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Introduction to Importing Data in R

4.1+
25 reviews
Beginner

In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.

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3 Hours10 Videos37 Exercises
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Course Description

Importing data into R should be the easiest step in your analysis. Unfortunately, that is almost never the case. Data can come in many formats, ranging from .csv and text files, to statistical software files, to databases and HTML data. Knowing which approach to use is key to getting started with the actual analysis. In this course, you’ll start by learning how to read .csv and text files in R. You will then cover the readr and data.table packages to easily and efficiently import flat file data. After that, you will learn how to read .xls files in R using readxl.
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In the following Tracks

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Associate Data Scientist in R

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Importing & Cleaning Data with R

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  1. 1

    Importing data from flat files with utils

    Free

    A lot of data comes in the form of flat files: simple tabular text files. Learn how to import the common formats of flat file data with base R functions.

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    Introduction & read.csv
    50 xp
    read.csv
    100 xp
    Reading from a path
    100 xp
    read.delim & read.table
    50 xp
    read.delim
    100 xp
    read.table
    100 xp
    Arguments
    100 xp
    Column classes
    100 xp
    Final Thoughts
    50 xp
  2. 2

    readr & data.table

    In addition to base R, there are dedicated packages to easily and efficiently import flat file data. We'll talk about two such packages: readr and data.table.

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  3. 3

    Importing Excel data

    Excel is a widely used data analysis tool. If you prefer to do your analyses in R, though, you'll need an understanding of how to import .csv data into R. This chapter will show you how to use readxl to do so.

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  4. 4

    Reproducible Excel work with XLConnect

    Beyond importing data from Excel, you can take things one step further with XLConnect. Learn all about it and bridge the gap between R and Excel.

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For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

In the following Tracks

Certification Available

Associate Data Scientist in R

Go To Track

Importing & Cleaning Data with R

Go To Track

Datasets

HotdogsPotatoes (CSV)Potatoes (TSV)Swimming poolsUrban population (XLS)Urban population (XLSX)

Prerequisites

Introduction to R
Filip Schouwenaars HeadshotFilip Schouwenaars

Data Science Instructor at DataCamp

Filip is the passionate developer behind several of DataCamp's most popular Python, SQL, and R courses. Currently, Filip leads the development of DataCamp Workspace, a collaborative data science notebook. Under the motto 'Eat your own dog food', he uses Workspace to understand how users learn on and interact with DataCamp. Filip holds degrees in Electrical Engineering and Artificial Intelligence.
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  • Zilong M.
    3 months

    It is good!

  • VAMSI P.
    8 months

    Detail and Imressive

  • Li D.
    11 months

    Review content required

  • James K.
    about 1 year

    Very comprehensive

  • Hicham T.
    about 1 year

    This is the most practical and most needed for every beginner in R with a background in Excel and want to start to use his own excel data...

"It is good!"

Zilong M.

"Detail and Imressive"

VAMSI P.

"Review content required"

Li D.

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