Datetime type in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Datetime type in pandas used for?

It is used to represent dates and times in a format that pandas can understand and work with easily, like sorting or calculating time differences.

beginner

How do you convert a string column to a datetime type in pandas?

Use pd.to_datetime() function to convert strings to datetime objects.

intermediate

What pandas data type is used internally to store datetime values?

pandas uses datetime64[ns] type internally to store datetime values with nanosecond precision.

beginner

How can you extract the year from a datetime column in pandas?

Use the .dt.year accessor on the datetime column to get the year part.

beginner

Why is it better to use datetime types instead of strings for dates in pandas?

Datetime types allow easy date calculations, filtering, and plotting, which are hard or slow with strings.

Which function converts a string to a datetime in pandas?

A pd.to_datetime()

B pd.to_string()

C pd.to_date()

D pd.convert_datetime()

The correct function to convert strings to datetime objects in pandas is pd.to_datetime().

What is the pandas datetime type called internally?

A dateobject

B datetime32

C datetime64[ns]

D time64

pandas uses datetime64[ns] to store datetime values with nanosecond precision.

How do you get the month from a pandas datetime column named 'date'?

A date.month()

B date.month

C date.get_month()

D date.dt.month

Use the .dt.month accessor to extract the month from a datetime column.

Why should you use datetime types instead of strings for dates?

A Datetime types allow easy date calculations and filtering

B Strings take less memory

C Strings are faster to process

D Datetime types cannot be sorted

Datetime types make it easy to do calculations, filtering, and plotting with dates.

What happens if you try to convert an invalid date string with pd.to_datetime()?

A It crashes the program

B It returns NaT (Not a Time)

C It returns the original string

D It converts to 1970-01-01

Invalid date strings convert to NaT, which means 'Not a Time' in pandas.

Explain how to convert a string column to datetime and extract the year in pandas.

Think about the function to convert and how to get parts of the date.

Describe why using datetime types in pandas is better than using strings for date data.

Consider what tasks become easier with datetime types.