Convert date to datetime in Python

Code breakdown and examples

Understanding the conversion process requires us to deconstruct it into digestible chunks. Below are step-by-step procedures to accomplish this:

Midnight conversion for romantics

Create a datetime object at midnight from a given date:

from datetime import datetime, date, time

# New Year's Eve
d = date(2021, 12, 31)

# Queue the fireworks and champagne! 🥂
dt = datetime.combine(d, time.min)  # The ball drops at midnight
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Manual datetime creation for control-freaks

Control freaks, rejoice! Construct a datetime object directly if you have year, month, and day details:

from datetime import datetime

# Manual Construction... Hard hats necessary!
dt = datetime(year=2021, month=12, day=31)  # aka conjuring a timestamp from thin air
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Extract, process, reload

Extract data from a date, process it and reload as a datetime to show off your data-wrangling skills:

# Perform open-heart surgery on our date
year, month, day = my_date.year, my_date.month, my_date.day

# Stimulate it back to a life as a datetime!
dt = datetime(year, month, day)  # It's alive! ...Uh, I mean, it's a datetime now!
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Complex applications

Converting dates to datetimes isn't merely a Python party trick; it has serious use-cases. Let's make this more useful with real-world applications:

Time zones with pandas Timestamp

Hop through timezones with pandas Timestamp. This approach provides timezone awareness, plus a ticket to join the Intergalactic Time Travelers Club!

import pandas as pd

# A humble date
d = pd.to_datetime('2021-12-31').date()

# Beam it up, Scotty
dt = pd.Timestamp(d)  # Now with added timezone powers!
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Unpacking expert-level timetuple

Let's step up the game. For precision, timetuple is your Swiss Army Knife:

from datetime import datetime

# Extract the tuple like a magician pulls rabbits from a hat
t = my_date.timetuple()

# Transform your rabbit-tuple into a timestamp
dt = datetime(t.tm_year, t.tm_mon, t.tm_mday)  # Sleight of hand? Nah, just Python.
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Practical real-world scenarios

Let's apply our knowledge to some more real-world problem statements now:

Avoid coding confusions

How about making our code self-explaining? An ounce of clarity saves a ton of confusion:

# Demystifying the arcane with midnight 
my_datetime = datetime.combine(my_date, datetime.min.time())  # Clear as a bell... that tolls at midnight
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Bulk date extraction

Use automation for large datasets while sipping your coffee:

# Custom potion for bulk conversion
def convert_to_datetime(row):
    return datetime.combine(row['date'], datetime.min.time())

# Unleash the custom potion across an entire DataFrame
df['datetime'] = df.apply(convert_to_datetime, axis=1)  # Now you see dates, and... voila, datetimes!
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Harness the power of pandas

Sometimes, Pandas has a better alternative up its sleeve, especially if you are processing a data frame full of dates:

import pandas as pd

# Pandas transformation charm
df['datetime'] = pd.to_datetime(df['date'])  # Whoosh, and the dates were datetimes.
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