The ultimate guide to data analytics interviews using Pandas. Strengthen your skills with advanced concepts and practice with real-world interview questions. Developed by FAANG engineers.

In this course, you will face a number of challenges across different concepts, all with the data analytics library Pandas.

This course is mainly to refresh your knowledge, as well as help you understand more advanced concepts. By solving multiple challenges, you will surely strengthen your skills and it will help you ace your interview involving Pandas.

You will cover many topics such as: grouping, filtering, date manipulation, and more. By the time you finish this course, you will have the confidence you need to land your dream job.

Data Analytics Interview Prep Using Pandas

Assuming `date` is a column of type `datetime` , how can you access the year information?

Assuming <code>date</code> is a column of type <code>datetime</code> , how can you access the year information?

`pd.date_range(start='2015-01-01', freq='1M', period=24)`

`pd.date_range(start='2015-01-01', freq='30D', period=24)`

`pd.date_range(start='2015-01-01', freq='1M', period='24M')`

How can you generate a list of dates starting `2015-01-01` for a period of 24 months, with a frequency of one month? 

How can you generate a list of dates starting <code>2015-01-01</code> for a period of 24 months, with a frequency of one month?

What date accessors are predefined in `Pandas`?

What date accessors are predefined in <code>Pandas</code>?

Final date manipulation quiz

Final date manipulation quiz

This quiz will make sure you've covered the necessary knowledge of the date manipulation functionality in Pandas.

Course Introduction

Selection / Filters

Grouping

Dates Manipulation

Apply / Map

Merge/Concat

Quizzes: Assorted Topics

Conclusion

Final Quiz