5 Best Ways to Format Dates in Python to YYYY-MM-DD

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💡 Problem Formulation: When working with Python, a common requirement is to represent dates in the standardized “YYYY-MM-DD” format. For example, converting a date from the input “March 14, 2023” to the desired output “2023-03-14” can be essential for uniformity in date representation across different systems. This article explores various methods to perform this transformation effectively.

Method 1: Using datetime.strftime()

One of the most common and straightforward methods to format dates in Python is using the datetime.strftime() function from the datetime module. This method enables you to represent a datetime object as a string in the “YYYY-MM-DD” format by specifying the corresponding format code ‘%Y-%m-%d’.

Here’s an example:

from datetime import datetime

# example datetime object
dt = datetime(year=2023, month=3, day=14)

# formatting to "YYYY-MM-DD"
formatted_date = dt.strftime('%Y-%m-%d')
print(formatted_date)

Output:

2023-03-14

This code snippet first creates a datetime object named dt for March 14, 2023. It then applies the strftime method with ‘%Y-%m-%d’ to format the date accordingly, resulting in the string “2023-03-14”.

Method 2: Using date.isoformat()

The isoformat() method from Python’s date class inherently produces a string in “YYYY-MM-DD” format, following the ISO 8601 standard. It’s perfect for when you have a date object and want the formatted string without specifying a format code.

Here’s an example:

from datetime import date

# example date object
d = date(year=2023, month=3, day=14)

# generating "YYYY-MM-DD" format
formatted_date = d.isoformat()
print(formatted_date)

Output:

2023-03-14

In this code snippet, a date object named d is created and then the isoformat() method is called to retrieve the formatted date as a string, which outputs “2023-03-14”.

Method 3: String Formatting with f-strings

Python 3.6 introduced f-strings, a succinct way to embed expressions inside string literals using minimal syntax. You can directly insert a date or datetime object within an f-string and specify the desired format.

Here’s an example:

from datetime import date

# example date object
d = date(year=2023, month=3, day=14)

# formatting using f-string
formatted_date = f'{d:%Y-%m-%d}'
print(formatted_date)

Output:

2023-03-14

The f-string f'{d:%Y-%m-%d}' succinctly specifies the format for the date object d, resulting in the string “2023-03-14”.

Method 4: Using pandas.to_datetime() and Series.dt.strftime()

If you’re working with dates in a data analysis context, the pandas library offers powerful tools for date formatting. The to_datetime() function can parse a variety of date formats to a Timestamp object, which can then be formatted using dt.strftime().

Here’s an example:

import pandas as pd

# example date string
date_string = '14/03/2023'

# convert to datetime and format
formatted_date = pd.to_datetime(date_string, dayfirst=True).strftime('%Y-%m-%d')
print(formatted_date)

Output:

2023-03-14

The function pd.to_datetime() converts the date string to a datetime object, understanding that the day comes first in the input string. The result is then formatted to “YYYY-MM-DD” using strftime().

Bonus One-Liner Method 5: Using datetime.strptime() and Back to strftime()

For a quick one-liner, you can parse a date string into a datetime object with strptime() and immediately format it back to a string with strftime() in the same line of code.

Here’s an example:

from datetime import datetime

date_input = 'March 14, 2023'
formatted_date = datetime.strptime(date_input, '%B %d, %Y').strftime('%Y-%m-%d')
print(formatted_date)

Output:

2023-03-14

This one-liner effectively parses the input string representing the date and re-formats it using strftime() into the desired “YYYY-MM-DD” format.

Summary/Discussion

  • Method 1: Using datetime.strftime(). Flexible with format codes. Requires an existing datetime object.
  • Method 2: Using date.isoformat(). Simple and clean, follows ISO 8601. Limited to date objects, not datetime.
  • Method 3: String Formatting with f-strings. Concise and inline. Python 3.6+ required, and format codes still needed.
  • Method 4: Using pandas.to_datetime() and Series.dt.strftime(). Best for data analysis tasks. Requires pandas installation, might be overkill for simple tasks.
  • Bonus Method 5: One-Liner with strptime() and strftime(). Quick and handy for converting strings. May throw errors with incompatible format strings.