Hands-On Data Exploration with R

Hands-On Data Exploration with R
Hands-On Data Exploration with R
English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 2h 09m | 320 MB

Break down data, summarize information, and produce visually appealing plots to demonstrate powerful insights

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.

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

What You Will Learn

  • 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

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