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Data Manipulation with dplyr

4.5+
64 reviews
Beginner

Build Tidyverse skills by learning how to transform and manipulate data with dplyr.

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Course Description

Say you've found a great dataset and would like to learn more about it. How can you start to answer the questions you have about the data? Use dplyr to answer those questions.

First steps: Transforming data with dplyr

This course is designed to teach users how to efficiently manipulate and transform data using the dplyr package in R.

First, explore fundamental data transformation techniques, including the use of key dplyr verbs like select, filter, arrange, and mutate. These functions will teach you how to modify datasets by selecting specific columns, filtering rows based on conditions, sorting data, and creating new calculated columns​​.

Aggregating data with dplyr

Next, the course covers data aggregation, teaching users how to summarize and condense data for better interpretation.

You’ll understand how to make your data more interpretable and manageable​​. Functions such as count, group_by, and summarize are introduced to perform operations that aggregate many observations into meaningful summaries, essential for data analysis and reporting.

Selecting and transforming data

Finally, you will learn advanced data selection and transformation techniques, such as using select helpers and the rename verb. You will also get to apply your skills to a real-world case study and practice grouped mutates, window functions, and data visualization with ggplot2.

By the end of the course, you will have developed robust data manipulation skills using dplyr, enabling more efficient and effective data analysis​​—a vital capability for any data analyst or scientist.
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In the following Tracks

Certification Available

Data Analyst in R

Go To Track
Certification Available

Associate Data Scientist in R

Go To Track

Data Manipulation in R

Go To Track
  1. 1

    Transforming Data with dplyr

    Free

    Learn verbs you can use to transform your data, including select, filter, arrange, and mutate. You'll use these functions to modify the counties dataset to view particular observations and answer questions about the data.

    Play Chapter Now
    Exploring data with dplyr
    50 xp
    Understanding your data
    50 xp
    Selecting columns
    100 xp
    The filter and arrange verbs
    50 xp
    Arranging observations
    100 xp
    Filtering for conditions
    100 xp
    Filtering and arranging
    100 xp
    The mutate() verb
    50 xp
    Calculating the number of government employees
    100 xp
    Calculating the percentage of women in a county
    100 xp
    Mutate, filter, and arrange
    100 xp
  2. 2

    Aggregating Data

    Now that you know how to transform your data, you'll want to know more about how to aggregate your data to make it more interpretable. You'll learn a number of functions you can use to take many observations in your data and summarize them, including count, group_by, summarize, ungroup, and slice_min/slice_max.

    Play Chapter Now
  3. 3

    Selecting and Transforming Data

    Learn advanced methods to select and transform columns. Also, learn about select helpers, which are functions that specify criteria for columns you want to choose, as well as the rename verb.

    Play Chapter Now
  4. 4

    Case Study: The babynames Dataset

    Work with a new dataset that represents the names of babies born in the United States each year. Learn how to use grouped mutates and window functions to ask and answer more complex questions about your data. And use a combination of dplyr and ggplot2 to make interesting graphs to further explore your data.

    Play Chapter Now
For Business

Training 2 or more people?

Get your team access to the full DataCamp platform, including all the features.

In the following Tracks

Certification Available

Data Analyst in R

Go To Track
Certification Available

Associate Data Scientist in R

Go To Track

Data Manipulation in R

Go To Track

In other tracks

R Developer

datasets

2015 US CensusUS Baby Name Records

collaborators

Collaborator's avatar
Amy Peterson

audio recorded by

James Chapman's avatar
James Chapman
James Chapman HeadshotJames Chapman

Data Science & AI Curriculum Manager, DataCamp

James is a Curriculum Manager at DataCamp, where he collaborates with experts from industry and academia to create courses on AI, data science, and analytics. He has led nine DataCamp courses on diverse topics in Python, R, AI developer tooling, and Google Sheets. He has a Master's degree in Physics and Astronomy from Durham University, where he specialized in high-redshift quasar detection. In his spare time, he enjoys restoring retro toys and electronics.

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Don’t just take our word for it

*4.5
from 64 reviews
70%
20%
5%
0%
5%
  • Yuxiang Z.
    2 months

    Great

  • Amit A.
    3 months

    Well designed and useful.

  • Praveen S.
    3 months

    Please put more details in presentations

  • Daniel N.
    3 months

    It's exciting!

  • estelle d.
    3 months

    An easy and interesting course to master r language and manipulating data

"Great"

Yuxiang Z.

"Well designed and useful."

Amit A.

"Please put more details in presentations"

Praveen S.

FAQs

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