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_decreasing attribute return True if the underlying data in the given Index object is monotonically decreasing else it return False.
Syntax: Index.is_monotonic_decreasing
Parameter : None
Returns : boolean
Example #1: Use Index.is_monotonic_decreasing attribute to find out if the underlying data in the given Index object is monotonically decreasing or not.
# importing pandas as pd import pandas as pd   # Creating the index idx = pd.Index([900, 700, 620, 388, 24])   # Print the index print(idx) |
Output :
Now we will use Index.is_monotonic_decreasing attribute to find out if the underlying data in the given Index object is monotonically decreasing or not.
# check if the values in the Index # are monotonically decreasing result = idx.is_monotonic_decreasing   # Print the result print(result) |
Output :
As we can see in the output, the Index.is_monotonic_decreasing attribute has returned True indicating that the underlying data of the given Index object is monotonically decreasing.
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Example #2 : Use Index.is_monotonic_decreasing attribute to find out if the underlying data in the given Index object is monotonically decreasing 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) |
Output :
Now we will use Index.is_monotonic_decreasing attribute to find out if the underlying data in the given Index object is monotonically decreasing or not.
# check if the values in the Index # are monotonically decreasing result = idx.is_monotonic_decreasing   # Print the result print(result) |
Output :
As we can see in the output, the Index.is_monotonic_decreasing attribute has returned False indicating that the underlying data of the given Index object is not monotonically decreasing.
