# Articles by Rsquared Academy Blog - Explore Discover Learn

### Handling Categorical Data in R – Part 4

January 13, 2022 |

This is part 4 of a series on “Handling Categorical Data in R” where we are learning to read, store, summarize, reshape & visualize categorical data. Below are the links to the other articles of this series: Part 1 - Introduction to Factor Par...

### Handling Categorical Data in R – Part 3

January 12, 2022 |

This is part 3 of a series on “Handling Categorical Data in R where we are learning to read, store, summarize, visualize & manipulate categorical data..” In part 1 and part 2 of this series, we understood how R stores categorical data using f...

### Handling Categorical Data in R – Part 2

January 11, 2022 |

This is part 2 of a series on “Handling Categorical Data in R where we are learning to read, store, summarize, visualize & manipulate categorical data..” In part 1 of this series, we understood what categorical data is, how R stores it using fa...

### Handling Categorical Data in R – Part 1

January 6, 2022 |

This is part 1 of a series on “Handling Categorical Data in R.” Almost every data science project involves working with categorical data, and we should know how to read, store, summarize, visualize & manipulate such data. Working with categor...

### rfm 0.2.2

July 30, 2020 |

We’re excited to announce the release of rfm 0.2.2 on CRAN! rfm provides tools for customer segmentation using Recency Frequency Monetary value analysis. It includes a Shiny app for interactive segmentation. You can install rfm with:
`install.packages("rfm")`
In this blog post, we will summarize the changes implemented in the current (0.2.2) ...

### A Comprehensive Introduction to Handling Date & Time in R

April 16, 2020 |

In this tutorial, we will learn to handle date & time in R. We will start off by learning how to get current date & time before moving on to understand how R handles date/time internally and the different classes such as Date & POSIXct/lt. We will spend some time exploring ...

### Date & Time in R – Introduction

April 15, 2020 |

In this new series Handling Date & Time in R, we will learn to handle date & time in R. We will start off by learning how to get current date & time before moving on to understand how R handles date/time internally and the different c...

### Introducing nse2r

January 16, 2020 |

We are excited to announce the nse2r package. NSE (National Stock Exchange) is the leading stock exchange of India, located in the city of Mumbai. While users can manually download data from NSE through a browser, importing this data into R becomes cumbersome. The nse2r R package implements ...

### A Comprehensive Introduction to Command Line for R Users

October 25, 2019 |

In this tutorial, you will be introduced to the command line. We have selected a set of commands we think will be useful in general to a wide range of audience. We have created a RStudio Cloud Project to ensure that all readers are using the same environment while going ...

### A Comprehensive Introduction to Working with Databases using R

August 7, 2019 |

Introduction In a previous post, we had briefly looked at connecting to databases from R and using dplyr for querying data. In this new expanded post, we will focus on the following: connect to & explore database read & write data use RStudio SQL script & knitr SQL engine query data using dplyr ...

### Customer Segmentation using RFM Analysis

July 21, 2019 |

Introduction In a previous post, we had introduced our R package rfm but did not go into the conceptual details of RFM analysis. In this post, we will explore RFM in much more depth and work through a case study as well. RFM (Recency, Frequency & Monetary) analysis is a behavior ...

### pkginfo: Tools for Retrieving R Package Information

July 4, 2019 |

Motivation There are several wonderful tools for retrieving information about R packages, some of which are listed below: cranlogs, dlstats and packageRank for R package download stats pkgsearch and packagefinder for searching CRAN R packages crandb provides API for programatically accessing meta-data cchecks for CRAN check results We have used ...

### Practical Introduction to Market Basket Analysis – Asociation Rules

May 1, 2019 |

Introduction Ever wondered why items are displayed in a particular way in retail/online stores. Why certain items are suggested to you based on what you have added to the cart? Blame it on market basket analysis or association rule mining. Resources Below are the links to all the resources ...

### A follow up note on our web scraping tutorial

April 12, 2019 |

We had published a web scraping tutorial a couple of days back and it had received a good response from the #rstats community. While we thank you for that, we made a mistake in choosing one of the case study as pointed out by @hrbrmstr in this tweet: Whomever runs "... [Read more...]

### Practical Introduction to Web Scraping in R

April 10, 2019 |

Introduction Are you trying to compare price of products across websites? Are you trying to monitor price changes every hour? Or planning to do some text mining or sentiment analysis on reviews of products or services? If yes, how would you do that? How do you get the details available ...

### Shiny Apps for Interactive Data Analysis

March 31, 2019 |

We are excited and happy to share a set of shiny apps built for interactive data analysis and teaching at Rsquared Academy. The apps are part of our R packages and presently cover the following topics: Descriptive Statistics Probability Distributions...

### Visually explore Probability Distributions with vistributions

March 13, 2019 |

We are happy to introduce the vistributions package, a set of tools for visually exploring probability distributions. Installation
```# Install release version from CRAN
install.packages("vistributions")

# Install development version from GitHub
# install.packages("devtools")
Shiny App vistributions includes a shiny app which can be launched using
`vdist_launch_app()`

### Getting Help in R

March 4, 2019 |

Introduction In this post, we will learn about the different methods of getting help in R. Often, we get stuck while doing some analysis as either we do not know the correct function to use or its syntax. It is important for anyone who is new to R to know ...