How to Use pandas.date_range for Date Sequences

Use pandas.date_range() to create a sequence of dates between a start and end date or for a specified number of periods. You can customize the frequency with the freq parameter to generate daily, monthly, or other intervals.

Syntax

The basic syntax of pandas.date_range() is:

• start: The starting date of the sequence.
• end: The ending date of the sequence.
• periods: Number of dates to generate (optional if start and end are given).
• freq: Frequency string like 'D' for daily, 'M' for month end, 'H' for hourly, etc.
• tz: Time zone (optional).

python

pandas.date_range(start=None, end=None, periods=None, freq='D', tz=None)

Example

This example creates a daily date range from January 1, 2024 to January 7, 2024.

python

import pandas as pd

dates = pd.date_range(start='2024-01-01', end='2024-01-07')
print(dates)

Output

DatetimeIndex(['2024-01-01', '2024-01-02', '2024-01-03', '2024-01-04', '2024-01-05', '2024-01-06', '2024-01-07'], dtype='datetime64[ns]', freq='D')

Common Pitfalls

Common mistakes include:

• Specifying both periods and end which causes an error.
• Using an invalid frequency string.
• Not formatting dates as strings or Timestamp objects.

Always provide either start and end, or start and periods, but not all three.

python

import pandas as pd

# Wrong: specifying both end and periods
# dates = pd.date_range(start='2024-01-01', end='2024-01-07', periods=5)  # This raises an error

# Right: specify start and periods
correct_dates = pd.date_range(start='2024-01-01', periods=5, freq='D')
print(correct_dates)

Output

DatetimeIndex(['2024-01-01', '2024-01-02', '2024-01-03', '2024-01-04', '2024-01-05'], dtype='datetime64[ns]', freq='D')

Quick Reference

Parameter	Description	Example Values
start	Start date of the range	'2024-01-01', pd.Timestamp('2024-01-01')
end	End date of the range	'2024-01-07', pd.Timestamp('2024-01-07')
periods	Number of dates to generate	5, 10
freq	Frequency of dates	'D' (daily), 'M' (month end), 'H' (hourly), 'W' (weekly)
tz	Time zone for dates	'UTC', 'Europe/London'

Key Takeaways

Use pandas.date_range() to create sequences of dates easily by specifying start, end, or periods.

Do not specify both end and periods together; choose one with start.

Customize the frequency with the freq parameter to get daily, monthly, or other intervals.

Input dates as strings or pandas Timestamp objects for best results.

Check frequency strings carefully to avoid errors.