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R Programming for Data Science

17 chapters · 1 free to read, 16 in the PDF

Learn the fundamentals of R programming essential for data science.

This is an essential ebook in R programming and discusses the core programming principles of R.

The first section covers the fundamentals of R programming language and how to start using it for finance. You will also learn the basics of data analysis with R using the common data structures such as vectors, matrices, lists and data frames.

The next section covers the key topics like control structures, relational and logical operators, conditional statements, loops and functions.

You will also learn about how to import data into R from various sources such as flat files, excel files, databases, web and other software.

Finally, you will learn the concepts of R functions so that you can write your own functions and automate analysis tasks.

Chapters

  1. 1Relational Operators in RRead free
  2. 2Logical Operators in RIn the PDF
  3. 3Conditional Statements in RIn the PDF
  4. 4For Loop in R ProgrammingIn the PDF
  5. 5While and Repeat Loop in R ProgrammingIn the PDF
  6. 6Functions in R ProgrammingIn the PDF
  7. 7Creating Functions in RIn the PDF
  8. 8Apply Functions in RIn the PDF
  9. 9Importing Data from External Data Sources in RIn the PDF
  10. 10Importing Data Using read.csv in RIn the PDF
  11. 11Import Data using read.table in RIn the PDF
  12. 12Importing Data Using data.table – fread in RIn the PDF
  13. 13Importing Data from Excel in RIn the PDF
  14. 14Using XLConnect in R ProgrammingIn the PDF
  15. 15Importing Data from a Database in RIn the PDF
  16. 16SQL Queries from RIn the PDF
  17. 17Importing Data from Web in RIn the PDF