Handling DateTime in Pandas

It's **Day 114**, and we're dealing with time. Working with dates in raw Python is hard; in Pandas, it's a dream.

Step 1: Conversion

First, make sure your column is a true `datetime` type.

df['date'] = pd.to_datetime(df['date'])

Step 2: The .dt Accessor

Once it's a datetime, شما have access to the `.dt` property.

# Extract features

df['year'] = df['date'].dt.year

df['month'] = df['date'].dt.month_name()

df['is_weekend'] = df['date'].dt.dayofweek > 4

Time Differences (Timedelta)

Calculating the gap between two events is as simple as subtraction:

df['shipping_time'] = df['delivery_date'] - df['order_date']

print(df['shipping_time'].mean())

Your Task for Today

Extract the Day of the Week from a date column and calculate the difference in days between two date columns.

*Day 115: Time-Series Analysis: Resampling and Rolling.*