Wrangling Data in the Tidyverse

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Course overview

Provider
Coursera
Course type
Free online course
Level
Mixed
Deadline
Flexible
Duration
14 hours
Certificate
Paid Certificate Available
Course author
Carrie Wright, PhD
  • A​pply Tidyverse functions to transform non-tidy data to tidy data

  • C​onduct basic exploratory data analysis

  • C​onduct analyses of text data

Description

Data never arrive in the condition that you need them in order to do effective data analysis. Data need to be re-shaped, re-arranged, and re-formatted, so that they can be visualized or be inputted into a machine learning algorithm. This course addresses the problem of wrangling your data so that you can bring them under control and analyze them effectively. The key goal in data wrangling is transforming non-tidy data into tidy data.This course covers many of the critical details about handling tidy and non-tidy data in R such as converting from wide to long formats, manipulating tables with the dplyr package, understanding different R data types, processing text data with regular expressions, and conducting basic exploratory data analyses. Investing the time to learn these data wrangling techniques will make your analyses more efficient, more reproducible, and more understandable to your data science team. In this specialization we assume familiarity with the R programming language. If you are not yet familiar with R, we suggest you first complete R Programming before returning to complete this course.

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