Pandas DataFrame: set_index() function

Last update on August 19 2022 21:50:33 (UTC/GMT +8 hours)

DataFrame - set_index() function

The set_index() function is used to 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. The index can replace the existing index or expand on it.

Syntax:

DataFrame.set_index(self, keys, drop=True, append=False, inplace=False, verify_integrity=False)

Parameters:

Name	Description	Type / Default Value	Required / Optional
keys	This parameter can be either a single column key, a single array of the same length as the calling DataFrame, or a list containing an arbitrary combination of column keys and arrays. Here, “array” encompasses Series,Index, np.ndarray, and instances of Iterator.	label or array-like or list of labels/arrays	Required
drop	Delete columns to be used as the new index.	bool Default Value: True	Required
append	Whether to append columns to existing index.	bool Default Value: False	Required
inplace	Modify the DataFrame in place (do not create a new object).	bool Default Value: False	Required
verify_integrity	Check the new index for duplicates. Otherwise defer the check until necessary. Setting to False will improve the performance of this method.	bool Default Value: False	Required

Returns: DataFrame
Changed row labels.

Example:

Download the Pandas DataFrame Notebooks from here.

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