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

Will return percentage counts/ratios of total rather than actual count values

Will modify the values returned to be between [-1, 1]

What is the effect of passing `normalize=True` in `df[col].value_counts()`?

What is the effect of passing <code>normalize=True</code> in <code>df[col].value_counts()</code>?

Which statistics are returned by the `.describe()` function for numerical columns?

Which statistics are returned by the <code>.describe()</code> function for numerical columns?

Which statistical functions are built in `Pandas`?

Which statistical functions are built in <code>Pandas</code>?

Different statistical functions in Pandas

Different statistical functions in Pandas

This quiz covers some of the basic statistical functions available for use in Pandas. 

Basic Statistics

This quiz covers some of the basic statistical functions available for use in Pandas.

Course Introduction

Selection / Filters

Grouping

Dates Manipulation

Apply / Map

Merge/Concat

Quizzes: Assorted Topics

Conclusion

Basic Statistics