Programming R for Data Analysts

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Programming R for Data Analysts

Authors: Justin Flett, Martin Burger

The R language is widely used among statisticians and data miners for developing statistical software and data analysis.

What You Will Learn

  • You will learn analytical skills with one of the most widely used languages in data

Pre-requisites

  • Fundamentals of computer programming
  • Fundamentals of creating variables

Beginner

Learn to work with basic data types and select the appropriate data structure as well as create a vector variable and access data in a factor.

Programming R Vectors and Factors

by Justin Flett

Dec 31, 2019 / 1h 8m

1h 8m

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Description

R is a popular programming language for statistical computing. In this course, Programming R Vectors and Factors, you will gain foundational knowledge of all data types and structures within R. First, you will learn some of the most commonly used data types and data structures used in R. Then, we will explore all of the data types and structures in R. Next, we will dive deeper into the specific data structures of vectors and factors. Finally, we will discover how to program and work with vectors and factors including accessing, adding and removing elements, using and understanding coercion and performing common operations on vectors and factors.

Table of contents
  1. Course Overview
  2. Understanding Vectors in R
  3. Working with Vectors in R
  4. Understanding Factors in R
  5. Working with Factors in R

Intermediate

Store and access data in a data frame, a matrix, and a list, and remove elements from a list and store and access data in an array.

Managing Data in R Using Data Frames

by Martin Burger

Sep 25, 2019 / 2h 1m

2h 1m

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Description

Learn to work with very popular and versatile tabular data types in R. When using R, there is no way around the data frame and its alternatives. In this course, Managing Data in R Using Data Frames, you will learn that tabular data (data.frame, data.table, tibble) are the standard data type in R and most of the analyses performed in R use this data format. First, you will discover how to manipulate and reshape a raw data frame. Then, you will explore the common tasks such as table import, factor conversion, formatting of a table header, orientation in a table, column splits, column removal and addition, fusion of multiple tables, variable transformations, query, as well as export of a table. Finally, you will produce a clean data frame which can be used for detailed analysis or passed on to team members.

When you complete this course, you’ll have the skills and knowledge to perform standard tasks on data frames and can understand the many advantages of a data frame.

Table of contents
  1. Course Overview
  2. Understanding the Concepts Behind a Data Frame
  3. Exploring a Data Frame
  4. Making Changes to a Data Frame
  5. Continuing your Learning Path and Summary

Programming R Matrices, Lists, and Arrays

by Pluralsight

Jan 6, 2020 / 1h 20m

1h 20m

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Description

R is a popular programming language for statistical computing. In this course, Programming R Matrices, Lists, and Arrays, you will gain foundational knowledge of data types and structures used within R. First, you will discover how to work specifically with the list data structure within R. Next, you will learn about matrices and how to work with matrices in R. Finally, you will explore how to work with the array data structure within R. When you are finished with this course, you will have the skills and knowledge of working with some of the most commonly used data types and structures in R.

Table of contents
  1. Course Overview
  2. Understanding Lists in R
  3. Working with Lists in R
  4. Understanding Matrices in R
  5. Working with Matrices in R
  6. Understanding Arrays in R
  7. Working with Arrays in R
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