Python Pandas - Convert given Timestamp to Period

To convert a given Timestamp to Period in Pandas, use the timestamp.to_period() method. The freq parameter sets the frequency for the period conversion.

Syntax

timestamp.to_period(freq=None)

Parameters

freq ? Frequency string (e.g., 'D' for daily, 'M' for monthly, 'Y' for yearly)

Basic Example

Here's how to convert a timestamp to a monthly period ?

import pandas as pd

# Create a timestamp object
timestamp = pd.Timestamp('2021-09-14T15:12:34.261811624')

# Display the original timestamp
print("Original Timestamp:")
print(timestamp)

# Convert timestamp to monthly period
monthly_period = timestamp.to_period(freq='M')
print("\nConverted to Monthly Period:")
print(monthly_period)

Original Timestamp:
2021-09-14 15:12:34.261811624

Converted to Monthly Period:
2021-09

Different Frequency Options

You can use various frequency strings for different period types ?

import pandas as pd

timestamp = pd.Timestamp('2021-09-14T15:12:34')

# Different frequency conversions
daily = timestamp.to_period(freq='D')
weekly = timestamp.to_period(freq='W')
monthly = timestamp.to_period(freq='M')
quarterly = timestamp.to_period(freq='Q')
yearly = timestamp.to_period(freq='Y')

print("Daily Period:", daily)
print("Weekly Period:", weekly)
print("Monthly Period:", monthly)
print("Quarterly Period:", quarterly)
print("Yearly Period:", yearly)

Daily Period: 2021-09-14
Weekly Period: 2021-09-12/2021-09-18
Monthly Period: 2021-09
Quarterly Period: 2021Q3
Yearly Period: 2021

Common Frequency Codes

Conclusion

The to_period() method converts timestamps to periods with specified frequency. Use appropriate frequency codes like 'D', 'M', 'Q', or 'Y' to group timestamps into meaningful time periods for analysis.