Check elementwise if the Intervals in the IntervalIndex contain the value in Python Pandas

To return an IntervalArray identical to the current one but closed on the specified side, use the set_closed() method with parameter set as both.

At first, import the required libraries −

import pandas as pd

Create IntervalArray −

index = pd.arrays.IntervalArray.from_breaks(range(6)) 

Display the interval −

print("IntervalIndex...\n",index)

Return an IntervalArray identical to the current one but closed on specified side i.e. "both" here −

print("\nResult...",index.set_closed('both')) 

Example

Following is the code −

import pandas as pd # Create IntervalArray index = pd.arrays.IntervalArray.from_breaks(range(6)) # Display the interval print("IntervalIndex...\n",index) # Display the interval length print("\nIntervalIndex length...\n",index.length) # the left bound print("\nThe left bound for the IntervalIndex...\n",index.left) # the right bound print("\nThe right bound for the IntervalIndex...\n",index.right) # Return an IntervalArray identical to the current one but closed on specified # side i.e. "both" here print("\nResult...",index.set_closed('both'))

Output

This will produce the following output −

IntervalIndex... <IntervalArray> [(0, 1], (1, 2], (2, 3], (3, 4], (4, 5]] Length: 5, dtype: interval[int64, right] IntervalIndex length... Int64Index([1, 1, 1, 1, 1], dtype='int64') The left bound for the IntervalIndex... Int64Index([0, 1, 2, 3, 4], dtype='int64') The right bound for the IntervalIndex... Int64Index([1, 2, 3, 4, 5], dtype='int64') Result... <IntervalArray> [[0, 1], [1, 2], [2, 3], [3, 4], [4, 5]] Length: 5, dtype: interval[int64, both]