Track
Data Manipulation in R
Included withPremium or Teams
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Loved by learners at thousands of companies
Training 2 or more people?
Try DataCamp for BusinessTrack Description
Data Manipulation in R
Master Data Manipulation with dplyr and tidyr
The R packages dplyr and tidyr are essential tools for efficient data manipulation, providing a clear and concise way to wrangle messy real-world data. In this Track, you'll learn the key functions of these packages, enabling you to expertly extract, filter, and transform your data, setting the stage for smooth and effective analysis.Become a Data Manipulation Expert
Through hands-on exercises, you'll learn how to:- Select, filter, and arrange data using dplyr's intuitive verb-based functions
- Reshape data between wide and long formats with tidyr for easy analysis and visualization
- Join multiple tables together to combine data and answer complex questions
- Handle missing values and create tidy data that's analysis-ready
Solve Real Business Problems with dplyr
Put your skills into practice by working with real-world datasets. You'll analyze voting data from the United Nations to uncover insights and trends. By applying dplyr's powerful functions, you'll quickly manipulate the data, enabling you to focus on the important questions and deliver meaningful results.Why dplyr and tidyr?
dplyr and tidyr are part of the renowned tidyverse collection of R packages. They've revolutionized data manipulation in R by providing a consistent and readable syntax. With dplyr and tidyr in your toolkit, you'll spend less time struggling with data formats and more time uncovering insights. These packages are essential for any R user working with data.Advance Your Data Science Career
Proficiency in data manipulation is a critical skill for data analysts and data scientists. By mastering dplyr and tidyr, you'll be well-equipped to tackle the data wrangling challenges you'll face in your data career. You'll work more efficiently, write cleaner code, and be able to seamlessly collaborate with other tidyverse users.Start Manipulating Data with Confidence
Whether you're a beginner looking to build a strong data science foundation or an experienced analyst seeking to upgrade your skills, this Track will help you become a data manipulation expert. Get ready to transform the way you work with data in R.Prerequisites
There are no prerequisites for this trackCourse
Build Tidyverse skills by learning how to transform and manipulate data with dplyr.
Course
Transform almost any dataset into a tidy format to make analysis easier.
Course
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Project
Exploring flight data from NYC using advanced data joining techniques in R.
Course
Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.
Complete
Earn Statement of Accomplishment
Add this credential to your LinkedIn profile, resume, or CVShare it on social media and in your performance review
Included withPremium or Teams
Enroll NowFAQs
Is this Track suitable for beginners?
Yes, this Track is suitable for beginners. Although knowledge of R is useful, the courses are designed to be accessible to those with limited prior programming experience.
What is the programming language of this Track?
The programming language of this Track is R.
Which jobs will benefit from this Track?
This Track is well-suited to individuals whose jobs involve extracting, manipulating, and analyzing data as part of their job responsibilities. Jobs in research, engineering, and finance, for instance, stand to benefit greatly from the skills developed in this Track.
How will this Track prepare me for my career?
By completing this Track, users will develop proficiency in packages like dplyr and tidyr, which are invaluable for data manipulation tasks. Ultimately, users will be equipped with the necessary skillset to effectively manage a wide range of data-related tasks related to their career.
How long does it take to complete this Track?
This Track typically takes around 16 hours to complete.
What's the difference between a skill track and a career track?
A skill track focuses on building specific skills and expertise, while a career track tends to prepare individuals for a range of job roles. This Track is a skill track as it focuses on mastering the skills of data manipulation.
Join over 19 million learners and start Data Manipulation in R today!
Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.