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Pandas DataFrame memory_usage() Method

❮ DataFrame Reference


Example

Return the memory usage of each column:

import pandas as pd

df = pd.read_csv('data.csv')

print(df.memory_usage())
Try it Yourself »

Definition and Usage

The memory_usage() method returns a Series that contains the memory usage of each column.


Syntax

dataframe.memory_usage(index, deep)

Parameters

The parameters are keyword arguments.

Parameter Value Description
index True|False Optional. Default True. Specifies whether to include the index (and its memory usage) or not
deep True|False Optional. Default False. Specifies whether to to a deep calculation of the memory usage or not. If True the systems finds the actual system-level memory consumption to do a real calculation of the memory usage (at a high computer resource cost) instead of an estimate based on dtypes and number of rows (lower cost).

Return Value

a Pandas Series showing the memory usage of each column.


❮ DataFrame Reference

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