How can i classify and handle pandas drop duplicate columns

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Thanks for sharing this very interesting question! Finding and removing duplicate column names can be a challenge with large data. As you said, pivot, pivot_table, Snow Rider, and corr can help in certain cases, but to identify duplicate columns in both name and value, I think you should try a more efficient approach by using df.columns.duplicated() to detect duplicate columns in name, then compare the values ​​of these columns to remove them. Optimizing with these methods will help to process large data faster.

In some cases, you may have columns fall guys with the same name but with an additional prefix (like _duplicate or _1), and you want to treat them as a group. To handle this, you can normalize the column names and then work with these columns.