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Data Analysis with Tidyverse
  • Level Foundation
  • المدة 17 ساعات hours
  • الطبع بواسطة University of Colorado Boulder
  • Offered by

عن

This course continues our gentle introduction to programming in R designed for 3 types of learners. It will be right for you, if: • you want to do data analysis but don’t know programming • you know programming but aren’t too familiar with R • you know some R programming but want to learn more about the tidyverse verbs It is best taken following the first course in the specialization or if you already are familiar with ggplot, RMarkdown, and basic function writing in R. You will use learn to use readr to read in your data, dplyr to analyze your data, and stringr and forcats to manipulate strings and factors.

الوحدات

Projects

    • 1 Videos
    • 1 Plugin
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1 Videos

  • Projects and the R Environment

Importing Data

    • 1 Videos
    • 1 Plugin
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1 Videos

  • Importing Data

Tibbles

    • 2 Videos
    • 1 Plugin
    • 1 Assignment
Show info about module content

1 Assignment

  • Tibbles and DataFrames

2 Videos

  • Introduction to Tibbles
  • Tibble Indexing

Parsing Data

    • 3 Videos
    • 1 Plugin
    • 1 Assignment
Show info about module content

1 Assignment

  • Importing and Parsing Data

3 Videos

  • Parsing Vectors
  • Parsing Dates
  • Using the readr Library

Resources

    • 1 Readings
    • 1 Plugin
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1 Readings

  • Other Resources

Tidying Data

    • 6 Videos
    • 1 Assignment
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1 Assignment

  • Tidying Data

6 Videos

  • What is Tidy Data?
  • Pivoting Data
  • Separating and Uniting Variables
  • Handling Missing Data
  • Pivoting Data and Grouping
  • Tidying Multiple Observations Per Row

Practice Tidying Data

    • 1 Lab
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1 Labs

  • Practice Tidying Data

Module Assignment

    • 1 PeerReview
    • 1 Lab
Show info about module content

1 Peer Review

  • Tidying Data

1 Labs

  • Tidying Data

Resources

    • 1 Readings
    • 2 Plugin
Show info about module content

1 Readings

  • Data Transformation with dplyr: Cheat Sheet

Working With Packages

    • 1 Videos
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1 Videos

  • Working with Packages

Working With Relational Data

    • 3 Videos
    • 1 Assignment
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1 Assignment

  • Relational Data

3 Videos

  • Mutating Joins
  • Filtering Joins
  • Set Operations

Module Assignment

    • 1 PeerReview
    • 1 Lab
Show info about module content

1 Peer Review

  • Relational Data with dplyr

1 Labs

  • Relational Data with dplyr

Resourses

    • 1 Readings
    • 2 Plugin
Show info about module content

1 Readings

  • String Manipulation with stringr: Cheat Sheet

Strings

    • 2 Videos
    • 1 Assignment
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1 Assignment

  • String Basics

2 Videos

  • Introduction to Strings
  • Subsetting Strings

Regular Expressions

    • 5 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Regular Expressions

5 Videos

  • Basic String Matching
  • Anchoring Expressions
  • Character Classes
  • Controlling the Number of Pattern Matches
  • Groups and Backreferences

Applying Regular Expressions with stringr

    • 4 Videos
    • 1 Assignment
Show info about module content

1 Assignment

  • Applying Regular Expressions

4 Videos

  • Detect Matches
  • Extract Matches
  • Grouped Matches
  • String Splitting and regex()

Practicing String Manipulation and Regular Expressions

    • 1 Lab
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1 Labs

  • Practice Exercises

Module Assignment

    • 1 PeerReview
    • 1 Lab
Show info about module content

1 Peer Review

  • String Manipulation and Regular Expressions

1 Labs

  • String Manipulation and Regular Expressions

Resources

    • 2 Readings
    • 3 Plugin
Show info about module content

2 Readings

  • Factors with forcats: Cheat Sheet
  • Other Resources

Factors

    • 6 Videos
    • 1 Assignment
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1 Assignment

  • Factors

6 Videos

  • What Are Factors
  • Creating Factors
  • Other Factor Verbs and the GSS
  • Modifying Factor Order: Part 1
  • Modifying Factor Order: Part 2
  • Modifying Factor Levels

Module Assignment

    • 1 PeerReview
    • 1 Lab
Show info about module content

1 Peer Review

  • Categorical Variables and Factors

1 Labs

  • Categorical Variables and Factors

Auto Summary

"Data Analysis with Tidyverse" is a foundational course in Big Data and Analytics, perfect for those new to programming, familiarizing themselves with R, or wanting to master tidyverse verbs. Taught by Coursera, it covers readr, dplyr, stringr, and forcats over 1020 minutes. Available through Starter and Professional subscriptions, it's ideal for learners at various stages of their R programming journey.

Jane Wall
Instructor

Jane Wall