One of the most popular plotting libraries in R is not the plotting function in R base, but the ggplot2 library. People use that because it is flexible. This library also works using the philosophy of “grammar of graphics”, which is not to generate a visualization upon a function call, but to define what should […]

# Archive | R for Data Science

## Exploring Data using dplyr in R

When you are working on a data science project, the data is often tabular structured. You can use the built-in data table to handle such data in R. You can also use the famous library dplyr instead to benefit from its rich toolset. In this post, you will learn how dplyr can help you explore […]

## A Gentle Introduction to Using R Markdown

One reason people would like to use RStudio for their work is because of the R Markdown. This made the RStudio not only an IDE for programming in R, but also a notepad in which they could put down their thoughts with R code and results. In this post, you will learn how to use […]

## Statistical Tests in R

R as a data analytics platform is expected to have a lot of support for various statistical tests. In this post, you are going to see how you can run statistical tests using the built-in functions in R. Specifically, you are going to learn: What is t-test and how to do it in R What […]

## Generating Random Numbers in R

Whether working on a machine learning project, a simulation, or other models, you need to generate random numbers in your code. R as a programming language, has several functions for random number generation. In this post, you will learn about them and see how they can be used in a larger program. Specifically, you will […]

## Plotting Graphs in R

Visualizing data can sometimes help people understand it better. As a data analytics platform, R provided some advanced plotting functions. In this post, you will learn how to use the built-in plot functions to create some common visualization. Specifically, you will learn how to create: Line plot Scatter plot Pie charts Let’s get started. Overview […]

## Logic, Flow Control, and Functions in R

R is a procedural programming language. Therefore, it has the full set of flow control syntax like many other languages. Indeed, the flow control syntax in R is similar to Java and C. In this post, you will see some examples of using the flow control syntax in R. Let’s get started. Overview This post […]

## Built-in Datasets in R

The ecosystem in R contains not only the function libraries to help you perform statistical analysis but also the data library that gives you some famous datasets to test out your program. There are a lot of built-in datasets in R. In this post, you will: Learn some of the built-in datasets Know how to […]

## Operations on Vectors in R

Vectors in R is the native way of handling data. In addition to the vector operations you saw in the linear algebra textbook, R supports a lot more. In this post, you will learn about: How to manipulate a vector How to treat vectors as sets Let’s get started. Overview This post is divided into […]

## Surviving in the R Environment

R is not only a programming language but also a programming shell with read-eval-print loop (REPL). The shell is how most people use R. But when you drill deeper, knowing more about what’s working behind the scenes is handy. In this post, you will learn: How to manage variables in R How to manage packages […]