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

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.

Introduction

Selection / Filters

Grouping

Dates Manipulation

Apply / Map

Merge/Concat

Quizzes: Assorted Topics

Conclusion

Basic Statistics