Python | Pandas Index.memory_usage ()



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.