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Working with Durations in Python – Complete Guide for Data Science 2026

Durations (the difference between two points in time) are fundamental in data science — calculating customer lifetime, session length, time since last purchase, delivery delays, or rolling windows. Python’s timedelta and pandas Timedelta make working with durations clean, accurate, and highly performant.

TL;DR — Core Tools for Durations

timedelta → basic arithmetic
(dt2 - dt1) → automatic duration
.total_seconds(), .days, etc. → convert to numbers
Pandas Timedelta for vectorized operations on DataFrames

1. Basic Duration Creation and Arithmetic

from datetime import datetime, timedelta
from zoneinfo import ZoneInfo

start = datetime(2026, 3, 19, 9, 0, 0, tzinfo=ZoneInfo("UTC"))
end   = datetime(2026, 3, 19, 14, 30, 0, tzinfo=ZoneInfo("UTC"))

duration = end - start
print(duration)                    # 5:30:00
print(duration.total_seconds())    # 19800.0
print(duration.days)               # 0

2. Real-World Data Science Examples

import pandas as pd

df = pd.read_csv("sales_data.csv", parse_dates=["order_date", "delivery_date"])

# Calculate duration between two columns
df["delivery_duration"] = df["delivery_date"] - df["order_date"]

# Convert to useful units
df["days_to_deliver"] = df["delivery_duration"].dt.days
df["hours_to_deliver"] = df["delivery_duration"].dt.total_seconds() / 3600

# Example: Session duration
df["session_duration"] = df["end_time"] - df["start_time"]
df["session_minutes"] = df["session_duration"].dt.total_seconds() / 60

3. Creating Durations Manually

# Create specific durations
one_week = timedelta(weeks=1)
three_days = timedelta(days=3)
two_hours = timedelta(hours=2, minutes=30)

# Add to existing dates
future_date = datetime.now(ZoneInfo("UTC")) + timedelta(days=14)
past_date = datetime.now(ZoneInfo("UTC")) - timedelta(days=30)

4. Best Practices in 2026

Use Timedelta for all pandas-based duration calculations
Always work with timezone-aware datetimes before calculating differences
Convert durations to numeric units (.days, .total_seconds()) for modeling
Use pendulum for human-readable duration strings when needed
Keep raw datetime columns and derived duration columns separate

Conclusion

Working with durations is a core skill in data science. In 2026, Python’s timedelta and pandas Timedelta make time difference calculations fast, accurate, and vectorized. Use these tools to build features like delivery time, session length, customer recency, and rolling windows with clean and professional code.

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