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After mastering the basics of R, you're now ready to expand your R toolkit and learn some essential data analysis skills. In this course, we'll take a look at the list data structure, learn all there is to know about functions, and perform one-line coding wizardry with "apply" functions.

Lists are special data structures in R, but they're present in many other programming languages, too. R list is just an unordered collection of objects; these objects can range from anything like single values to vectors, data frames, and even other lists! Lists are especially popular in R data analysis, so it's important that you learn them well.

Functions allow us to write abstract, reusable code. You've already worked with many built-in functions in R (and possibly other languages as well). Suffice to say that writing and using functions is a fundamental skill for data analysis, so we'll help you unpack everything about R functions.

A special family of functions allows you to apply a given function to each member of R list, data frame, or vector. These functions include lapply(), sapply(), and tapply(). We'll teach you how to use these "apply" functions to perform powerful data analysis in R with just a single line of code!

Looking for hands-on practice with the material? There's plenty to go around! We've carefully designed 105 exercises to present you with real-world business problems.

Ready to dive deep into R? Join us for a world of data analysis fun!

Requirements

  • Just a web browser and an Internet connection.
  • We assume you've completed Introduction to R; we'll build on that knowledge here.

Learn How To:

  • Use R list to perform more complex data analysis.
  • Create your own functions for analyzing data.
  • Use conditional "if" statements in your code, especially within functions.
  • Manipulate data more efficiently with the use of lapply(), sapply() and tapply().

Who Should Take This Course?

  • Students who already passed Introduction to R.
  • Data and business analysts who want to go beyond data frames and perform more complex data analysis.
  • Those who are interested in data science and data analysis and are familiar with the basics of R.
  • Anyone who wants to go deeper into the R programming world.

What's in It for Me?

  • 105 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.
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    One to Rule 'Em All

    Includes 41 courses Python Basics. Part 1, Python Basics. Part 2, Python Basics. Part 3, Python Data Structures in Practice, Built-in Algorithms in Python, Working with Strings in Python, SQL Basics, SQL Practice Set, SQL JOINs, Standard SQL Functions, Creating Basic SQL Reports, Window Functions, Revenue Trend Analysis in SQL, How to INSERT, UPDATE, and DELETE Data in SQL, Recursive Queries, Creating Tables in SQL, Introduction to R, Tidyverse, Data Visualization 101, Statistics 101, SQL Basics in MS SQL Server, How to Insert, Update, or Delete Data in MS SQL Server, Common Functions in MS SQL Server, Revenue Trend Analysis in SQL Server, Creating Basic SQL Reports in SQL Server, Window Functions in MS SQL Server, Recursive Queries in MS SQL Server, GROUP BY Extensions in MS SQL Server, Introduction to Python for Data Science, How to Read and Write CSV Files in Python, How to Read and Write JSON Files in Python, Lists and Functions in R, Data Manipulation in R, SQL Basics in PostgreSQL, PostgreSQL JOINs, SQL Practice Set in PostgreSQL, Window Functions in PostgreSQL, Recursive Queries in PostgreSQL, Writing User-Defined Functions in PostgreSQL, PostGIS, How to Read and Write Excel Files in Python

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    Table of contents

    Progress: 0% completed 0 of 105 exercises done

    1. Intro Quiz

    Review and check your knowledge of base R.

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    2. Lists

    Learn how to work with lists, R's data type to combine values of different data types into one object.

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    Introduction

    3. Functions

    Learn how to create your own functions in R.

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    4. Apply functions

    Learn how to apply a function to each row, column, or list member in parallel without using loops.

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    Introduction

    5. Final Quiz

    Test your knowledge of lists and functions.

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