Date range creation with date_range in Pandas

Introduction

We use date ranges to create a list of dates between two points in time. This helps us analyze data over days, weeks, or months easily.

You want to create a calendar of dates for a report.

You need to fill missing dates in a time series dataset.

You want to generate dates for scheduling or planning.

You want to analyze data trends over a specific period.

You want to create time-based indexes for data frames.

Syntax

Pandas

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

start: The first date in the range.

end: The last date in the range.

periods: Number of dates to generate (optional if start and end are given).

freq: Frequency of dates, 'D' means daily (default).

Examples

This creates dates from January 1 to January 5, 2024, one day apart.

Pandas

import pandas as pd

# Create daily dates from Jan 1 to Jan 5, 2024
dates = pd.date_range(start='2024-01-01', end='2024-01-05')
print(dates)

This creates 4 daily dates starting from January 1, 2024.

Pandas

import pandas as pd

# Create 4 dates starting from Jan 1, 2024, daily frequency
dates = pd.date_range(start='2024-01-01', periods=4)
print(dates)

This creates dates every 2 days between January 1 and January 9, 2024.

Pandas

import pandas as pd

# Create dates every 2 days from Jan 1 to Jan 9, 2024
dates = pd.date_range(start='2024-01-01', end='2024-01-09', freq='2D')
print(dates)

Sample Program

This program creates 7 daily dates starting from June 1, 2024, and shows them in a table.

Pandas

import pandas as pd

# Create a date range for one week starting from 2024-06-01
dates = pd.date_range(start='2024-06-01', periods=7)

# Convert to a DataFrame to show nicely
df = pd.DataFrame({'Date': dates})
print(df)

Important Notes

If you provide both start and end, periods is ignored.

You can use other frequencies like 'H' for hourly, 'M' for month end, or 'W' for weekly.

The output is a DatetimeIndex, which works well with pandas data frames.

Summary

date_range helps create a list of dates easily.

You can control start, end, number of dates, and frequency.

This is useful for time-based data analysis and filling missing dates.