Make working with "relational" or "labeled" data both easy and intuitive

Edit Package python-pandas

pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for
doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language.

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Source Files
Filename Size Changed
_constraints 0000000163 163 Bytes
_multibuild 0000000122 122 Bytes
_service 0000000605 605 Bytes
pandas-2.1.3.tar.gz 0049603896 47.3 MB
python-pandas.changes 0000215149 210 KB
python-pandas.spec 0000020536 20.1 KB
Revision 58 (latest revision is 72)
Ana Guerrero's avatar Ana Guerrero (anag+factory) accepted request 1130126 from Steve Kowalik's avatar Steve Kowalik (StevenK) (revision 58)
- Update to 2.1.3:
  * Reverted deprecation of fill_method=None in DataFrame.pct_change(),
    Series.pct_change(), DataFrameGroupBy.pct_change(), and
    SeriesGroupBy.pct_change(); the values 'backfill', 'bfill', 'pad', and
    'ffill' are still deprecated
  * Fixed regressions
    + Fixed infinite recursion from operations that return a new object on
      some DataFrame subclasses
    + Fixed regression in DataFrame.join() where result has missing values
      and dtype is arrow backed string
    + Fixed regression in rolling() where non-nanosecond index or on column
      would produce incorrect results
    + Fixed regression in DataFrame.resample() which was extrapolating back
      to origin when origin was outside its bounds
    + Fixed regression in DataFrame.sort_index() which was not sorting
      correctly when the index was a sliced MultiIndex
    + Fixed regression in DataFrameGroupBy.agg() and SeriesGroupBy.agg()
      where if the option compute.use_numba was set to True, groupby methods
      not supported by the numba engine would raise a TypeError
    + Fixed performance regression with wide DataFrames, typically
      involving methods where all columns were accessed individually
    + Fixed regression in merge_asof() raising TypeError for by with
      datetime and timedelta dtypes
    + Fixed regression in read_parquet() when reading a file with a string
      column consisting of more than 2 GB of string data and using the
      "string" dtype
    + Fixed regression in DataFrame.to_sql() not roundtripping datetime
      columns correctly for sqlite when using detect_types
    + Fixed regression in construction of certain DataFrame or Series
      subclasses
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