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DataFrame.reset_index is what you're looking for. If you don't want it saved as a column, then do: df = df.reset_index(drop=True) If you don't want to reassign: df.reset_index(drop=True, inplace=True)
DataFrame.reset_index(level=None, *, drop=False, inplace=False, col_level=0, col_fill='', allow_duplicates=<no_default>, names=None)[source] #. Reset the index, or a level of it. Reset the index of the DataFrame, and use the default one instead.
13 mar 2023 · Luckily, Pandas offers a powerful feature that allows you to selectively reset certain levels of your DataFrame’s multi-index, known as the level= parameter. By using thelevel=parameter, you can target specific index levels and reset only those levels while leaving other levels unchanged.
pandas.DataFrame.set_index #. DataFrame.set_index(keys, *, drop=True, append=False, inplace=False, verify_integrity=False)[source] #. Set the DataFrame index using existing columns. Set the DataFrame index (row labels) using one or more existing columns or arrays (of the correct length).
27 cze 2024 · Learn the pandas reset_index () method to reset the index of a DataFrame. Explore the different options available with this method and how to reset the index for simple and multi-level DataFrame.
30 lis 2023 · Reset Index Syntax. Syntax : DataFrame.reset_index (level=None, drop=False, inplace=False, col_level=0, col_fill=”) Parameters: level: Specifies multi-level index levels to reset. drop: Discards current index if True; adds as a new column if False. inplace: Modifies DataFrame in place if True; returns a new DataFrame if False.
In fact, since set_axis() assigns a new object to the index, i.e. resets the index, it can be used instead of reset_index(). It is especially useful if you need to make the index to start from 1 in a pipeline (where assigning or incrementing index wouldn't work).
