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Version 2.0 Compatibility Tracker #624
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Is the cut-off for removal of support for 1.5 effectively immediately? For instance, there are bugs constantly being fixed in the annotations, and so I currently stay up-to-date on the version. However I don't know if I'll be able to easily upgrade to 2.0 without breaking anything, and so I'd probably defer that upgrade. It seems 2.0 brings a fair amount of backwards-incompatible changes. |
Yes. The idea is that we want to encourage people to use the 2.0 API. I think that the 2.0 stubs (when released) will still work with 1.5 code, and, if not, they are telling you places in your code that you should change in order to be compatible with 2.0 in the future. As an example, anything that was deprecated in 1.5 was already removed from the stubs. |
…nt to `Series.add_suffix(), DataFrame.add_suffix(), Series.add_prefix() and DataFrame.add_prefix()` (#638) * added arguments * changed axis parameters * req changes and created a different overload and corrected index args * creating overloads * Update frame.pyi * corrected diff overload args * added the tests * corrected the tests * Update test_series.py
@Dr-Irv i think you can mark this |
Thanks. I've done that update |
What is actually needed to be done to disallow non-keyword arguments? Most of the stubs already have the If so I can take those over. |
It's a mix of using PR's are welcome. Maybe do one function so we can agree on the approach, then you can expand it to others. |
This is the list of things that are in pandas 2.0 release notes that need to be addressed in pandas-stubs. PR's welcome. If you do a PR, check off the item and put a link to the PR that closed it. One PR can address multiple issues.
Some of these may already have been taken care of, so if so, check them off and indicate with a comment such as "previously complete"
dtype_backend
to allread_*
functions #655dtype
arg toread_sql
#649Added support for str accessor methods when using ArrowDtype with a pyarrow.string typeAdded support for dt accessor methods when using ArrowDtype with a pyarrow.timestamp typeread_sas() now supports using encoding='infer' to correctly read and use the encoding specified by the sas file.index
parameter toto_dict
and addedaxis
argument toSeries.add_suffix(), DataFrame.add_suffix(), Series.add_prefix() and DataFrame.add_prefix()
#638index
parameter toto_dict
and addedaxis
argument toSeries.add_suffix(), DataFrame.add_suffix(), Series.add_prefix() and DataFrame.add_prefix()
#638mode
keyword toDataFrame.to_json
#684Added name parameter to IntervalIndex.from_breaks(), IntervalIndex.from_arrays() and IntervalIndex.from_tuples()ignore_index
keyword arg indropna
anddrop_duplicates
(Part of GH624) #1030ignore_index
keyword arg indropna
anddrop_duplicates
(Part of GH624) #1030dtype
arg toread_sql
#649date_format
toread_table
,read_fwf
andread_excel
#695pd.Series()
)Added "None" to default na_values in read_csv()GH: 624 - added newis_any_real_numeric_dtype
function #715is_any_real_numeric_dtype
function #715date_format
toread_table
,read_fwf
andread_excel
#695Deprecated Grouper.grouper()Deprecated Grouper.obj()Deprecated Grouper.indexer()Deprecated Grouper.ax()index
parameter toto_dict
and addedaxis
argument toSeries.add_suffix(), DataFrame.add_suffix(), Series.add_prefix() and DataFrame.add_prefix()
#638Change the default argument of regex for Series.str.replace() from True to FalseChanged default of numeric_only to False in all DataFrame methods with that argumentChanged default of numeric_only to False in [Series.rank()](https://pandas.pydata.org/docs/reference/api/pandas.Series.rank.html#pandas.Series.rank)Removed deprecated methods ExcelWriter.write_cells(), ExcelWriter.save(), ExcelWriter.cur_sheet(), ExcelWriter.handles(), ExcelWriter.path()The ExcelWriter attribute book can no longer be setRemoved the deprecated argument line_terminator from DataFrame.to_csv()Removed the deprecated argument label from lreshape()Arguments after expr in DataFrame.eval() and DataFrame.query() are keyword-onlyRemoved Index._get_attributes_dict()The text was updated successfully, but these errors were encountered: