{"product_id":"learn-r-programming-in-24-hours","title":"Learn R Programming in 24 Hours","description":"\u003cp\u003eR 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.\u003c\/p\u003e\n\u003cp\u003eR programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple.\u003c\/p\u003e\n\u003cp\u003eR provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable of Contents\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 1: What is R Programming Language? Introduction \u0026 Basics\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 2: How to Download \u0026 Install R, RStudio, Anaconda on Mac or Windows\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 3: R Data Types, Arithmetic \u0026 Logical Operators with Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 4: R Matrix Tutorial: Create, Print, add Column, Slice\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 5: Factor in R: Categorical \u0026 Continuous Variables\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 6: R Data Frame: Create, Append, Select, Subset\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 7: List in R: Create, Select Elements with Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 8: R Sort a Data Frame using Order()\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 9: R Dplyr Tutorial: Data Manipulation(Join) \u0026 Cleaning(Spread)\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 10: Merge Data Frames in R: Full and Partial Match\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 11: Functions in R Programming (with Example)\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 12: IF, ELSE, ELSE IF Statement in R\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 13: For Loop in R with Examples for List and Matrix\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 14: While Loop in R with Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 17: How to Replace Missing Values(NA) in R: na.omit \u0026 na.rm\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 19: Correlation in R: Pearson \u0026 Spearman with Matrix Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 20: R Aggregate Function: Summarise \u0026 Group_by() Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 21: R Select(), Filter(), Arrange(), Pipeline with Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 22: Scatter Plot in R using ggplot2 (with Example)\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 23: How to make Boxplot in R (with EXAMPLE)\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 24: Bar Chart \u0026 Histogram in R (with Example)\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 25: T Test in R: One Sample and Paired (with Example)\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 26: R ANOVA Tutorial: One way \u0026 Two way (with Examples)\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example]\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 28: Decision Tree in R with Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 29: R Random Forest Tutorial with Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 30: Generalized Linear Model (GLM) in R with Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 31: K-means Clustering in R with Example\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 32: R Vs Python: What's the Difference?\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eChapter 33: SAS vs R: What's the Difference?\u003c\/strong\u003e\u003c\/p\u003e","brand":"None","offers":[{"title":"Livre numérique Kobo","offer_id":46668417269970,"sku":"44582125-e76e-3e28-b339-88b47d5bbfb4","price":14.08,"currency_code":"CAD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0655\/8980\/5233\/files\/image_e6c82300-5ed6-4a4e-87eb-7214e5b2d47c.jpg?v=1762417517","url":"https:\/\/www.indigo.ca\/fr\/products\/learn-r-programming-in-24-hours","provider":"Indigo","version":"1.0","type":"link"}