API/DEPR: Deprecate inplace parameter

[gfyoung]

The parameter inplace=False should be deprecated across the board in preparation for pandas 2, which will not support that input (we will always return a copy). That would give people time to stop using it.

Thoughts?

Methods using inplace:

Deprecation non controvertial (a copy will be made anyway, and inplace=True does not add value):

• (Series/DataFrame).drop
• (Series/DataFrame).drop_duplicates
• (Series/DataFrame).dropna
• DataFrame.set_index (with drop=False wouldn't change the data, but that doesn't seem the main use case)
• DataFrame.query
• DataFrame.eval

Not sure:

• (Series/DataFrame).sort_values
• (Series/DataFrame).sort_index

Should be able to not copy memory (under discussion on what to do):

• (Series/DataFrame).clip
• (Series/DataFrame).where
• (Series/DataFrame).fillna
• (Series/DataFrame).rename_axis
• (Series/DataFrame).reset_index
• (Series/DataFrame).replace
• (Series/DataFrame).set_axis
• (Series/DataFrame).mask
• (Series/DataFrame).interpolate
• DataFrame.rename
• Index.rename
• Index.set_names
• MultiIndex.set_levels
• MultiIndex.set_labels
• pandas.core.resample.Resampler.interpolate

Special cases:

• pandas.eval (with inplace=False the value is not returned but set to an argument target)

[drafter250]

I thought The main usage of this feature was to mitigate memory usage in case of large DataFrames?

[gfyoung]

I thought The main usage of this feature was to mitigate memory usage in case of large DataFrames?

I think @jreback might know more about the initial usage, but generally from previous discussion, this parameter is misused and is more prone to introducing bugs.

[jreback]

inplace does not generally do anything inplace
but makes a copy and reassigns the pointer

mutating code is much harder to debug (not to mentiin more complicated to support actual inplace ops)

so except for inplace indexing generally these operations are simply more verbose and serve just to provide corner cases for testing