Lecture No.1 Introduction To R Language

Tayyab Rajput

Learning Agenda :

R is an open-source programming language that is widely used as a statistical software and data analysis tool. R generally comes with the Command-line interface. R is available across widely used platforms like Windows, Linux, and macOS. Also, the R programming language is the latest cutting-edge tool.

Instalation of R:

Easy way to install the R language in system to checking this link "Click Here"

History Of R Language:

R was first implemented in the early 1990's by Robert Gentleman and Ross Ihaka, both faculty members at the University of Auckland. Robert and Ross established R as an open source project in 1995. Since 1997, the R project has been managed by the R Core Group.

Uses Of R:

Although R is a popular language used by many programmers, it is especially effective when used for R offers a wide variety of statistics-related libraries and provides a favorable environment for statistical computing and design. In addition, the R programming language gets used by many quantitative analysts as a programming tool since it's useful for data importing and cleaning.

  • Data analysis
  • Statistical inference
  • Machine learning algorithms

why we use R:

R offers a wide variety of statistics-related libraries and provides a favorable environment for statistical computing and design. In addition, the R programming language gets used by many quantitative analysts as a programming tool since it's useful for data importing and cleaning.

Advantages of R:

There are many advantages of the R language by which we can solve of different problems. Following are some advantages of the R language.

  • It's open-source
  • It's platform-independent
  • It has lots of packages
  • It's great for statistics
  • It's well suited for Machine Learning
  • R lets you perform data wrangling
  • R is still growing

Disadvantages of R :

Here we will discuss some disadvantages of the R.

  • It’s a complicated language. R has a steep learning curve. It’s a language best suited for people who have previous programming experience.
  • It’s not as secure. R doesn’t have basic security measures. Consequently, it’s not a good choice for making web-safe applications. Also, R can’t be embedded in web browsers.
  • It’s slow. R is slower than other programming languages like Python or MATLAB.
  • It takes up a lot of memory. Memory management isn’t one of R’s strong points. R’s data must be stored in physical memory. However, the increasing use of cloud-based memory may eventually make this drawback moot.
  • It doesn’t have consistent documentation/package quality. Docs and packages can be patchy and inconsistent, or incomplete. That’s the price you pay for a language that doesn’t have official, dedicated support and instead is maintained and added to by the community. For your more information we add a picture that will describe better.

Environment for the R language:

There are many IDE's for R language but the most famaous are three for the execution of our R scripts.

  • R Studio
  • Visual Studio
  • Jupyter Notebook