Module 3: Tidy Data and Joining Dataframes

In this Module, you will learn about tidy data and how to transform your dataset into a tidy format. It will also focus on how to concatenate and join multiple dataframes.

0Module Learning Outcomes

1What is Tidy Data?

2Tidy Data Questions

3Is it Tidy I ?

4Is it Tidy II?

5Statistical Questions and Tidy Data

6Which is Tidy?

7Tidy Data True or False

8Reshaping with Pivot

9Pivoting Questions

10Applying Pivot

11Reshaping with Pivot Table

12Pivot Table Questions

13Applying Pivot Table

14Reshaping with Melt

15Melting Questions

16Applying Melt


18Concat questions

19Concatenating Vertically

20Concatenating Horizontally

21Joining Dataframes using Merge

22Merge Questions

23Merging I

24Merging II

25What Did We Just Learn?

About this course

Learn the fundamentals of programming in Python, including how to clean, filter, arrange, aggregate and transform data. You will learn the foundations of programming in Python while writing human-readable code that sets a foundation of best practices and coding style. You will gain the skills to clean, filter, manipulate (wrangle) and summarize data using Python libraries for more effective data analysis. An overview of data structures, iteration, flow control and program design relevant to data exploration and analysis will be addressed along with fundamental programming concepts such as loops, conditionals and data structures that create a solid foundation in data science programming.

About the program

The University of British Columbia (UBC) is a comprehensive research-intensive university, consistently ranked among the 40 best universities in the world. The Key Capabilities in Data Science program was launched in September 2020 and is developed and taught by many of the same instructors as the UBC Master of Data Science program.