(Belatedly) chasing some threatening pandas deprecations... #485
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This was referenced Mar 18, 2024
3 tasks
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
sep=r's\+': DEPR: read_csv keywords: keep_date_col, delim_whitespace pandas-dev/pandas#57480df.loc[:, col] = df2.loc[:, col]is set to fail if it would change the type of df[col]. Seems the preferred (if potentially ambiguous) approach now is to createcola fresh new column withdf[col] = df2.loc[:, col].pd.to_numeric()casting. DEPR: deprecate errors='ignore' in to_datetime and make output dtype predictable pandas-dev/pandas#54467. But I think we can "coerce" and thenfillna()with the original values.