Extracting year, month, day in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

How do you extract the year from a pandas datetime column?

Use the .dt.year attribute on the datetime column. For example, df['date'].dt.year gives the year part of each date.

beginner

What pandas attribute extracts the month from a datetime column?

The .dt.month attribute extracts the month as an integer (1 to 12) from a datetime column.

beginner

How can you get the day of the month from a pandas datetime column?

Use .dt.day on the datetime column to get the day number (1 to 31) for each date.

intermediate

What type should a pandas column be to use .dt.year, .dt.month, or .dt.day?

The column must be of datetime type, like datetime64[ns]. If not, convert it using pd.to_datetime().

beginner

Write a pandas code snippet to create separate columns for year, month, and day from a 'date' column.

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

Which pandas attribute extracts the month from a datetime column?

A .dt.year

B .dt.month

C .dt.day

D .dt.hour

The .dt.month attribute extracts the month number from a datetime column.

If a pandas column is not datetime type, what should you do before extracting year, month, or day?

A Convert it using <code>pd.to_datetime()</code>

B Use <code>.astype(int)</code>

C Use <code>.dt.year</code> directly

D Drop the column

You must convert the column to datetime type using pd.to_datetime() before using .dt attributes.

What does df['date'].dt.day return?

A The month number

B The day of the week as a string

C The day of the month as an integer

D The year

.dt.day returns the day number (1 to 31) from each date.

Which data type is required for a pandas column to use .dt.year?

A datetime64[ns]

B int64

C object

D float64

The column must be datetime type like datetime64[ns] to use .dt.year.

How do you create a new column 'year' from a datetime column 'date' in pandas?

A df['year'] = df['date'].astype(int)

B df['year'] = df['date'].year()

C df['year'] = year(df['date'])

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

Use df['date'].dt.year to extract the year and assign it to a new column.

Explain how to extract year, month, and day from a pandas datetime column and why the column type matters.

Think about the .dt accessor and data types.

Write a short pandas code snippet to add three new columns for year, month, and day from a 'date' column.

Use the .dt accessor on the 'date' column.