R Programming
indgår i R Programming serien
- Indbinding:
- Paperback
- Sideantal:
- 210
- Udgivet:
- 6. maj 2023
- Størrelse:
- 152x12x229 mm.
- Vægt:
- 312 g.
- 8-11 hverdage.
- 21. november 2024
På lager
Normalpris
Abonnementspris
- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af R Programming
R is an open-source statistical environment and programming language that has grown in popularity for data management and analysis in various industries. "R" Programming teaches you all the R you'll ever need in a rapid and painless manner. This accessible tutorial taught you your way around a list with no previous programming expertise and loads of practical examples, step-by-step exercises, and sample code. This book covers the most significant modeling and prediction methods, as well as their applications.
Learn how to use R to transform raw data into knowledge, understanding, and insight. This book introduces you to R, RStudio, and the tidyverse, a set of R tools that work together to make data research simple, fluent, and enjoyable. This book is meant to get you practicing data science as fast as possible, even if you have no prior programming expertise. You'll get a comprehensive grasp of the data science cycle and the fundamental tools you'll need to handle the details.
R is becoming more well-known by the day, as large institutions embrace it as a standard. Its popularity stems partly from the fact that it is a free tool replacing expensive statistical software products that may take an undue amount of time to master. Furthermore, R allows a user to do complicated statistical analyses with only a few keystrokes, making advanced studies accessible and clear to a broad audience.
Learn how to import data, construct and dismantle data objects, traverse R's environment system, develop your own functions, and utilize all of R's programming tools with this book. This book will not only teach you how to program but also how to use R for more than simply displaying and analyzing data.
Most of the chapters are written for you to understand statistical data, so if you are a student, this book can guarantee to teach you some basic statistics that will help you get good grades.
The first two chapters are based on beginner's level of R programming, mainly teaching how to successfully install and run the program on your device and introducing Rstudio to you. You will get complete guidance.
Chapters three and four will teach you some basic and simple lines of code and how you can successfully execute them on your device. There will be some simple maths included. After that, you will start chapter five, which is completely based on statistics.
Chapters six and seven will take your attention to more IT. If you already know basic HTML you will get more information in these chapters as they include similar topics as HTML.
Finally, you arrived at chapters eight, nine, and ten, which will enable you to create and run your data. These chapters will complete your journey by allowing you to understand how data frames work and how you can work with different types of data. You will also see how you can install premade data packages that can be helpful when you want to practice more. After that, you will know how to visualize your data in different forms of charts, graphs, etc.
The book is highly informative with lots of code, and also I added tons of pictures of how the code will look in r studio. Following the book, you will be able to start Rstudio and use the program smoothly.
Learn how to use R to transform raw data into knowledge, understanding, and insight. This book introduces you to R, RStudio, and the tidyverse, a set of R tools that work together to make data research simple, fluent, and enjoyable. This book is meant to get you practicing data science as fast as possible, even if you have no prior programming expertise. You'll get a comprehensive grasp of the data science cycle and the fundamental tools you'll need to handle the details.
R is becoming more well-known by the day, as large institutions embrace it as a standard. Its popularity stems partly from the fact that it is a free tool replacing expensive statistical software products that may take an undue amount of time to master. Furthermore, R allows a user to do complicated statistical analyses with only a few keystrokes, making advanced studies accessible and clear to a broad audience.
Learn how to import data, construct and dismantle data objects, traverse R's environment system, develop your own functions, and utilize all of R's programming tools with this book. This book will not only teach you how to program but also how to use R for more than simply displaying and analyzing data.
Most of the chapters are written for you to understand statistical data, so if you are a student, this book can guarantee to teach you some basic statistics that will help you get good grades.
The first two chapters are based on beginner's level of R programming, mainly teaching how to successfully install and run the program on your device and introducing Rstudio to you. You will get complete guidance.
Chapters three and four will teach you some basic and simple lines of code and how you can successfully execute them on your device. There will be some simple maths included. After that, you will start chapter five, which is completely based on statistics.
Chapters six and seven will take your attention to more IT. If you already know basic HTML you will get more information in these chapters as they include similar topics as HTML.
Finally, you arrived at chapters eight, nine, and ten, which will enable you to create and run your data. These chapters will complete your journey by allowing you to understand how data frames work and how you can work with different types of data. You will also see how you can install premade data packages that can be helpful when you want to practice more. After that, you will know how to visualize your data in different forms of charts, graphs, etc.
The book is highly informative with lots of code, and also I added tons of pictures of how the code will look in r studio. Following the book, you will be able to start Rstudio and use the program smoothly.
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