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Python | Pandas Index.ndim

Last Updated : 20 Feb, 2019
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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.ndim attribute return the number of dimensions of the underlying data in the given Index object. By definition it is 1.

Syntax: Index.ndim

Parameter : None

Returns : number of dimensions

Example #1: Use Index.ndim attribute to find out the number of dimensions 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', 'Rio'])
  
# Print the index
print(idx)


Output :

Now we will use Index.ndim attribute to find out the number of dimensions of the underlying data in the given Index object.




# return the number of dimensions
result = idx.ndim
  
# Print the result
print(result)


Output :

As we can see in the output, the Index.ndim attribute has returned 1, indicating that the dimension of the underlying data in the given Index object is 1.
 
Example #2 : Use Index.ndim attribute to find out the number of dimensions 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.ndim attribute to find out the number of dimensions of the underlying data in the given Index object.




# return the number of dimensions
result = idx.ndim
  
# Print the result
print(result)


Output :

As we can see in the output, the Index.ndim attribute has returned 1, indicating that the dimension of the underlying data in the given Index object is 1.



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