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

What are the different functions used to loop over `DataFrame` objects?

What are the different functions used to loop over <code>DataFrame</code> objects?

Which method of iterating over `DataFrame` objects returns a list of pairs (index and row [`Series`])?

Which method of iterating over <code>DataFrame</code> objects returns a list of pairs (index and row [<code>Series</code>])?

Named tuples in Python allow only for 255 pairs, so regular tuples will be returned

It is slower than using `.apply()` functions

It is slower than looping use `.iterrows()`

What are the limitations of using `df.itertuples()`?

What are the limitations of using <code>df.itertuples()</code>?

Different techniques for looping over `DataFrames`

Different techniques for looping over <code>DataFrames</code>

This quiz covers how to loop over rows in a DataFrame object.

Course Introduction

Selection / Filters

Grouping

Dates Manipulation

Apply / Map

Merge/Concat

Quizzes: Assorted Topics

Conclusion

Looping over a DataFrame