Loading Iris Data Set in R

Loading Data using data()

Loading and importing Iris Data set

Iris Data set is present in R by default . We can load Iris data by using data() function :

data() - It is used to load specified data sets

data("iris")

It can load iris data in R.

We can see iris data by using following command-

iris

 

The Iris dataset looks like below :

5.1

3.5

1.4

0.2

setosa

4.9

3

1.4

0.2

setosa

4.7

3.2

1.3

0.2

setosa

4.6

3.1

1.5

0.2

setosa

5

3.6

1.4

0.2

setosa

5.4

3.9

1.7

0.4

setosa

4.6

3.4

1.4

0.3

setosa

5

3.4

1.5

0.2

setosa

4.4

2.9

1.4

0.2

setosa

4.9

3.1

1.5

0.1

setosa

5.4

3.7

1.5

0.2

setosa

4.8

3.4

1.6

0.2

setosa

4.8

3

1.4

0.1

setosa

4.3

3

1.1

0.1

setosa

5.8

4

1.2

0.2

setosa

5.7

4.4

1.5

0.4

setosa

5.4

3.9

1.3

0.4

setosa

5.1

3.5

1.4

0.3

setosa

5.7

3.8

1.7

0.3

setosa

5.1

3.8

1.5

0.3

setosa

5.4

3.4

1.7

0.2

setosa

5.1

3.7

1.5

0.4

setosa

4.6

3.6

1

0.2

setosa

5.1

3.3

1.7

0.5

setosa

4.8

3.4

1.9

0.2

setosa

5

3

1.6

0.2

setosa

5

3.4

1.6

0.4

setosa

5.2

3.5

1.5

0.2

setosa

5.2

3.4

1.4

0.2

setosa

4.7

3.2

1.6

0.2

setosa

4.8

3.1

1.6

0.2

setosa

5.4

3.4

1.5

0.4

setosa

5.2

4.1

1.5

0.1

setosa

5.5

4.2

1.4

0.2

setosa

4.9

3.1

1.5

0.1

setosa

5

3.2

1.2

0.2

setosa

5.5

3.5

1.3

0.2

setosa

4.9

3.1

1.5

0.1

setosa

4.4

3

1.3

0.2

setosa

5.1

3.4

1.5

0.2

setosa

5

3.5

1.3

0.3

setosa

4.5

2.3

1.3

0.3

setosa

4.4

3.2

1.3

0.2

setosa

5

3.5

1.6

0.6

setosa

5.1

3.8

1.9

0.4

setosa

4.8

3

1.4

0.3

setosa

5.1

3.8

1.6

0.2

setosa

4.6

3.2

1.4

0.2

setosa

5.3

3.7

1.5

0.2

setosa

5

3.3

1.4

0.2

setosa

7

3.2

4.7

1.4

versicolor

6.4

3.2

4.5

1.5

versicolor

6.9

3.1

4.9

1.5

versicolor

5.5

2.3

4

1.3

versicolor

6.5

2.8

4.6

1.5

versicolor

5.7

2.8

4.5

1.3

versicolor

6.3

3.3

4.7

1.6

versicolor

4.9

2.4

3.3

1

versicolor

6.6

2.9

4.6

1.3

versicolor

5.2

2.7

3.9

1.4

versicolor

5

2

3.5

1

versicolor

5.9

3

4.2

1.5

versicolor

6

2.2

4

1

versicolor

6.1

2.9

4.7

1.4

versicolor

5.6

2.9

3.6

1.3

versicolor

6.7

3.1

4.4

1.4

versicolor

5.6

3

4.5

1.5

versicolor

5.8

2.7

4.1

1

versicolor

6.2

2.2

4.5

1.5

versicolor

5.6

2.5

3.9

1.1

versicolor

5.9

3.2

4.8

1.8

versicolor

6.1

2.8

4

1.3

versicolor

6.3

2.5

4.9

1.5

versicolor

6.1

2.8

4.7

1.2

versicolor

6.4

2.9

4.3

1.3

versicolor

6.6

3

4.4

1.4

versicolor

6.8

2.8

4.8

1.4

versicolor

6.7

3

5

1.7

versicolor

6

2.9

4.5

1.5

versicolor

5.7

2.6

3.5

1

versicolor

5.5

2.4

3.8

1.1

versicolor

5.5

2.4

3.7

1

versicolor

5.8

2.7

3.9

1.2

versicolor

6

2.7

5.1

1.6

versicolor

5.4

3

4.5

1.5

versicolor

6

3.4

4.5

1.6

versicolor

6.7

3.1

4.7

1.5

versicolor

6.3

2.3

4.4

1.3

versicolor

5.6

3

4.1

1.3

versicolor

5.5

2.5

4

1.3

versicolor

5.5

2.6

4.4

1.2

versicolor

6.1

3

4.6

1.4

versicolor

5.8

2.6

4

1.2

versicolor

5

2.3

3.3

1

versicolor

5.6

2.7

4.2

1.3

versicolor

5.7

3

4.2

1.2

versicolor

5.7

2.9

4.2

1.3

versicolor

6.2

2.9

4.3

1.3

versicolor

5.1

2.5

3

1.1

versicolor

5.7

2.8

4.1

1.3

versicolor

6.3

3.3

6

2.5

virginica

5.8

2.7

5.1

1.9

virginica

7.1

3

5.9

2.1

virginica

6.3

2.9

5.6

1.8

virginica

6.5

3

5.8

2.2

virginica

7.6

3

6.6

2.1

virginica

4.9

2.5

4.5

1.7

virginica

7.3

2.9

6.3

1.8

virginica

6.7

2.5

5.8

1.8

virginica

7.2

3.6

6.1

2.5

virginica

6.5

3.2

5.1

2

virginica

6.4

2.7

5.3

1.9

virginica

6.8

3

5.5

2.1

virginica

5.7

2.5

5

2

virginica

5.8

2.8

5.1

2.4

virginica

6.4

3.2

5.3

2.3

virginica

6.5

3

5.5

1.8

virginica

7.7

3.8

6.7

2.2

virginica

7.7

2.6

6.9

2.3

virginica

6

2.2

5

1.5

virginica

6.9

3.2

5.7

2.3

virginica

5.6

2.8

4.9

2

virginica

7.7

2.8

6.7

2

virginica

6.3

2.7

4.9

1.8

virginica

6.7

3.3

5.7

2.1

virginica

7.2

3.2

6

1.8

virginica

6.2

2.8

4.8

1.8

virginica

6.1

3

4.9

1.8

virginica

6.4

2.8

5.6

2.1

virginica

7.2

3

5.8

1.6

virginica

7.4

2.8

6.1

1.9

virginica

7.9

3.8

6.4

2

virginica

6.4

2.8

5.6

2.2

virginica

6.3

2.8

5.1

1.5

virginica

6.1

2.6

5.6

1.4

virginica

7.7

3

6.1

2.3

virginica

6.3

3.4

5.6

2.4

virginica

6.4

3.1

5.5

1.8

virginica

6

3

4.8

1.8

virginica

6.9

3.1

5.4

2.1

virginica

6.7

3.1

5.6

2.4

virginica

6.9

3.1

5.1

2.3

virginica

5.8

2.7

5.1

1.9

virginica

6.8

3.2

5.9

2.3

virginica

6.7

3.3

5.7

2.5

virginica

6.7

3

5.2

2.3

virginica

6.3

2.5

5

1.9

virginica

6.5

3

5.2

2

virginica

6.2

3.4

5.4

2.3

virginica

5.9

3

5.1

1.8

virginica

 

Now if we want to export this iris data set as a csv file we can do it as below

Export to CSV in R 

 

iris_datset <- data("iris")

 

# Export as CSV file in R

write.csv(iris, file = "iris.csv")
 
#This gets saved in your working directory as iris.csv 
#To know your current working directory 
 
getwd()
 
#if you want to set your working directory to a folder of your choice use
setwd()
 
To clear the console use "CTRL L "
 
 
 
 
 

Reading Data From a CSV File 

 

Now Suppose We have iris data set in a CSV file as iris.csv .

We can import this iris data set in a csv file by using read.csv() function :

?read.csv()

It opens help window of read.csv function .

read.csv() - It is used to read csv files and create a data frame from it.

We import iris data by giving path of data file of "iris.csv" .

iris<- read.csv("C:\\Users\\dell\\Desktop\\blogs\\iris.csv")

iris

It looks like as -

 

We can assign column names of iris data by using names () function :

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

It is used to assign column names to iris data .

 

We can check various attributes of iris dataset :

dim() :

It shows total number of rows and columns .

dim(iris)

Output :

[1] 149 5

 

attributes() :

It shows attributes of iris data

attributes(iris)

$names - It shows names of columns of iris data

$class - it shows data type of iris

$row.names - It represents row numbers

We can check various attributes of iris data -

attr(iris,"names")  

Output :-

It shows column names of iris data .

attr(iris,"row.names")

attr(iris,"class")

We can find summary of iris data :

summary(iris)

It shows minimum , first quartile , median , mean , third quartile and maximum value of numeric columns and count of character columns.

 

Contact at TJT@TechnicalJockey.com , if you are looking for an Instructor Based Online Training !

 

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