Blog Archives

RFM Analysis in R

February 11, 2019
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RFM Analysis in R

We are pleased to announce the rfm package, a set of tools for recency, frequency and monetary value analysis, designed keeping in mind beginner/intermediate R users. It can handle: transaction level data customer level data Installation # Install release version from CRAN install.packages("rfm") # Install development version from GitHub # install.packages("devtools") devtools::install_github("rsquaredacademy/rfm") Shiny App rfm includes a shiny app which can be launched using rfm_launch_app() or try the live version here. Read on to...

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Introducing olsrr

February 7, 2019
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Introducing olsrr

I am pleased to announce the olsrr package, a set of tools for improved output from linear regression models, designed keeping in mind beginner/intermediate R users. The package includes: comprehensive regression output variable selection procedures heteroskedasticiy, collinearity diagnostics and measures of influence various plots and underlying data If you know how to build models using lm(), you will find olsrr very useful. Most of the functions use...

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SQL for Data Science – Part 2

January 1, 2019
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Introduction This is the fourth post in the series R & Databases. You can find the links to the other two posts of this series below: Quick Guide: R & SQLite Data Wrangling with dbplyr SQL for Data Science - Part 1 In this post, we will learn to aggregate data order data and group data Libraries, Code & Data We will use the following libraries in this post: DBI RSQLite dbplyr All...

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SQL for Data Science – Part 1

December 20, 2018
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Introduction This is the third post in the series R & Databases. You can find the links to the other two posts of this series below: Quick Guide: R & SQLite Data Wrangling with dbplyr SQL for Data Science - Part 2 In this post, we will learn to: select single column multiple columns distinct values in a column limit the number of records returned handle NULL values and filter columns...

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Data Wrangling with dbplyr

December 8, 2018
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Introduction This is the second post in the series R & Databases. You can find the links to the first post of this series below: Quick Guide: R & SQLite In this post, we will learn to query data from a database using dplyr. Libraries, Code & Data We will use the following libraries in this post: DBI RSQLite dbplyr dplyr All the data sets used in this post...

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Quick Guide: R & SQLite

November 26, 2018
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Introduction This is the first post in the series R & Databases. You can find the links to the other two posts of this series below: Data Wrangling with dbplyr SQL for Data Science - Part 1 SQL for Data Science - Part 2 In this post, we will learn to: connect to a SQLite database from R display database information list tables in the database query data read...

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Categorical Data Analysis using forcats

November 14, 2018
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Categorical Data Analysis using forcats

Introduction In this post, we will learn to work with categorical/qualitative data in R using forcats. Let us begin by installing and loading forcats and a set of other pacakges we will be using. Libraries & Code We will use the following packages: forcats dplyr magrittr ggplot2 tibbe purrr and readr The codes from here. library(forcats) library(tibble) library(magrittr) library(purrr) library(dplyr) library(ggplot2) library(readr) Case Study We will use a case study to explore the various features of the forcats package. You can download...

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Working with Date and Time in R

November 2, 2018
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Working with Date and Time in R

Introduction In this post, we will learn to work with date/time data in R using lubridate, an R package that makes it easy to work with dates and time. Let us begin by installing and loading the pacakge. Libraries, Code & Data We will use the following packages: lubridate dplyr magrittr readr The data sets can be downloaded from here and the codes from here. library(lubridate) library(dplyr) library(magrittr) library(readr) Quick Intro Origin Let us look...

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Hacking strings with stringr

October 21, 2018
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Hacking strings with stringr

Introduction In this post, we will learn to work with string data in R using stringr. As we did in the other posts, we will use a case study to explore the various features of the stringr package. Let us begin by installing and loading stringr and a set of other pacakges we will be using. Libraries, Code & Data We will...

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Readable Code with Pipes

October 9, 2018
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Readable Code with Pipes

Introduction R code contain a lot of parentheses in case of a sequence of multiple operations. When you are dealing with complex code, it results in nested function calls which are hard to read and maintain. The magrittr package by Stefan Milton Bache provides pipes enabling us to write R code that is readable. Pipes allow us to clearly express a sequence...

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