DSCI011ProgramminginPythonforDataScience

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 combine and stack 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

17Concatenation

18Concat questions

19Concatenating Vertically

20Concatenating Horizontally

21Joining Dataframes using Merge

22Merge Questions

23Merging I

24Merging II

25What Did We Just Learn?

About this course

Basic programming in Python. Overview of iteration and flow control and data types relevant to data exploration and analysis. When and how to exploit pre-existing libraries. Numerical data types with Numpy and tabular data with Pandas.

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 MDS Mid Career Learners program was launched in September 2020 and is offered by the MDS program who are a collaboration between the UBC Department of Computer Science and Department of Statistics.