Learn R Programming in 24 Hours (eBook, ePUB)
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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 ContentsChapter 1: What is R Programming Language? Introduction & BasicsChapter 2: How to Download & Install ...
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?
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?
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