BUG: DataFrame.drop_duplicates method fails when a column with a list… #56958
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| To handle mutable objects such as list, convert the list column | ||
| to a tuple before using it in the subset. |
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This does not handle all cases. I think the note should start with something more general like:
This method requires data in the columns to be hashable.
| ... ]) | ||
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| >>> df['item_ids'] = df['item_ids'].apply(tuple) | ||
| >>> df.drop_duplicates(inplace=True) |
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The inplace argument should be going away (hopefully soon); it should not be used here.
| >>> df['item_ids'] = df['item_ids'].apply(list) | ||
| number item_ids | ||
| 0 1 [1, 2, 3] |
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This line doesn't produce any output. If you want to show output, you can make it just df['items_ids'].apply(list) instead of assigning it back to the column.
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Thank you so much for your suggestions @rhshadrach I'll make changes accordingly. |
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This pull request is stale because it has been open for thirty days with no activity. Please update and respond to this comment if you're still interested in working on this. |
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This PR has gone stale. @manlattan - if you are interested in continuing, just comment here and we're happy to reopen! |
resolved #56784 in the file pandas/core/frame.py