We cover some basic functions of dplyr including the mighty group_by and summarize combo that makes dividing up datasets a breeze, as well as arrange, select, and filter that help get the data in a cleaner and more organized format. Group-by aggregation is one of the most powerful, yet simple, tools you can use to truly make a difference in the way you manage and approach data. We’ll also walk you through how to subset columns and rows, as well as how to reorder data the way you like it.

dplyr is a a great tool to perform data manipulation. It makes your data analysis process a lot more efficient. Even better, it’s fairly simple to learn and start applying immediately to your work! Oftentimes, with just a few elegant lines of code, your data becomes that much easier to dissect and analyze. For these reasons, it is an essential and foundational skill to master for any aspiring data scientist.

Be sure to also check our accompanying blog post here:
https://blog.datasciencedojo.com/explorations-with-dplyr/

Github:
https://github.com/datasciencedojo/tutorials

To get setup with dplyr, watch our first tutorial:

Introduction to dplyr: Setup and Data Preparation

 

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Introduction to dplyr: Reshape, Subset, and Summarize Data

About The Author
- Data Science Dojo is a paradigm shift in data science learning. We enable all professionals (and students) to extract actionable insights from data.

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