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Video: Tidyverse Exploratory Analysis

In this video tutorial, you'll be given a brief introduction to the concept of the tidyverse and then walk through an exploratory analysis.
Mar 2019  · 2 min read

If you would like to learn more about the Tidyverse, take Emily Robinson's Categorical Data in the Tidyverse course.

While most R programmers have heard of ggplot2 and dplyr, many are unfamiliar with the breadth of the tidyverse and the variety of problems it can solve. In this video, Emily Robinson, a data scientist at DataCamp, will give a brief introduction to the concept of the tidyverse and then walk through an exploratory analysis of the 2017 Kaggle Data Science and Machine Learning Survey. You’ll see how functions like purrr’s map_if, forcat’s fct_reorder, dplyr’s select_if, and tidyr’s separate_rows all work together to create some great plots and interesting insights!

Whether you’ve been an R programmer for years but never used the tidyverse or are just starting on your R journey, you’ll probably find some new tricks. If you want to learn more, check out our Tidyverse Fundamental track.

Check out our Getting Started with the Tidyverse: Tutorial.

Introduction to R

4 hours
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
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Intermediate R

6 hours
Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

Introduction to the Tidyverse

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Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.
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