Author: Paul Teetor Publisher: "O'Reilly Media, Inc." ISBN: 1449303862 Category : Computers Languages : en Pages : 56
Book Description
R is a powerful tool for statistics and graphics, but getting started with this language can be frustrating. This short, concise book provides beginners with a selection of how-to recipes to solve simple problems with R. Each solution gives you just what you need to know to use R for basic statistics, graphics, and regression. You'll find recipes on reading data files, creating data frames, computing basic statistics, testing means and correlations, creating a scatter plot, performing simple linear regression, and many more. These solutions were selected from O'Reilly's R Cookbook, which contains more than 200 recipes for R that you'll find useful once you move beyond the basics.
Author: Paul Teetor Publisher: "O'Reilly Media, Inc." ISBN: 1449303234 Category : Computers Languages : en Pages : 56
Book Description
R is a powerful tool for statistics and graphics, but getting started with this language can be frustrating. This short, concise book provides beginners with a selection of how-to recipes to solve simple problems with R. Each solution gives you just what you need to know to use R for basic statistics, graphics, and regression. You'll find recipes on reading data files, creating data frames, computing basic statistics, testing means and correlations, creating a scatter plot, performing simple linear regression, and many more. These solutions were selected from O'Reilly's R Cookbook, which contains more than 200 recipes for R that you'll find useful once you move beyond the basics.
Author: Molly Baz Publisher: Clarkson Potter ISBN: 0593138279 Category : Cooking Languages : en Pages : 306
Book Description
NEW YORK TIMES BESTSELLER • A thoroughly modern guide to becoming a better, faster, more creative cook, featuring fun, flavorful recipes anyone can make. ONE OF THE BEST COOKBOOKS OF THE YEAR: NPR, Food52, Taste of Home “Surprising no one, Molly has written a book as smart, stylish, and entertaining as she is.”—Carla Lalli Music, author of Where Cooking Begins If you seek out, celebrate, and obsess over good food but lack the skills and confidence necessary to make it at home, you’ve just won a ticket to a life filled with supreme deliciousness. Cook This Book is a new kind of foundational cookbook from Molly Baz, who’s here to teach you absolutely everything she knows and equip you with the tools to become a better, more efficient cook. Molly breaks the essentials of cooking down to clear and uncomplicated recipes that deliver big flavor with little effort and a side of education, including dishes like Pastrami Roast Chicken with Schmaltzy Onions and Dill, Chorizo and Chickpea Carbonara, and of course, her signature Cae Sal. But this is not your average cookbook. More than a collection of recipes, Cook This Book teaches you the invaluable superpower of improvisation though visually compelling lessons on such topics as the importance of salt and how to balance flavor, giving you all the tools necessary to make food taste great every time. Throughout, you’ll encounter dozens of QR codes, accessed through the camera app on your smartphone, that link to short technique-driven videos hosted by Molly to help illuminate some of the trickier skills. As Molly says, “Cooking is really fun, I swear. You simply need to set yourself up for success to truly enjoy it.” Cook This Book will help you do just that, inspiring a new generation to find joy in the kitchen and take pride in putting a home-cooked meal on the table, all with the unbridled fun and spirit that only Molly could inspire.
Author: JD Long Publisher: "O'Reilly Media, Inc." ISBN: 1492040630 Category : Computers Languages : en Pages : 600
Book Description
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data
Author: Hadley Wickham Publisher: "O'Reilly Media, Inc." ISBN: 1491910364 Category : Computers Languages : en Pages : 521
Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author: Atmajitsinh Gohil Publisher: Packt Publishing Ltd ISBN: 1783989513 Category : Computers Languages : en Pages : 236
Book Description
If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.
Author: Alex Nordeen Publisher: Guru99 ISBN: Category : Computers Languages : en Pages : 349
Book Description
R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?
Author: Moshe Arye Milevsky Publisher: Springer Nature ISBN: 303051434X Category : Business & Economics Languages : en Pages : 302
Book Description
This book provides computational tools that readers can use to flourish in the retirement income industry. Each chapter describes recipe-like algorithms and explains how to implement them via simple scripts in the freely available R coding language. Students can use those skills to generate quantitative answers to the most common questions in retirement income planning, as well as to develop a deeper understanding of the finance and economics underlying the field itself. The book will be an excellent asset for experienced students who are interested in advanced wealth management, and specifically within courses that focus on holistic modeling of the retirement income process. The material will also be useful to current and future wealth management professionals within the financial services industry. Readers should have a solid understanding of financial principles, as well as a rudimentary background in economics and accounting.
Author: Larry Pace Publisher: Apress ISBN: 1484201302 Category : Computers Languages : en Pages : 253
Book Description
R Recipes is your handy problem-solution reference for learning and using the popular R programming language for statistics and other numerical analysis. Packed with hundreds of code and visual recipes, this book helps you to quickly learn the fundamentals and explore the frontiers of programming, analyzing and using R. R Recipes provides textual and visual recipes for easy and productive templates for use and re-use in your day-to-day R programming and data analysis practice. Whether you're in finance, cloud computing, big or small data analytics, or other applied computational and data science - R Recipes should be a staple for your code reference library.
Proudly powered by WordPress |
Theme: Rits Blog by Crimson Themes.
Author: Paul Teetor
Author: Paul Teetor
Author: Molly Baz
Author: JD Long
Author: Hadley Wickham
Author: Atmajitsinh Gohil
Author: Alex Nordeen
Author: Moshe Arye Milevsky
Author: Winston Chang
Author: Larry Pace