Python Pandas - Return the midpoint of each Interval in the IntervalArray as an Index

To return the midpoint of each Interval in the IntervalArray as an Index, use the array.mid property. This property calculates the center point of each interval by taking the average of the left and right endpoints.

Syntax

IntervalArray.mid

This property returns an Index containing the midpoint values of each interval.

Creating IntervalArray

First, import the required libraries and create Interval objects ?

import pandas as pd

# Create two Interval objects
# Closed intervals set using the "closed" parameter with value "both"
interval1 = pd.Interval(50, 75, closed='both')
interval2 = pd.Interval(65, 90, closed='both')

# Display the intervals
print("Interval1...")
print(interval1)
print("Interval2...")
print(interval2)

# Construct a new IntervalArray from Interval objects
array = pd.arrays.IntervalArray([interval1, interval2])
print("\nOur IntervalArray...")
print(array)

Interval1...
[50, 75]
Interval2...
[65, 90]

Our IntervalArray...
<IntervalArray>
[[50, 75], [65, 90]]
Length: 2, dtype: interval[int64, both]

Getting Midpoints

Use the mid property to get the midpoint of each interval ?

import pandas as pd

# Create IntervalArray
interval1 = pd.Interval(50, 75, closed='both')
interval2 = pd.Interval(65, 90, closed='both')
array = pd.arrays.IntervalArray([interval1, interval2])

# Get midpoint of each Interval in the IntervalArray as an Index
midpoints = array.mid
print("The midpoint of each interval in the IntervalArray...")
print(midpoints)
print(f"\nType: {type(midpoints)}")

The midpoint of each interval in the IntervalArray...
Float64Index([62.5, 77.5], dtype='float64')

Type: <class 'pandas.core.indexes.numeric.Float64Index'>

Complete Example

Here's a comprehensive example showing IntervalArray creation and midpoint calculation ?

import pandas as pd

# Create multiple Interval objects with different ranges
interval1 = pd.Interval(10, 20, closed='both')
interval2 = pd.Interval(30, 50, closed='both') 
interval3 = pd.Interval(100, 120, closed='both')

# Create IntervalArray
array = pd.arrays.IntervalArray([interval1, interval2, interval3])

print("IntervalArray:")
print(array)

print("\nInterval lengths:")
print(array.length)

print("\nInterval midpoints:")
print(array.mid)

# Access individual midpoints
print(f"\nFirst interval midpoint: {array.mid[0]}")
print(f"Second interval midpoint: {array.mid[1]}")

IntervalArray:
<IntervalArray>
[[10, 20], [30, 50], [100, 120]]
Length: 3, dtype: interval[int64, both]

Interval lengths:
Int64Index([10, 20, 20], dtype='int64')

Interval midpoints:
Float64Index([15.0, 40.0, 110.0], dtype='float64')

First interval midpoint: 15.0
Second interval midpoint: 40.0

Key Points

• The mid property returns a Float64Index containing midpoint values
• Midpoint is calculated as (left + right) / 2
• Works with both integer and float intervals
• The returned Index can be used for further operations

Conclusion

The mid property provides an efficient way to calculate midpoints of all intervals in an IntervalArray. It returns a Float64Index that can be used for indexing or further mathematical operations.