Pandas DataFrame: drop() function

Last update on August 19 2022 21:50:51 (UTC/GMT +8 hours)

DataFrame - drop() function

The drop() function is used to drop specified labels from rows or columns.

Remove rows or columns by specifying label names and corresponding axis, or by specifying directly index or column names. When using a multi-index, labels on different levels can be removed by specifying the level.

Syntax:

DataFrame.drop(self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise')

Parameters:

Name	Description	Type/Default Value	Required / Optional
labels	Index or column labels to drop.	single label or list-like	Required
axis	Whether to drop labels from the index (0 or ‘index’) or columns (1 or ‘columns’).	{0 or ‘index’, 1 or ‘columns’} Default Value: 0	Required
index	Alternative to specifying axis (labels, axis=0 is equivalent to index=labels).	single label or list-like	Required
columns	Alternative to specifying axis (labels, axis=1 is equivalent to columns=labels).	single label or list-like	Required
level	For MultiIndex, level from which the labels will be removed.	int or level name	Optional
inplace	If True, do operation inplace and return None.	bool Default Value: False	Required
errors	If ‘ignore’, suppress error and only existing labels are dropped.	{‘ignore’, ‘raise’} Default Value: ‘raise’	Required

Returns: DataFrame
DataFrame without the removed index or column labels.

Raises: KeyError
If any of the labels is not found in the selected axis.

Example:

Download the Pandas DataFrame Notebooks from here.

Previous: DataFrame - between_time() function
Next: DataFrame - equals() function