Module 8: A Slice of NumPy and Advanced Data Wrangling

In this module, you will learn about NumPy arrays and more advanced wrangling techniques such as handling columns with dates and strings and identifying null values.

0Module Learning Outcomes

1NumPy and 1D Arrays

2NumPy and Array Questions

3More NumPy

4NumPy Practice

5Multi-dimensional Arrays

6Make that Array

7Shape, Size, and Dimension

8More Arrays Questions

9Making an Array

10Array Practice

11Working with Null Values

12Finding and Dropping Null Values Questions

13Filling Methods

14Practice Filling Null Values

15Practice Identifying Null Values

16Working with Dates and Time

17Datetime Questions

18Practice Processing Dates

19Introduction to Working with Strings

20String Questions

21Identify the String Code

22Practice Handling Strings

23More Advanced String Processing

24Advanced String Questions


26Processing Strings in a Dataframe

27What 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.