Book Image

Hands-On Data Science with R

By : Vitor Bianchi Lanzetta, Doug Ortiz, Nataraj Dasgupta, Ricardo Anjoleto Farias
Book Image

Hands-On Data Science with R

By: Vitor Bianchi Lanzetta, Doug Ortiz, Nataraj Dasgupta, Ricardo Anjoleto Farias

Overview of this book

R is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world. This book covers the entire data science ecosystem for aspiring data scientists, right from zero to a level where you are confident enough to get hands-on with real-world data science problems. The book starts with an introduction to data science and introduces readers to popular R libraries for executing data science routine tasks. This book covers all the important processes in data science such as data gathering, cleaning data, and then uncovering patterns from it. You will explore algorithms such as machine learning algorithms, predictive analytical models, and finally deep learning algorithms. You will learn to run the most powerful visualization packages available in R so as to ensure that you can easily derive insights from your data. Towards the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity.
Table of Contents (16 chapters)


In this chapter, you learned what the terms KDD and data mining could mean. You have also learned about diverse ways of retrieving text from the web and even how to get a dwarf name for yourself. Otherwise, you may have learned how to run a term frequency and a clustering analysis. To wrap it up, here are the things that we did with Twitter data:

  • Cleaned and transformed data
  • Ran a term frequency analysis
  • Drew lollipop and word cloud charts to aid interpreting
  • Made hierarchical clustering from the term frequency

There is much more we could do with data retrieved from Twitter, such as the following:

  • Topic modeling
  • Sentiment analysis
  • Follower analysis
  • Retweet analysis—this might be useful for you to get more retweets
  • Favorite analysis

Given that we visited some ways of retrieving and manipulating data from Twitter, I am pretty confident that you can do this by...