pandas for Python - A Quick Guide - Processing-Date/Time Format

This video tutorial covers datetime data processing using pandas. It begins with converting string data to datetime objects, then explores working with timestamp objects and their attributes. The tutorial also demonstrates applying functions on a series of timestamps, filtering and reindexing dataframes using datetime columns, and performing arithmetic operations on datetime data. The video uses the UFO report dataset and an employee dataset to illustrate these concepts.

What is the primary challenge programmers face when working with datetime data?

How can you filter a DataFrame using a datetime column?

Describe the process of converting a string data type to a datetime object in pandas.

What are some attributes and methods available for timestamp objects in pandas?

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

What is the purpose of the 'dt' accessor in pandas when working with datetime data?

Explain how to create a new datetime column from separate year, month, and day columns.

What is the significance of reindexing a DataFrame when working with time series data?

How do you perform arithmetic operations on datetime columns in pandas?

What steps would you take to visualize datetime data using pandas?