYSITELIB}/pandas/tests/test_panelnd.pyc
${PYSITELIB}/pandas/tests/test_panelnd.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/test_resample.py
${PYSITELIB}/pandas/tests/test_resample.pyc
${PYSITELIB}/pandas/tests/test_resample.pyo
${PYSITELIB}/pandas/tests/test_sorting.py
${PYSITELIB}/pandas/tests/test_sorting.pyc
${PYSITELIB}/pandas/tests/test_sorting.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tests/test_strings.py
${PYSITELIB}/pandas/tests/test_strings.pyc
${PYSITELIB}/pandas/tests/test_strings.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/tests/test_take.py
${PYSITELIB}/pandas/tests/test_take.pyc
${PYSITELIB}/pandas/tests/test_take.pyo
${PYSITELIB}/pandas/tests/test_window.py
${PYSITELIB}/pandas/tests/test_window.pyc
${PYSITELIB}/pandas/tests/test_window.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/tools/__init__.py
${PYSITELIB}/pandas/tests/tools/__init__.pyc
${PYSITELIB}/pandas/tests/tools/__init__.pyo
${PYSITELIB}/pandas/tests/tools/test_numeric.py
${PYSITELIB}/pandas/tests/tools/test_numeric.pyc
${PYSITELIB}/pandas/tests/tools/test_numeric.pyo
${PYSITELIB}/pandas/tests/tseries/__init__.py
${PYSITELIB}/pandas/tests/tseries/__init__.pyc
${PYSITELIB}/pandas/tests/tseries/__init__.pyo
py-pandas: updated to 0.21.0 v0.21.0 Final: This is a major release from 0.20.3 and includes a number of API changes, deprecations, new features, enhancements, and performance improvements along with a large number of bug fixes. We recommend that all users upgrade to this version. Highlights include: * Integration with Apache Parquet, including a new top-level read_parquet function and DataFrame.to_parquet method, see here. * New user-facing dtype 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
2017-11-02 10:41:38 +01:00
${PYSITELIB}/pandas/tests/tseries/conftest.py
${PYSITELIB}/pandas/tests/tseries/conftest.pyc
${PYSITELIB}/pandas/tests/tseries/conftest.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tests/tseries/data/cday-0.14.1.pickle
${PYSITELIB}/pandas/tests/tseries/data/dateoffset_0_15_2.pickle
${PYSITELIB}/pandas/tests/tseries/test_frequencies.py
${PYSITELIB}/pandas/tests/tseries/test_frequencies.pyc
${PYSITELIB}/pandas/tests/tseries/test_frequencies.pyo
${PYSITELIB}/pandas/tests/tseries/test_holiday.py
${PYSITELIB}/pandas/tests/tseries/test_holiday.pyc
${PYSITELIB}/pandas/tests/tseries/test_holiday.pyo
${PYSITELIB}/pandas/tests/tseries/test_offsets.py
${PYSITELIB}/pandas/tests/tseries/test_offsets.pyc
${PYSITELIB}/pandas/tests/tseries/test_offsets.pyo
${PYSITELIB}/pandas/tests/tseries/test_timezones.py
${PYSITELIB}/pandas/tests/tseries/test_timezones.pyc
${PYSITELIB}/pandas/tests/tseries/test_timezones.pyo
${PYSITELIB}/pandas/tests/util/__init__.py
${PYSITELIB}/pandas/tests/util/__init__.pyc
${PYSITELIB}/pandas/tests/util/__init__.pyo
${PYSITELIB}/pandas/tests/util/test_hashing.py
${PYSITELIB}/pandas/tests/util/test_hashing.pyc
${PYSITELIB}/pandas/tests/util/test_hashing.pyo
${PYSITELIB}/pandas/tests/util/test_testing.py
${PYSITELIB}/pandas/tests/util/test_testing.pyc
${PYSITELIB}/pandas/tests/util/test_testing.pyo
${PYSITELIB}/pandas/tests/util/test_util.py
${PYSITELIB}/pandas/tests/util/test_util.pyc
${PYSITELIB}/pandas/tests/util/test_util.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tools/__init__.py
${PYSITELIB}/pandas/tools/__init__.pyc
${PYSITELIB}/pandas/tools/__init__.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tools/hashing.py
${PYSITELIB}/pandas/tools/hashing.pyc
${PYSITELIB}/pandas/tools/hashing.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tools/merge.py
${PYSITELIB}/pandas/tools/merge.pyc
${PYSITELIB}/pandas/tools/merge.pyo
${PYSITELIB}/pandas/tools/plotting.py
${PYSITELIB}/pandas/tools/plotting.pyc
${PYSITELIB}/pandas/tools/plotting.pyo
${PYSITELIB}/pandas/tseries/__init__.py
${PYSITELIB}/pandas/tseries/__init__.pyc
${PYSITELIB}/pandas/tseries/__init__.pyo
${PYSITELIB}/pandas/tseries/api.py
${PYSITELIB}/pandas/tseries/api.pyc
${PYSITELIB}/pandas/tseries/api.pyo
${PYSITELIB}/pandas/tseries/converter.py
${PYSITELIB}/pandas/tseries/converter.pyc
${PYSITELIB}/pandas/tseries/converter.pyo
${PYSITELIB}/pandas/tseries/frequencies.py
${PYSITELIB}/pandas/tseries/frequencies.pyc
${PYSITELIB}/pandas/tseries/frequencies.pyo
Update math/py-pandas to 0.14.1. This is two major releases since 0.12.0. Changes include API changes, new features, enhancements, and performance improvements along with a large number of bug fixes. For the detailed list of changes see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
2014-07-19 15:17:46 +02:00
${PYSITELIB}/pandas/tseries/holiday.py
${PYSITELIB}/pandas/tseries/holiday.pyc
${PYSITELIB}/pandas/tseries/holiday.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/tseries/offsets.py
${PYSITELIB}/pandas/tseries/offsets.pyc
${PYSITELIB}/pandas/tseries/offsets.pyo
${PYSITELIB}/pandas/tseries/plotting.py
${PYSITELIB}/pandas/tseries/plotting.pyc
${PYSITELIB}/pandas/tseries/plotting.pyo
${PYSITELIB}/pandas/tseries/util.py
${PYSITELIB}/pandas/tseries/util.pyc
${PYSITELIB}/pandas/tseries/util.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/tslib.py
${PYSITELIB}/pandas/tslib.pyc
${PYSITELIB}/pandas/tslib.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/types/__init__.py
${PYSITELIB}/pandas/types/__init__.pyc
${PYSITELIB}/pandas/types/__init__.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/types/common.py
${PYSITELIB}/pandas/types/common.pyc
${PYSITELIB}/pandas/types/common.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/types/concat.py
${PYSITELIB}/pandas/types/concat.pyc
${PYSITELIB}/pandas/types/concat.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/util/__init__.py
${PYSITELIB}/pandas/util/__init__.pyc
${PYSITELIB}/pandas/util/__init__.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/util/_decorators.py
${PYSITELIB}/pandas/util/_decorators.pyc
${PYSITELIB}/pandas/util/_decorators.pyo
${PYSITELIB}/pandas/util/_depr_module.py
${PYSITELIB}/pandas/util/_depr_module.pyc
${PYSITELIB}/pandas/util/_depr_module.pyo
${PYSITELIB}/pandas/util/_doctools.py
${PYSITELIB}/pandas/util/_doctools.pyc
${PYSITELIB}/pandas/util/_doctools.pyo
Update py-pandas to 0.18.1 Highlights in changelog: v0.18.1: .groupby(...) has been enhanced to provide convenient syntax when working with .rolling(..), .expanding(..) and .resample(..) per group, see here pd.to_datetime() has gained the ability to assemble dates from a DataFrame, see here Method chaining improvements, see here. Custom business hour offset, see here. Many bug fixes in the handling of sparse, see here Expanded the Tutorials section with a feature on modern pandas, courtesy of @TomAugsburger. (GH13045). v0.18.0: Moving and expanding window functions are now methods on Series and DataFrame, similar to .groupby, see here. Adding support for a RangeIndex as a specialized form of the Int64Index for memory savings, see here. API breaking change to the .resample method to make it more .groupby like, see here. Removal of support for positional indexing with floats, which was deprecated since 0.14.0. This will now raise a TypeError, see here. The .to_xarray() function has been added for compatibility with the xarray package, see here. The read_sas function has been enhanced to read sas7bdat files, see here. 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). Update by K.I.A.Derouiche in PR pkg/51272 Slightly modified.
2016-08-16 05:22:12 +02:00
${PYSITELIB}/pandas/util/_move.so
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/util/_print_versions.py
${PYSITELIB}/pandas/util/_print_versions.pyc
${PYSITELIB}/pandas/util/_print_versions.pyo
${PYSITELIB}/pandas/util/_tester.py
${PYSITELIB}/pandas/util/_tester.pyc
${PYSITELIB}/pandas/util/_tester.pyo
${PYSITELIB}/pandas/util/_validators.py
${PYSITELIB}/pandas/util/_validators.pyc
${PYSITELIB}/pandas/util/_validators.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/util/decorators.py
${PYSITELIB}/pandas/util/decorators.pyc
${PYSITELIB}/pandas/util/decorators.pyo
Changes 0.20.1: New .agg() API for Series/DataFrame similar to the groupby-rolling-resample API’s, see here Integration with the feather-format, including a new top-level pd.read_feather() and DataFrame.to_feather() method, see here. The .ix indexer has been deprecated, see here Panel has been deprecated, see here Addition of an IntervalIndex and Interval scalar type, see here Improved user API when grouping by index levels in .groupby(), see here Improved support for UInt64 dtypes, see here 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, see here Experimental support for exporting styled DataFrames (DataFrame.style) to Excel, see here Window binary corr/cov operations now return a MultiIndexed DataFrame rather than a Panel, as Panel is now deprecated, see here Support for S3 handling now uses s3fs, see here Google BigQuery support now uses the pandas-gbq library, see here
2017-05-21 10:54:33 +02:00
${PYSITELIB}/pandas/util/hashing.py
${PYSITELIB}/pandas/util/hashing.pyc
${PYSITELIB}/pandas/util/hashing.pyo
Initial import of pandas 0.9.1. pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.
2012-11-22 01:15:13 +01:00
${PYSITELIB}/pandas/util/testing.py
${PYSITELIB}/pandas/util/testing.pyc
${PYSITELIB}/pandas/util/testing.pyo
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