Description
Course info
Level
Beginner
Updated
Aug 15, 2019
Duration
2h 6m
Description

Have you ever wanted to learn how R is used to handle the most common data types? The knowledge you will gain here is foundational for any aspiring R programmer. In this course, Querying and Converting Data Types in R, you will develop an understanding of all of these data types and how they are processed, converted, and filtered. First, you will explore general data analysis concepts and take a look at the data frame and its main alternatives. Next, you will learn the major data types in R: numeric, integer, factor, character, boolean, and date and time. Finally, you will discover how these data types are used in a data frame. The query and filtering methods largely depend on the data types available in that data frame. When you are finished with this course, you will have your first set of skills that will be invaluable in your further learning path. In fact, the skills taught here are so important in data science, that most of it can be used in other languages (Python, Matlab) and programs (SPSS).

About the author
About the author

Martin is a trained biostatistician, programmer, consultant and data science enthusiast. His main objective: Explaining data science in a straightforward way. You can find his latest work over at: r-tutorials.com

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
[Autogenerated] welcome to clearing and converting data types in our This is Martin Berger for Blore. Aside, in these entry level course, you will see how our issues to handle the most common data types. The knowledge you will gain here is foundational for any aspiring our program. The main date of former in our is the data frame. The beauty off that former is its ability to capture various state of types like numbers, text categories or logical data. In this course, you will develop in understanding off all of these data types and how they are processed, converted and felt it. We also work at the data frame Lau and perform queries. Clearing or filtering is a common task in analytics. Therefore, it is important to learn it early on in your learning path, and you will also learn about the most common alternatives to a data frame, namely the table and the data dot table. By the end of discourse, you should know the common data types until they handled in our and you will also know how to perform standard tasks on a date, a frame to fully benefit from this course, you do not need any prior coding or data analysis skills, I will guide you through the most important concepts off our and data analysis. We're going to start right at the beginning. In fact, the material taught here has relevance in other analytics programs as well. I really hope you used this course as your primer to data analysis and are the pleura side cost library will then give you plenty of opportunity to get you another step further into our