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Python Pandas - Get the right bound for the interval
In Pandas, an Interval represents a range between two bounds. To get the right bound of an interval, use the interval.right property. This is useful when working with time ranges or numeric intervals.
Syntax
interval.right
Creating a Time Interval
First, let's create a time interval using timestamps ?
import pandas as pd
# Create a time interval using Timestamps
interval = pd.Interval(pd.Timestamp('2020-01-01 00:00:00'),
pd.Timestamp('2021-01-01 00:00:00'),
closed='left')
print("Interval:", interval)
Interval: [2020-01-01, 2021-01-01)
Getting the Right Bound
Use the right property to extract the right bound of the interval ?
import pandas as pd
interval = pd.Interval(pd.Timestamp('2020-01-01 00:00:00'),
pd.Timestamp('2021-01-01 00:00:00'),
closed='left')
# Get the right bound
right_bound = interval.right
print("Right bound:", right_bound)
print("Type:", type(right_bound))
Right bound: 2021-01-01 00:00:00 Type: <class 'pandas._libs.tslibs.timestamps.Timestamp'>
Complete Example
Here's a comprehensive example showing interval properties ?
import pandas as pd
# Create a time interval
interval = pd.Interval(pd.Timestamp('2020-01-01 00:00:00'),
pd.Timestamp('2021-01-01 00:00:00'),
closed='left')
print("Interval:", interval)
print("Left bound:", interval.left)
print("Right bound:", interval.right)
print("Interval length:", interval.length)
print("Is closed on left:", interval.closed_left)
print("Is closed on right:", interval.closed_right)
Interval: [2020-01-01, 2021-01-01) Left bound: 2020-01-01 00:00:00 Right bound: 2021-01-01 00:00:00 Interval length: 366 days 00:00:00 Is closed on left: True Is closed on right: False
Numeric Intervals
The right property also works with numeric intervals ?
import pandas as pd
# Create a numeric interval
numeric_interval = pd.Interval(1.5, 7.8, closed='both')
print("Numeric interval:", numeric_interval)
print("Right bound:", numeric_interval.right)
Numeric interval: [1.5, 7.8] Right bound: 7.8
Conclusion
The interval.right property provides easy access to the right boundary of any Pandas interval. This is particularly useful when working with time series data or numeric ranges where you need to extract specific boundary values.
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