What is Data Wrangling?
Data wrangling is an important part of the data analysis process. It involves transforming data from one form into another to make it valuable for analysis. This process is essential for preparing data for analysis.
In the R programming language, two powerful packages for data wrangling are dplyr and tidyr. These packages are part of the tidyverse, a collection of R packages.
What you’ll learn in this course
In this course, you’ll learn how to efficiently manipulate and reshape data using dplyr and tidyr. You’ll learn how to work with rows, columns, groups. You’ll also learn how to join and reshape data.
Here is a brief overview of what you’ll learn in this course:
Working with Rows
- Order rows
- Keep only unique rows
- Filter rows based on conditions
- Subset rows based on their positions
Working with Columns
- Get a glimpse of your data
- Create and modify columns
- Extract a single column
- Change column order
- Rename columns
- Select specific columns
Working with Groups
- Count observations
- Group data
- Use per-operation grouping
- Perform rowwise operations
- Summarize grouped data
- Use helper functions
Joining Data
- Combine matching rows from two datasets
- Use left and right joins
- Combine all rows
- Find rows that don’t match using anti joins
- Specify join conditions
Reshaping Data
- Transform data from wide to long format
- Transform data from long to wide format
- Use additional arguments
Getting Started
This is an interactive course. This means that you can run code in the browser without having to install anything on your computer. The required packages are already installed and loaded for you.
If you need to install on your computer, you can run the following code in your R console:
install.packages("tidyverse") Once installed, you can load the packages by running
library(tidyverse) Review
Loading...
Loading...
Loading...
By the end of this course, you’ll have a solid foundation in data wrangling techniques using dplyr and tidyr, enabling you to efficiently prepare your data for analysis and visualization.
Let’s begin our journey into the world of data wrangling!