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.