Tidyverse is a very popular set of R packages developed by RStudio’s chief scientist, Hadley Wickham. It’s designed to make data operations easier, thus helping to improve data manipulation, exploration, and visualization. Tidyverse is essential for any data scientist working with R. Whether or not you’re on that path, you’ll never want to go back to vanilla R again!

The name "tidyverse" hints at the package’s role in data science — it excels at tidying up even excessively large datasets. "Tidy data" is structured properly and in a way that makes data analysis and visualization easier. Wickham’s "tidy" approach means each variable should be a column, each observation should be a row, and each type of observational unit should be a table. If you’ve worked with SQL and relational databases before, you’ll recognize most of the concepts in this course.

Programming with R is one of most desired skill sets in the current data analytics job market. Every step towards a greater understanding of R and its capabilities allows you to use the language more wisely and efficiently.

Problems you encounter while working with data can be easily solved with tidyverse. Your data isn’t in a standard format? Your tables have a strange structure? Or perhaps you’ve encountered errors in the encoding of factor data? Well, your worries are over! In this course, we’ll learn how to handle all of these problems and more.

What Are the Requirements?

Just a web browser and an Internet connection

This Course Will Teach You How To:

  • Use packages in R
  • Work with a new data format – tibble
  • Manipulate data with dplyr and tidyr
  • Import files with readr
  • Work with factors using forcats

Who Should Take This Course?

  • Students taking classes in data analysis
  • Data and business analysts
  • Beginner data scientists
  • Anyone who wants to clarify data before creating any kind of charts
  • Anyone interested in data science or statistical analysis
  • You!

What’s in it for me?

  • 148 interactive exercises. Learn at your own pace, from anywhere and anytime. Interact with hands-on exercises for improved retention.
  • Lifetime access to the course. When you purchase the course, you’ll get instant personal access to all of its content.
  • Certificate of completion. After you successfully finish all of the exercises, you’ll get a downloadable PDF certificate to showcase your accomplishment.
  • 30-day money back guarantee. If you’re not satisfied with the quality of the course, you can get a refund within 30 days of your purchase.
  • Hints for the exercises. You can ask questions and share insights with other members of the Vertabelo Academy community through the Disqus tab. You can also drop us a line directly, and we’ll be more than happy to answer! 😉
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    Basic Data Analytics

    Includes 8 courses Tidyverse, SQL Practice Set, Introduction to Python for Data Science, Statistics 101, Data Visualization 101, Introduction to R, SQL Basics, SQL JOINs

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    Table of contents

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    1. Introduction

    Briefly review your knowledge of R programming basics.

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    2. Tibble

    Meet tibble, the most convenient package for dealing with data frames in R.

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    3. Dplyr – basics

    Learn how to filter rows, select columns, and sort data with dplyr.

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    4. Dplyr – advanced

    Learn how to change the structure of data with dplyr.

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    5. Tidyr

    Learn about tidyr and its functions to convert between wide and long data format, and other ways to convert between data formats in R.

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    6. Forcats

    Categorical variables? Character vectors? Factors? Bring it on!

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    7. Readr

    Files... there are lots of ways to create them, but how do we extract data from them? Let's learn how to read data from files using readr!

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    8. Final quiz

    This is it! You’ve come a long way. Now, it’s time to check what you know about tidyverse!

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