Skill Track

Importing & Cleaning Data with R

Understanding how to prep your data is an essential skill when working in R. It’s what you have to do before you can reveal the insights that matter. In this track, you’ll learn how to import your data from a variety of sources, including .csv, .xls, text files, and more. You'll then gain the skills you'll need to prepare your data for analysis, including converting data types, filling in missing values, and using fuzzy string matching. Throughout the track, you'll have the chance to apply your skills to real-world data such as customer asset portfolios and restaurant reviews. Start this track and gain the data prepping skills you need to clean your dirty data.

  • R
  • 14 hours
  • 4 courses
1
R Icon

Introduction to Importing Data in R

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

3 hours
Filip Schouwenaars

Data Science Instructor at DataCamp

2
R Icon

Intermediate Importing Data in R

Parse data in any format. Whether it's flat files, statistical software, databases, or data right from the web.

3 hours
Filip Schouwenaars

Data Science Instructor at DataCamp

3
R Icon

Data Cleaning in R

Develop the skills you need to go from raw data to awesome insights as quickly and accurately as possible.

4 hours
Maggie Matsui

Content Developer at DataCamp

Instructors

Filip Schouwenaars

Data Science Instructor at DataCamp

Maggie Matsui

Content Developer at DataCamp

Alison Hill

Professor and Data Scientist

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