Data wrangling : I/O (Part-1)

May 24, 2017
By

(This article was first published on R-exercises, and kindly contributed to R-bloggers)


Data wrangling is a task of great importance in data analysis. Data wrangling, is the process of importing, cleaning and transforming raw data into actionable information for analysis. It is a time-consuming process which is estimated to take about 60-80% of analyst’s time. In this series we will go through this process. It will be a brief series with goal to craft the reader’s skills on the data wrangling task. This is the first part of this series and it aims to cover the importing and exporting of data locally.
Please download the data from here

Before proceeding, it might be helpful to look over the help pages for the read.csv, read.table, read_excel, fromJSON, as.data.frame, xmlParse, xmlToList, write.csv, write.table, write.xlsx, toJSON, write, write.xml.

Moreover please load the following libraries.
install.packages("readxl")
library(readxl)
install.packages("xlsx")
library(xlsx)
install.packages("rjson")
library(rjson)
install.packages("plyr")
library(plyr)
install.packages("XML")
library(XML)
install.packages("kulife")
library(kulife)

Answers to the exercises are available here.

If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page.

Exercise 1

Import the data.csv file to the csv_file object.

Exercise 2

Import the data.txt file to the txt_file object.

Exercise 3

Import the data.xls file to the xls_file object.

Exercise 4

Import the data.xlsx file to the xlsx_file object.

Learn more about Data Pre-Processing in the online course R Data Pre-Processing & Data Management – Shape your Data!. In this course you will learn how to:

  • import data into R in several ways while also beeing able to identify a suitable import tool
  • use SQL code within R
  • And much more

Exercise 5

Import the data.json file to the json_file object.

Exercise 6

Import the data.xml file to the xml_file object.

Exercise 7

Export the csv_file as “data.csv” and txt_file as “data.txt”.

Exercise 8

Export the xls_file as “data.xls” and xlsx_file as “data.xlsx”.

Exercise 9

Export the json_file as “data.json”.

Exercise 10

Export the xml_file as “data.xml”.

To leave a comment for the author, please follow the link and comment on their blog: R-exercises.

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