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

Concatenate two `DataFrame` objects by appending rows only

Concatenate two `DataFrame` objects by appending columns only

Concatenate two `DataFrame` objects by appending either rows or columns

The `.concat()` function can be used to do the following:

The <code>.concat()</code> function can be used to do the following:

Given two `DataFrame` objects, `df1` and `df2`, how can you merge them in a way that keeps records that exist in `df1`, but don't exist in `df2`? It should also drop records from `df2` that exist in `df1`?

Given two <code>DataFrame</code> objects, <code>df1</code> and <code>df2</code>, how can you merge them in a way that keeps records that exist in <code>df1</code>, but don’t exist in <code>df2</code>? It should also drop records from <code>df2</code> that exist in <code>df1</code>?

`pd.merge(df1, df2, on=['city', 'city_id'])`

`pd.merge(df1, df2, left_on='city_id', right_on='city')`

Given two `DataFrame` objects, where the columns that should be matched are named `city_id` and `city`, how can you merge both?

Given two <code>DataFrame</code> objects, where the columns that should be matched are named <code>city_id</code> and <code>city</code>, how can you merge both?

Merging/Concatenation final quiz

Merging/Concatenation final quiz

This quiz will make sure you've covered the necessary knowledge in the merging/concatenation functionality in Pandas.

Course Introduction

Selection / Filters

Grouping

Dates Manipulation

Apply / Map

Merge/Concat

Quizzes: Assorted Topics

Conclusion

Final Quiz