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Introduction to the Tidyverse

4.8+
110 reviews
Beginner

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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4 Hours16 Videos50 Exercises
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Course Description

This is an introduction to the programming language R, focused on a powerful set of tools known as the Tidyverse. You'll learn the intertwined processes of data manipulation and visualization using the tools dplyr and ggplot2. You'll learn to manipulate data by filtering, sorting, and summarizing a real dataset of historical country data in order to answer exploratory questions. You'll then learn to turn this processed data into informative line plots, bar plots, histograms, and more with the ggplot2 package. You’ll get a taste of the value of exploratory data analysis and the power of Tidyverse tools. This is a suitable introduction for those who have no previous experience in R and are interested in performing data analysis.
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In the following Tracks

Certification Available

Data Analyst with R

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Associate Data Scientist in R

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R Developer

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  1. 1

    Data wrangling

    Free

    In this chapter, you'll learn to do three things with a table: filter for particular observations, arrange the observations in a desired order, and mutate to add or change a column. You'll see how each of these steps allows you to answer questions about your data.

    Play Chapter Now
    The gapminder dataset
    50 xp
    Loading the gapminder and dplyr packages
    100 xp
    Understanding a data frame
    50 xp
    The filter verb
    50 xp
    Filtering for one year
    100 xp
    Filtering for one country and one year
    100 xp
    The arrange verb
    50 xp
    Arranging observations by life expectancy
    100 xp
    Filtering and arranging
    100 xp
    The mutate verb
    50 xp
    Using mutate to change or create a column
    100 xp
    Combining filter, mutate, and arrange
    100 xp
  2. 2

    Data visualization

    Often a better way to understand and present data as a graph. In this chapter, you'll learn the essential skills of data visualization using the ggplot2 package, and you'll see how the dplyr and ggplot2 packages work closely together to create informative graphs.

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  3. 3

    Grouping and summarizing

    So far you've been answering questions about individual country-year pairs, but you may be interested in aggregations of the data, such as the average life expectancy of all countries within each year. Here you'll learn to use the group by and summarize verbs, which collapse large datasets into manageable summaries.

    Play Chapter Now
  4. 4

    Types of visualizations

    In this chapter, you'll learn how to create line plots, bar plots, histograms, and boxplots. You'll see how each plot requires different methods of data manipulation and preparation, and you’ll understand how each of these plot types plays a different role in data analysis.

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In the following Tracks

Certification Available

Data Analyst with R

Go To Track
Certification Available

Associate Data Scientist in R

Go To Track

R Developer

Go To Track

In other tracks

Tidyverse Fundamentals with R

Datasets

Gapminder

Collaborators

Collaborator's avatar
Yashas Roy
Collaborator's avatar
Chester Ismay
David Robinson HeadshotDavid Robinson

Principal Data Scientist at Heap

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Don’t just take our word for it

*4.8
from 110 reviews
85%
13%
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  • Mariano T.
    about 2 months

    Good introduction to TidyVerse package

  • Susana S.
    3 months

    na

  • Niklas W.
    3 months

    It was my first time working with the tidyverse package, but the course had a great structure and was easy to understand.

  • Nutwarut N.
    3 months

    It's very useful and make me understand it more! Thanks!

  • Olga L.
    3 months

    I really liked this course because it is neatly split into small enough chunks easy to process and remember. Dave speaks very clearly and his explanations are really simple and concise.

"Good introduction to TidyVerse package"

Mariano T.

"na"

Susana S.

"It was my first time working with the tidyverse package, but the course had a great structure and was easy to understand."

Niklas W.

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