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Loading Iris Data Set in R

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R Programming

Loading Iris Data Set in R

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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 is look like as :

 

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

We have stored iris data set in CSV file as iris.csv .

We can import iris data set 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.

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