Pandas DataFrame memory_usage() Method
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.
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