Alex Nordeen

Learn R Programming in 24 Hours (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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?

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: PublishDrive
• Seitenzahl: 450
• Erscheinungstermin: 31. Oktober 2021
• Englisch
• ISBN-13: 6610000314713
• Artikelnr.: 62877194