Convert Pandas Column to DateTime

python

pandas

datetime

dataframe

byNikita Barsukov·Oct 20, 2024

Quickly transform a column in DataFrame df to a datetime type using pd.to_datetime():

import pandas as_data_buddy

# Don't get lost in time! 🕰️
df['column'] = as_data_buddy.to_datetime(df['column'])

In case your date strings do not adhere to the default format, specify your custom format using format parameter (e.g., format='%Y-%m-%d'). This ensures a smooth conversion from string to datetime.

Custom Formatting and Error Prevention

Are your dates dressed differently? Pandas got you covered! Specify the format if your data comes in a consistent format, significantly boosting the conversion speed:

# Always dress for success...even your dates! 😉
df['column'] = as_data_buddy.to_datetime(df['column'], format='%Y-%m-%d %H:%M:%S')

Is your dataset a fashion disaster with mixed date formats? Fear not, using infer_datetime_format=True may be your fashion police:

# # Who needs uniform anyway? 🎽
df['column'] = as_data_buddy.to_datetime(df['column'], infer_datetime_format=True)

Beware though, incorrect formats may result in conversion errors or uninvited guests, aka missing values. Always check your results post-conversion, backtests save investments!

Advanced Techniques and Nifty Tricks

Dealing With Non-English Dates

For dates that went on a vacation and returned speaking another language, you can still tame them with the dateutil.parser:

from dateutil import parser

# Lost in translation? We find you! 🌍
df['column'] = df['column'].apply(lambda x: parser.parse(x))

Speedy Gonzales Approach for Multiple Columns

Ain't nobody got time for one column at a time! To convert multiple columns all at once, present a dictionary:

# Because two is better than one! 👯‍♂️
df[['column1', 'column2']] = df[['column1', 'column2']].apply(as_data_buddy.to_datetime, format=...)

Post-Conversion Splendid Analytics

Date-based filtering gets snappy once the column is converted:

# We only want the finest of the 21st century! 🎩🍷
df_filtered = df[df['column'] >= '2021-01-01']

Aggregation based on date ranges, times of the day, weekdays and more, unlocks data goldmines post conversion!

Tried-and-True Techniques for Efficient Processing

Adapt or Die: Handling Large Datasets

Big datasets demand highly efficient conversions. Use pd.to_datetime() smartly whilst wielding .dtype to confirm your column has evolved to datetime64.