Read and import different data files in R: Excel, CSV, SPSS, txt, url

Steps to Read and import different data files in R

Using point and click option without R codes

1. Click on file (Top left corner)

2. Click on Import datasets

3. If you are importing,
• .txt file in R, then click on “from Text(base)”
• .csv file (comma separated values) in R, then click on “from Text(readr)”
• Excel file in R, then click on “Excel”
• SPSS file in R, then click on “SPSS
• SAS file in R, then click on “SAS”

4. This will open up prompt window, R will require an additional package names “readr” for importing this data set. R will ask “Do you want to install these packages”.

5. Click “yes”

6. Click on “Browse” (Top right)

7. Identify the location of the file which you would like to import

8. As soon as you identify the location, this will give you a data preview.

9. If the data preview is correct, then click on “Import”

Steps to read and import data with R codes

1. Reading data from .csv file (comma separated values)

Install the “readr” package

        install.packages("readr")

        library(readr)

        Titanic <- read_csv("D:/2.0 Titanic/my_solution_tree.csv")

2. Reading data from Excel file

       install.packages("readxl")

Recall readxl package for reading excel files

       library(readxl) 

       store_visits <- read_excel("D:/store visits.xlsx")

       View(store_visits)

3. Reading data from Text file

        install.packages("read.table")

        library("read.table")

        text <- read.table("C:/Users/Ateeque Shaikh/Desktop/text.txt", header=TRUE, quote="\"")

Where,

text – name of the file

read.table – command for reading the text file

“” – within double quotes is the path where your is located

Header = TRUE – takes the header as the name

Quote = “” – considers the data in double quotes

         View(text)

4. Reading data from SPSS file

# Recall library haven – for import and export of SPSS Stata and SAS files

    install.packages("haven")

    library(haven)

    Train <- read_sav("D:/Train.sav")

    View(text)

5. Reading data from from a weblink or url

# https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data

   iris <- read.csv(url("https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data"), header = FALSE)

# Assigning names to the columns/ variables in the url

   names(iris) <- c("Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width", "Species")

   View(iris)

Data Science Vidhya