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.

R14 hours4 Courses1 Project

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Loved by learners at thousands of companies

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

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

Cleaning Data in R

Learn to clean data as quickly and accurately as possible to help your business move from raw data to awesome insights.

4 hours

Reshaping Data with tidyr

Transform almost any dataset into a tidy format to make analysis easier.

4 hours

NYC Airbnb Data Analysis

Apply data importing and cleaning skills to extract insights about the New York City Airbnb market.

2 hours

Importing & Cleaning Data with R

Loved by learners at thousands of companies

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Join over .css-1osvizq-TrackShowPage{color:#03ef62;}11,710,000 learners and start Importing & Cleaning Data with R today!

Create Your Free Account

Join over 11,710,000 learners and start Importing & Cleaning Data with R today!