Data Science and Machine Learning (Theory and Projects) A to Z - Pandas for Data Manipulation and Understanding: Pandas

The video tutorial addresses the challenges of handling inconsistent date and time formats in data using pandas. It introduces the pd.to_datetime function, which standardizes various date formats into a consistent format, making data manipulation easier. The tutorial demonstrates how to convert different date formats and calculate differences between dates. It also highlights the practical application of these techniques when working with CSV files containing date columns.

What challenges might arise when dealing with date and time data in pandas?

Explain how the 'pd.to_datetime' function helps in standardizing date formats.

Describe the different formats of dates that can be encountered in real data.

What is the significance of setting frequency for working days in date calculations?

How can you calculate the difference between two dates using pandas?

In what scenarios would you need to apply the 'pd.to_datetime' function on a CSV file?

What functionalities does pandas offer for manipulating date and time data?