Solve different challenging problems to prepare yourself for data analytics interviews.

Pandas: Python for Data Analysis

In this module, we’ll try to solve a number of challenges covering different concepts related to data analytics in pandas, such as grouping, filtering, date manipulation, and more. This module will mainly test our knowledge while also helping us understand more advanced concepts. By the end of this module, we’ll have the confidence we need to land our dream job in data science.

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.

Introduction

Selection / Filters

Grouping

Dates Manipulation

Apply / Map

Merge/Concat

Quizzes: Assorted Topics

Conclusion

Looping over a DataFrame