Introduction to R, Part 3 of 3: Working with Data image

Introduction to R, Part 3 of 3: Working with Data

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Folder lesson (170 mins)

Introduction to R, Part 3 of 3: Working with Data

Popularity
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Course Description

Course description

Programmers, data analysts, data scientists, and anyone who works with data has probably spent many hours staring at data organized into rows and columns. Those data structures are referred to as spreadsheets or tables and they form the basis for much of the data manipulation done today. Finish the first leg in your R journey with a look at two special objects in R used to work with tabular, or tabled data: the Data Frame and Data Table. Explore their internal structure, how to create them, and how they can be manipulated, queried, filtered, joined, grouped, or sorted just as if they were database table objects. Lastly, take a look at some helpful functions in R which can be used to streamline your code.

Each LearnNowOnline training course is made up of Modules (typically an hour in length). Within each module there are Topics (typically 15-30 minutes each) and Subtopics (typically 2-5 minutes each). There is a Post Exam for each Module that must be passed with a score of 70% or higher to successfully and fully complete the course.


Prerequisites

This course assumes that student has some programming experience and using a personal computer. No other experience is required.


Meet the expert

Kevin McCarty

Kevin McCarty is a computer professional with over 30 years of experience in the industry as a programmer, project manager, database administrator, architect, and data scientist. He is a Microsoft Certified Trainer with over 25 individual certifications in programming and database technologies and serves as the chapter leader of the Boise SQL Server Users Group. A former Army officer and Eagle Scout, he holds a doctorate in Computer Science and a lifelong love of learning.

Video Runtime

100 Minutes

Time to complete

170 Minutes

Course Outline

Data Frames and Tables

Data Frames (10:54)

  • Introduction (00:44)
  • Data Frames (01:26)
  • Data Frame vs. Matrix (01:14)
  • Working with Data Frames (02:06)
  • Subsetting Data Frames (00:25)
  • Negative Subsetting (00:37)
  • Subsetting with Logicals (00:38)
  • Sorting a Data Frame (00:35)
  • Grouping Data Frame Data (01:10)
  • But Wait, There's More! (01:17)
  • Summary (00:37)

Working With Data Frames (30:39)

  • Introduction (00:31)
  • Demo: Creating and Accessing Data Frames (05:35)
  • Demo: Negative and Logical Subsetting (02:59)
  • Demo: Viewing and Summarizing Subsets (04:08)
  • Demo: Summarize with Filters (03:59)
  • Demo: Joins – The Inner (04:53)
  • Demo: The Outer, Right, and Left Joins (02:19)
  • Exercise - Working with Data Frames (00:40)
  • Demo: Data Frame Solutions (04:50)
  • Summary (00:42)

Data Tables (15:22)

  • Introduction (00:46)
  • Data Tables vs. Data Frame (01:19)
  • Working with the Data Table (02:45)
  • Joining Data Tables - Merge (01:08)
  • Inner Join (01:29)
  • Outer Join (04:35)
  • Left Join (00:47)
  • Right Join (00:31)
  • NOT Inner Join (01:15)
  • Summary (00:42)

Working With Data Tables (19:19)

  • Introduction (00:36)
  • Demo: Working with Data Tables (05:26)
  • Demo: Subsetting with the Data Table (03:21)
  • Demo: A More Complex Query (05:32)
  • Demo: The Joins (03:32)
  • Summary (00:49)

Shortcuts (23:53)

  • Introduction (00:35)
  • Time Savers - cut() (01:31)
  • The cut() Function (00:20)
  • Time Savers – with() Function (00:46)
  • Time Savers – attach() Function (00:58)
  • Alternatives to attach() Function (01:21)
  • Demo - Timesaver Functions (00:38)
  • Demo: Shortcuts - cut() Function (05:26)
  • Demo: Shortcuts - with() and attach() Functions (03:49)
  • Exercise - Data Table (01:10)
  • Demo: Data Table Solutions (05:57)
  • Summary (01:15)