Ementorhub

Data Analysis with Tidyverse

This course is part of Expressway to Data Science: R Programming and Tidyverse Specialization

Instructor: Jane Wall

What you'll learn

You will learn to identify and describe tidy data and transform a non-tidy data set to be tidy in R.

You will learn to analyze data between multiple related data tables.

You will be learn to apply regular expressions to detect patterns in strings and return matches and replace patterns with new values.

Skills you'll gain

Data Import/Export

Data Analysis

Tidyverse (R Package)

Data Wrangling

Data Manipulation

Relational Databases

R Programming

Ggplot2

Data Transformation

Data Cleansing

There are 5 modules in this course

• you want to do data analysis but don’t know programming • you know programming but aren’t too familiar with R • you know some R programming but want to learn more about the tidyverse verbs It is best taken following the first course in the specialization or if you already are familiar with ggplot, RMarkdown, and basic function writing in R. You will use learn to use readr to read in your data, dplyr to analyze your data, and stringr and forcats to manipulate strings and factors.

Tidying Data

Relational Data

String Manipulation and Regular Expressions

Categorical Variables and Factors

Explore more from Data Analysis

Introduction to R Programming and Tidyverse

Expressway to Data Science: R Programming and Tidyverse

Wrangling Data in the Tidyverse

Tidyverse Skills for Data Science in R