Pandas: Date range using a startpoint date and a number of periods

Last update on April 04 2025 13:47:56 (UTC/GMT +8 hours)

8. Date Range Generation

Write a Pandas program to create a date range using a startpoint date and a number of periods.

Sample Solution:

Python Code :

import pandas as pd
date_range = pd.date_range('2020-01-01', periods=45)
print("Date range of perods 45:")
print(date_range)

Sample Output:

Date range of perods 45:
DatetimeIndex(['2020-01-01', '2020-01-02', '2020-01-03', '2020-01-04',
               '2020-01-05', '2020-01-06', '2020-01-07', '2020-01-08',
               '2020-01-09', '2020-01-10', '2020-01-11', '2020-01-12',
               '2020-01-13', '2020-01-14', '2020-01-15', '2020-01-16',
               '2020-01-17', '2020-01-18', '2020-01-19', '2020-01-20',
               '2020-01-21', '2020-01-22', '2020-01-23', '2020-01-24',
               '2020-01-25', '2020-01-26', '2020-01-27', '2020-01-28',
               '2020-01-29', '2020-01-30', '2020-01-31', '2020-02-01',
               '2020-02-02', '2020-02-03', '2020-02-04', '2020-02-05',
               '2020-02-06', '2020-02-07', '2020-02-08', '2020-02-09',
               '2020-02-10', '2020-02-11', '2020-02-12', '2020-02-13',
               '2020-02-14'],
              dtype='datetime64[ns]', freq='D')

For more Practice: Solve these Related Problems:

• Write a Pandas program to generate a date range starting from a specific date with a fixed number of periods, skipping weekends.
• Write a Pandas program to create a date range with a custom frequency (e.g., every 3 days) and then visualize the dates.
• Write a Pandas program to generate a date range with irregular intervals by randomly dropping dates from a complete sequence.
• Write a Pandas program to create a date range from a start date and period count, then display the first and last dates.

Python Code Editor:

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Previous: Write a Pandas program to create a time series object that has time indexed data. Also select the dates of same year and select the dates between certain dates.
Next: Write a Pandas program to create a whole month of dates in daily frequencies. Also find the maximum, minimum timestamp and indexs.