Pandas: Create an Intervals index

Last update on May 01 2025 12:56:42 (UTC/GMT +8 hours)

5. DataFrame with Interval Index

Write a Pandas program to create a DataFrame using intervals as an index.

IntervalIndex represents an Index of Interval objects that are all closed on the same side.
pandas.IntervalIndex.from_breaks: Construct an IntervalIndex from an array of splits
pandas.IntervalIndex.from_tuples: Construct an IntervalIndex from a list/array of tuples
pandas.IntervalIndex.from_arrays: Construct from two arrays defining the left and right bounds.

Sample Solution:

Python Code :

import pandas as pd
print("Create an Interval Index using IntervalIndex.from_breaks:")
df_interval = pd.DataFrame({"X":[1, 2, 3, 4, 5, 6, 7]},
                            index = pd.IntervalIndex.from_breaks(
                            [0, 0.5, 1.0, 1.5, 2.0, 2.5, 3, 3.5]))    
print(df_interval)
print(df_interval.index)

print("\nCreate an Interval Index using IntervalIndex.from_tuples:")
df_interval = pd.DataFrame({"X":[1, 2, 3, 4, 5, 6, 7]},             
                            index = pd.IntervalIndex.from_tuples(
                            [(0, .5), (.5, 1), (1, 1.5), (1.5, 2), (2, 2.5), (2.5, 3), (3, 3.5)]))
print(df_interval)
print(df_interval.index)

print("\nCreate an Interval Index using IntervalIndex.from_arrays:")
df_interval = pd.DataFrame({"X":[1, 2, 3, 4, 5, 6, 7]},             
                            index = pd.IntervalIndex.from_arrays(
                            [0, .5, 1, 1.5, 2, 2.5, 3], [.5, 1, 1.5, 2, 2.5, 3, 3.5]))
print(df_interval)
print(df_interval.index)

Sample Output:

Create an Interval Index using IntervalIndex.from_breaks:
            X
(0.0, 0.5]  1
(0.5, 1.0]  2
(1.0, 1.5]  3
(1.5, 2.0]  4
(2.0, 2.5]  5
(2.5, 3.0]  6
(3.0, 3.5]  7
IntervalIndex([(0.0, 0.5], (0.5, 1.0], (1.0, 1.5], (1.5, 2.0], (2.0, 2.5], (2.5, 3.0], (3.0, 3.5]]
              closed='right',
              dtype='interval[float64]')

Create an Interval Index using IntervalIndex.from_tuples:
            X
(0.0, 0.5]  1
(0.5, 1.0]  2
(1.0, 1.5]  3
(1.5, 2.0]  4
(2.0, 2.5]  5
(2.5, 3.0]  6
(3.0, 3.5]  7
IntervalIndex([(0.0, 0.5], (0.5, 1.0], (1.0, 1.5], (1.5, 2.0], (2.0, 2.5], (2.5, 3.0], (3.0, 3.5]]
              closed='right',
              dtype='interval[float64]')

Create an Interval Index using IntervalIndex.from_arrays:
            X
(0.0, 0.5]  1
(0.5, 1.0]  2
(1.0, 1.5]  3
(1.5, 2.0]  4
(2.0, 2.5]  5
(2.5, 3.0]  6
(3.0, 3.5]  7
IntervalIndex([(0.0, 0.5], (0.5, 1.0], (1.0, 1.5], (1.5, 2.0], (2.0, 2.5], (2.5, 3.0], (3.0, 3.5]]
              closed='right',
              dtype='interval[float64]')

For more Practice: Solve these Related Problems:

Write a Pandas program to create a DataFrame whose index is an IntervalIndex and then display its intervals.
Write a Pandas program to build a DataFrame with intervals as the index and then perform a lookup using an interval value.
Write a Pandas program to assign an IntervalIndex to a DataFrame and then compute summary statistics based on the intervals.
Write a Pandas program to generate a DataFrame with an interval index and then reset the index to convert intervals into columns.

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Python Code Editor:

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