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.
Python3
# 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.
Python3 1==
# 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.
Python3
# 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.
Python3 1==
# 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.
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