However, if you have looked at a standard text on R or read some of the online discussions, you might feel that there is a steep learning curve of six months or more to grok the language. I will debunk this myth through my book by focusing on practical essentials instead of theory.
If you have programmed in some language in the past (whether that language be SAS, SPSS, C, C++, C#, Java, Python, Perl, Visual Basic, Ruby, Scala, shell scripts, or plain old SQL), even if you are rusty, this book will get you up and running with R in a single day, writing programs for data analysis and visualization.
Table of contents
- Introduction
- R syntax
- Variables and Scope
- Data Structures
- Functions
- Objects
- R packages
- Interactive R through the REPL interface
- Inbuilt help in R
- R programs and scripts
- Reading in Data
- Data Quality Checks in R
- Descriptive Statistics and Visualization
- Interactive Charts and Plots
- Geographical Maps and Charts
- Regression Modeling & Predictive Models
- Machine Learning & Predictive Models
Pages : | 172 |
Size : | 5.5 MB |
Downloads: | 71 |
Created: | 2022-02-03 |
License: | CC BY-SA |
Author(s): | Sivakumaran Raman |
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