Python | Pandas Index.ndim

Python | Pandas Index.itemsize

Last Updated : 20 Feb, 2019

Pandas Index is an immutable ndarray implementing an ordered, sliceable set. It is the basic object which stores the axis labels for all pandas objects.

Pandas Index.itemsize attribute return the size of the dtype of the items of the underlying data in the given Index object.

Syntax: Index.itemsize

Parameter : None

Returns : return the size of dtype

Example #1: Use Index.itemsize attribute to find out the size of the dtype of the underlying data in the given Index object.

# importing pandas as pd 
import pandas as pd 
  
# Creating the index 
idx = pd.Index(['Melbourne', 'Sanghai', 'Lisbon', 'Doha', 'Moscow']) 
  
# Print the index 
print(idx) 

Output :

Now we will use Index.itemsize attribute to find out the size of the dtype of the underlying data in the given Index object.

# return the size of dtype 
result = idx.itemsize 
  
# Print the result 
print(result) 

Output :

As we can see in the output, the Index.itemsize attribute has returned 8, indicating that the size of the dtype of the underlying data in the index object is 8.

Example #2 : Use Index.itemsize attribute to find out the size of the dtype of the underlying data in the given Index object.

# importing pandas as pd 
import pandas as pd 
  
# Creating the index 
idx = pd.Index([900 + 3j, 700 + 25j, 620 + 10j, 388 + 44j, 900]) 
  
# Print the index 
print(idx) 

Output :

Now we will use Index.itemsize attribute to find out the size of the dtype of the underlying data in the given Index object.

# return the size of dtype 
result = idx.itemsize 
  
# Print the result 
print(result) 

Output :

As we can see in the output, the Index.itemsize attribute has returned 8, indicating that the size of the dtype of the underlying data in the index object is 8.

Python | Pandas Index.ndim

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Shubham__Ranjan

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