Ementorhub

Wrangling Data in the Tidyverse

This course is part of Tidyverse Skills for Data Science in R Specialization

Instructors: Shannon Ellis, PhD +3 more

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What you'll learn

Apply Tidyverse functions to transform non-tidy data to tidy data

Conduct basic exploratory data analysis

Conduct analyses of text data

Skills you'll gain

Data Wrangling

Text Mining

Data Cleansing

Data Transformation

Time Series Analysis and Forecasting

Data Processing

Exploratory Data Analysis

R Programming

Tidyverse (R Package)

Data Manipulation

There are 6 modules in this course

This course covers many of the critical details about handling tidy and non-tidy data in R such as converting from wide to long formats, manipulating tables with the dplyr package, understanding different R data types, processing text data with regular expressions, and conducting basic exploratory data analyses. Investing the time to learn these data wrangling techniques will make your analyses more efficient, more reproducible, and more understandable to your data science team. In this specialization we assume familiarity with the R programming language. If you are not yet familiar with R, we suggest you first complete R Programming before returning to complete this course.

Working With Factors, Dates, and Times

Working With Strings and Text and Functional Programming

Exploratory Data Analysis

Case Studies

Project: Wrangling data in the Tidyverse