Python | Pandas Index.inferred_type

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.inferred_type attribute return a string of the data type inferred from the values of the given Index object.

Syntax: Index.inferred_type



Parameter : None

Returns : inferred_type

Example #1: Use Index.inferred_type attribute to find out the inferred data type of the value in the given Index object.

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# importing pandas as pd
import pandas as pd
  
# Creating the index
idx = pd.Index(['Jan', 'Feb', 'Mar', 'Apr', 'May'])
  
# Print the index
print(idx)

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Output :

Index(['Jan', 'Feb', 'Mar', 'Apr', 'May'], dtype='object')

Now we will use Index.inferred_type attribute to find out the inferred dtype of the underlying data of the given Index object.

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# return the inferred dtype
result = idx.inferred_type
  
# Print the result
print(result)

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Output :

mixed

As we can see in the output, the Index.inferred_type attribute has returned String as the inferred data type of the given Index object.

Example #2 : Use Index.inferred_type attribute to find out the inferred data type of the value in the given Index object.

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# importing pandas as pd
import pandas as pd
  
# Creating the index
idx = pd.Index(['2012-12-12', None, '2002-1-10', None])
  
# Print the index
print(idx)

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Output :

Index(['2012-12-12', None, '2002-1-10', None], dtype='object')

Now we will use Index.inferred_type attribute to find out the inferred dtype of the underlying data of the given Index object.

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# return the inferred dtype
result = idx.inferred_type
  
# Print the result
print(result)

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Output :

mixed

As we can see in the output, the Index.inferred_type attribute has returned mixed as the inferred data type of the given Index object.



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