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Course Description
Julia is a new and exciting programming language designed for machine learning, scientific computing, and data mining. This course will provide you with the knowledge necessary for starting your own data manipulation journey in Julia.We'll build on your knowledge of DataFrames from the Introduction to Julia and Intermediate Julia courses. By the end of the course, you'll be equipped with core skills for inspecting, transforming, grouping, visualizing DataFrames, and many more.
Prerequisites
Curriculum
Course outline
1
Inspecting DataFrames
Take your first steps toward complex data manipulation in Julia! Learn how to personalize your experience with the DataFrames package and how to create data visualizations using the Plots package.
- Diving into DataFrames50 XP
- Symbols vs. Strings100 XP
- Describe it to me100 XP
- Missing anything?50 XP
- Selecting columns50 XP
- Column selection100 XP
- Selecting patterns100 XP
- Regular penguins100 XP
- Exploring Data with Visualizations50 XP
- Flipper distribution100 XP
- Rating vs. cocoa percentages100 XP
- Plotting minimum wages over time100 XP
2
Working with columns
Columns are the basic building blocks of DataFrames. Knowing how to handle columns is essential for your data manipulation journey. You'll learn how to reorder and drop columns, as well as how to apply functions to individual rows and whole columns.
3
Aggregating DataFrames
In this chapter, you'll learn how to group data and calculate grouped summary statistics, as well as how to create pivot tables. You'll also learn how to improve the readability of your code with the Chain.jl package.
4
Improving Your Workflow
Learn how to load and join datasets, as well as how to handle missing values. Then it's time to fit everything together!
J
Data Manipulation in Julia
Course
Complete
