Pandas DataFrame: memory_usage() function

Last update on August 19 2022 21:50:52 (UTC/GMT +8 hours)

DataFrame - memory_usage() function

The memory_usage function is used to get the memory usage of each column in bytes.

The memory usage can optionally include the contribution of the index and elements of object dtype.

This value is displayed in DataFrame.info by default. This can be suppressed by setting pandas.options.display.memory_usage to False.

Syntax:

DataFrame.memory_usage(self, index=True, deep=False)

Parameters:

Name	Description	Type/Default Value	Required / Optional
index	Specifies whether to include the memory usage of the DataFrame’s index in returned Series. If index=True, the memory usage of the index is the first item in the output.	bool Default Value: True	Required
deep	If True, introspect the data deeply by interrogating object dtypes for system-level memory consumption, and include it in the returned values.	bool Default Value: False	Required

Returns: Series
A Series whose index is the original column names and whose values is the memory usage of each column in bytes.

Example:

Download the Pandas DataFrame Notebooks from here.

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