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.is_monotonic attribute is an alias for is_monotonic_increasing. It return True if the underlying data in the given Index object is monotonically increasing else it return False.
Syntax: Index.is_monotonic
Parameter : None
Returns : boolean
Example #1: Use Index.is_monotonic attribute to find out if the underlying data in the given Index object is monotonically increasing or not.
# importing pandas as pd import pandas as pd
# Creating the index idx = pd.Index([100, 200, 420, 888, 924])
# Print the index print(idx)
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Output :
Int64Index([100, 200, 420, 888, 924], dtype='int64')
Now we will use Index.is_monotonic attribute to find out if the underlying data in the given Index object is monotonically increasing or not.
# check if the values in the Index # are monotonically increasing result = idx.is_monotonic
# Print the result print(result)
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Output :
True
As we can see in the output, the Index.is_monotonic attribute has returned True indicating that the underlying data of the given Index object is monotonically increasing.
Example #2 : Use Index.is_monotonic attribute to find out if the underlying data in the given Index object is monotonically increasing or not.
# 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.is_monotonic attribute to find out if the underlying data in the given Index object is monotonically increasing or not.
# check if the values in the Index # are monotonically increasing result = idx.is_monotonic
# Print the result print(result)
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Output :
False
As we can see in the output, the Index.is_monotonic attribute has returned False indicating that the underlying data of the given Index object is not monotonically increasing.