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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]
Updated on: 18-Oct-2021
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