Wrangling Data in the Tidyverse

  • 4.8
Approx. 14 hours to complete

Course Summary

Learn how to use the Tidyverse suite of tools for data wrangling in R. This course covers the basics of data manipulation, cleaning, and transformation techniques using Tidyverse packages such as dplyr, tidyr, and ggplot2.

Key Learning Points

  • Learn how to effectively manipulate and transform data using the Tidyverse suite of tools in R
  • Discover techniques for cleaning and preparing data for analysis
  • Understand how to visualize and communicate data using ggplot2

Related Topics for further study


Learning Outcomes

  • Ability to manipulate and transform data using Tidyverse tools
  • Understanding of data cleaning and preparation techniques
  • Proficiency in visualizing and communicating data using ggplot2

Prerequisites or good to have knowledge before taking this course

  • Basic knowledge of R programming
  • Familiarity with data analysis and visualization concepts

Course Difficulty Level

Intermediate

Course Format

  • Online
  • Self-paced

Similar Courses

  • Data Wrangling with Python
  • Data Cleaning and Preprocessing
  • Data Visualization with ggplot2

Related Education Paths


Notable People in This Field

  • Data Scientist and Assistant Professor
  • Professor of Statistics

Related Books

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.

Knowledge

  • A​pply Tidyverse functions to transform non-tidy data to tidy data
  • C​onduct basic exploratory data analysis
  • C​onduct analyses of text data

Outline

  • Wrangling Data in the Tidyverse
  • About This Course
  • Tidy Data Review
  • Reshaping Data
  • Wide Data
  • Long Data
  • Reshaping Data
  • R Packages
  • The Pipe Operator
  • Filtering Data
  • Reordering
  • Creating New Columns
  • Separating Columns
  • Merging Columns
  • Cleaning Column Names
  • Combining Data Across Data Frames
  • Grouping Data
  • Summarizing Data
  • Operations Across Columns
  • Reshaping Data Quiz
  • Data Wrangling Quiz
  • Working With Factors, Dates, and Times
  • Working with Factors
  • Factor Review
  • Manually Changing the Labels of Factor Levels: fct_releve()
  • Keeping the Order of the Factor Levels: fct_inorder()
  • Advanced Factoring
  • Re-ordering Factor Levels by Frequency: fct_infreq()
  • Reversing Order Levels: fct_rev()
  • Re-ordering Factor Levels by Another Variable: fct_reorder()
  • Combining Several Levels into One: fct_recode()
  • Converting Numeric Levels to factors: ifelse() + factor()
  • Dates and Times Basics
  • Creating Dates and Date-Time Objects
  • Working with Dates
  • Time Spans
  • Working With Factors Quiz
  • Working With Dates Quiz
  • Working With Strings and Text and Functional Programming
  • Working with Strings
  • stringr
  • String Basics
  • Regular Expressions
  • glue
  • Tidy Text Format
  • Sentiment Analysis
  • Word and Document Frequency
  • Functional Programming
  • For Loops vs. Functionals
  • map Functions
  • Multiple Vectors
  • Anonymous Functions
  • Working With Strings Quiz
  • Functional Programming Quiz
  • Exploratory Data Analysis
  • Exploratory Data Analysis
  • General Principles of EDA
  • Case Studies
  • Case Studies
  • Healthcare Coverage Data
  • Healthcare Spending Data
  • Join the Data
  • Census Data
  • Violent Crime
  • Brady Scores
  • The Counted Fatal Shootings
  • Unemployment Data
  • Population Density: 2015
  • Firearm Ownership
  • Project: Wrangling data in the Tidyverse
  • Important information before you start the project
  • Wrangling Data in the Tidyverse Course Project

Summary of User Reviews

Learn data wrangling with Tidyverse on Coursera. Users have rated this course highly for its comprehensive coverage and practical application. Many commented on the clear explanations and easy-to-follow examples.

Key Aspect Users Liked About This Course

Clear explanations and easy-to-follow examples

Pros from User Reviews

  • Comprehensive coverage of Tidyverse
  • Practical application of data wrangling skills
  • Engaging and knowledgeable instructor
  • Interactive assignments and quizzes
  • Flexible schedule and self-paced learning

Cons from User Reviews

  • May be too basic for advanced users
  • Some technical issues with the platform
  • Lack of personalized feedback on assignments
  • Limited interaction with other students
  • No certificate of completion for audit learners
English
Available now
Approx. 14 hours to complete
Carrie Wright, PhD, Shannon Ellis, PhD, Stephanie Hicks, PhD, Roger D. Peng, PhD
Johns Hopkins University
Coursera

Instructor

Carrie Wright, PhD

  • 4.8 Raiting
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