Hands-On Data Exploration with R [Video]

More Information
  • Learn to explore data in R, using summarizations, aggregations, and visualizations
  • Learn to extract data stored in different formats, transform it if necessary, and load it into R ready for exploration
  • Explore data effectively from a variety of perspectives and determine relationships and correlations
  • Extend exploration via summarization and aggregation to look at patterns and trends within and between data groups
  • Facilitate data exploration with an introduction to the dplyr package
  • Advance your R programming capabilities by learning how to create and work with lists
  • Produce visually appealing plots to demonstrate the insights you have gained

R can help you work with data you already have. You can do this by learning some common R data commands, exploring your data, aggregating the data into summary information, and visualizing the results to share with others. But before that, data cleaning is a very important aspect. Here we will talk about using tidyr to create tidy data.

This course will teach you how to put R to practical use in a world where decisions are data-driven. We start off by understanding how to prepare your data for analysis. You will learn how to organize data in a way that is easily workable. We will then explore data and understand how easy it is to gain insights from it by summarizing, aggregating, and visualizing data in R.

By the end of this course, you will be equipped with the skills you need to explore a Retail, Telecom, or any other dataset handed to you, break down its key feature into easily digestible information, summarize this information, and produce visually appealing plots to demonstrate these insights.

All the code files for this course are available on Github at - https://github.com/PacktPublishing/Hands-On-Data-Exploration-with-R-V-

Style and Approach

This course follows a hands-on learning style with step-by-step instructions for implementing best practices and monitoring/preventing critical issues with Xcode.

  • Go from a basic knowledge of R to being able to explore data effectively using R, a highly prized skill in the data world
  • Use TidyR to ensure that your data is tidy and you spend less time fighting with tools and more time working on your analysis.
  • The course covers popular data-oriented techniques ranging from ETL (Extract, Transform, Load) to the use of lists, a valuable data type used by data professionals due to its versatility
Course Length 2 hours 9 minutes
ISBN 9781789137163
Date Of Publication 28 Feb 2019


Rahul Tiwari

Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as Big Data, Data Science, Machine Learning, and Cloud Computing. Over the past few years, they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the World's most popular soft drinks companies, helping each of them to better make sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.

Rahul Tiwari trains and consults organizations and individuals on Business Analytics, Data Science, and Machine Learning (Using R and Python). For 12 years, he has been helping students and organizations in various domains (such as retail, telecom, life sciences, finance, and more) solve their business problems using Data Science, Business Analytics, and Machine Learning. He has implemented machine learning algorithms in R extensively. He worked on various classification and regression models for his clients using R and Python. He has a sound knowledge of statistics as well, which is very much necessary for Data Science projects.

After starting his career 12 years back in data warehousing, he moved on to the Data Science domain and held various roles. Mostly working with CTOs, key IT decision makers, and students, he has always focused on building capacity, knowledge, and solutions in Data Science, Business Analytics, and Machine Learning.

He is a certified Tableau and Teradata associate. His core expertise is in R, Python, Tableau, Power BI, and SQL.