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Introduction to R for Business Intelligence

You're reading from Introduction to R for Business Intelligence

Product type Book

Published in Aug 2016

Publisher Packt

ISBN-13 9781785280252

Pages 228 pages

Edition 1st Edition

Languages

Concepts

Business Intelligence

Author (1):

Jay Gendron

Table of Contents (19) Chapters

Introduction to R for Business Intelligence

Credits

About the Author

Acknowledgement

About the Reviewers

www.PacktPub.com

Preface

1. Extract, Transform, and Load

2. Data Cleaning

3. Exploratory Data Analysis

4. Linear Regression for Business

5. Data Mining with Cluster Analysis

6. Time Series Analysis

7. Visualizing the Datas Story

8. Web Dashboards with Shiny

References

Other Helpful R Functions

R Packages Used in the Book

R Code for Supporting Market Segment Business Case Calculations

Geo-mapping using Leaflet

Geo-mapping is the process of placing markers representing data in a geographic context, typically using latitude and longitude. Leaflet is an open source JavaScript library for building interactive geo-maps with ease. Why are we talking about a JavaScript mapping library in an R book? The R package leaflet is a wrapper around this JavaScript library that translates most of its functionality into a set of R functions. It allows analysts to visualize geospatial data easily. With this package, you can generate maps from within RStudio or embed them in R Markdown documents or Shiny web applications.

Note

Use case: Geo-mapping Bike Stations

Remember when you supported management by creating a business case for the location of customer service kiosks? You had data on each of the 244 Bike Sharing stations throughout the city. Go ahead and pull this same data from the file called Ch7_bike_station_locations.csv, located on the book's website at http://jgendron.github.io...

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Authors (1)

Jay Gendron

Jay Gendron is an associate data scientist working with Booz Allen Hamilton. He has worked in the fields of machine learning, data analysis, and statistics for over a decade, and believes that good questions and compelling visualization make analytics accessible to decision makers. Jay is a business leader, entrepreneurial employee, artist, and author. He has a B.S.M.E. in mechanical engineering, an M.S. in management of technology, an M.S. in operations research, and graduate certificates for chief information officer and IT program management. Jay is a lifelong learnera member of the first cohort to earn the 10-course specialization in data science by Johns Hopkins University on Coursera. He is an award-winning speaker who has presented internationally and provides pro bono data science expertise to numerous not-for-profit organizations to improve their operational insights. Connect with Jay Gendron at https://www.linkedin.com/in/jaygendron, visit http://jgendron.github.io/, or Twitter @jaygendron.

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