Python | Pandas Index.memory_usage ()

Arrays | Python Methods and Functions | String Variables

Index.memory_usage() Pandas Index.memory_usage() returns the memory usage of an index. Returns the amount of memory used by all individual tags present in the index.

Syntax: Index.memory_usage (deep = False)

Parameters:
deep: Introspect the data deeply, interrogate object dtypes for system-level memory consumption

Returns: bytes used

Example # 1: Use Index.memory_usage () to find the total memory used by the Index.

# import pandas as pd

import pandas as pd

 
# Create index

idx = pd.Index ([ 'Labrador' , 'Beagle' , 'Mastiff' , ' Lhasa' , 'Husky' , ' Beagle' ])

 
# Print index
idx

Exit :

Now we will use Index.memory_usage () to find the memory usage of the idx object.

# find memory used by idx
idx.memory_usage ()  

Output:

The function returned 48, indicating that 48 bytes of memory are being used.

Example # 2: Use Index.memory_usage () to check the memory usage of a MultiIndex object.

# import pandas as pd

import pandas as pd

  
# Create MutiIndex

midx = pd.MultiIndex.from_arrays ([[ ' Mon' , 'Tue' , ' Wed' < code class = "plain">, 'Thr' ], [ 10 , 20 , 30 , 40 ]],

names = ( ' Days' , 'Target' ))

 
# Print MultiIndex
midx

Output:

Now we check the amount of memory used by midx.

# return the total amount of memory used by the multi-index object
midx.memory_usage ()

Output:

As we can see in the output, the function returned 180, indicating that the midx object is using 180 bytes of memory.





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