Class_1_R
Ravi
September 29, 2015
Day 1
Assigning Operator
It will store a value in a variable
a<-2
a## [1] 2R markdown cheat sheet link
https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf
Functions Vectors
c<-c(1,2,3)
c## [1] 1 2 3Extension Packages
Tools-> Install Packages through U.I
>install.packages("ggplot2")Insert Chunk
ctrl+alt+i
Execution of script
ctrl+r (or) ctrl+Enter
Arugument
x<-c(1,2,3,5:10,NA)
?sd
??sd
help(sd)
args(sd)
example(sd)
sd(x)
sd(x,na.rm = TRUE)
sd(x,TRUE)
sd(TRUE,x) # for arguments inside it
sd(na.rm=TRUE,x)
sd(TRUE,x=x)
Day 2
Create 5 dimentional vector of values 4,7,3,2,5
x<-c(4,7,3,2,5)Add 2 with x and assign the value to y
y<-x+2Mean of y
mean(y)## [1] 6.2Create another variable z as combination of 2,3
z<-c(2,3)Add xand z
x+z## Warning in x + z: longer object length is not a multiple of shorter object
## length## [1] 6 10 5 5 7Five Basic Classes of Objects
Character, Numeric, Integer, Complex, Logical
x<-1
class(x) ## --> Represents class of x ## [1] "numeric"x<-1L
class(x)## [1] "integer"?class ## --> Help Text about class ## starting httpd help server ... donelength (x) ## --> Length of X Variable## [1] 1x<-c(1:20,"Ravi")
length(x)## [1] 21class(x)## [1] "character"x<-c(1:20)
x<-as.character(x) ## --> Converts to Character From Integer
class(x)## [1] "character"Sequence Operator (:)
x<-c(20:50) ## It Printts the Values from 20 to 50
x## [1] 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
## [24] 43 44 45 46 47 48 49 50Creating Vectors
x<-c(0.5,0.6) ## Numeic
y<-c(TRUE, FALSE) ## Logical
z<-c(T, F) ## Logical
a<-c("a","b","c") ## Character
b<-9:29 ## Integer
c<-c(1+0i, 2+4i) ##Complex
x<-vector("numeric", length = 10)
x## [1] 0 0 0 0 0 0 0 0 0 0Order of Prefernce
char>Numeric>Integer>Logical
y<-c(T,2,F, "Ravi")
x<-c(1,2,3)
x## [1] 1 2 3x<-1:6
x## [1] 1 2 3 4 5 6class(x)## [1] "integer"x<-as.numeric(x) ## Converts x class to Numeric
class(x)## [1] "numeric"x<-as.integer(x)
x## [1] 1 2 3 4 5 6class(x)## [1] "integer"Matrices
m<-matrix(1:20,nrow=2,byrow = TRUE) ## Creates a Matrix of 2 Rows and 10 Columns
m## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 1 2 3 4 5 6 7 8 9 10
## [2,] 11 12 13 14 15 16 17 18 19 20m1<-matrix(1:50,nrow =5,byrow = TRUE) ## Creates a Matrix of 5 Rows and 10 Columns
m1## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 1 2 3 4 5 6 7 8 9 10
## [2,] 11 12 13 14 15 16 17 18 19 20
## [3,] 21 22 23 24 25 26 27 28 29 30
## [4,] 31 32 33 34 35 36 37 38 39 40
## [5,] 41 42 43 44 45 46 47 48 49 50m1<-matrix(1:20,nrow =2, byrow = TRUE)
m1## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 1 2 3 4 5 6 7 8 9 10
## [2,] 11 12 13 14 15 16 17 18 19 20m2 <- matrix(1:10,nrow = 2, byrow = TRUE)
m2## [,1] [,2] [,3] [,4] [,5]
## [1,] 1 2 3 4 5
## [2,] 6 7 8 9 10dim(m2)<-c(2,5) ## Displays the dimensions of the Matrix
m2## [,1] [,2] [,3] [,4] [,5]
## [1,] 1 2 3 4 5
## [2,] 6 7 8 9 10y<-11:20
x<-1:10
cbind(x,y) ## Binds the two matrices through columns## x y
## [1,] 1 11
## [2,] 2 12
## [3,] 3 13
## [4,] 4 14
## [5,] 5 15
## [6,] 6 16
## [7,] 7 17
## [8,] 8 18
## [9,] 9 19
## [10,] 10 20rbind(x,y) ## Binds the two matrices through rows ## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## x 1 2 3 4 5 6 7 8 9 10
## y 11 12 13 14 15 16 17 18 19 20x1<-c(1,3,5,6)
y1<-c(2,3,4,5)
cbind(x1,y1)## x1 y1
## [1,] 1 2
## [2,] 3 3
## [3,] 5 4
## [4,] 6 5Lists
x<-list(c(1,2,3),c("Ravi","Tej"))
x## [[1]]
## [1] 1 2 3
##
## [[2]]
## [1] "Ravi" "Tej"x[1]## [[1]]
## [1] 1 2 3x[[c(1,2)]]## [1] 2x[[c(2,1)]]## [1] "Ravi"x<-factor(c("yes", "yes","no", "yes"))
x## [1] yes yes no yes
## Levels: no yesclass(x)## [1] "factor"x<-c("yes", "yes","no", "yes")
x## [1] "yes" "yes" "no" "yes"class(x)## [1] "character"x<-factor(x)
x## [1] yes yes no yes
## Levels: no yesx<-factor(c("yes", "yes","no", "yes"))
x## [1] yes yes no yes
## Levels: no yesDAY 3
Create a list whose first elements is 2 elements set of names say “ravi” and “pavan” second element is a set of numbers like 2,3,5,19,2,7,5,5,
k<-list(c("ravi", "pavan") ,c(2,3,5,19,2,7,5,5))
k## [[1]]
## [1] "ravi" "pavan"
##
## [[2]]
## [1] 2 3 5 19 2 7 5 5check the class of second element of list
class(x[[2]])## [1] "factor"4th element of 2nd element of list
k[[c(2,4)]]## [1] 191st element of list as factor
l<-as.factor(k[[1]])
class(l[[1]])## [1] "factor"frequency of each element of 2nd element of the list
``{r}
table(k[2])
```
missing Values are blank,na,nan
x<-c(1,2,3,NA,1,NaN)
is.na(x)## [1] FALSE FALSE FALSE TRUE FALSE TRUEis.nan(x)## [1] FALSE FALSE FALSE FALSE FALSE TRUEData frames
Frame = coloums & each cell is called block
List = row so length of each element of list = no. of rows
in order to read a table or csv file = read.table() and read.csv()
args(data.frame)## function (..., row.names = NULL, check.rows = FALSE, check.names = TRUE,
## stringsAsFactors = default.stringsAsFactors())
## NULLy<-data.frame(Name = c("Ravi","Tej","sam","king"),Age = c(24,25,26,27),Sex = c("M","M","F","M"))
y## Name Age Sex
## 1 Ravi 24 M
## 2 Tej 25 M
## 3 sam 26 F
## 4 king 27 Mclass(y)## [1] "data.frame"x<-cbind(Name = c("Ravi","Tej","sam","king"),Age = c(24,25,26,27),Sex = c("M","M","F","M"))
x## Name Age Sex
## [1,] "Ravi" "24" "M"
## [2,] "Tej" "25" "M"
## [3,] "sam" "26" "F"
## [4,] "king" "27" "M"class(x)## [1] "matrix"z = as.data.frame(x)
class(z)## [1] "data.frame"z## Name Age Sex
## 1 Ravi 24 M
## 2 Tej 25 M
## 3 sam 26 F
## 4 king 27 Moverview of variable
str(z)## 'data.frame': 4 obs. of 3 variables:
## $ Name: Factor w/ 4 levels "king","Ravi",..: 2 4 3 1
## $ Age : Factor w/ 4 levels "24","25","26",..: 1 2 3 4
## $ Sex : Factor w/ 2 levels "F","M": 2 2 1 2z[row,coloum]
z[2,2]## [1] 25
## Levels: 24 25 26 27z[,2]## [1] 24 25 26 27
## Levels: 24 25 26 27z[2,]## Name Age Sex
## 2 Tej 25 Mconverting to char
as.character(z[,1])## [1] "Ravi" "Tej" "sam" "king"class(as.character(z[,1]))## [1] "character"coverting column to char and integer
z[,1] = as.character(z[,1])
str(z)## 'data.frame': 4 obs. of 3 variables:
## $ Name: chr "Ravi" "Tej" "sam" "king"
## $ Age : Factor w/ 4 levels "24","25","26",..: 1 2 3 4
## $ Sex : Factor w/ 2 levels "F","M": 2 2 1 2z[,2] = as.integer(z[,2])
str(z)## 'data.frame': 4 obs. of 3 variables:
## $ Name: chr "Ravi" "Tej" "sam" "king"
## $ Age : int 1 2 3 4
## $ Sex : Factor w/ 2 levels "F","M": 2 2 1 2class(x)## [1] "matrix"x = as.data.frame(x)
str(x)## 'data.frame': 4 obs. of 3 variables:
## $ Name: Factor w/ 4 levels "king","Ravi",..: 2 4 3 1
## $ Age : Factor w/ 4 levels "24","25","26",..: 1 2 3 4
## $ Sex : Factor w/ 2 levels "F","M": 2 2 1 2x[,1] = as.character(x[,1])
str(x)## 'data.frame': 4 obs. of 3 variables:
## $ Name: chr "Ravi" "Tej" "sam" "king"
## $ Age : Factor w/ 4 levels "24","25","26",..: 1 2 3 4
## $ Sex : Factor w/ 2 levels "F","M": 2 2 1 2coverting factors to integers we need to covert to char(string) and then integer
x<-data.frame(Name = c("Ravi","Tej","sam","king"),Age = c(24,25,26,27),Sex = c("M","M","F","M"))
x[,2] = as.character(x[,2])
x[,2] = as.integer(x[,2])
str(x)## 'data.frame': 4 obs. of 3 variables:
## $ Name: Factor w/ 4 levels "king","Ravi",..: 2 4 3 1
## $ Age : int 24 25 26 27
## $ Sex : Factor w/ 2 levels "F","M": 2 2 1 2class(x)## [1] "data.frame"class(x)## [1] "data.frame"str(x)## 'data.frame': 4 obs. of 3 variables:
## $ Name: Factor w/ 4 levels "king","Ravi",..: 2 4 3 1
## $ Age : int 24 25 26 27
## $ Sex : Factor w/ 2 levels "F","M": 2 2 1 2class(x)## [1] "data.frame"converting sex to char
x[,3] = as.character(x[,3])
names(x)## [1] "Name" "Age" "Sex"no. of row and coloums
nrow(x)## [1] 4ncol(x)## [1] 3applying coloum names
m<-data.frame(c("Ravi","Tej","sam","king"),c(24,25,26,27),c("M","M","F","M"))
colnames(m) <- c("Name","Age","Sex")
m## Name Age Sex
## 1 Ravi 24 M
## 2 Tej 25 M
## 3 sam 26 F
## 4 king 27 Mwrite.csv(Wine,“C:\Users\localadmin\Desktop\R\Wine.csv”)
read.csv(“C:\Users\localadmin\Desktop\R\Wine.csv”)
4th Day Class on R
write.csv(Wine, “C:\Users\localadmin\Desktop\R\Wine.csv”)
wine=read.csv("C:\\Users\\localadmin\\Desktop\\R\\Wine.csv")Subsetting The Data Set from Original Data Set
wine1 <- wine[,6]
wine1## [1] 15.6 11.2 18.6 16.8 21.0 15.2 14.6 17.6 14.0 16.0 18.0 16.8 16.0 11.4
## [15] 12.0 17.2 20.0 20.0 16.5 15.2 16.0 18.6 16.6 17.8 20.0 25.0 16.1 17.0
## [29] 19.4 16.0 22.5 19.1 17.2 19.5 19.0 20.5 15.5 18.0 15.5 13.2 16.2 18.8
## [43] 15.0 17.5 17.0 18.9 16.0 16.0 18.8 17.4 12.4 17.2 14.0 17.1 16.4 20.5
## [57] 16.3 16.8 16.7 10.6 16.0 16.8 18.0 19.0 19.0 18.1 15.0 19.6 17.0 16.8
## [71] 20.4 25.0 24.0 30.0 21.0 16.0 16.0 18.0 14.8 23.0 19.0 18.8 24.0 22.5
## [85] 18.0 18.0 22.8 26.0 21.6 23.6 18.5 22.0 20.7 18.0 18.0 19.0 21.5 16.0
## [99] 18.5 18.0 17.5 18.5 21.0 19.5 20.5 22.0 19.0 22.5 19.0 20.0 19.5 21.0
## [113] 20.0 21.0 22.5 21.5 20.8 22.5 16.0 19.0 20.0 28.5 26.5 21.5 21.0 21.0
## [127] 21.5 28.5 24.5 22.0 18.0 20.0 24.0 21.5 17.5 18.5 21.0 25.0 19.5 24.0
## [141] 21.0 20.0 23.5 20.0 18.5 21.0 20.0 21.5 21.5 21.5 24.0 22.0 25.5 18.5
## [155] 20.0 22.0 19.5 27.0 25.0 22.5 21.0 20.0 22.0 18.5 22.0 22.5 23.0 19.5
## [169] 24.5 25.0 19.0 19.5 20.0 20.5 23.0 20.0 20.0 24.5String Function
str(wine1) ## num [1:178] 15.6 11.2 18.6 16.8 21 15.2 14.6 17.6 14 16 ...Class of Wine 1
class(wine1) ## [1] "numeric"view of Wine1
View(wine1) Displays only Column names
colnames(wine, do.NULL = TRUE)## [1] "X" "V1" "V2" "V3" "V4" "V5" "V6" "V7" "V8" "V9" "V10"
## [12] "V11" "V12" "V13" "V14"Extracts 10th Column Names
wine10<-wine$V10
wine10## [1] 2.29 1.28 2.81 2.18 1.82 1.97 1.98 1.25 1.98 1.85 2.38 1.57 1.81 2.81
## [15] 2.96 1.46 1.97 1.72 1.86 1.66 2.10 1.98 1.69 1.46 1.66 1.92 1.45 1.35
## [29] 1.76 1.98 2.38 1.95 1.97 1.35 1.54 1.86 1.36 1.44 1.37 2.08 2.34 1.48
## [43] 1.70 1.66 2.03 1.25 2.19 2.14 2.38 2.08 2.91 2.29 1.87 1.68 1.62 2.45
## [57] 2.03 1.66 2.04 0.42 0.41 0.62 0.73 1.87 1.03 2.08 2.28 1.04 0.42 2.50
## [71] 1.46 1.87 1.03 1.96 1.65 1.15 1.46 0.95 2.76 1.95 1.43 1.77 1.40 1.62
## [85] 2.35 1.46 1.56 1.34 1.35 1.38 1.64 1.63 1.62 1.99 1.35 3.28 1.56 1.77
## [99] 1.95 2.81 1.40 1.35 1.31 1.42 1.48 1.42 1.63 1.63 2.08 2.49 3.58 1.22
## [113] 1.05 1.44 1.04 2.01 1.53 1.61 0.83 1.87 1.83 1.87 1.71 2.01 2.91 1.35
## [127] 1.77 1.76 1.90 1.35 0.94 0.83 0.83 0.84 1.25 0.94 0.80 1.10 0.88 0.81
## [141] 0.75 0.64 0.55 1.02 1.14 1.30 0.68 0.86 1.25 1.14 1.25 1.26 1.56 1.87
## [155] 1.40 1.55 1.56 1.14 2.70 2.29 1.04 0.80 0.96 0.94 1.03 1.15 1.46 0.97
## [169] 1.54 1.11 0.73 0.64 1.24 1.06 1.41 1.35 1.46 1.35Removes column 1
wine2<-wine[-1]
wine2## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13
## 1 1 14.23 1.71 2.43 15.6 127 2.80 3.06 0.28 2.29 5.640000 1.040 3.92
## 2 1 13.20 1.78 2.14 11.2 100 2.65 2.76 0.26 1.28 4.380000 1.050 3.40
## 3 1 13.16 2.36 2.67 18.6 101 2.80 3.24 0.30 2.81 5.680000 1.030 3.17
## 4 1 14.37 1.95 2.50 16.8 113 3.85 3.49 0.24 2.18 7.800000 0.860 3.45
## 5 1 13.24 2.59 2.87 21.0 118 2.80 2.69 0.39 1.82 4.320000 1.040 2.93
## 6 1 14.20 1.76 2.45 15.2 112 3.27 3.39 0.34 1.97 6.750000 1.050 2.85
## 7 1 14.39 1.87 2.45 14.6 96 2.50 2.52 0.30 1.98 5.250000 1.020 3.58
## 8 1 14.06 2.15 2.61 17.6 121 2.60 2.51 0.31 1.25 5.050000 1.060 3.58
## 9 1 14.83 1.64 2.17 14.0 97 2.80 2.98 0.29 1.98 5.200000 1.080 2.85
## 10 1 13.86 1.35 2.27 16.0 98 2.98 3.15 0.22 1.85 7.220000 1.010 3.55
## 11 1 14.10 2.16 2.30 18.0 105 2.95 3.32 0.22 2.38 5.750000 1.250 3.17
## 12 1 14.12 1.48 2.32 16.8 95 2.20 2.43 0.26 1.57 5.000000 1.170 2.82
## 13 1 13.75 1.73 2.41 16.0 89 2.60 2.76 0.29 1.81 5.600000 1.150 2.90
## 14 1 14.75 1.73 2.39 11.4 91 3.10 3.69 0.43 2.81 5.400000 1.250 2.73
## 15 1 14.38 1.87 2.38 12.0 102 3.30 3.64 0.29 2.96 7.500000 1.200 3.00
## 16 1 13.63 1.81 2.70 17.2 112 2.85 2.91 0.30 1.46 7.300000 1.280 2.88
## 17 1 14.30 1.92 2.72 20.0 120 2.80 3.14 0.33 1.97 6.200000 1.070 2.65
## 18 1 13.83 1.57 2.62 20.0 115 2.95 3.40 0.40 1.72 6.600000 1.130 2.57
## 19 1 14.19 1.59 2.48 16.5 108 3.30 3.93 0.32 1.86 8.700000 1.230 2.82
## 20 1 13.64 3.10 2.56 15.2 116 2.70 3.03 0.17 1.66 5.100000 0.960 3.36
## 21 1 14.06 1.63 2.28 16.0 126 3.00 3.17 0.24 2.10 5.650000 1.090 3.71
## 22 1 12.93 3.80 2.65 18.6 102 2.41 2.41 0.25 1.98 4.500000 1.030 3.52
## 23 1 13.71 1.86 2.36 16.6 101 2.61 2.88 0.27 1.69 3.800000 1.110 4.00
## 24 1 12.85 1.60 2.52 17.8 95 2.48 2.37 0.26 1.46 3.930000 1.090 3.63
## 25 1 13.50 1.81 2.61 20.0 96 2.53 2.61 0.28 1.66 3.520000 1.120 3.82
## 26 1 13.05 2.05 3.22 25.0 124 2.63 2.68 0.47 1.92 3.580000 1.130 3.20
## 27 1 13.39 1.77 2.62 16.1 93 2.85 2.94 0.34 1.45 4.800000 0.920 3.22
## 28 1 13.30 1.72 2.14 17.0 94 2.40 2.19 0.27 1.35 3.950000 1.020 2.77
## 29 1 13.87 1.90 2.80 19.4 107 2.95 2.97 0.37 1.76 4.500000 1.250 3.40
## 30 1 14.02 1.68 2.21 16.0 96 2.65 2.33 0.26 1.98 4.700000 1.040 3.59
## 31 1 13.73 1.50 2.70 22.5 101 3.00 3.25 0.29 2.38 5.700000 1.190 2.71
## 32 1 13.58 1.66 2.36 19.1 106 2.86 3.19 0.22 1.95 6.900000 1.090 2.88
## 33 1 13.68 1.83 2.36 17.2 104 2.42 2.69 0.42 1.97 3.840000 1.230 2.87
## 34 1 13.76 1.53 2.70 19.5 132 2.95 2.74 0.50 1.35 5.400000 1.250 3.00
## 35 1 13.51 1.80 2.65 19.0 110 2.35 2.53 0.29 1.54 4.200000 1.100 2.87
## 36 1 13.48 1.81 2.41 20.5 100 2.70 2.98 0.26 1.86 5.100000 1.040 3.47
## 37 1 13.28 1.64 2.84 15.5 110 2.60 2.68 0.34 1.36 4.600000 1.090 2.78
## 38 1 13.05 1.65 2.55 18.0 98 2.45 2.43 0.29 1.44 4.250000 1.120 2.51
## 39 1 13.07 1.50 2.10 15.5 98 2.40 2.64 0.28 1.37 3.700000 1.180 2.69
## 40 1 14.22 3.99 2.51 13.2 128 3.00 3.04 0.20 2.08 5.100000 0.890 3.53
## 41 1 13.56 1.71 2.31 16.2 117 3.15 3.29 0.34 2.34 6.130000 0.950 3.38
## 42 1 13.41 3.84 2.12 18.8 90 2.45 2.68 0.27 1.48 4.280000 0.910 3.00
## 43 1 13.88 1.89 2.59 15.0 101 3.25 3.56 0.17 1.70 5.430000 0.880 3.56
## 44 1 13.24 3.98 2.29 17.5 103 2.64 2.63 0.32 1.66 4.360000 0.820 3.00
## 45 1 13.05 1.77 2.10 17.0 107 3.00 3.00 0.28 2.03 5.040000 0.880 3.35
## 46 1 14.21 4.04 2.44 18.9 111 2.85 2.65 0.30 1.25 5.240000 0.870 3.33
## 47 1 14.38 3.59 2.28 16.0 102 3.25 3.17 0.27 2.19 4.900000 1.040 3.44
## 48 1 13.90 1.68 2.12 16.0 101 3.10 3.39 0.21 2.14 6.100000 0.910 3.33
## 49 1 14.10 2.02 2.40 18.8 103 2.75 2.92 0.32 2.38 6.200000 1.070 2.75
## 50 1 13.94 1.73 2.27 17.4 108 2.88 3.54 0.32 2.08 8.900000 1.120 3.10
## 51 1 13.05 1.73 2.04 12.4 92 2.72 3.27 0.17 2.91 7.200000 1.120 2.91
## 52 1 13.83 1.65 2.60 17.2 94 2.45 2.99 0.22 2.29 5.600000 1.240 3.37
## 53 1 13.82 1.75 2.42 14.0 111 3.88 3.74 0.32 1.87 7.050000 1.010 3.26
## 54 1 13.77 1.90 2.68 17.1 115 3.00 2.79 0.39 1.68 6.300000 1.130 2.93
## 55 1 13.74 1.67 2.25 16.4 118 2.60 2.90 0.21 1.62 5.850000 0.920 3.20
## 56 1 13.56 1.73 2.46 20.5 116 2.96 2.78 0.20 2.45 6.250000 0.980 3.03
## 57 1 14.22 1.70 2.30 16.3 118 3.20 3.00 0.26 2.03 6.380000 0.940 3.31
## 58 1 13.29 1.97 2.68 16.8 102 3.00 3.23 0.31 1.66 6.000000 1.070 2.84
## 59 1 13.72 1.43 2.50 16.7 108 3.40 3.67 0.19 2.04 6.800000 0.890 2.87
## 60 2 12.37 0.94 1.36 10.6 88 1.98 0.57 0.28 0.42 1.950000 1.050 1.82
## 61 2 12.33 1.10 2.28 16.0 101 2.05 1.09 0.63 0.41 3.270000 1.250 1.67
## 62 2 12.64 1.36 2.02 16.8 100 2.02 1.41 0.53 0.62 5.750000 0.980 1.59
## 63 2 13.67 1.25 1.92 18.0 94 2.10 1.79 0.32 0.73 3.800000 1.230 2.46
## 64 2 12.37 1.13 2.16 19.0 87 3.50 3.10 0.19 1.87 4.450000 1.220 2.87
## 65 2 12.17 1.45 2.53 19.0 104 1.89 1.75 0.45 1.03 2.950000 1.450 2.23
## 66 2 12.37 1.21 2.56 18.1 98 2.42 2.65 0.37 2.08 4.600000 1.190 2.30
## 67 2 13.11 1.01 1.70 15.0 78 2.98 3.18 0.26 2.28 5.300000 1.120 3.18
## 68 2 12.37 1.17 1.92 19.6 78 2.11 2.00 0.27 1.04 4.680000 1.120 3.48
## 69 2 13.34 0.94 2.36 17.0 110 2.53 1.30 0.55 0.42 3.170000 1.020 1.93
## 70 2 12.21 1.19 1.75 16.8 151 1.85 1.28 0.14 2.50 2.850000 1.280 3.07
## 71 2 12.29 1.61 2.21 20.4 103 1.10 1.02 0.37 1.46 3.050000 0.906 1.82
## 72 2 13.86 1.51 2.67 25.0 86 2.95 2.86 0.21 1.87 3.380000 1.360 3.16
## 73 2 13.49 1.66 2.24 24.0 87 1.88 1.84 0.27 1.03 3.740000 0.980 2.78
## 74 2 12.99 1.67 2.60 30.0 139 3.30 2.89 0.21 1.96 3.350000 1.310 3.50
## 75 2 11.96 1.09 2.30 21.0 101 3.38 2.14 0.13 1.65 3.210000 0.990 3.13
## 76 2 11.66 1.88 1.92 16.0 97 1.61 1.57 0.34 1.15 3.800000 1.230 2.14
## 77 2 13.03 0.90 1.71 16.0 86 1.95 2.03 0.24 1.46 4.600000 1.190 2.48
## 78 2 11.84 2.89 2.23 18.0 112 1.72 1.32 0.43 0.95 2.650000 0.960 2.52
## 79 2 12.33 0.99 1.95 14.8 136 1.90 1.85 0.35 2.76 3.400000 1.060 2.31
## 80 2 12.70 3.87 2.40 23.0 101 2.83 2.55 0.43 1.95 2.570000 1.190 3.13
## 81 2 12.00 0.92 2.00 19.0 86 2.42 2.26 0.30 1.43 2.500000 1.380 3.12
## 82 2 12.72 1.81 2.20 18.8 86 2.20 2.53 0.26 1.77 3.900000 1.160 3.14
## 83 2 12.08 1.13 2.51 24.0 78 2.00 1.58 0.40 1.40 2.200000 1.310 2.72
## 84 2 13.05 3.86 2.32 22.5 85 1.65 1.59 0.61 1.62 4.800000 0.840 2.01
## 85 2 11.84 0.89 2.58 18.0 94 2.20 2.21 0.22 2.35 3.050000 0.790 3.08
## 86 2 12.67 0.98 2.24 18.0 99 2.20 1.94 0.30 1.46 2.620000 1.230 3.16
## 87 2 12.16 1.61 2.31 22.8 90 1.78 1.69 0.43 1.56 2.450000 1.330 2.26
## 88 2 11.65 1.67 2.62 26.0 88 1.92 1.61 0.40 1.34 2.600000 1.360 3.21
## 89 2 11.64 2.06 2.46 21.6 84 1.95 1.69 0.48 1.35 2.800000 1.000 2.75
## 90 2 12.08 1.33 2.30 23.6 70 2.20 1.59 0.42 1.38 1.740000 1.070 3.21
## 91 2 12.08 1.83 2.32 18.5 81 1.60 1.50 0.52 1.64 2.400000 1.080 2.27
## 92 2 12.00 1.51 2.42 22.0 86 1.45 1.25 0.50 1.63 3.600000 1.050 2.65
## 93 2 12.69 1.53 2.26 20.7 80 1.38 1.46 0.58 1.62 3.050000 0.960 2.06
## 94 2 12.29 2.83 2.22 18.0 88 2.45 2.25 0.25 1.99 2.150000 1.150 3.30
## 95 2 11.62 1.99 2.28 18.0 98 3.02 2.26 0.17 1.35 3.250000 1.160 2.96
## 96 2 12.47 1.52 2.20 19.0 162 2.50 2.27 0.32 3.28 2.600000 1.160 2.63
## 97 2 11.81 2.12 2.74 21.5 134 1.60 0.99 0.14 1.56 2.500000 0.950 2.26
## 98 2 12.29 1.41 1.98 16.0 85 2.55 2.50 0.29 1.77 2.900000 1.230 2.74
## 99 2 12.37 1.07 2.10 18.5 88 3.52 3.75 0.24 1.95 4.500000 1.040 2.77
## 100 2 12.29 3.17 2.21 18.0 88 2.85 2.99 0.45 2.81 2.300000 1.420 2.83
## 101 2 12.08 2.08 1.70 17.5 97 2.23 2.17 0.26 1.40 3.300000 1.270 2.96
## 102 2 12.60 1.34 1.90 18.5 88 1.45 1.36 0.29 1.35 2.450000 1.040 2.77
## 103 2 12.34 2.45 2.46 21.0 98 2.56 2.11 0.34 1.31 2.800000 0.800 3.38
## 104 2 11.82 1.72 1.88 19.5 86 2.50 1.64 0.37 1.42 2.060000 0.940 2.44
## 105 2 12.51 1.73 1.98 20.5 85 2.20 1.92 0.32 1.48 2.940000 1.040 3.57
## 106 2 12.42 2.55 2.27 22.0 90 1.68 1.84 0.66 1.42 2.700000 0.860 3.30
## 107 2 12.25 1.73 2.12 19.0 80 1.65 2.03 0.37 1.63 3.400000 1.000 3.17
## 108 2 12.72 1.75 2.28 22.5 84 1.38 1.76 0.48 1.63 3.300000 0.880 2.42
## 109 2 12.22 1.29 1.94 19.0 92 2.36 2.04 0.39 2.08 2.700000 0.860 3.02
## 110 2 11.61 1.35 2.70 20.0 94 2.74 2.92 0.29 2.49 2.650000 0.960 3.26
## 111 2 11.46 3.74 1.82 19.5 107 3.18 2.58 0.24 3.58 2.900000 0.750 2.81
## 112 2 12.52 2.43 2.17 21.0 88 2.55 2.27 0.26 1.22 2.000000 0.900 2.78
## 113 2 11.76 2.68 2.92 20.0 103 1.75 2.03 0.60 1.05 3.800000 1.230 2.50
## 114 2 11.41 0.74 2.50 21.0 88 2.48 2.01 0.42 1.44 3.080000 1.100 2.31
## 115 2 12.08 1.39 2.50 22.5 84 2.56 2.29 0.43 1.04 2.900000 0.930 3.19
## 116 2 11.03 1.51 2.20 21.5 85 2.46 2.17 0.52 2.01 1.900000 1.710 2.87
## 117 2 11.82 1.47 1.99 20.8 86 1.98 1.60 0.30 1.53 1.950000 0.950 3.33
## 118 2 12.42 1.61 2.19 22.5 108 2.00 2.09 0.34 1.61 2.060000 1.060 2.96
## 119 2 12.77 3.43 1.98 16.0 80 1.63 1.25 0.43 0.83 3.400000 0.700 2.12
## 120 2 12.00 3.43 2.00 19.0 87 2.00 1.64 0.37 1.87 1.280000 0.930 3.05
## 121 2 11.45 2.40 2.42 20.0 96 2.90 2.79 0.32 1.83 3.250000 0.800 3.39
## 122 2 11.56 2.05 3.23 28.5 119 3.18 5.08 0.47 1.87 6.000000 0.930 3.69
## 123 2 12.42 4.43 2.73 26.5 102 2.20 2.13 0.43 1.71 2.080000 0.920 3.12
## 124 2 13.05 5.80 2.13 21.5 86 2.62 2.65 0.30 2.01 2.600000 0.730 3.10
## 125 2 11.87 4.31 2.39 21.0 82 2.86 3.03 0.21 2.91 2.800000 0.750 3.64
## 126 2 12.07 2.16 2.17 21.0 85 2.60 2.65 0.37 1.35 2.760000 0.860 3.28
## 127 2 12.43 1.53 2.29 21.5 86 2.74 3.15 0.39 1.77 3.940000 0.690 2.84
## 128 2 11.79 2.13 2.78 28.5 92 2.13 2.24 0.58 1.76 3.000000 0.970 2.44
## 129 2 12.37 1.63 2.30 24.5 88 2.22 2.45 0.40 1.90 2.120000 0.890 2.78
## 130 2 12.04 4.30 2.38 22.0 80 2.10 1.75 0.42 1.35 2.600000 0.790 2.57
## 131 3 12.86 1.35 2.32 18.0 122 1.51 1.25 0.21 0.94 4.100000 0.760 1.29
## 132 3 12.88 2.99 2.40 20.0 104 1.30 1.22 0.24 0.83 5.400000 0.740 1.42
## 133 3 12.81 2.31 2.40 24.0 98 1.15 1.09 0.27 0.83 5.700000 0.660 1.36
## 134 3 12.70 3.55 2.36 21.5 106 1.70 1.20 0.17 0.84 5.000000 0.780 1.29
## 135 3 12.51 1.24 2.25 17.5 85 2.00 0.58 0.60 1.25 5.450000 0.750 1.51
## 136 3 12.60 2.46 2.20 18.5 94 1.62 0.66 0.63 0.94 7.100000 0.730 1.58
## 137 3 12.25 4.72 2.54 21.0 89 1.38 0.47 0.53 0.80 3.850000 0.750 1.27
## 138 3 12.53 5.51 2.64 25.0 96 1.79 0.60 0.63 1.10 5.000000 0.820 1.69
## 139 3 13.49 3.59 2.19 19.5 88 1.62 0.48 0.58 0.88 5.700000 0.810 1.82
## 140 3 12.84 2.96 2.61 24.0 101 2.32 0.60 0.53 0.81 4.920000 0.890 2.15
## 141 3 12.93 2.81 2.70 21.0 96 1.54 0.50 0.53 0.75 4.600000 0.770 2.31
## 142 3 13.36 2.56 2.35 20.0 89 1.40 0.50 0.37 0.64 5.600000 0.700 2.47
## 143 3 13.52 3.17 2.72 23.5 97 1.55 0.52 0.50 0.55 4.350000 0.890 2.06
## 144 3 13.62 4.95 2.35 20.0 92 2.00 0.80 0.47 1.02 4.400000 0.910 2.05
## 145 3 12.25 3.88 2.20 18.5 112 1.38 0.78 0.29 1.14 8.210000 0.650 2.00
## 146 3 13.16 3.57 2.15 21.0 102 1.50 0.55 0.43 1.30 4.000000 0.600 1.68
## 147 3 13.88 5.04 2.23 20.0 80 0.98 0.34 0.40 0.68 4.900000 0.580 1.33
## 148 3 12.87 4.61 2.48 21.5 86 1.70 0.65 0.47 0.86 7.650000 0.540 1.86
## 149 3 13.32 3.24 2.38 21.5 92 1.93 0.76 0.45 1.25 8.420000 0.550 1.62
## 150 3 13.08 3.90 2.36 21.5 113 1.41 1.39 0.34 1.14 9.400000 0.570 1.33
## 151 3 13.50 3.12 2.62 24.0 123 1.40 1.57 0.22 1.25 8.600000 0.590 1.30
## 152 3 12.79 2.67 2.48 22.0 112 1.48 1.36 0.24 1.26 10.800000 0.480 1.47
## 153 3 13.11 1.90 2.75 25.5 116 2.20 1.28 0.26 1.56 7.100000 0.610 1.33
## 154 3 13.23 3.30 2.28 18.5 98 1.80 0.83 0.61 1.87 10.520000 0.560 1.51
## 155 3 12.58 1.29 2.10 20.0 103 1.48 0.58 0.53 1.40 7.600000 0.580 1.55
## 156 3 13.17 5.19 2.32 22.0 93 1.74 0.63 0.61 1.55 7.900000 0.600 1.48
## 157 3 13.84 4.12 2.38 19.5 89 1.80 0.83 0.48 1.56 9.010000 0.570 1.64
## 158 3 12.45 3.03 2.64 27.0 97 1.90 0.58 0.63 1.14 7.500000 0.670 1.73
## 159 3 14.34 1.68 2.70 25.0 98 2.80 1.31 0.53 2.70 13.000000 0.570 1.96
## 160 3 13.48 1.67 2.64 22.5 89 2.60 1.10 0.52 2.29 11.750000 0.570 1.78
## 161 3 12.36 3.83 2.38 21.0 88 2.30 0.92 0.50 1.04 7.650000 0.560 1.58
## 162 3 13.69 3.26 2.54 20.0 107 1.83 0.56 0.50 0.80 5.880000 0.960 1.82
## 163 3 12.85 3.27 2.58 22.0 106 1.65 0.60 0.60 0.96 5.580000 0.870 2.11
## 164 3 12.96 3.45 2.35 18.5 106 1.39 0.70 0.40 0.94 5.280000 0.680 1.75
## 165 3 13.78 2.76 2.30 22.0 90 1.35 0.68 0.41 1.03 9.580000 0.700 1.68
## 166 3 13.73 4.36 2.26 22.5 88 1.28 0.47 0.52 1.15 6.620000 0.780 1.75
## 167 3 13.45 3.70 2.60 23.0 111 1.70 0.92 0.43 1.46 10.680000 0.850 1.56
## 168 3 12.82 3.37 2.30 19.5 88 1.48 0.66 0.40 0.97 10.260000 0.720 1.75
## 169 3 13.58 2.58 2.69 24.5 105 1.55 0.84 0.39 1.54 8.660000 0.740 1.80
## 170 3 13.40 4.60 2.86 25.0 112 1.98 0.96 0.27 1.11 8.500000 0.670 1.92
## 171 3 12.20 3.03 2.32 19.0 96 1.25 0.49 0.40 0.73 5.500000 0.660 1.83
## 172 3 12.77 2.39 2.28 19.5 86 1.39 0.51 0.48 0.64 9.899999 0.570 1.63
## 173 3 14.16 2.51 2.48 20.0 91 1.68 0.70 0.44 1.24 9.700000 0.620 1.71
## 174 3 13.71 5.65 2.45 20.5 95 1.68 0.61 0.52 1.06 7.700000 0.640 1.74
## 175 3 13.40 3.91 2.48 23.0 102 1.80 0.75 0.43 1.41 7.300000 0.700 1.56
## 176 3 13.27 4.28 2.26 20.0 120 1.59 0.69 0.43 1.35 10.200000 0.590 1.56
## 177 3 13.17 2.59 2.37 20.0 120 1.65 0.68 0.53 1.46 9.300000 0.600 1.62
## 178 3 14.13 4.10 2.74 24.5 96 2.05 0.76 0.56 1.35 9.200000 0.610 1.60
## V14
## 1 1065
## 2 1050
## 3 1185
## 4 1480
## 5 735
## 6 1450
## 7 1290
## 8 1295
## 9 1045
## 10 1045
## 11 1510
## 12 1280
## 13 1320
## 14 1150
## 15 1547
## 16 1310
## 17 1280
## 18 1130
## 19 1680
## 20 845
## 21 780
## 22 770
## 23 1035
## 24 1015
## 25 845
## 26 830
## 27 1195
## 28 1285
## 29 915
## 30 1035
## 31 1285
## 32 1515
## 33 990
## 34 1235
## 35 1095
## 36 920
## 37 880
## 38 1105
## 39 1020
## 40 760
## 41 795
## 42 1035
## 43 1095
## 44 680
## 45 885
## 46 1080
## 47 1065
## 48 985
## 49 1060
## 50 1260
## 51 1150
## 52 1265
## 53 1190
## 54 1375
## 55 1060
## 56 1120
## 57 970
## 58 1270
## 59 1285
## 60 520
## 61 680
## 62 450
## 63 630
## 64 420
## 65 355
## 66 678
## 67 502
## 68 510
## 69 750
## 70 718
## 71 870
## 72 410
## 73 472
## 74 985
## 75 886
## 76 428
## 77 392
## 78 500
## 79 750
## 80 463
## 81 278
## 82 714
## 83 630
## 84 515
## 85 520
## 86 450
## 87 495
## 88 562
## 89 680
## 90 625
## 91 480
## 92 450
## 93 495
## 94 290
## 95 345
## 96 937
## 97 625
## 98 428
## 99 660
## 100 406
## 101 710
## 102 562
## 103 438
## 104 415
## 105 672
## 106 315
## 107 510
## 108 488
## 109 312
## 110 680
## 111 562
## 112 325
## 113 607
## 114 434
## 115 385
## 116 407
## 117 495
## 118 345
## 119 372
## 120 564
## 121 625
## 122 465
## 123 365
## 124 380
## 125 380
## 126 378
## 127 352
## 128 466
## 129 342
## 130 580
## 131 630
## 132 530
## 133 560
## 134 600
## 135 650
## 136 695
## 137 720
## 138 515
## 139 580
## 140 590
## 141 600
## 142 780
## 143 520
## 144 550
## 145 855
## 146 830
## 147 415
## 148 625
## 149 650
## 150 550
## 151 500
## 152 480
## 153 425
## 154 675
## 155 640
## 156 725
## 157 480
## 158 880
## 159 660
## 160 620
## 161 520
## 162 680
## 163 570
## 164 675
## 165 615
## 166 520
## 167 695
## 168 685
## 169 750
## 170 630
## 171 510
## 172 470
## 173 660
## 174 740
## 175 750
## 176 835
## 177 840
## 178 560Removes Even Columns in CSV File
wine3<-wine[,c(-2,-4,-6,-8,-10,-12,-14)]
wine3 ## X V2 V4 V6 V8 V10 V12 V14
## 1 1 14.23 2.43 127 3.06 2.29 1.040 1065
## 2 2 13.20 2.14 100 2.76 1.28 1.050 1050
## 3 3 13.16 2.67 101 3.24 2.81 1.030 1185
## 4 4 14.37 2.50 113 3.49 2.18 0.860 1480
## 5 5 13.24 2.87 118 2.69 1.82 1.040 735
## 6 6 14.20 2.45 112 3.39 1.97 1.050 1450
## 7 7 14.39 2.45 96 2.52 1.98 1.020 1290
## 8 8 14.06 2.61 121 2.51 1.25 1.060 1295
## 9 9 14.83 2.17 97 2.98 1.98 1.080 1045
## 10 10 13.86 2.27 98 3.15 1.85 1.010 1045
## 11 11 14.10 2.30 105 3.32 2.38 1.250 1510
## 12 12 14.12 2.32 95 2.43 1.57 1.170 1280
## 13 13 13.75 2.41 89 2.76 1.81 1.150 1320
## 14 14 14.75 2.39 91 3.69 2.81 1.250 1150
## 15 15 14.38 2.38 102 3.64 2.96 1.200 1547
## 16 16 13.63 2.70 112 2.91 1.46 1.280 1310
## 17 17 14.30 2.72 120 3.14 1.97 1.070 1280
## 18 18 13.83 2.62 115 3.40 1.72 1.130 1130
## 19 19 14.19 2.48 108 3.93 1.86 1.230 1680
## 20 20 13.64 2.56 116 3.03 1.66 0.960 845
## 21 21 14.06 2.28 126 3.17 2.10 1.090 780
## 22 22 12.93 2.65 102 2.41 1.98 1.030 770
## 23 23 13.71 2.36 101 2.88 1.69 1.110 1035
## 24 24 12.85 2.52 95 2.37 1.46 1.090 1015
## 25 25 13.50 2.61 96 2.61 1.66 1.120 845
## 26 26 13.05 3.22 124 2.68 1.92 1.130 830
## 27 27 13.39 2.62 93 2.94 1.45 0.920 1195
## 28 28 13.30 2.14 94 2.19 1.35 1.020 1285
## 29 29 13.87 2.80 107 2.97 1.76 1.250 915
## 30 30 14.02 2.21 96 2.33 1.98 1.040 1035
## 31 31 13.73 2.70 101 3.25 2.38 1.190 1285
## 32 32 13.58 2.36 106 3.19 1.95 1.090 1515
## 33 33 13.68 2.36 104 2.69 1.97 1.230 990
## 34 34 13.76 2.70 132 2.74 1.35 1.250 1235
## 35 35 13.51 2.65 110 2.53 1.54 1.100 1095
## 36 36 13.48 2.41 100 2.98 1.86 1.040 920
## 37 37 13.28 2.84 110 2.68 1.36 1.090 880
## 38 38 13.05 2.55 98 2.43 1.44 1.120 1105
## 39 39 13.07 2.10 98 2.64 1.37 1.180 1020
## 40 40 14.22 2.51 128 3.04 2.08 0.890 760
## 41 41 13.56 2.31 117 3.29 2.34 0.950 795
## 42 42 13.41 2.12 90 2.68 1.48 0.910 1035
## 43 43 13.88 2.59 101 3.56 1.70 0.880 1095
## 44 44 13.24 2.29 103 2.63 1.66 0.820 680
## 45 45 13.05 2.10 107 3.00 2.03 0.880 885
## 46 46 14.21 2.44 111 2.65 1.25 0.870 1080
## 47 47 14.38 2.28 102 3.17 2.19 1.040 1065
## 48 48 13.90 2.12 101 3.39 2.14 0.910 985
## 49 49 14.10 2.40 103 2.92 2.38 1.070 1060
## 50 50 13.94 2.27 108 3.54 2.08 1.120 1260
## 51 51 13.05 2.04 92 3.27 2.91 1.120 1150
## 52 52 13.83 2.60 94 2.99 2.29 1.240 1265
## 53 53 13.82 2.42 111 3.74 1.87 1.010 1190
## 54 54 13.77 2.68 115 2.79 1.68 1.130 1375
## 55 55 13.74 2.25 118 2.90 1.62 0.920 1060
## 56 56 13.56 2.46 116 2.78 2.45 0.980 1120
## 57 57 14.22 2.30 118 3.00 2.03 0.940 970
## 58 58 13.29 2.68 102 3.23 1.66 1.070 1270
## 59 59 13.72 2.50 108 3.67 2.04 0.890 1285
## 60 60 12.37 1.36 88 0.57 0.42 1.050 520
## 61 61 12.33 2.28 101 1.09 0.41 1.250 680
## 62 62 12.64 2.02 100 1.41 0.62 0.980 450
## 63 63 13.67 1.92 94 1.79 0.73 1.230 630
## 64 64 12.37 2.16 87 3.10 1.87 1.220 420
## 65 65 12.17 2.53 104 1.75 1.03 1.450 355
## 66 66 12.37 2.56 98 2.65 2.08 1.190 678
## 67 67 13.11 1.70 78 3.18 2.28 1.120 502
## 68 68 12.37 1.92 78 2.00 1.04 1.120 510
## 69 69 13.34 2.36 110 1.30 0.42 1.020 750
## 70 70 12.21 1.75 151 1.28 2.50 1.280 718
## 71 71 12.29 2.21 103 1.02 1.46 0.906 870
## 72 72 13.86 2.67 86 2.86 1.87 1.360 410
## 73 73 13.49 2.24 87 1.84 1.03 0.980 472
## 74 74 12.99 2.60 139 2.89 1.96 1.310 985
## 75 75 11.96 2.30 101 2.14 1.65 0.990 886
## 76 76 11.66 1.92 97 1.57 1.15 1.230 428
## 77 77 13.03 1.71 86 2.03 1.46 1.190 392
## 78 78 11.84 2.23 112 1.32 0.95 0.960 500
## 79 79 12.33 1.95 136 1.85 2.76 1.060 750
## 80 80 12.70 2.40 101 2.55 1.95 1.190 463
## 81 81 12.00 2.00 86 2.26 1.43 1.380 278
## 82 82 12.72 2.20 86 2.53 1.77 1.160 714
## 83 83 12.08 2.51 78 1.58 1.40 1.310 630
## 84 84 13.05 2.32 85 1.59 1.62 0.840 515
## 85 85 11.84 2.58 94 2.21 2.35 0.790 520
## 86 86 12.67 2.24 99 1.94 1.46 1.230 450
## 87 87 12.16 2.31 90 1.69 1.56 1.330 495
## 88 88 11.65 2.62 88 1.61 1.34 1.360 562
## 89 89 11.64 2.46 84 1.69 1.35 1.000 680
## 90 90 12.08 2.30 70 1.59 1.38 1.070 625
## 91 91 12.08 2.32 81 1.50 1.64 1.080 480
## 92 92 12.00 2.42 86 1.25 1.63 1.050 450
## 93 93 12.69 2.26 80 1.46 1.62 0.960 495
## 94 94 12.29 2.22 88 2.25 1.99 1.150 290
## 95 95 11.62 2.28 98 2.26 1.35 1.160 345
## 96 96 12.47 2.20 162 2.27 3.28 1.160 937
## 97 97 11.81 2.74 134 0.99 1.56 0.950 625
## 98 98 12.29 1.98 85 2.50 1.77 1.230 428
## 99 99 12.37 2.10 88 3.75 1.95 1.040 660
## 100 100 12.29 2.21 88 2.99 2.81 1.420 406
## 101 101 12.08 1.70 97 2.17 1.40 1.270 710
## 102 102 12.60 1.90 88 1.36 1.35 1.040 562
## 103 103 12.34 2.46 98 2.11 1.31 0.800 438
## 104 104 11.82 1.88 86 1.64 1.42 0.940 415
## 105 105 12.51 1.98 85 1.92 1.48 1.040 672
## 106 106 12.42 2.27 90 1.84 1.42 0.860 315
## 107 107 12.25 2.12 80 2.03 1.63 1.000 510
## 108 108 12.72 2.28 84 1.76 1.63 0.880 488
## 109 109 12.22 1.94 92 2.04 2.08 0.860 312
## 110 110 11.61 2.70 94 2.92 2.49 0.960 680
## 111 111 11.46 1.82 107 2.58 3.58 0.750 562
## 112 112 12.52 2.17 88 2.27 1.22 0.900 325
## 113 113 11.76 2.92 103 2.03 1.05 1.230 607
## 114 114 11.41 2.50 88 2.01 1.44 1.100 434
## 115 115 12.08 2.50 84 2.29 1.04 0.930 385
## 116 116 11.03 2.20 85 2.17 2.01 1.710 407
## 117 117 11.82 1.99 86 1.60 1.53 0.950 495
## 118 118 12.42 2.19 108 2.09 1.61 1.060 345
## 119 119 12.77 1.98 80 1.25 0.83 0.700 372
## 120 120 12.00 2.00 87 1.64 1.87 0.930 564
## 121 121 11.45 2.42 96 2.79 1.83 0.800 625
## 122 122 11.56 3.23 119 5.08 1.87 0.930 465
## 123 123 12.42 2.73 102 2.13 1.71 0.920 365
## 124 124 13.05 2.13 86 2.65 2.01 0.730 380
## 125 125 11.87 2.39 82 3.03 2.91 0.750 380
## 126 126 12.07 2.17 85 2.65 1.35 0.860 378
## 127 127 12.43 2.29 86 3.15 1.77 0.690 352
## 128 128 11.79 2.78 92 2.24 1.76 0.970 466
## 129 129 12.37 2.30 88 2.45 1.90 0.890 342
## 130 130 12.04 2.38 80 1.75 1.35 0.790 580
## 131 131 12.86 2.32 122 1.25 0.94 0.760 630
## 132 132 12.88 2.40 104 1.22 0.83 0.740 530
## 133 133 12.81 2.40 98 1.09 0.83 0.660 560
## 134 134 12.70 2.36 106 1.20 0.84 0.780 600
## 135 135 12.51 2.25 85 0.58 1.25 0.750 650
## 136 136 12.60 2.20 94 0.66 0.94 0.730 695
## 137 137 12.25 2.54 89 0.47 0.80 0.750 720
## 138 138 12.53 2.64 96 0.60 1.10 0.820 515
## 139 139 13.49 2.19 88 0.48 0.88 0.810 580
## 140 140 12.84 2.61 101 0.60 0.81 0.890 590
## 141 141 12.93 2.70 96 0.50 0.75 0.770 600
## 142 142 13.36 2.35 89 0.50 0.64 0.700 780
## 143 143 13.52 2.72 97 0.52 0.55 0.890 520
## 144 144 13.62 2.35 92 0.80 1.02 0.910 550
## 145 145 12.25 2.20 112 0.78 1.14 0.650 855
## 146 146 13.16 2.15 102 0.55 1.30 0.600 830
## 147 147 13.88 2.23 80 0.34 0.68 0.580 415
## 148 148 12.87 2.48 86 0.65 0.86 0.540 625
## 149 149 13.32 2.38 92 0.76 1.25 0.550 650
## 150 150 13.08 2.36 113 1.39 1.14 0.570 550
## 151 151 13.50 2.62 123 1.57 1.25 0.590 500
## 152 152 12.79 2.48 112 1.36 1.26 0.480 480
## 153 153 13.11 2.75 116 1.28 1.56 0.610 425
## 154 154 13.23 2.28 98 0.83 1.87 0.560 675
## 155 155 12.58 2.10 103 0.58 1.40 0.580 640
## 156 156 13.17 2.32 93 0.63 1.55 0.600 725
## 157 157 13.84 2.38 89 0.83 1.56 0.570 480
## 158 158 12.45 2.64 97 0.58 1.14 0.670 880
## 159 159 14.34 2.70 98 1.31 2.70 0.570 660
## 160 160 13.48 2.64 89 1.10 2.29 0.570 620
## 161 161 12.36 2.38 88 0.92 1.04 0.560 520
## 162 162 13.69 2.54 107 0.56 0.80 0.960 680
## 163 163 12.85 2.58 106 0.60 0.96 0.870 570
## 164 164 12.96 2.35 106 0.70 0.94 0.680 675
## 165 165 13.78 2.30 90 0.68 1.03 0.700 615
## 166 166 13.73 2.26 88 0.47 1.15 0.780 520
## 167 167 13.45 2.60 111 0.92 1.46 0.850 695
## 168 168 12.82 2.30 88 0.66 0.97 0.720 685
## 169 169 13.58 2.69 105 0.84 1.54 0.740 750
## 170 170 13.40 2.86 112 0.96 1.11 0.670 630
## 171 171 12.20 2.32 96 0.49 0.73 0.660 510
## 172 172 12.77 2.28 86 0.51 0.64 0.570 470
## 173 173 14.16 2.48 91 0.70 1.24 0.620 660
## 174 174 13.71 2.45 95 0.61 1.06 0.640 740
## 175 175 13.40 2.48 102 0.75 1.41 0.700 750
## 176 176 13.27 2.26 120 0.69 1.35 0.590 835
## 177 177 13.17 2.37 120 0.68 1.46 0.600 840
## 178 178 14.13 2.74 96 0.76 1.35 0.610 560Removes 1st and 15th Columns in the CSV File
wine4 <-wine[,c(-1,-15)]
wine4 ## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13
## 1 1 14.23 1.71 2.43 15.6 127 2.80 3.06 0.28 2.29 5.640000 1.040 3.92
## 2 1 13.20 1.78 2.14 11.2 100 2.65 2.76 0.26 1.28 4.380000 1.050 3.40
## 3 1 13.16 2.36 2.67 18.6 101 2.80 3.24 0.30 2.81 5.680000 1.030 3.17
## 4 1 14.37 1.95 2.50 16.8 113 3.85 3.49 0.24 2.18 7.800000 0.860 3.45
## 5 1 13.24 2.59 2.87 21.0 118 2.80 2.69 0.39 1.82 4.320000 1.040 2.93
## 6 1 14.20 1.76 2.45 15.2 112 3.27 3.39 0.34 1.97 6.750000 1.050 2.85
## 7 1 14.39 1.87 2.45 14.6 96 2.50 2.52 0.30 1.98 5.250000 1.020 3.58
## 8 1 14.06 2.15 2.61 17.6 121 2.60 2.51 0.31 1.25 5.050000 1.060 3.58
## 9 1 14.83 1.64 2.17 14.0 97 2.80 2.98 0.29 1.98 5.200000 1.080 2.85
## 10 1 13.86 1.35 2.27 16.0 98 2.98 3.15 0.22 1.85 7.220000 1.010 3.55
## 11 1 14.10 2.16 2.30 18.0 105 2.95 3.32 0.22 2.38 5.750000 1.250 3.17
## 12 1 14.12 1.48 2.32 16.8 95 2.20 2.43 0.26 1.57 5.000000 1.170 2.82
## 13 1 13.75 1.73 2.41 16.0 89 2.60 2.76 0.29 1.81 5.600000 1.150 2.90
## 14 1 14.75 1.73 2.39 11.4 91 3.10 3.69 0.43 2.81 5.400000 1.250 2.73
## 15 1 14.38 1.87 2.38 12.0 102 3.30 3.64 0.29 2.96 7.500000 1.200 3.00
## 16 1 13.63 1.81 2.70 17.2 112 2.85 2.91 0.30 1.46 7.300000 1.280 2.88
## 17 1 14.30 1.92 2.72 20.0 120 2.80 3.14 0.33 1.97 6.200000 1.070 2.65
## 18 1 13.83 1.57 2.62 20.0 115 2.95 3.40 0.40 1.72 6.600000 1.130 2.57
## 19 1 14.19 1.59 2.48 16.5 108 3.30 3.93 0.32 1.86 8.700000 1.230 2.82
## 20 1 13.64 3.10 2.56 15.2 116 2.70 3.03 0.17 1.66 5.100000 0.960 3.36
## 21 1 14.06 1.63 2.28 16.0 126 3.00 3.17 0.24 2.10 5.650000 1.090 3.71
## 22 1 12.93 3.80 2.65 18.6 102 2.41 2.41 0.25 1.98 4.500000 1.030 3.52
## 23 1 13.71 1.86 2.36 16.6 101 2.61 2.88 0.27 1.69 3.800000 1.110 4.00
## 24 1 12.85 1.60 2.52 17.8 95 2.48 2.37 0.26 1.46 3.930000 1.090 3.63
## 25 1 13.50 1.81 2.61 20.0 96 2.53 2.61 0.28 1.66 3.520000 1.120 3.82
## 26 1 13.05 2.05 3.22 25.0 124 2.63 2.68 0.47 1.92 3.580000 1.130 3.20
## 27 1 13.39 1.77 2.62 16.1 93 2.85 2.94 0.34 1.45 4.800000 0.920 3.22
## 28 1 13.30 1.72 2.14 17.0 94 2.40 2.19 0.27 1.35 3.950000 1.020 2.77
## 29 1 13.87 1.90 2.80 19.4 107 2.95 2.97 0.37 1.76 4.500000 1.250 3.40
## 30 1 14.02 1.68 2.21 16.0 96 2.65 2.33 0.26 1.98 4.700000 1.040 3.59
## 31 1 13.73 1.50 2.70 22.5 101 3.00 3.25 0.29 2.38 5.700000 1.190 2.71
## 32 1 13.58 1.66 2.36 19.1 106 2.86 3.19 0.22 1.95 6.900000 1.090 2.88
## 33 1 13.68 1.83 2.36 17.2 104 2.42 2.69 0.42 1.97 3.840000 1.230 2.87
## 34 1 13.76 1.53 2.70 19.5 132 2.95 2.74 0.50 1.35 5.400000 1.250 3.00
## 35 1 13.51 1.80 2.65 19.0 110 2.35 2.53 0.29 1.54 4.200000 1.100 2.87
## 36 1 13.48 1.81 2.41 20.5 100 2.70 2.98 0.26 1.86 5.100000 1.040 3.47
## 37 1 13.28 1.64 2.84 15.5 110 2.60 2.68 0.34 1.36 4.600000 1.090 2.78
## 38 1 13.05 1.65 2.55 18.0 98 2.45 2.43 0.29 1.44 4.250000 1.120 2.51
## 39 1 13.07 1.50 2.10 15.5 98 2.40 2.64 0.28 1.37 3.700000 1.180 2.69
## 40 1 14.22 3.99 2.51 13.2 128 3.00 3.04 0.20 2.08 5.100000 0.890 3.53
## 41 1 13.56 1.71 2.31 16.2 117 3.15 3.29 0.34 2.34 6.130000 0.950 3.38
## 42 1 13.41 3.84 2.12 18.8 90 2.45 2.68 0.27 1.48 4.280000 0.910 3.00
## 43 1 13.88 1.89 2.59 15.0 101 3.25 3.56 0.17 1.70 5.430000 0.880 3.56
## 44 1 13.24 3.98 2.29 17.5 103 2.64 2.63 0.32 1.66 4.360000 0.820 3.00
## 45 1 13.05 1.77 2.10 17.0 107 3.00 3.00 0.28 2.03 5.040000 0.880 3.35
## 46 1 14.21 4.04 2.44 18.9 111 2.85 2.65 0.30 1.25 5.240000 0.870 3.33
## 47 1 14.38 3.59 2.28 16.0 102 3.25 3.17 0.27 2.19 4.900000 1.040 3.44
## 48 1 13.90 1.68 2.12 16.0 101 3.10 3.39 0.21 2.14 6.100000 0.910 3.33
## 49 1 14.10 2.02 2.40 18.8 103 2.75 2.92 0.32 2.38 6.200000 1.070 2.75
## 50 1 13.94 1.73 2.27 17.4 108 2.88 3.54 0.32 2.08 8.900000 1.120 3.10
## 51 1 13.05 1.73 2.04 12.4 92 2.72 3.27 0.17 2.91 7.200000 1.120 2.91
## 52 1 13.83 1.65 2.60 17.2 94 2.45 2.99 0.22 2.29 5.600000 1.240 3.37
## 53 1 13.82 1.75 2.42 14.0 111 3.88 3.74 0.32 1.87 7.050000 1.010 3.26
## 54 1 13.77 1.90 2.68 17.1 115 3.00 2.79 0.39 1.68 6.300000 1.130 2.93
## 55 1 13.74 1.67 2.25 16.4 118 2.60 2.90 0.21 1.62 5.850000 0.920 3.20
## 56 1 13.56 1.73 2.46 20.5 116 2.96 2.78 0.20 2.45 6.250000 0.980 3.03
## 57 1 14.22 1.70 2.30 16.3 118 3.20 3.00 0.26 2.03 6.380000 0.940 3.31
## 58 1 13.29 1.97 2.68 16.8 102 3.00 3.23 0.31 1.66 6.000000 1.070 2.84
## 59 1 13.72 1.43 2.50 16.7 108 3.40 3.67 0.19 2.04 6.800000 0.890 2.87
## 60 2 12.37 0.94 1.36 10.6 88 1.98 0.57 0.28 0.42 1.950000 1.050 1.82
## 61 2 12.33 1.10 2.28 16.0 101 2.05 1.09 0.63 0.41 3.270000 1.250 1.67
## 62 2 12.64 1.36 2.02 16.8 100 2.02 1.41 0.53 0.62 5.750000 0.980 1.59
## 63 2 13.67 1.25 1.92 18.0 94 2.10 1.79 0.32 0.73 3.800000 1.230 2.46
## 64 2 12.37 1.13 2.16 19.0 87 3.50 3.10 0.19 1.87 4.450000 1.220 2.87
## 65 2 12.17 1.45 2.53 19.0 104 1.89 1.75 0.45 1.03 2.950000 1.450 2.23
## 66 2 12.37 1.21 2.56 18.1 98 2.42 2.65 0.37 2.08 4.600000 1.190 2.30
## 67 2 13.11 1.01 1.70 15.0 78 2.98 3.18 0.26 2.28 5.300000 1.120 3.18
## 68 2 12.37 1.17 1.92 19.6 78 2.11 2.00 0.27 1.04 4.680000 1.120 3.48
## 69 2 13.34 0.94 2.36 17.0 110 2.53 1.30 0.55 0.42 3.170000 1.020 1.93
## 70 2 12.21 1.19 1.75 16.8 151 1.85 1.28 0.14 2.50 2.850000 1.280 3.07
## 71 2 12.29 1.61 2.21 20.4 103 1.10 1.02 0.37 1.46 3.050000 0.906 1.82
## 72 2 13.86 1.51 2.67 25.0 86 2.95 2.86 0.21 1.87 3.380000 1.360 3.16
## 73 2 13.49 1.66 2.24 24.0 87 1.88 1.84 0.27 1.03 3.740000 0.980 2.78
## 74 2 12.99 1.67 2.60 30.0 139 3.30 2.89 0.21 1.96 3.350000 1.310 3.50
## 75 2 11.96 1.09 2.30 21.0 101 3.38 2.14 0.13 1.65 3.210000 0.990 3.13
## 76 2 11.66 1.88 1.92 16.0 97 1.61 1.57 0.34 1.15 3.800000 1.230 2.14
## 77 2 13.03 0.90 1.71 16.0 86 1.95 2.03 0.24 1.46 4.600000 1.190 2.48
## 78 2 11.84 2.89 2.23 18.0 112 1.72 1.32 0.43 0.95 2.650000 0.960 2.52
## 79 2 12.33 0.99 1.95 14.8 136 1.90 1.85 0.35 2.76 3.400000 1.060 2.31
## 80 2 12.70 3.87 2.40 23.0 101 2.83 2.55 0.43 1.95 2.570000 1.190 3.13
## 81 2 12.00 0.92 2.00 19.0 86 2.42 2.26 0.30 1.43 2.500000 1.380 3.12
## 82 2 12.72 1.81 2.20 18.8 86 2.20 2.53 0.26 1.77 3.900000 1.160 3.14
## 83 2 12.08 1.13 2.51 24.0 78 2.00 1.58 0.40 1.40 2.200000 1.310 2.72
## 84 2 13.05 3.86 2.32 22.5 85 1.65 1.59 0.61 1.62 4.800000 0.840 2.01
## 85 2 11.84 0.89 2.58 18.0 94 2.20 2.21 0.22 2.35 3.050000 0.790 3.08
## 86 2 12.67 0.98 2.24 18.0 99 2.20 1.94 0.30 1.46 2.620000 1.230 3.16
## 87 2 12.16 1.61 2.31 22.8 90 1.78 1.69 0.43 1.56 2.450000 1.330 2.26
## 88 2 11.65 1.67 2.62 26.0 88 1.92 1.61 0.40 1.34 2.600000 1.360 3.21
## 89 2 11.64 2.06 2.46 21.6 84 1.95 1.69 0.48 1.35 2.800000 1.000 2.75
## 90 2 12.08 1.33 2.30 23.6 70 2.20 1.59 0.42 1.38 1.740000 1.070 3.21
## 91 2 12.08 1.83 2.32 18.5 81 1.60 1.50 0.52 1.64 2.400000 1.080 2.27
## 92 2 12.00 1.51 2.42 22.0 86 1.45 1.25 0.50 1.63 3.600000 1.050 2.65
## 93 2 12.69 1.53 2.26 20.7 80 1.38 1.46 0.58 1.62 3.050000 0.960 2.06
## 94 2 12.29 2.83 2.22 18.0 88 2.45 2.25 0.25 1.99 2.150000 1.150 3.30
## 95 2 11.62 1.99 2.28 18.0 98 3.02 2.26 0.17 1.35 3.250000 1.160 2.96
## 96 2 12.47 1.52 2.20 19.0 162 2.50 2.27 0.32 3.28 2.600000 1.160 2.63
## 97 2 11.81 2.12 2.74 21.5 134 1.60 0.99 0.14 1.56 2.500000 0.950 2.26
## 98 2 12.29 1.41 1.98 16.0 85 2.55 2.50 0.29 1.77 2.900000 1.230 2.74
## 99 2 12.37 1.07 2.10 18.5 88 3.52 3.75 0.24 1.95 4.500000 1.040 2.77
## 100 2 12.29 3.17 2.21 18.0 88 2.85 2.99 0.45 2.81 2.300000 1.420 2.83
## 101 2 12.08 2.08 1.70 17.5 97 2.23 2.17 0.26 1.40 3.300000 1.270 2.96
## 102 2 12.60 1.34 1.90 18.5 88 1.45 1.36 0.29 1.35 2.450000 1.040 2.77
## 103 2 12.34 2.45 2.46 21.0 98 2.56 2.11 0.34 1.31 2.800000 0.800 3.38
## 104 2 11.82 1.72 1.88 19.5 86 2.50 1.64 0.37 1.42 2.060000 0.940 2.44
## 105 2 12.51 1.73 1.98 20.5 85 2.20 1.92 0.32 1.48 2.940000 1.040 3.57
## 106 2 12.42 2.55 2.27 22.0 90 1.68 1.84 0.66 1.42 2.700000 0.860 3.30
## 107 2 12.25 1.73 2.12 19.0 80 1.65 2.03 0.37 1.63 3.400000 1.000 3.17
## 108 2 12.72 1.75 2.28 22.5 84 1.38 1.76 0.48 1.63 3.300000 0.880 2.42
## 109 2 12.22 1.29 1.94 19.0 92 2.36 2.04 0.39 2.08 2.700000 0.860 3.02
## 110 2 11.61 1.35 2.70 20.0 94 2.74 2.92 0.29 2.49 2.650000 0.960 3.26
## 111 2 11.46 3.74 1.82 19.5 107 3.18 2.58 0.24 3.58 2.900000 0.750 2.81
## 112 2 12.52 2.43 2.17 21.0 88 2.55 2.27 0.26 1.22 2.000000 0.900 2.78
## 113 2 11.76 2.68 2.92 20.0 103 1.75 2.03 0.60 1.05 3.800000 1.230 2.50
## 114 2 11.41 0.74 2.50 21.0 88 2.48 2.01 0.42 1.44 3.080000 1.100 2.31
## 115 2 12.08 1.39 2.50 22.5 84 2.56 2.29 0.43 1.04 2.900000 0.930 3.19
## 116 2 11.03 1.51 2.20 21.5 85 2.46 2.17 0.52 2.01 1.900000 1.710 2.87
## 117 2 11.82 1.47 1.99 20.8 86 1.98 1.60 0.30 1.53 1.950000 0.950 3.33
## 118 2 12.42 1.61 2.19 22.5 108 2.00 2.09 0.34 1.61 2.060000 1.060 2.96
## 119 2 12.77 3.43 1.98 16.0 80 1.63 1.25 0.43 0.83 3.400000 0.700 2.12
## 120 2 12.00 3.43 2.00 19.0 87 2.00 1.64 0.37 1.87 1.280000 0.930 3.05
## 121 2 11.45 2.40 2.42 20.0 96 2.90 2.79 0.32 1.83 3.250000 0.800 3.39
## 122 2 11.56 2.05 3.23 28.5 119 3.18 5.08 0.47 1.87 6.000000 0.930 3.69
## 123 2 12.42 4.43 2.73 26.5 102 2.20 2.13 0.43 1.71 2.080000 0.920 3.12
## 124 2 13.05 5.80 2.13 21.5 86 2.62 2.65 0.30 2.01 2.600000 0.730 3.10
## 125 2 11.87 4.31 2.39 21.0 82 2.86 3.03 0.21 2.91 2.800000 0.750 3.64
## 126 2 12.07 2.16 2.17 21.0 85 2.60 2.65 0.37 1.35 2.760000 0.860 3.28
## 127 2 12.43 1.53 2.29 21.5 86 2.74 3.15 0.39 1.77 3.940000 0.690 2.84
## 128 2 11.79 2.13 2.78 28.5 92 2.13 2.24 0.58 1.76 3.000000 0.970 2.44
## 129 2 12.37 1.63 2.30 24.5 88 2.22 2.45 0.40 1.90 2.120000 0.890 2.78
## 130 2 12.04 4.30 2.38 22.0 80 2.10 1.75 0.42 1.35 2.600000 0.790 2.57
## 131 3 12.86 1.35 2.32 18.0 122 1.51 1.25 0.21 0.94 4.100000 0.760 1.29
## 132 3 12.88 2.99 2.40 20.0 104 1.30 1.22 0.24 0.83 5.400000 0.740 1.42
## 133 3 12.81 2.31 2.40 24.0 98 1.15 1.09 0.27 0.83 5.700000 0.660 1.36
## 134 3 12.70 3.55 2.36 21.5 106 1.70 1.20 0.17 0.84 5.000000 0.780 1.29
## 135 3 12.51 1.24 2.25 17.5 85 2.00 0.58 0.60 1.25 5.450000 0.750 1.51
## 136 3 12.60 2.46 2.20 18.5 94 1.62 0.66 0.63 0.94 7.100000 0.730 1.58
## 137 3 12.25 4.72 2.54 21.0 89 1.38 0.47 0.53 0.80 3.850000 0.750 1.27
## 138 3 12.53 5.51 2.64 25.0 96 1.79 0.60 0.63 1.10 5.000000 0.820 1.69
## 139 3 13.49 3.59 2.19 19.5 88 1.62 0.48 0.58 0.88 5.700000 0.810 1.82
## 140 3 12.84 2.96 2.61 24.0 101 2.32 0.60 0.53 0.81 4.920000 0.890 2.15
## 141 3 12.93 2.81 2.70 21.0 96 1.54 0.50 0.53 0.75 4.600000 0.770 2.31
## 142 3 13.36 2.56 2.35 20.0 89 1.40 0.50 0.37 0.64 5.600000 0.700 2.47
## 143 3 13.52 3.17 2.72 23.5 97 1.55 0.52 0.50 0.55 4.350000 0.890 2.06
## 144 3 13.62 4.95 2.35 20.0 92 2.00 0.80 0.47 1.02 4.400000 0.910 2.05
## 145 3 12.25 3.88 2.20 18.5 112 1.38 0.78 0.29 1.14 8.210000 0.650 2.00
## 146 3 13.16 3.57 2.15 21.0 102 1.50 0.55 0.43 1.30 4.000000 0.600 1.68
## 147 3 13.88 5.04 2.23 20.0 80 0.98 0.34 0.40 0.68 4.900000 0.580 1.33
## 148 3 12.87 4.61 2.48 21.5 86 1.70 0.65 0.47 0.86 7.650000 0.540 1.86
## 149 3 13.32 3.24 2.38 21.5 92 1.93 0.76 0.45 1.25 8.420000 0.550 1.62
## 150 3 13.08 3.90 2.36 21.5 113 1.41 1.39 0.34 1.14 9.400000 0.570 1.33
## 151 3 13.50 3.12 2.62 24.0 123 1.40 1.57 0.22 1.25 8.600000 0.590 1.30
## 152 3 12.79 2.67 2.48 22.0 112 1.48 1.36 0.24 1.26 10.800000 0.480 1.47
## 153 3 13.11 1.90 2.75 25.5 116 2.20 1.28 0.26 1.56 7.100000 0.610 1.33
## 154 3 13.23 3.30 2.28 18.5 98 1.80 0.83 0.61 1.87 10.520000 0.560 1.51
## 155 3 12.58 1.29 2.10 20.0 103 1.48 0.58 0.53 1.40 7.600000 0.580 1.55
## 156 3 13.17 5.19 2.32 22.0 93 1.74 0.63 0.61 1.55 7.900000 0.600 1.48
## 157 3 13.84 4.12 2.38 19.5 89 1.80 0.83 0.48 1.56 9.010000 0.570 1.64
## 158 3 12.45 3.03 2.64 27.0 97 1.90 0.58 0.63 1.14 7.500000 0.670 1.73
## 159 3 14.34 1.68 2.70 25.0 98 2.80 1.31 0.53 2.70 13.000000 0.570 1.96
## 160 3 13.48 1.67 2.64 22.5 89 2.60 1.10 0.52 2.29 11.750000 0.570 1.78
## 161 3 12.36 3.83 2.38 21.0 88 2.30 0.92 0.50 1.04 7.650000 0.560 1.58
## 162 3 13.69 3.26 2.54 20.0 107 1.83 0.56 0.50 0.80 5.880000 0.960 1.82
## 163 3 12.85 3.27 2.58 22.0 106 1.65 0.60 0.60 0.96 5.580000 0.870 2.11
## 164 3 12.96 3.45 2.35 18.5 106 1.39 0.70 0.40 0.94 5.280000 0.680 1.75
## 165 3 13.78 2.76 2.30 22.0 90 1.35 0.68 0.41 1.03 9.580000 0.700 1.68
## 166 3 13.73 4.36 2.26 22.5 88 1.28 0.47 0.52 1.15 6.620000 0.780 1.75
## 167 3 13.45 3.70 2.60 23.0 111 1.70 0.92 0.43 1.46 10.680000 0.850 1.56
## 168 3 12.82 3.37 2.30 19.5 88 1.48 0.66 0.40 0.97 10.260000 0.720 1.75
## 169 3 13.58 2.58 2.69 24.5 105 1.55 0.84 0.39 1.54 8.660000 0.740 1.80
## 170 3 13.40 4.60 2.86 25.0 112 1.98 0.96 0.27 1.11 8.500000 0.670 1.92
## 171 3 12.20 3.03 2.32 19.0 96 1.25 0.49 0.40 0.73 5.500000 0.660 1.83
## 172 3 12.77 2.39 2.28 19.5 86 1.39 0.51 0.48 0.64 9.899999 0.570 1.63
## 173 3 14.16 2.51 2.48 20.0 91 1.68 0.70 0.44 1.24 9.700000 0.620 1.71
## 174 3 13.71 5.65 2.45 20.5 95 1.68 0.61 0.52 1.06 7.700000 0.640 1.74
## 175 3 13.40 3.91 2.48 23.0 102 1.80 0.75 0.43 1.41 7.300000 0.700 1.56
## 176 3 13.27 4.28 2.26 20.0 120 1.59 0.69 0.43 1.35 10.200000 0.590 1.56
## 177 3 13.17 2.59 2.37 20.0 120 1.65 0.68 0.53 1.46 9.300000 0.600 1.62
## 178 3 14.13 4.10 2.74 24.5 96 2.05 0.76 0.56 1.35 9.200000 0.610 1.60Renaming the Column Names
colnames(wine4)<-c( "Alcohol", " Malicacid", "Ash", "Alcalinityofash", "Magnesium", "Totalphenols", "Flavanoids", "Nonflavanoidphenols", "Proanthocyanins", "Colorintensity", "Hue", "OD280/OD315 of diluted wines", "Proline")
wine4 ## Alcohol Malicacid Ash Alcalinityofash Magnesium Totalphenols
## 1 1 14.23 1.71 2.43 15.6 127
## 2 1 13.20 1.78 2.14 11.2 100
## 3 1 13.16 2.36 2.67 18.6 101
## 4 1 14.37 1.95 2.50 16.8 113
## 5 1 13.24 2.59 2.87 21.0 118
## 6 1 14.20 1.76 2.45 15.2 112
## 7 1 14.39 1.87 2.45 14.6 96
## 8 1 14.06 2.15 2.61 17.6 121
## 9 1 14.83 1.64 2.17 14.0 97
## 10 1 13.86 1.35 2.27 16.0 98
## 11 1 14.10 2.16 2.30 18.0 105
## 12 1 14.12 1.48 2.32 16.8 95
## 13 1 13.75 1.73 2.41 16.0 89
## 14 1 14.75 1.73 2.39 11.4 91
## 15 1 14.38 1.87 2.38 12.0 102
## 16 1 13.63 1.81 2.70 17.2 112
## 17 1 14.30 1.92 2.72 20.0 120
## 18 1 13.83 1.57 2.62 20.0 115
## 19 1 14.19 1.59 2.48 16.5 108
## 20 1 13.64 3.10 2.56 15.2 116
## 21 1 14.06 1.63 2.28 16.0 126
## 22 1 12.93 3.80 2.65 18.6 102
## 23 1 13.71 1.86 2.36 16.6 101
## 24 1 12.85 1.60 2.52 17.8 95
## 25 1 13.50 1.81 2.61 20.0 96
## 26 1 13.05 2.05 3.22 25.0 124
## 27 1 13.39 1.77 2.62 16.1 93
## 28 1 13.30 1.72 2.14 17.0 94
## 29 1 13.87 1.90 2.80 19.4 107
## 30 1 14.02 1.68 2.21 16.0 96
## 31 1 13.73 1.50 2.70 22.5 101
## 32 1 13.58 1.66 2.36 19.1 106
## 33 1 13.68 1.83 2.36 17.2 104
## 34 1 13.76 1.53 2.70 19.5 132
## 35 1 13.51 1.80 2.65 19.0 110
## 36 1 13.48 1.81 2.41 20.5 100
## 37 1 13.28 1.64 2.84 15.5 110
## 38 1 13.05 1.65 2.55 18.0 98
## 39 1 13.07 1.50 2.10 15.5 98
## 40 1 14.22 3.99 2.51 13.2 128
## 41 1 13.56 1.71 2.31 16.2 117
## 42 1 13.41 3.84 2.12 18.8 90
## 43 1 13.88 1.89 2.59 15.0 101
## 44 1 13.24 3.98 2.29 17.5 103
## 45 1 13.05 1.77 2.10 17.0 107
## 46 1 14.21 4.04 2.44 18.9 111
## 47 1 14.38 3.59 2.28 16.0 102
## 48 1 13.90 1.68 2.12 16.0 101
## 49 1 14.10 2.02 2.40 18.8 103
## 50 1 13.94 1.73 2.27 17.4 108
## 51 1 13.05 1.73 2.04 12.4 92
## 52 1 13.83 1.65 2.60 17.2 94
## 53 1 13.82 1.75 2.42 14.0 111
## 54 1 13.77 1.90 2.68 17.1 115
## 55 1 13.74 1.67 2.25 16.4 118
## 56 1 13.56 1.73 2.46 20.5 116
## 57 1 14.22 1.70 2.30 16.3 118
## 58 1 13.29 1.97 2.68 16.8 102
## 59 1 13.72 1.43 2.50 16.7 108
## 60 2 12.37 0.94 1.36 10.6 88
## 61 2 12.33 1.10 2.28 16.0 101
## 62 2 12.64 1.36 2.02 16.8 100
## 63 2 13.67 1.25 1.92 18.0 94
## 64 2 12.37 1.13 2.16 19.0 87
## 65 2 12.17 1.45 2.53 19.0 104
## 66 2 12.37 1.21 2.56 18.1 98
## 67 2 13.11 1.01 1.70 15.0 78
## 68 2 12.37 1.17 1.92 19.6 78
## 69 2 13.34 0.94 2.36 17.0 110
## 70 2 12.21 1.19 1.75 16.8 151
## 71 2 12.29 1.61 2.21 20.4 103
## 72 2 13.86 1.51 2.67 25.0 86
## 73 2 13.49 1.66 2.24 24.0 87
## 74 2 12.99 1.67 2.60 30.0 139
## 75 2 11.96 1.09 2.30 21.0 101
## 76 2 11.66 1.88 1.92 16.0 97
## 77 2 13.03 0.90 1.71 16.0 86
## 78 2 11.84 2.89 2.23 18.0 112
## 79 2 12.33 0.99 1.95 14.8 136
## 80 2 12.70 3.87 2.40 23.0 101
## 81 2 12.00 0.92 2.00 19.0 86
## 82 2 12.72 1.81 2.20 18.8 86
## 83 2 12.08 1.13 2.51 24.0 78
## 84 2 13.05 3.86 2.32 22.5 85
## 85 2 11.84 0.89 2.58 18.0 94
## 86 2 12.67 0.98 2.24 18.0 99
## 87 2 12.16 1.61 2.31 22.8 90
## 88 2 11.65 1.67 2.62 26.0 88
## 89 2 11.64 2.06 2.46 21.6 84
## 90 2 12.08 1.33 2.30 23.6 70
## 91 2 12.08 1.83 2.32 18.5 81
## 92 2 12.00 1.51 2.42 22.0 86
## 93 2 12.69 1.53 2.26 20.7 80
## 94 2 12.29 2.83 2.22 18.0 88
## 95 2 11.62 1.99 2.28 18.0 98
## 96 2 12.47 1.52 2.20 19.0 162
## 97 2 11.81 2.12 2.74 21.5 134
## 98 2 12.29 1.41 1.98 16.0 85
## 99 2 12.37 1.07 2.10 18.5 88
## 100 2 12.29 3.17 2.21 18.0 88
## 101 2 12.08 2.08 1.70 17.5 97
## 102 2 12.60 1.34 1.90 18.5 88
## 103 2 12.34 2.45 2.46 21.0 98
## 104 2 11.82 1.72 1.88 19.5 86
## 105 2 12.51 1.73 1.98 20.5 85
## 106 2 12.42 2.55 2.27 22.0 90
## 107 2 12.25 1.73 2.12 19.0 80
## 108 2 12.72 1.75 2.28 22.5 84
## 109 2 12.22 1.29 1.94 19.0 92
## 110 2 11.61 1.35 2.70 20.0 94
## 111 2 11.46 3.74 1.82 19.5 107
## 112 2 12.52 2.43 2.17 21.0 88
## 113 2 11.76 2.68 2.92 20.0 103
## 114 2 11.41 0.74 2.50 21.0 88
## 115 2 12.08 1.39 2.50 22.5 84
## 116 2 11.03 1.51 2.20 21.5 85
## 117 2 11.82 1.47 1.99 20.8 86
## 118 2 12.42 1.61 2.19 22.5 108
## 119 2 12.77 3.43 1.98 16.0 80
## 120 2 12.00 3.43 2.00 19.0 87
## 121 2 11.45 2.40 2.42 20.0 96
## 122 2 11.56 2.05 3.23 28.5 119
## 123 2 12.42 4.43 2.73 26.5 102
## 124 2 13.05 5.80 2.13 21.5 86
## 125 2 11.87 4.31 2.39 21.0 82
## 126 2 12.07 2.16 2.17 21.0 85
## 127 2 12.43 1.53 2.29 21.5 86
## 128 2 11.79 2.13 2.78 28.5 92
## 129 2 12.37 1.63 2.30 24.5 88
## 130 2 12.04 4.30 2.38 22.0 80
## 131 3 12.86 1.35 2.32 18.0 122
## 132 3 12.88 2.99 2.40 20.0 104
## 133 3 12.81 2.31 2.40 24.0 98
## 134 3 12.70 3.55 2.36 21.5 106
## 135 3 12.51 1.24 2.25 17.5 85
## 136 3 12.60 2.46 2.20 18.5 94
## 137 3 12.25 4.72 2.54 21.0 89
## 138 3 12.53 5.51 2.64 25.0 96
## 139 3 13.49 3.59 2.19 19.5 88
## 140 3 12.84 2.96 2.61 24.0 101
## 141 3 12.93 2.81 2.70 21.0 96
## 142 3 13.36 2.56 2.35 20.0 89
## 143 3 13.52 3.17 2.72 23.5 97
## 144 3 13.62 4.95 2.35 20.0 92
## 145 3 12.25 3.88 2.20 18.5 112
## 146 3 13.16 3.57 2.15 21.0 102
## 147 3 13.88 5.04 2.23 20.0 80
## 148 3 12.87 4.61 2.48 21.5 86
## 149 3 13.32 3.24 2.38 21.5 92
## 150 3 13.08 3.90 2.36 21.5 113
## 151 3 13.50 3.12 2.62 24.0 123
## 152 3 12.79 2.67 2.48 22.0 112
## 153 3 13.11 1.90 2.75 25.5 116
## 154 3 13.23 3.30 2.28 18.5 98
## 155 3 12.58 1.29 2.10 20.0 103
## 156 3 13.17 5.19 2.32 22.0 93
## 157 3 13.84 4.12 2.38 19.5 89
## 158 3 12.45 3.03 2.64 27.0 97
## 159 3 14.34 1.68 2.70 25.0 98
## 160 3 13.48 1.67 2.64 22.5 89
## 161 3 12.36 3.83 2.38 21.0 88
## 162 3 13.69 3.26 2.54 20.0 107
## 163 3 12.85 3.27 2.58 22.0 106
## 164 3 12.96 3.45 2.35 18.5 106
## 165 3 13.78 2.76 2.30 22.0 90
## 166 3 13.73 4.36 2.26 22.5 88
## 167 3 13.45 3.70 2.60 23.0 111
## 168 3 12.82 3.37 2.30 19.5 88
## 169 3 13.58 2.58 2.69 24.5 105
## 170 3 13.40 4.60 2.86 25.0 112
## 171 3 12.20 3.03 2.32 19.0 96
## 172 3 12.77 2.39 2.28 19.5 86
## 173 3 14.16 2.51 2.48 20.0 91
## 174 3 13.71 5.65 2.45 20.5 95
## 175 3 13.40 3.91 2.48 23.0 102
## 176 3 13.27 4.28 2.26 20.0 120
## 177 3 13.17 2.59 2.37 20.0 120
## 178 3 14.13 4.10 2.74 24.5 96
## Flavanoids Nonflavanoidphenols Proanthocyanins Colorintensity
## 1 2.80 3.06 0.28 2.29
## 2 2.65 2.76 0.26 1.28
## 3 2.80 3.24 0.30 2.81
## 4 3.85 3.49 0.24 2.18
## 5 2.80 2.69 0.39 1.82
## 6 3.27 3.39 0.34 1.97
## 7 2.50 2.52 0.30 1.98
## 8 2.60 2.51 0.31 1.25
## 9 2.80 2.98 0.29 1.98
## 10 2.98 3.15 0.22 1.85
## 11 2.95 3.32 0.22 2.38
## 12 2.20 2.43 0.26 1.57
## 13 2.60 2.76 0.29 1.81
## 14 3.10 3.69 0.43 2.81
## 15 3.30 3.64 0.29 2.96
## 16 2.85 2.91 0.30 1.46
## 17 2.80 3.14 0.33 1.97
## 18 2.95 3.40 0.40 1.72
## 19 3.30 3.93 0.32 1.86
## 20 2.70 3.03 0.17 1.66
## 21 3.00 3.17 0.24 2.10
## 22 2.41 2.41 0.25 1.98
## 23 2.61 2.88 0.27 1.69
## 24 2.48 2.37 0.26 1.46
## 25 2.53 2.61 0.28 1.66
## 26 2.63 2.68 0.47 1.92
## 27 2.85 2.94 0.34 1.45
## 28 2.40 2.19 0.27 1.35
## 29 2.95 2.97 0.37 1.76
## 30 2.65 2.33 0.26 1.98
## 31 3.00 3.25 0.29 2.38
## 32 2.86 3.19 0.22 1.95
## 33 2.42 2.69 0.42 1.97
## 34 2.95 2.74 0.50 1.35
## 35 2.35 2.53 0.29 1.54
## 36 2.70 2.98 0.26 1.86
## 37 2.60 2.68 0.34 1.36
## 38 2.45 2.43 0.29 1.44
## 39 2.40 2.64 0.28 1.37
## 40 3.00 3.04 0.20 2.08
## 41 3.15 3.29 0.34 2.34
## 42 2.45 2.68 0.27 1.48
## 43 3.25 3.56 0.17 1.70
## 44 2.64 2.63 0.32 1.66
## 45 3.00 3.00 0.28 2.03
## 46 2.85 2.65 0.30 1.25
## 47 3.25 3.17 0.27 2.19
## 48 3.10 3.39 0.21 2.14
## 49 2.75 2.92 0.32 2.38
## 50 2.88 3.54 0.32 2.08
## 51 2.72 3.27 0.17 2.91
## 52 2.45 2.99 0.22 2.29
## 53 3.88 3.74 0.32 1.87
## 54 3.00 2.79 0.39 1.68
## 55 2.60 2.90 0.21 1.62
## 56 2.96 2.78 0.20 2.45
## 57 3.20 3.00 0.26 2.03
## 58 3.00 3.23 0.31 1.66
## 59 3.40 3.67 0.19 2.04
## 60 1.98 0.57 0.28 0.42
## 61 2.05 1.09 0.63 0.41
## 62 2.02 1.41 0.53 0.62
## 63 2.10 1.79 0.32 0.73
## 64 3.50 3.10 0.19 1.87
## 65 1.89 1.75 0.45 1.03
## 66 2.42 2.65 0.37 2.08
## 67 2.98 3.18 0.26 2.28
## 68 2.11 2.00 0.27 1.04
## 69 2.53 1.30 0.55 0.42
## 70 1.85 1.28 0.14 2.50
## 71 1.10 1.02 0.37 1.46
## 72 2.95 2.86 0.21 1.87
## 73 1.88 1.84 0.27 1.03
## 74 3.30 2.89 0.21 1.96
## 75 3.38 2.14 0.13 1.65
## 76 1.61 1.57 0.34 1.15
## 77 1.95 2.03 0.24 1.46
## 78 1.72 1.32 0.43 0.95
## 79 1.90 1.85 0.35 2.76
## 80 2.83 2.55 0.43 1.95
## 81 2.42 2.26 0.30 1.43
## 82 2.20 2.53 0.26 1.77
## 83 2.00 1.58 0.40 1.40
## 84 1.65 1.59 0.61 1.62
## 85 2.20 2.21 0.22 2.35
## 86 2.20 1.94 0.30 1.46
## 87 1.78 1.69 0.43 1.56
## 88 1.92 1.61 0.40 1.34
## 89 1.95 1.69 0.48 1.35
## 90 2.20 1.59 0.42 1.38
## 91 1.60 1.50 0.52 1.64
## 92 1.45 1.25 0.50 1.63
## 93 1.38 1.46 0.58 1.62
## 94 2.45 2.25 0.25 1.99
## 95 3.02 2.26 0.17 1.35
## 96 2.50 2.27 0.32 3.28
## 97 1.60 0.99 0.14 1.56
## 98 2.55 2.50 0.29 1.77
## 99 3.52 3.75 0.24 1.95
## 100 2.85 2.99 0.45 2.81
## 101 2.23 2.17 0.26 1.40
## 102 1.45 1.36 0.29 1.35
## 103 2.56 2.11 0.34 1.31
## 104 2.50 1.64 0.37 1.42
## 105 2.20 1.92 0.32 1.48
## 106 1.68 1.84 0.66 1.42
## 107 1.65 2.03 0.37 1.63
## 108 1.38 1.76 0.48 1.63
## 109 2.36 2.04 0.39 2.08
## 110 2.74 2.92 0.29 2.49
## 111 3.18 2.58 0.24 3.58
## 112 2.55 2.27 0.26 1.22
## 113 1.75 2.03 0.60 1.05
## 114 2.48 2.01 0.42 1.44
## 115 2.56 2.29 0.43 1.04
## 116 2.46 2.17 0.52 2.01
## 117 1.98 1.60 0.30 1.53
## 118 2.00 2.09 0.34 1.61
## 119 1.63 1.25 0.43 0.83
## 120 2.00 1.64 0.37 1.87
## 121 2.90 2.79 0.32 1.83
## 122 3.18 5.08 0.47 1.87
## 123 2.20 2.13 0.43 1.71
## 124 2.62 2.65 0.30 2.01
## 125 2.86 3.03 0.21 2.91
## 126 2.60 2.65 0.37 1.35
## 127 2.74 3.15 0.39 1.77
## 128 2.13 2.24 0.58 1.76
## 129 2.22 2.45 0.40 1.90
## 130 2.10 1.75 0.42 1.35
## 131 1.51 1.25 0.21 0.94
## 132 1.30 1.22 0.24 0.83
## 133 1.15 1.09 0.27 0.83
## 134 1.70 1.20 0.17 0.84
## 135 2.00 0.58 0.60 1.25
## 136 1.62 0.66 0.63 0.94
## 137 1.38 0.47 0.53 0.80
## 138 1.79 0.60 0.63 1.10
## 139 1.62 0.48 0.58 0.88
## 140 2.32 0.60 0.53 0.81
## 141 1.54 0.50 0.53 0.75
## 142 1.40 0.50 0.37 0.64
## 143 1.55 0.52 0.50 0.55
## 144 2.00 0.80 0.47 1.02
## 145 1.38 0.78 0.29 1.14
## 146 1.50 0.55 0.43 1.30
## 147 0.98 0.34 0.40 0.68
## 148 1.70 0.65 0.47 0.86
## 149 1.93 0.76 0.45 1.25
## 150 1.41 1.39 0.34 1.14
## 151 1.40 1.57 0.22 1.25
## 152 1.48 1.36 0.24 1.26
## 153 2.20 1.28 0.26 1.56
## 154 1.80 0.83 0.61 1.87
## 155 1.48 0.58 0.53 1.40
## 156 1.74 0.63 0.61 1.55
## 157 1.80 0.83 0.48 1.56
## 158 1.90 0.58 0.63 1.14
## 159 2.80 1.31 0.53 2.70
## 160 2.60 1.10 0.52 2.29
## 161 2.30 0.92 0.50 1.04
## 162 1.83 0.56 0.50 0.80
## 163 1.65 0.60 0.60 0.96
## 164 1.39 0.70 0.40 0.94
## 165 1.35 0.68 0.41 1.03
## 166 1.28 0.47 0.52 1.15
## 167 1.70 0.92 0.43 1.46
## 168 1.48 0.66 0.40 0.97
## 169 1.55 0.84 0.39 1.54
## 170 1.98 0.96 0.27 1.11
## 171 1.25 0.49 0.40 0.73
## 172 1.39 0.51 0.48 0.64
## 173 1.68 0.70 0.44 1.24
## 174 1.68 0.61 0.52 1.06
## 175 1.80 0.75 0.43 1.41
## 176 1.59 0.69 0.43 1.35
## 177 1.65 0.68 0.53 1.46
## 178 2.05 0.76 0.56 1.35
## Hue OD280/OD315 of diluted wines Proline
## 1 5.640000 1.040 3.92
## 2 4.380000 1.050 3.40
## 3 5.680000 1.030 3.17
## 4 7.800000 0.860 3.45
## 5 4.320000 1.040 2.93
## 6 6.750000 1.050 2.85
## 7 5.250000 1.020 3.58
## 8 5.050000 1.060 3.58
## 9 5.200000 1.080 2.85
## 10 7.220000 1.010 3.55
## 11 5.750000 1.250 3.17
## 12 5.000000 1.170 2.82
## 13 5.600000 1.150 2.90
## 14 5.400000 1.250 2.73
## 15 7.500000 1.200 3.00
## 16 7.300000 1.280 2.88
## 17 6.200000 1.070 2.65
## 18 6.600000 1.130 2.57
## 19 8.700000 1.230 2.82
## 20 5.100000 0.960 3.36
## 21 5.650000 1.090 3.71
## 22 4.500000 1.030 3.52
## 23 3.800000 1.110 4.00
## 24 3.930000 1.090 3.63
## 25 3.520000 1.120 3.82
## 26 3.580000 1.130 3.20
## 27 4.800000 0.920 3.22
## 28 3.950000 1.020 2.77
## 29 4.500000 1.250 3.40
## 30 4.700000 1.040 3.59
## 31 5.700000 1.190 2.71
## 32 6.900000 1.090 2.88
## 33 3.840000 1.230 2.87
## 34 5.400000 1.250 3.00
## 35 4.200000 1.100 2.87
## 36 5.100000 1.040 3.47
## 37 4.600000 1.090 2.78
## 38 4.250000 1.120 2.51
## 39 3.700000 1.180 2.69
## 40 5.100000 0.890 3.53
## 41 6.130000 0.950 3.38
## 42 4.280000 0.910 3.00
## 43 5.430000 0.880 3.56
## 44 4.360000 0.820 3.00
## 45 5.040000 0.880 3.35
## 46 5.240000 0.870 3.33
## 47 4.900000 1.040 3.44
## 48 6.100000 0.910 3.33
## 49 6.200000 1.070 2.75
## 50 8.900000 1.120 3.10
## 51 7.200000 1.120 2.91
## 52 5.600000 1.240 3.37
## 53 7.050000 1.010 3.26
## 54 6.300000 1.130 2.93
## 55 5.850000 0.920 3.20
## 56 6.250000 0.980 3.03
## 57 6.380000 0.940 3.31
## 58 6.000000 1.070 2.84
## 59 6.800000 0.890 2.87
## 60 1.950000 1.050 1.82
## 61 3.270000 1.250 1.67
## 62 5.750000 0.980 1.59
## 63 3.800000 1.230 2.46
## 64 4.450000 1.220 2.87
## 65 2.950000 1.450 2.23
## 66 4.600000 1.190 2.30
## 67 5.300000 1.120 3.18
## 68 4.680000 1.120 3.48
## 69 3.170000 1.020 1.93
## 70 2.850000 1.280 3.07
## 71 3.050000 0.906 1.82
## 72 3.380000 1.360 3.16
## 73 3.740000 0.980 2.78
## 74 3.350000 1.310 3.50
## 75 3.210000 0.990 3.13
## 76 3.800000 1.230 2.14
## 77 4.600000 1.190 2.48
## 78 2.650000 0.960 2.52
## 79 3.400000 1.060 2.31
## 80 2.570000 1.190 3.13
## 81 2.500000 1.380 3.12
## 82 3.900000 1.160 3.14
## 83 2.200000 1.310 2.72
## 84 4.800000 0.840 2.01
## 85 3.050000 0.790 3.08
## 86 2.620000 1.230 3.16
## 87 2.450000 1.330 2.26
## 88 2.600000 1.360 3.21
## 89 2.800000 1.000 2.75
## 90 1.740000 1.070 3.21
## 91 2.400000 1.080 2.27
## 92 3.600000 1.050 2.65
## 93 3.050000 0.960 2.06
## 94 2.150000 1.150 3.30
## 95 3.250000 1.160 2.96
## 96 2.600000 1.160 2.63
## 97 2.500000 0.950 2.26
## 98 2.900000 1.230 2.74
## 99 4.500000 1.040 2.77
## 100 2.300000 1.420 2.83
## 101 3.300000 1.270 2.96
## 102 2.450000 1.040 2.77
## 103 2.800000 0.800 3.38
## 104 2.060000 0.940 2.44
## 105 2.940000 1.040 3.57
## 106 2.700000 0.860 3.30
## 107 3.400000 1.000 3.17
## 108 3.300000 0.880 2.42
## 109 2.700000 0.860 3.02
## 110 2.650000 0.960 3.26
## 111 2.900000 0.750 2.81
## 112 2.000000 0.900 2.78
## 113 3.800000 1.230 2.50
## 114 3.080000 1.100 2.31
## 115 2.900000 0.930 3.19
## 116 1.900000 1.710 2.87
## 117 1.950000 0.950 3.33
## 118 2.060000 1.060 2.96
## 119 3.400000 0.700 2.12
## 120 1.280000 0.930 3.05
## 121 3.250000 0.800 3.39
## 122 6.000000 0.930 3.69
## 123 2.080000 0.920 3.12
## 124 2.600000 0.730 3.10
## 125 2.800000 0.750 3.64
## 126 2.760000 0.860 3.28
## 127 3.940000 0.690 2.84
## 128 3.000000 0.970 2.44
## 129 2.120000 0.890 2.78
## 130 2.600000 0.790 2.57
## 131 4.100000 0.760 1.29
## 132 5.400000 0.740 1.42
## 133 5.700000 0.660 1.36
## 134 5.000000 0.780 1.29
## 135 5.450000 0.750 1.51
## 136 7.100000 0.730 1.58
## 137 3.850000 0.750 1.27
## 138 5.000000 0.820 1.69
## 139 5.700000 0.810 1.82
## 140 4.920000 0.890 2.15
## 141 4.600000 0.770 2.31
## 142 5.600000 0.700 2.47
## 143 4.350000 0.890 2.06
## 144 4.400000 0.910 2.05
## 145 8.210000 0.650 2.00
## 146 4.000000 0.600 1.68
## 147 4.900000 0.580 1.33
## 148 7.650000 0.540 1.86
## 149 8.420000 0.550 1.62
## 150 9.400000 0.570 1.33
## 151 8.600000 0.590 1.30
## 152 10.800000 0.480 1.47
## 153 7.100000 0.610 1.33
## 154 10.520000 0.560 1.51
## 155 7.600000 0.580 1.55
## 156 7.900000 0.600 1.48
## 157 9.010000 0.570 1.64
## 158 7.500000 0.670 1.73
## 159 13.000000 0.570 1.96
## 160 11.750000 0.570 1.78
## 161 7.650000 0.560 1.58
## 162 5.880000 0.960 1.82
## 163 5.580000 0.870 2.11
## 164 5.280000 0.680 1.75
## 165 9.580000 0.700 1.68
## 166 6.620000 0.780 1.75
## 167 10.680000 0.850 1.56
## 168 10.260000 0.720 1.75
## 169 8.660000 0.740 1.80
## 170 8.500000 0.670 1.92
## 171 5.500000 0.660 1.83
## 172 9.899999 0.570 1.63
## 173 9.700000 0.620 1.71
## 174 7.700000 0.640 1.74
## 175 7.300000 0.700 1.56
## 176 10.200000 0.590 1.56
## 177 9.300000 0.600 1.62
## 178 9.200000 0.610 1.60Extracting the 1st 100 Rows in the CSV File
wine5<-wine4[1:100,]
wine5## Alcohol Malicacid Ash Alcalinityofash Magnesium Totalphenols
## 1 1 14.23 1.71 2.43 15.6 127
## 2 1 13.20 1.78 2.14 11.2 100
## 3 1 13.16 2.36 2.67 18.6 101
## 4 1 14.37 1.95 2.50 16.8 113
## 5 1 13.24 2.59 2.87 21.0 118
## 6 1 14.20 1.76 2.45 15.2 112
## 7 1 14.39 1.87 2.45 14.6 96
## 8 1 14.06 2.15 2.61 17.6 121
## 9 1 14.83 1.64 2.17 14.0 97
## 10 1 13.86 1.35 2.27 16.0 98
## 11 1 14.10 2.16 2.30 18.0 105
## 12 1 14.12 1.48 2.32 16.8 95
## 13 1 13.75 1.73 2.41 16.0 89
## 14 1 14.75 1.73 2.39 11.4 91
## 15 1 14.38 1.87 2.38 12.0 102
## 16 1 13.63 1.81 2.70 17.2 112
## 17 1 14.30 1.92 2.72 20.0 120
## 18 1 13.83 1.57 2.62 20.0 115
## 19 1 14.19 1.59 2.48 16.5 108
## 20 1 13.64 3.10 2.56 15.2 116
## 21 1 14.06 1.63 2.28 16.0 126
## 22 1 12.93 3.80 2.65 18.6 102
## 23 1 13.71 1.86 2.36 16.6 101
## 24 1 12.85 1.60 2.52 17.8 95
## 25 1 13.50 1.81 2.61 20.0 96
## 26 1 13.05 2.05 3.22 25.0 124
## 27 1 13.39 1.77 2.62 16.1 93
## 28 1 13.30 1.72 2.14 17.0 94
## 29 1 13.87 1.90 2.80 19.4 107
## 30 1 14.02 1.68 2.21 16.0 96
## 31 1 13.73 1.50 2.70 22.5 101
## 32 1 13.58 1.66 2.36 19.1 106
## 33 1 13.68 1.83 2.36 17.2 104
## 34 1 13.76 1.53 2.70 19.5 132
## 35 1 13.51 1.80 2.65 19.0 110
## 36 1 13.48 1.81 2.41 20.5 100
## 37 1 13.28 1.64 2.84 15.5 110
## 38 1 13.05 1.65 2.55 18.0 98
## 39 1 13.07 1.50 2.10 15.5 98
## 40 1 14.22 3.99 2.51 13.2 128
## 41 1 13.56 1.71 2.31 16.2 117
## 42 1 13.41 3.84 2.12 18.8 90
## 43 1 13.88 1.89 2.59 15.0 101
## 44 1 13.24 3.98 2.29 17.5 103
## 45 1 13.05 1.77 2.10 17.0 107
## 46 1 14.21 4.04 2.44 18.9 111
## 47 1 14.38 3.59 2.28 16.0 102
## 48 1 13.90 1.68 2.12 16.0 101
## 49 1 14.10 2.02 2.40 18.8 103
## 50 1 13.94 1.73 2.27 17.4 108
## 51 1 13.05 1.73 2.04 12.4 92
## 52 1 13.83 1.65 2.60 17.2 94
## 53 1 13.82 1.75 2.42 14.0 111
## 54 1 13.77 1.90 2.68 17.1 115
## 55 1 13.74 1.67 2.25 16.4 118
## 56 1 13.56 1.73 2.46 20.5 116
## 57 1 14.22 1.70 2.30 16.3 118
## 58 1 13.29 1.97 2.68 16.8 102
## 59 1 13.72 1.43 2.50 16.7 108
## 60 2 12.37 0.94 1.36 10.6 88
## 61 2 12.33 1.10 2.28 16.0 101
## 62 2 12.64 1.36 2.02 16.8 100
## 63 2 13.67 1.25 1.92 18.0 94
## 64 2 12.37 1.13 2.16 19.0 87
## 65 2 12.17 1.45 2.53 19.0 104
## 66 2 12.37 1.21 2.56 18.1 98
## 67 2 13.11 1.01 1.70 15.0 78
## 68 2 12.37 1.17 1.92 19.6 78
## 69 2 13.34 0.94 2.36 17.0 110
## 70 2 12.21 1.19 1.75 16.8 151
## 71 2 12.29 1.61 2.21 20.4 103
## 72 2 13.86 1.51 2.67 25.0 86
## 73 2 13.49 1.66 2.24 24.0 87
## 74 2 12.99 1.67 2.60 30.0 139
## 75 2 11.96 1.09 2.30 21.0 101
## 76 2 11.66 1.88 1.92 16.0 97
## 77 2 13.03 0.90 1.71 16.0 86
## 78 2 11.84 2.89 2.23 18.0 112
## 79 2 12.33 0.99 1.95 14.8 136
## 80 2 12.70 3.87 2.40 23.0 101
## 81 2 12.00 0.92 2.00 19.0 86
## 82 2 12.72 1.81 2.20 18.8 86
## 83 2 12.08 1.13 2.51 24.0 78
## 84 2 13.05 3.86 2.32 22.5 85
## 85 2 11.84 0.89 2.58 18.0 94
## 86 2 12.67 0.98 2.24 18.0 99
## 87 2 12.16 1.61 2.31 22.8 90
## 88 2 11.65 1.67 2.62 26.0 88
## 89 2 11.64 2.06 2.46 21.6 84
## 90 2 12.08 1.33 2.30 23.6 70
## 91 2 12.08 1.83 2.32 18.5 81
## 92 2 12.00 1.51 2.42 22.0 86
## 93 2 12.69 1.53 2.26 20.7 80
## 94 2 12.29 2.83 2.22 18.0 88
## 95 2 11.62 1.99 2.28 18.0 98
## 96 2 12.47 1.52 2.20 19.0 162
## 97 2 11.81 2.12 2.74 21.5 134
## 98 2 12.29 1.41 1.98 16.0 85
## 99 2 12.37 1.07 2.10 18.5 88
## 100 2 12.29 3.17 2.21 18.0 88
## Flavanoids Nonflavanoidphenols Proanthocyanins Colorintensity Hue
## 1 2.80 3.06 0.28 2.29 5.64
## 2 2.65 2.76 0.26 1.28 4.38
## 3 2.80 3.24 0.30 2.81 5.68
## 4 3.85 3.49 0.24 2.18 7.80
## 5 2.80 2.69 0.39 1.82 4.32
## 6 3.27 3.39 0.34 1.97 6.75
## 7 2.50 2.52 0.30 1.98 5.25
## 8 2.60 2.51 0.31 1.25 5.05
## 9 2.80 2.98 0.29 1.98 5.20
## 10 2.98 3.15 0.22 1.85 7.22
## 11 2.95 3.32 0.22 2.38 5.75
## 12 2.20 2.43 0.26 1.57 5.00
## 13 2.60 2.76 0.29 1.81 5.60
## 14 3.10 3.69 0.43 2.81 5.40
## 15 3.30 3.64 0.29 2.96 7.50
## 16 2.85 2.91 0.30 1.46 7.30
## 17 2.80 3.14 0.33 1.97 6.20
## 18 2.95 3.40 0.40 1.72 6.60
## 19 3.30 3.93 0.32 1.86 8.70
## 20 2.70 3.03 0.17 1.66 5.10
## 21 3.00 3.17 0.24 2.10 5.65
## 22 2.41 2.41 0.25 1.98 4.50
## 23 2.61 2.88 0.27 1.69 3.80
## 24 2.48 2.37 0.26 1.46 3.93
## 25 2.53 2.61 0.28 1.66 3.52
## 26 2.63 2.68 0.47 1.92 3.58
## 27 2.85 2.94 0.34 1.45 4.80
## 28 2.40 2.19 0.27 1.35 3.95
## 29 2.95 2.97 0.37 1.76 4.50
## 30 2.65 2.33 0.26 1.98 4.70
## 31 3.00 3.25 0.29 2.38 5.70
## 32 2.86 3.19 0.22 1.95 6.90
## 33 2.42 2.69 0.42 1.97 3.84
## 34 2.95 2.74 0.50 1.35 5.40
## 35 2.35 2.53 0.29 1.54 4.20
## 36 2.70 2.98 0.26 1.86 5.10
## 37 2.60 2.68 0.34 1.36 4.60
## 38 2.45 2.43 0.29 1.44 4.25
## 39 2.40 2.64 0.28 1.37 3.70
## 40 3.00 3.04 0.20 2.08 5.10
## 41 3.15 3.29 0.34 2.34 6.13
## 42 2.45 2.68 0.27 1.48 4.28
## 43 3.25 3.56 0.17 1.70 5.43
## 44 2.64 2.63 0.32 1.66 4.36
## 45 3.00 3.00 0.28 2.03 5.04
## 46 2.85 2.65 0.30 1.25 5.24
## 47 3.25 3.17 0.27 2.19 4.90
## 48 3.10 3.39 0.21 2.14 6.10
## 49 2.75 2.92 0.32 2.38 6.20
## 50 2.88 3.54 0.32 2.08 8.90
## 51 2.72 3.27 0.17 2.91 7.20
## 52 2.45 2.99 0.22 2.29 5.60
## 53 3.88 3.74 0.32 1.87 7.05
## 54 3.00 2.79 0.39 1.68 6.30
## 55 2.60 2.90 0.21 1.62 5.85
## 56 2.96 2.78 0.20 2.45 6.25
## 57 3.20 3.00 0.26 2.03 6.38
## 58 3.00 3.23 0.31 1.66 6.00
## 59 3.40 3.67 0.19 2.04 6.80
## 60 1.98 0.57 0.28 0.42 1.95
## 61 2.05 1.09 0.63 0.41 3.27
## 62 2.02 1.41 0.53 0.62 5.75
## 63 2.10 1.79 0.32 0.73 3.80
## 64 3.50 3.10 0.19 1.87 4.45
## 65 1.89 1.75 0.45 1.03 2.95
## 66 2.42 2.65 0.37 2.08 4.60
## 67 2.98 3.18 0.26 2.28 5.30
## 68 2.11 2.00 0.27 1.04 4.68
## 69 2.53 1.30 0.55 0.42 3.17
## 70 1.85 1.28 0.14 2.50 2.85
## 71 1.10 1.02 0.37 1.46 3.05
## 72 2.95 2.86 0.21 1.87 3.38
## 73 1.88 1.84 0.27 1.03 3.74
## 74 3.30 2.89 0.21 1.96 3.35
## 75 3.38 2.14 0.13 1.65 3.21
## 76 1.61 1.57 0.34 1.15 3.80
## 77 1.95 2.03 0.24 1.46 4.60
## 78 1.72 1.32 0.43 0.95 2.65
## 79 1.90 1.85 0.35 2.76 3.40
## 80 2.83 2.55 0.43 1.95 2.57
## 81 2.42 2.26 0.30 1.43 2.50
## 82 2.20 2.53 0.26 1.77 3.90
## 83 2.00 1.58 0.40 1.40 2.20
## 84 1.65 1.59 0.61 1.62 4.80
## 85 2.20 2.21 0.22 2.35 3.05
## 86 2.20 1.94 0.30 1.46 2.62
## 87 1.78 1.69 0.43 1.56 2.45
## 88 1.92 1.61 0.40 1.34 2.60
## 89 1.95 1.69 0.48 1.35 2.80
## 90 2.20 1.59 0.42 1.38 1.74
## 91 1.60 1.50 0.52 1.64 2.40
## 92 1.45 1.25 0.50 1.63 3.60
## 93 1.38 1.46 0.58 1.62 3.05
## 94 2.45 2.25 0.25 1.99 2.15
## 95 3.02 2.26 0.17 1.35 3.25
## 96 2.50 2.27 0.32 3.28 2.60
## 97 1.60 0.99 0.14 1.56 2.50
## 98 2.55 2.50 0.29 1.77 2.90
## 99 3.52 3.75 0.24 1.95 4.50
## 100 2.85 2.99 0.45 2.81 2.30
## OD280/OD315 of diluted wines Proline
## 1 1.040 3.92
## 2 1.050 3.40
## 3 1.030 3.17
## 4 0.860 3.45
## 5 1.040 2.93
## 6 1.050 2.85
## 7 1.020 3.58
## 8 1.060 3.58
## 9 1.080 2.85
## 10 1.010 3.55
## 11 1.250 3.17
## 12 1.170 2.82
## 13 1.150 2.90
## 14 1.250 2.73
## 15 1.200 3.00
## 16 1.280 2.88
## 17 1.070 2.65
## 18 1.130 2.57
## 19 1.230 2.82
## 20 0.960 3.36
## 21 1.090 3.71
## 22 1.030 3.52
## 23 1.110 4.00
## 24 1.090 3.63
## 25 1.120 3.82
## 26 1.130 3.20
## 27 0.920 3.22
## 28 1.020 2.77
## 29 1.250 3.40
## 30 1.040 3.59
## 31 1.190 2.71
## 32 1.090 2.88
## 33 1.230 2.87
## 34 1.250 3.00
## 35 1.100 2.87
## 36 1.040 3.47
## 37 1.090 2.78
## 38 1.120 2.51
## 39 1.180 2.69
## 40 0.890 3.53
## 41 0.950 3.38
## 42 0.910 3.00
## 43 0.880 3.56
## 44 0.820 3.00
## 45 0.880 3.35
## 46 0.870 3.33
## 47 1.040 3.44
## 48 0.910 3.33
## 49 1.070 2.75
## 50 1.120 3.10
## 51 1.120 2.91
## 52 1.240 3.37
## 53 1.010 3.26
## 54 1.130 2.93
## 55 0.920 3.20
## 56 0.980 3.03
## 57 0.940 3.31
## 58 1.070 2.84
## 59 0.890 2.87
## 60 1.050 1.82
## 61 1.250 1.67
## 62 0.980 1.59
## 63 1.230 2.46
## 64 1.220 2.87
## 65 1.450 2.23
## 66 1.190 2.30
## 67 1.120 3.18
## 68 1.120 3.48
## 69 1.020 1.93
## 70 1.280 3.07
## 71 0.906 1.82
## 72 1.360 3.16
## 73 0.980 2.78
## 74 1.310 3.50
## 75 0.990 3.13
## 76 1.230 2.14
## 77 1.190 2.48
## 78 0.960 2.52
## 79 1.060 2.31
## 80 1.190 3.13
## 81 1.380 3.12
## 82 1.160 3.14
## 83 1.310 2.72
## 84 0.840 2.01
## 85 0.790 3.08
## 86 1.230 3.16
## 87 1.330 2.26
## 88 1.360 3.21
## 89 1.000 2.75
## 90 1.070 3.21
## 91 1.080 2.27
## 92 1.050 2.65
## 93 0.960 2.06
## 94 1.150 3.30
## 95 1.160 2.96
## 96 1.160 2.63
## 97 0.950 2.26
## 98 1.230 2.74
## 99 1.040 2.77
## 100 1.420 2.83Extracting the 5th and 7th Column of Wine
wine[1:100,c(5,7)]## V4 V6
## 1 2.43 127
## 2 2.14 100
## 3 2.67 101
## 4 2.50 113
## 5 2.87 118
## 6 2.45 112
## 7 2.45 96
## 8 2.61 121
## 9 2.17 97
## 10 2.27 98
## 11 2.30 105
## 12 2.32 95
## 13 2.41 89
## 14 2.39 91
## 15 2.38 102
## 16 2.70 112
## 17 2.72 120
## 18 2.62 115
## 19 2.48 108
## 20 2.56 116
## 21 2.28 126
## 22 2.65 102
## 23 2.36 101
## 24 2.52 95
## 25 2.61 96
## 26 3.22 124
## 27 2.62 93
## 28 2.14 94
## 29 2.80 107
## 30 2.21 96
## 31 2.70 101
## 32 2.36 106
## 33 2.36 104
## 34 2.70 132
## 35 2.65 110
## 36 2.41 100
## 37 2.84 110
## 38 2.55 98
## 39 2.10 98
## 40 2.51 128
## 41 2.31 117
## 42 2.12 90
## 43 2.59 101
## 44 2.29 103
## 45 2.10 107
## 46 2.44 111
## 47 2.28 102
## 48 2.12 101
## 49 2.40 103
## 50 2.27 108
## 51 2.04 92
## 52 2.60 94
## 53 2.42 111
## 54 2.68 115
## 55 2.25 118
## 56 2.46 116
## 57 2.30 118
## 58 2.68 102
## 59 2.50 108
## 60 1.36 88
## 61 2.28 101
## 62 2.02 100
## 63 1.92 94
## 64 2.16 87
## 65 2.53 104
## 66 2.56 98
## 67 1.70 78
## 68 1.92 78
## 69 2.36 110
## 70 1.75 151
## 71 2.21 103
## 72 2.67 86
## 73 2.24 87
## 74 2.60 139
## 75 2.30 101
## 76 1.92 97
## 77 1.71 86
## 78 2.23 112
## 79 1.95 136
## 80 2.40 101
## 81 2.00 86
## 82 2.20 86
## 83 2.51 78
## 84 2.32 85
## 85 2.58 94
## 86 2.24 99
## 87 2.31 90
## 88 2.62 88
## 89 2.46 84
## 90 2.30 70
## 91 2.32 81
## 92 2.42 86
## 93 2.26 80
## 94 2.22 88
## 95 2.28 98
## 96 2.20 162
## 97 2.74 134
## 98 1.98 85
## 99 2.10 88
## 100 2.21 88Extracting the 5th and 7th Column of Wine
wine[1:100,10:14]## V9 V10 V11 V12 V13
## 1 0.28 2.29 5.64 1.040 3.92
## 2 0.26 1.28 4.38 1.050 3.40
## 3 0.30 2.81 5.68 1.030 3.17
## 4 0.24 2.18 7.80 0.860 3.45
## 5 0.39 1.82 4.32 1.040 2.93
## 6 0.34 1.97 6.75 1.050 2.85
## 7 0.30 1.98 5.25 1.020 3.58
## 8 0.31 1.25 5.05 1.060 3.58
## 9 0.29 1.98 5.20 1.080 2.85
## 10 0.22 1.85 7.22 1.010 3.55
## 11 0.22 2.38 5.75 1.250 3.17
## 12 0.26 1.57 5.00 1.170 2.82
## 13 0.29 1.81 5.60 1.150 2.90
## 14 0.43 2.81 5.40 1.250 2.73
## 15 0.29 2.96 7.50 1.200 3.00
## 16 0.30 1.46 7.30 1.280 2.88
## 17 0.33 1.97 6.20 1.070 2.65
## 18 0.40 1.72 6.60 1.130 2.57
## 19 0.32 1.86 8.70 1.230 2.82
## 20 0.17 1.66 5.10 0.960 3.36
## 21 0.24 2.10 5.65 1.090 3.71
## 22 0.25 1.98 4.50 1.030 3.52
## 23 0.27 1.69 3.80 1.110 4.00
## 24 0.26 1.46 3.93 1.090 3.63
## 25 0.28 1.66 3.52 1.120 3.82
## 26 0.47 1.92 3.58 1.130 3.20
## 27 0.34 1.45 4.80 0.920 3.22
## 28 0.27 1.35 3.95 1.020 2.77
## 29 0.37 1.76 4.50 1.250 3.40
## 30 0.26 1.98 4.70 1.040 3.59
## 31 0.29 2.38 5.70 1.190 2.71
## 32 0.22 1.95 6.90 1.090 2.88
## 33 0.42 1.97 3.84 1.230 2.87
## 34 0.50 1.35 5.40 1.250 3.00
## 35 0.29 1.54 4.20 1.100 2.87
## 36 0.26 1.86 5.10 1.040 3.47
## 37 0.34 1.36 4.60 1.090 2.78
## 38 0.29 1.44 4.25 1.120 2.51
## 39 0.28 1.37 3.70 1.180 2.69
## 40 0.20 2.08 5.10 0.890 3.53
## 41 0.34 2.34 6.13 0.950 3.38
## 42 0.27 1.48 4.28 0.910 3.00
## 43 0.17 1.70 5.43 0.880 3.56
## 44 0.32 1.66 4.36 0.820 3.00
## 45 0.28 2.03 5.04 0.880 3.35
## 46 0.30 1.25 5.24 0.870 3.33
## 47 0.27 2.19 4.90 1.040 3.44
## 48 0.21 2.14 6.10 0.910 3.33
## 49 0.32 2.38 6.20 1.070 2.75
## 50 0.32 2.08 8.90 1.120 3.10
## 51 0.17 2.91 7.20 1.120 2.91
## 52 0.22 2.29 5.60 1.240 3.37
## 53 0.32 1.87 7.05 1.010 3.26
## 54 0.39 1.68 6.30 1.130 2.93
## 55 0.21 1.62 5.85 0.920 3.20
## 56 0.20 2.45 6.25 0.980 3.03
## 57 0.26 2.03 6.38 0.940 3.31
## 58 0.31 1.66 6.00 1.070 2.84
## 59 0.19 2.04 6.80 0.890 2.87
## 60 0.28 0.42 1.95 1.050 1.82
## 61 0.63 0.41 3.27 1.250 1.67
## 62 0.53 0.62 5.75 0.980 1.59
## 63 0.32 0.73 3.80 1.230 2.46
## 64 0.19 1.87 4.45 1.220 2.87
## 65 0.45 1.03 2.95 1.450 2.23
## 66 0.37 2.08 4.60 1.190 2.30
## 67 0.26 2.28 5.30 1.120 3.18
## 68 0.27 1.04 4.68 1.120 3.48
## 69 0.55 0.42 3.17 1.020 1.93
## 70 0.14 2.50 2.85 1.280 3.07
## 71 0.37 1.46 3.05 0.906 1.82
## 72 0.21 1.87 3.38 1.360 3.16
## 73 0.27 1.03 3.74 0.980 2.78
## 74 0.21 1.96 3.35 1.310 3.50
## 75 0.13 1.65 3.21 0.990 3.13
## 76 0.34 1.15 3.80 1.230 2.14
## 77 0.24 1.46 4.60 1.190 2.48
## 78 0.43 0.95 2.65 0.960 2.52
## 79 0.35 2.76 3.40 1.060 2.31
## 80 0.43 1.95 2.57 1.190 3.13
## 81 0.30 1.43 2.50 1.380 3.12
## 82 0.26 1.77 3.90 1.160 3.14
## 83 0.40 1.40 2.20 1.310 2.72
## 84 0.61 1.62 4.80 0.840 2.01
## 85 0.22 2.35 3.05 0.790 3.08
## 86 0.30 1.46 2.62 1.230 3.16
## 87 0.43 1.56 2.45 1.330 2.26
## 88 0.40 1.34 2.60 1.360 3.21
## 89 0.48 1.35 2.80 1.000 2.75
## 90 0.42 1.38 1.74 1.070 3.21
## 91 0.52 1.64 2.40 1.080 2.27
## 92 0.50 1.63 3.60 1.050 2.65
## 93 0.58 1.62 3.05 0.960 2.06
## 94 0.25 1.99 2.15 1.150 3.30
## 95 0.17 1.35 3.25 1.160 2.96
## 96 0.32 3.28 2.60 1.160 2.63
## 97 0.14 1.56 2.50 0.950 2.26
## 98 0.29 1.77 2.90 1.230 2.74
## 99 0.24 1.95 4.50 1.040 2.77
## 100 0.45 2.81 2.30 1.420 2.83Reading IRIS DATA SET
``{r} write.csv(iris,“C:\Users\localadmin\Desktop\R\iris.csv”) View(iris)
read.csv(iris,“C:\Users\localadmin\Desktop\R\iris.csv”) ``` ## Renaming the Column Names
View(iris)subsetting
table(iris$class)
colnames(iris)<-c( "sepal.length", "sepal.width", "petal.length", "petal.width","class")
iris_setosa <- subset(iris, class == "setosa")
iris_setosa## sepal.length sepal.width petal.length petal.width class
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 13 4.8 3.0 1.4 0.1 setosa
## 14 4.3 3.0 1.1 0.1 setosa
## 15 5.8 4.0 1.2 0.2 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 17 5.4 3.9 1.3 0.4 setosa
## 18 5.1 3.5 1.4 0.3 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 23 4.6 3.6 1.0 0.2 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 25 4.8 3.4 1.9 0.2 setosa
## 26 5.0 3.0 1.6 0.2 setosa
## 27 5.0 3.4 1.6 0.4 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 29 5.2 3.4 1.4 0.2 setosa
## 30 4.7 3.2 1.6 0.2 setosa
## 31 4.8 3.1 1.6 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 34 5.5 4.2 1.4 0.2 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 36 5.0 3.2 1.2 0.2 setosa
## 37 5.5 3.5 1.3 0.2 setosa
## 38 4.9 3.6 1.4 0.1 setosa
## 39 4.4 3.0 1.3 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 41 5.0 3.5 1.3 0.3 setosa
## 42 4.5 2.3 1.3 0.3 setosa
## 43 4.4 3.2 1.3 0.2 setosa
## 44 5.0 3.5 1.6 0.6 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 46 4.8 3.0 1.4 0.3 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 48 4.6 3.2 1.4 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosa
## 50 5.0 3.3 1.4 0.2 setosairis_versicolor <- subset(iris, class == "versicolor")
iris_versicolor## sepal.length sepal.width petal.length petal.width class
## 51 7.0 3.2 4.7 1.4 versicolor
## 52 6.4 3.2 4.5 1.5 versicolor
## 53 6.9 3.1 4.9 1.5 versicolor
## 54 5.5 2.3 4.0 1.3 versicolor
## 55 6.5 2.8 4.6 1.5 versicolor
## 56 5.7 2.8 4.5 1.3 versicolor
## 57 6.3 3.3 4.7 1.6 versicolor
## 58 4.9 2.4 3.3 1.0 versicolor
## 59 6.6 2.9 4.6 1.3 versicolor
## 60 5.2 2.7 3.9 1.4 versicolor
## 61 5.0 2.0 3.5 1.0 versicolor
## 62 5.9 3.0 4.2 1.5 versicolor
## 63 6.0 2.2 4.0 1.0 versicolor
## 64 6.1 2.9 4.7 1.4 versicolor
## 65 5.6 2.9 3.6 1.3 versicolor
## 66 6.7 3.1 4.4 1.4 versicolor
## 67 5.6 3.0 4.5 1.5 versicolor
## 68 5.8 2.7 4.1 1.0 versicolor
## 69 6.2 2.2 4.5 1.5 versicolor
## 70 5.6 2.5 3.9 1.1 versicolor
## 71 5.9 3.2 4.8 1.8 versicolor
## 72 6.1 2.8 4.0 1.3 versicolor
## 73 6.3 2.5 4.9 1.5 versicolor
## 74 6.1 2.8 4.7 1.2 versicolor
## 75 6.4 2.9 4.3 1.3 versicolor
## 76 6.6 3.0 4.4 1.4 versicolor
## 77 6.8 2.8 4.8 1.4 versicolor
## 78 6.7 3.0 5.0 1.7 versicolor
## 79 6.0 2.9 4.5 1.5 versicolor
## 80 5.7 2.6 3.5 1.0 versicolor
## 81 5.5 2.4 3.8 1.1 versicolor
## 82 5.5 2.4 3.7 1.0 versicolor
## 83 5.8 2.7 3.9 1.2 versicolor
## 84 6.0 2.7 5.1 1.6 versicolor
## 85 5.4 3.0 4.5 1.5 versicolor
## 86 6.0 3.4 4.5 1.6 versicolor
## 87 6.7 3.1 4.7 1.5 versicolor
## 88 6.3 2.3 4.4 1.3 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.5 2.5 4.0 1.3 versicolor
## 91 5.5 2.6 4.4 1.2 versicolor
## 92 6.1 3.0 4.6 1.4 versicolor
## 93 5.8 2.6 4.0 1.2 versicolor
## 94 5.0 2.3 3.3 1.0 versicolor
## 95 5.6 2.7 4.2 1.3 versicolor
## 96 5.7 3.0 4.2 1.2 versicolor
## 97 5.7 2.9 4.2 1.3 versicolor
## 98 6.2 2.9 4.3 1.3 versicolor
## 99 5.1 2.5 3.0 1.1 versicolor
## 100 5.7 2.8 4.1 1.3 versicoloriris_virginica<- subset(iris, class == "virginica")
iris_virginica## sepal.length sepal.width petal.length petal.width class
## 101 6.3 3.3 6.0 2.5 virginica
## 102 5.8 2.7 5.1 1.9 virginica
## 103 7.1 3.0 5.9 2.1 virginica
## 104 6.3 2.9 5.6 1.8 virginica
## 105 6.5 3.0 5.8 2.2 virginica
## 106 7.6 3.0 6.6 2.1 virginica
## 107 4.9 2.5 4.5 1.7 virginica
## 108 7.3 2.9 6.3 1.8 virginica
## 109 6.7 2.5 5.8 1.8 virginica
## 110 7.2 3.6 6.1 2.5 virginica
## 111 6.5 3.2 5.1 2.0 virginica
## 112 6.4 2.7 5.3 1.9 virginica
## 113 6.8 3.0 5.5 2.1 virginica
## 114 5.7 2.5 5.0 2.0 virginica
## 115 5.8 2.8 5.1 2.4 virginica
## 116 6.4 3.2 5.3 2.3 virginica
## 117 6.5 3.0 5.5 1.8 virginica
## 118 7.7 3.8 6.7 2.2 virginica
## 119 7.7 2.6 6.9 2.3 virginica
## 120 6.0 2.2 5.0 1.5 virginica
## 121 6.9 3.2 5.7 2.3 virginica
## 122 5.6 2.8 4.9 2.0 virginica
## 123 7.7 2.8 6.7 2.0 virginica
## 124 6.3 2.7 4.9 1.8 virginica
## 125 6.7 3.3 5.7 2.1 virginica
## 126 7.2 3.2 6.0 1.8 virginica
## 127 6.2 2.8 4.8 1.8 virginica
## 128 6.1 3.0 4.9 1.8 virginica
## 129 6.4 2.8 5.6 2.1 virginica
## 130 7.2 3.0 5.8 1.6 virginica
## 131 7.4 2.8 6.1 1.9 virginica
## 132 7.9 3.8 6.4 2.0 virginica
## 133 6.4 2.8 5.6 2.2 virginica
## 134 6.3 2.8 5.1 1.5 virginica
## 135 6.1 2.6 5.6 1.4 virginica
## 136 7.7 3.0 6.1 2.3 virginica
## 137 6.3 3.4 5.6 2.4 virginica
## 138 6.4 3.1 5.5 1.8 virginica
## 139 6.0 3.0 4.8 1.8 virginica
## 140 6.9 3.1 5.4 2.1 virginica
## 141 6.7 3.1 5.6 2.4 virginica
## 142 6.9 3.1 5.1 2.3 virginica
## 143 5.8 2.7 5.1 1.9 virginica
## 144 6.8 3.2 5.9 2.3 virginica
## 145 6.7 3.3 5.7 2.5 virginica
## 146 6.7 3.0 5.2 2.3 virginica
## 147 6.3 2.5 5.0 1.9 virginica
## 148 6.5 3.0 5.2 2.0 virginica
## 149 6.2 3.4 5.4 2.3 virginica
## 150 5.9 3.0 5.1 1.8 virginicairis3 = subset(iris, "sepal.width" >"3.1")
iris3## sepal.length sepal.width petal.length petal.width class
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 13 4.8 3.0 1.4 0.1 setosa
## 14 4.3 3.0 1.1 0.1 setosa
## 15 5.8 4.0 1.2 0.2 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 17 5.4 3.9 1.3 0.4 setosa
## 18 5.1 3.5 1.4 0.3 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 23 4.6 3.6 1.0 0.2 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 25 4.8 3.4 1.9 0.2 setosa
## 26 5.0 3.0 1.6 0.2 setosa
## 27 5.0 3.4 1.6 0.4 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 29 5.2 3.4 1.4 0.2 setosa
## 30 4.7 3.2 1.6 0.2 setosa
## 31 4.8 3.1 1.6 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 34 5.5 4.2 1.4 0.2 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 36 5.0 3.2 1.2 0.2 setosa
## 37 5.5 3.5 1.3 0.2 setosa
## 38 4.9 3.6 1.4 0.1 setosa
## 39 4.4 3.0 1.3 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 41 5.0 3.5 1.3 0.3 setosa
## 42 4.5 2.3 1.3 0.3 setosa
## 43 4.4 3.2 1.3 0.2 setosa
## 44 5.0 3.5 1.6 0.6 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 46 4.8 3.0 1.4 0.3 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 48 4.6 3.2 1.4 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosa
## 50 5.0 3.3 1.4 0.2 setosa
## 51 7.0 3.2 4.7 1.4 versicolor
## 52 6.4 3.2 4.5 1.5 versicolor
## 53 6.9 3.1 4.9 1.5 versicolor
## 54 5.5 2.3 4.0 1.3 versicolor
## 55 6.5 2.8 4.6 1.5 versicolor
## 56 5.7 2.8 4.5 1.3 versicolor
## 57 6.3 3.3 4.7 1.6 versicolor
## 58 4.9 2.4 3.3 1.0 versicolor
## 59 6.6 2.9 4.6 1.3 versicolor
## 60 5.2 2.7 3.9 1.4 versicolor
## 61 5.0 2.0 3.5 1.0 versicolor
## 62 5.9 3.0 4.2 1.5 versicolor
## 63 6.0 2.2 4.0 1.0 versicolor
## 64 6.1 2.9 4.7 1.4 versicolor
## 65 5.6 2.9 3.6 1.3 versicolor
## 66 6.7 3.1 4.4 1.4 versicolor
## 67 5.6 3.0 4.5 1.5 versicolor
## 68 5.8 2.7 4.1 1.0 versicolor
## 69 6.2 2.2 4.5 1.5 versicolor
## 70 5.6 2.5 3.9 1.1 versicolor
## 71 5.9 3.2 4.8 1.8 versicolor
## 72 6.1 2.8 4.0 1.3 versicolor
## 73 6.3 2.5 4.9 1.5 versicolor
## 74 6.1 2.8 4.7 1.2 versicolor
## 75 6.4 2.9 4.3 1.3 versicolor
## 76 6.6 3.0 4.4 1.4 versicolor
## 77 6.8 2.8 4.8 1.4 versicolor
## 78 6.7 3.0 5.0 1.7 versicolor
## 79 6.0 2.9 4.5 1.5 versicolor
## 80 5.7 2.6 3.5 1.0 versicolor
## 81 5.5 2.4 3.8 1.1 versicolor
## 82 5.5 2.4 3.7 1.0 versicolor
## 83 5.8 2.7 3.9 1.2 versicolor
## 84 6.0 2.7 5.1 1.6 versicolor
## 85 5.4 3.0 4.5 1.5 versicolor
## 86 6.0 3.4 4.5 1.6 versicolor
## 87 6.7 3.1 4.7 1.5 versicolor
## 88 6.3 2.3 4.4 1.3 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.5 2.5 4.0 1.3 versicolor
## 91 5.5 2.6 4.4 1.2 versicolor
## 92 6.1 3.0 4.6 1.4 versicolor
## 93 5.8 2.6 4.0 1.2 versicolor
## 94 5.0 2.3 3.3 1.0 versicolor
## 95 5.6 2.7 4.2 1.3 versicolor
## 96 5.7 3.0 4.2 1.2 versicolor
## 97 5.7 2.9 4.2 1.3 versicolor
## 98 6.2 2.9 4.3 1.3 versicolor
## 99 5.1 2.5 3.0 1.1 versicolor
## 100 5.7 2.8 4.1 1.3 versicolor
## 101 6.3 3.3 6.0 2.5 virginica
## 102 5.8 2.7 5.1 1.9 virginica
## 103 7.1 3.0 5.9 2.1 virginica
## 104 6.3 2.9 5.6 1.8 virginica
## 105 6.5 3.0 5.8 2.2 virginica
## 106 7.6 3.0 6.6 2.1 virginica
## 107 4.9 2.5 4.5 1.7 virginica
## 108 7.3 2.9 6.3 1.8 virginica
## 109 6.7 2.5 5.8 1.8 virginica
## 110 7.2 3.6 6.1 2.5 virginica
## 111 6.5 3.2 5.1 2.0 virginica
## 112 6.4 2.7 5.3 1.9 virginica
## 113 6.8 3.0 5.5 2.1 virginica
## 114 5.7 2.5 5.0 2.0 virginica
## 115 5.8 2.8 5.1 2.4 virginica
## 116 6.4 3.2 5.3 2.3 virginica
## 117 6.5 3.0 5.5 1.8 virginica
## 118 7.7 3.8 6.7 2.2 virginica
## 119 7.7 2.6 6.9 2.3 virginica
## 120 6.0 2.2 5.0 1.5 virginica
## 121 6.9 3.2 5.7 2.3 virginica
## 122 5.6 2.8 4.9 2.0 virginica
## 123 7.7 2.8 6.7 2.0 virginica
## 124 6.3 2.7 4.9 1.8 virginica
## 125 6.7 3.3 5.7 2.1 virginica
## 126 7.2 3.2 6.0 1.8 virginica
## 127 6.2 2.8 4.8 1.8 virginica
## 128 6.1 3.0 4.9 1.8 virginica
## 129 6.4 2.8 5.6 2.1 virginica
## 130 7.2 3.0 5.8 1.6 virginica
## 131 7.4 2.8 6.1 1.9 virginica
## 132 7.9 3.8 6.4 2.0 virginica
## 133 6.4 2.8 5.6 2.2 virginica
## 134 6.3 2.8 5.1 1.5 virginica
## 135 6.1 2.6 5.6 1.4 virginica
## 136 7.7 3.0 6.1 2.3 virginica
## 137 6.3 3.4 5.6 2.4 virginica
## 138 6.4 3.1 5.5 1.8 virginica
## 139 6.0 3.0 4.8 1.8 virginica
## 140 6.9 3.1 5.4 2.1 virginica
## 141 6.7 3.1 5.6 2.4 virginica
## 142 6.9 3.1 5.1 2.3 virginica
## 143 5.8 2.7 5.1 1.9 virginica
## 144 6.8 3.2 5.9 2.3 virginica
## 145 6.7 3.3 5.7 2.5 virginica
## 146 6.7 3.0 5.2 2.3 virginica
## 147 6.3 2.5 5.0 1.9 virginica
## 148 6.5 3.0 5.2 2.0 virginica
## 149 6.2 3.4 5.4 2.3 virginica
## 150 5.9 3.0 5.1 1.8 virginicaConditonal Statements
AND
iris4 = subset(iris, iris$"petal.length" >"1.4" & iris$"class"== "setosa")
iris4## sepal.length sepal.width petal.length petal.width class
## 4 4.6 3.1 1.5 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 25 4.8 3.4 1.9 0.2 setosa
## 26 5.0 3.0 1.6 0.2 setosa
## 27 5.0 3.4 1.6 0.4 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 30 4.7 3.2 1.6 0.2 setosa
## 31 4.8 3.1 1.6 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 44 5.0 3.5 1.6 0.6 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosaOR
iris5 = subset(iris, iris$"petal.length" >"1.4" | iris$"class"== "setosa")
iris5## sepal.length sepal.width petal.length petal.width class
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 11 5.4 3.7 1.5 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 13 4.8 3.0 1.4 0.1 setosa
## 14 4.3 3.0 1.1 0.1 setosa
## 15 5.8 4.0 1.2 0.2 setosa
## 16 5.7 4.4 1.5 0.4 setosa
## 17 5.4 3.9 1.3 0.4 setosa
## 18 5.1 3.5 1.4 0.3 setosa
## 19 5.7 3.8 1.7 0.3 setosa
## 20 5.1 3.8 1.5 0.3 setosa
## 21 5.4 3.4 1.7 0.2 setosa
## 22 5.1 3.7 1.5 0.4 setosa
## 23 4.6 3.6 1.0 0.2 setosa
## 24 5.1 3.3 1.7 0.5 setosa
## 25 4.8 3.4 1.9 0.2 setosa
## 26 5.0 3.0 1.6 0.2 setosa
## 27 5.0 3.4 1.6 0.4 setosa
## 28 5.2 3.5 1.5 0.2 setosa
## 29 5.2 3.4 1.4 0.2 setosa
## 30 4.7 3.2 1.6 0.2 setosa
## 31 4.8 3.1 1.6 0.2 setosa
## 32 5.4 3.4 1.5 0.4 setosa
## 33 5.2 4.1 1.5 0.1 setosa
## 34 5.5 4.2 1.4 0.2 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 36 5.0 3.2 1.2 0.2 setosa
## 37 5.5 3.5 1.3 0.2 setosa
## 38 4.9 3.6 1.4 0.1 setosa
## 39 4.4 3.0 1.3 0.2 setosa
## 40 5.1 3.4 1.5 0.2 setosa
## 41 5.0 3.5 1.3 0.3 setosa
## 42 4.5 2.3 1.3 0.3 setosa
## 43 4.4 3.2 1.3 0.2 setosa
## 44 5.0 3.5 1.6 0.6 setosa
## 45 5.1 3.8 1.9 0.4 setosa
## 46 4.8 3.0 1.4 0.3 setosa
## 47 5.1 3.8 1.6 0.2 setosa
## 48 4.6 3.2 1.4 0.2 setosa
## 49 5.3 3.7 1.5 0.2 setosa
## 50 5.0 3.3 1.4 0.2 setosa
## 51 7.0 3.2 4.7 1.4 versicolor
## 52 6.4 3.2 4.5 1.5 versicolor
## 53 6.9 3.1 4.9 1.5 versicolor
## 54 5.5 2.3 4.0 1.3 versicolor
## 55 6.5 2.8 4.6 1.5 versicolor
## 56 5.7 2.8 4.5 1.3 versicolor
## 57 6.3 3.3 4.7 1.6 versicolor
## 58 4.9 2.4 3.3 1.0 versicolor
## 59 6.6 2.9 4.6 1.3 versicolor
## 60 5.2 2.7 3.9 1.4 versicolor
## 61 5.0 2.0 3.5 1.0 versicolor
## 62 5.9 3.0 4.2 1.5 versicolor
## 63 6.0 2.2 4.0 1.0 versicolor
## 64 6.1 2.9 4.7 1.4 versicolor
## 65 5.6 2.9 3.6 1.3 versicolor
## 66 6.7 3.1 4.4 1.4 versicolor
## 67 5.6 3.0 4.5 1.5 versicolor
## 68 5.8 2.7 4.1 1.0 versicolor
## 69 6.2 2.2 4.5 1.5 versicolor
## 70 5.6 2.5 3.9 1.1 versicolor
## 71 5.9 3.2 4.8 1.8 versicolor
## 72 6.1 2.8 4.0 1.3 versicolor
## 73 6.3 2.5 4.9 1.5 versicolor
## 74 6.1 2.8 4.7 1.2 versicolor
## 75 6.4 2.9 4.3 1.3 versicolor
## 76 6.6 3.0 4.4 1.4 versicolor
## 77 6.8 2.8 4.8 1.4 versicolor
## 78 6.7 3.0 5.0 1.7 versicolor
## 79 6.0 2.9 4.5 1.5 versicolor
## 80 5.7 2.6 3.5 1.0 versicolor
## 81 5.5 2.4 3.8 1.1 versicolor
## 82 5.5 2.4 3.7 1.0 versicolor
## 83 5.8 2.7 3.9 1.2 versicolor
## 84 6.0 2.7 5.1 1.6 versicolor
## 85 5.4 3.0 4.5 1.5 versicolor
## 86 6.0 3.4 4.5 1.6 versicolor
## 87 6.7 3.1 4.7 1.5 versicolor
## 88 6.3 2.3 4.4 1.3 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.5 2.5 4.0 1.3 versicolor
## 91 5.5 2.6 4.4 1.2 versicolor
## 92 6.1 3.0 4.6 1.4 versicolor
## 93 5.8 2.6 4.0 1.2 versicolor
## 94 5.0 2.3 3.3 1.0 versicolor
## 95 5.6 2.7 4.2 1.3 versicolor
## 96 5.7 3.0 4.2 1.2 versicolor
## 97 5.7 2.9 4.2 1.3 versicolor
## 98 6.2 2.9 4.3 1.3 versicolor
## 99 5.1 2.5 3.0 1.1 versicolor
## 100 5.7 2.8 4.1 1.3 versicolor
## 101 6.3 3.3 6.0 2.5 virginica
## 102 5.8 2.7 5.1 1.9 virginica
## 103 7.1 3.0 5.9 2.1 virginica
## 104 6.3 2.9 5.6 1.8 virginica
## 105 6.5 3.0 5.8 2.2 virginica
## 106 7.6 3.0 6.6 2.1 virginica
## 107 4.9 2.5 4.5 1.7 virginica
## 108 7.3 2.9 6.3 1.8 virginica
## 109 6.7 2.5 5.8 1.8 virginica
## 110 7.2 3.6 6.1 2.5 virginica
## 111 6.5 3.2 5.1 2.0 virginica
## 112 6.4 2.7 5.3 1.9 virginica
## 113 6.8 3.0 5.5 2.1 virginica
## 114 5.7 2.5 5.0 2.0 virginica
## 115 5.8 2.8 5.1 2.4 virginica
## 116 6.4 3.2 5.3 2.3 virginica
## 117 6.5 3.0 5.5 1.8 virginica
## 118 7.7 3.8 6.7 2.2 virginica
## 119 7.7 2.6 6.9 2.3 virginica
## 120 6.0 2.2 5.0 1.5 virginica
## 121 6.9 3.2 5.7 2.3 virginica
## 122 5.6 2.8 4.9 2.0 virginica
## 123 7.7 2.8 6.7 2.0 virginica
## 124 6.3 2.7 4.9 1.8 virginica
## 125 6.7 3.3 5.7 2.1 virginica
## 126 7.2 3.2 6.0 1.8 virginica
## 127 6.2 2.8 4.8 1.8 virginica
## 128 6.1 3.0 4.9 1.8 virginica
## 129 6.4 2.8 5.6 2.1 virginica
## 130 7.2 3.0 5.8 1.6 virginica
## 131 7.4 2.8 6.1 1.9 virginica
## 132 7.9 3.8 6.4 2.0 virginica
## 133 6.4 2.8 5.6 2.2 virginica
## 134 6.3 2.8 5.1 1.5 virginica
## 135 6.1 2.6 5.6 1.4 virginica
## 136 7.7 3.0 6.1 2.3 virginica
## 137 6.3 3.4 5.6 2.4 virginica
## 138 6.4 3.1 5.5 1.8 virginica
## 139 6.0 3.0 4.8 1.8 virginica
## 140 6.9 3.1 5.4 2.1 virginica
## 141 6.7 3.1 5.6 2.4 virginica
## 142 6.9 3.1 5.1 2.3 virginica
## 143 5.8 2.7 5.1 1.9 virginica
## 144 6.8 3.2 5.9 2.3 virginica
## 145 6.7 3.3 5.7 2.5 virginica
## 146 6.7 3.0 5.2 2.3 virginica
## 147 6.3 2.5 5.0 1.9 virginica
## 148 6.5 3.0 5.2 2.0 virginica
## 149 6.2 3.4 5.4 2.3 virginica
## 150 5.9 3.0 5.1 1.8 virginicairis3 <- iris[which(iris$"sepal.length" == "4.9" & iris$"class" == "setosa"),]
iris3## sepal.length sepal.width petal.length petal.width class
## 2 4.9 3.0 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa
## 35 4.9 3.1 1.5 0.2 setosa
## 38 4.9 3.6 1.4 0.1 setosaimport ADULT dataset into R
Adult<-read.csv("C:\\Users\\localadmin\\Desktop\\R\\Adult.csv ")Adult<-read.csv("C:\\Users\\localadmin\\Desktop\\R\\Adult.csv ")
attach(Adult)Trim Function
Adult\(income=str_trim(Adult\)income)
str(Adult)
Assignment
import ADULT dataset into R
Adult<-read.csv("C:\\Users\\localadmin\\Desktop\\R\\Adult.csv ")
write.csv(Adult, "C:\\Users\\localadmin\\Desktop\\R\\Adult.csv ")
attach(Adult)## The following objects are masked from Adult (pos = 3):
##
## V1, V10, V11, V12, V13, V14, V15, V2, V3, V4, V5, V6, V7, V8,
## V9, X, X.1, X.10, X.11, X.12, X.13, X.14, X.15, X.16, X.17,
## X.18, X.19, X.2, X.20, X.21, X.22, X.23, X.24, X.25, X.26,
## X.3, X.4, X.5, X.6, X.7, X.8, X.9Rename the Variables.
colnames(Adult)<-c("age", "workclass" ,"fnlwgt","education", "education-num","marital-status","occupation","relationship ","race","sex","capital-gain","capital-loss","hours-per-week", "native-country","income")
View(Adult)Howmany observations income >50k, ==50k
Adult1<-subset(Adult, income==" <=50K")
Adult1## [1] age workclass fnlwgt education
## [5] education-num marital-status occupation relationship
## [9] race sex capital-gain capital-loss
## [13] hours-per-week native-country income <NA>
## [17] NA.1 NA.2 NA.3 NA.4
## [21] NA.5 NA.6 NA.7 NA.8
## [25] NA.9 NA.10 NA.11 NA.12
## [29] NA.13 NA.14 NA.15 NA.16
## [33] NA.17 NA.18 NA.19 NA.20
## [37] NA.21 NA.22 NA.23 NA.24
## [41] NA.25 NA.26
## <0 rows> (or 0-length row.names)Adult2<-subset(Adult, income==" >50K")
Adult2## [1] age workclass fnlwgt education
## [5] education-num marital-status occupation relationship
## [9] race sex capital-gain capital-loss
## [13] hours-per-week native-country income <NA>
## [17] NA.1 NA.2 NA.3 NA.4
## [21] NA.5 NA.6 NA.7 NA.8
## [25] NA.9 NA.10 NA.11 NA.12
## [29] NA.13 NA.14 NA.15 NA.16
## [33] NA.17 NA.18 NA.19 NA.20
## [37] NA.21 NA.22 NA.23 NA.24
## [41] NA.25 NA.26
## <0 rows> (or 0-length row.names)Howmany observations have age greater than 20 and income>50k
Adult3<- subset(Adult, Adult$"age" >= 20 & Adult$"income" == " >50K" )
Adult3## [1] age workclass fnlwgt education
## [5] education-num marital-status occupation relationship
## [9] race sex capital-gain capital-loss
## [13] hours-per-week native-country income <NA>
## [17] NA.1 NA.2 NA.3 NA.4
## [21] NA.5 NA.6 NA.7 NA.8
## [25] NA.9 NA.10 NA.11 NA.12
## [29] NA.13 NA.14 NA.15 NA.16
## [33] NA.17 NA.18 NA.19 NA.20
## [37] NA.21 NA.22 NA.23 NA.24
## [41] NA.25 NA.26
## <0 rows> (or 0-length row.names)Howmany observations have age lessthan 30 and income >50k
Adult5<- Adult[which(Adult$ "age" < 30 | Adult$ "income"== " >50K"),]
Adult5## age workclass fnlwgt education education-num marital-status occupation
## 1 1 1 1 1 1 1 1
## 2 2 2 2 2 2 2 2
## 3 3 3 3 3 3 3 3
## 4 4 4 4 4 4 4 4
## 5 5 5 5 5 5 5 5
## 6 6 6 6 6 6 6 6
## 7 7 7 7 7 7 7 7
## 8 8 8 8 8 8 8 8
## 9 9 9 9 9 9 9 9
## 10 10 10 10 10 10 10 10
## 11 11 11 11 11 11 11 11
## 12 12 12 12 12 12 12 12
## 13 13 13 13 13 13 13 13
## 14 14 14 14 14 14 14 14
## 15 15 15 15 15 15 15 15
## 16 16 16 16 16 16 16 16
## 17 17 17 17 17 17 17 17
## 18 18 18 18 18 18 18 18
## 19 19 19 19 19 19 19 19
## 20 20 20 20 20 20 20 20
## 21 21 21 21 21 21 21 21
## 22 22 22 22 22 22 22 22
## 23 23 23 23 23 23 23 23
## 24 24 24 24 24 24 24 24
## 25 25 25 25 25 25 25 25
## 26 26 26 26 26 26 26 26
## 27 27 27 27 27 27 27 27
## 28 28 28 28 28 28 28 28
## 29 29 29 29 29 29 29 29
## relationship race sex capital-gain capital-loss hours-per-week
## 1 1 1 1 1 1 1
## 2 2 2 2 2 2 2
## 3 3 3 3 3 3 3
## 4 4 4 4 4 4 4
## 5 5 5 5 5 5 5
## 6 6 6 6 6 6 6
## 7 7 7 7 7 7 7
## 8 8 8 8 8 8 8
## 9 9 9 9 9 9 9
## 10 10 10 10 10 10 10
## 11 11 11 11 11 11 11
## 12 12 12 12 12 12 12
## 13 13 13 13 13 13 13
## 14 14 14 14 14 14 14
## 15 15 15 15 15 15 15
## 16 16 16 16 16 16 16
## 17 17 17 17 17 17 17
## 18 18 18 18 18 18 18
## 19 19 19 19 19 19 19
## 20 20 20 20 20 20 20
## 21 21 21 21 21 21 21
## 22 22 22 22 22 22 22
## 23 23 23 23 23 23 23
## 24 24 24 24 24 24 24
## 25 25 25 25 25 25 25
## 26 26 26 26 26 26 26
## 27 27 27 27 27 27 27
## 28 28 28 28 28 28 28
## 29 29 29 29 29 29 29
## native-country income NA NA NA NA NA NA NA NA NA NA NA NA NA
## 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 39
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 50
## 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 38
## 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 53
## 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 28
## 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 37
## 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 49
## 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 52
## 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 31
## 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 42
## 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 37
## 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 30
## 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 23
## 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 32
## 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 40
## 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 34
## 17 17 17 17 17 17 17 17 17 17 17 17 17 17 17 25
## 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 32
## 19 19 19 19 19 19 19 19 19 19 19 19 19 19 19 38
## 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 43
## 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 40
## 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 54
## 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 35
## 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 43
## 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 59
## 26 26 26 26 26 26 26 26 26 26 26 26 26 26 26 56
## 27 27 27 27 27 27 27 27 27 27 27 27 27 27 27 19
## 28 28 28 28 28 28 28 28 28 28 28 28 28 28 28 54
## 29 29 29 29 29 29 29 29 29 29 29 29 29 29 29 39
## NA NA NA NA NA
## 1 State-gov 77516 Bachelors 13 Never-married
## 2 Self-emp-not-inc 83311 Bachelors 13 Married-civ-spouse
## 3 Private 215646 HS-grad 9 Divorced
## 4 Private 234721 11th 7 Married-civ-spouse
## 5 Private 338409 Bachelors 13 Married-civ-spouse
## 6 Private 284582 Masters 14 Married-civ-spouse
## 7 Private 160187 9th 5 Married-spouse-absent
## 8 Self-emp-not-inc 209642 HS-grad 9 Married-civ-spouse
## 9 Private 45781 Masters 14 Never-married
## 10 Private 159449 Bachelors 13 Married-civ-spouse
## 11 Private 280464 Some-college 10 Married-civ-spouse
## 12 State-gov 141297 Bachelors 13 Married-civ-spouse
## 13 Private 122272 Bachelors 13 Never-married
## 14 Private 205019 Assoc-acdm 12 Never-married
## 15 Private 121772 Assoc-voc 11 Married-civ-spouse
## 16 Private 245487 7th-8th 4 Married-civ-spouse
## 17 Self-emp-not-inc 176756 HS-grad 9 Never-married
## 18 Private 186824 HS-grad 9 Never-married
## 19 Private 28887 11th 7 Married-civ-spouse
## 20 Self-emp-not-inc 292175 Masters 14 Divorced
## 21 Private 193524 Doctorate 16 Married-civ-spouse
## 22 Private 302146 HS-grad 9 Separated
## 23 Federal-gov 76845 9th 5 Married-civ-spouse
## 24 Private 117037 11th 7 Married-civ-spouse
## 25 Private 109015 HS-grad 9 Divorced
## 26 Local-gov 216851 Bachelors 13 Married-civ-spouse
## 27 Private 168294 HS-grad 9 Never-married
## 28 ? 180211 Some-college 10 Married-civ-spouse
## 29 Private 367260 HS-grad 9 Divorced
## NA NA NA NA NA
## 1 Adm-clerical Not-in-family White Male 2174
## 2 Exec-managerial Husband White Male 0
## 3 Handlers-cleaners Not-in-family White Male 0
## 4 Handlers-cleaners Husband Black Male 0
## 5 Prof-specialty Wife Black Female 0
## 6 Exec-managerial Wife White Female 0
## 7 Other-service Not-in-family Black Female 0
## 8 Exec-managerial Husband White Male 0
## 9 Prof-specialty Not-in-family White Female 14084
## 10 Exec-managerial Husband White Male 5178
## 11 Exec-managerial Husband Black Male 0
## 12 Prof-specialty Husband Asian-Pac-Islander Male 0
## 13 Adm-clerical Own-child White Female 0
## 14 Sales Not-in-family Black Male 0
## 15 Craft-repair Husband Asian-Pac-Islander Male 0
## 16 Transport-moving Husband Amer-Indian-Eskimo Male 0
## 17 Farming-fishing Own-child White Male 0
## 18 Machine-op-inspct Unmarried White Male 0
## 19 Sales Husband White Male 0
## 20 Exec-managerial Unmarried White Female 0
## 21 Prof-specialty Husband White Male 0
## 22 Other-service Unmarried Black Female 0
## 23 Farming-fishing Husband Black Male 0
## 24 Transport-moving Husband White Male 0
## 25 Tech-support Unmarried White Female 0
## 26 Tech-support Husband White Male 0
## 27 Craft-repair Own-child White Male 0
## 28 ? Husband Asian-Pac-Islander Male 0
## 29 Exec-managerial Not-in-family White Male 0
## NA NA NA NA
## 1 0 40 United-States <=50K
## 2 0 13 United-States <=50K
## 3 0 40 United-States <=50K
## 4 0 40 United-States <=50K
## 5 0 40 Cuba <=50K
## 6 0 40 United-States <=50K
## 7 0 16 Jamaica <=50K
## 8 0 45 United-States >50K
## 9 0 50 United-States >50K
## 10 0 40 United-States >50K
## 11 0 80 United-States >50K
## 12 0 40 India >50K
## 13 0 30 United-States <=50K
## 14 0 50 United-States <=50K
## 15 0 40 ? >50K
## 16 0 45 Mexico <=50K
## 17 0 35 United-States <=50K
## 18 0 40 United-States <=50K
## 19 0 50 United-States <=50K
## 20 0 45 United-States >50K
## 21 0 60 United-States >50K
## 22 0 20 United-States <=50K
## 23 0 40 United-States <=50K
## 24 2042 40 United-States <=50K
## 25 0 40 United-States <=50K
## 26 0 40 United-States >50K
## 27 0 40 United-States <=50K
## 28 0 60 South >50K
## 29 0 80 United-States <=50KHowmany observations Education Bachelors and Age lessthan 24
Adult6<- Adult[which(Adult$"education" == " Bachelors" & Adult$"age" < 24),]
Adult6## [1] age workclass fnlwgt education
## [5] education-num marital-status occupation relationship
## [9] race sex capital-gain capital-loss
## [13] hours-per-week native-country income <NA>
## [17] <NA> <NA> <NA> <NA>
## [21] <NA> <NA> <NA> <NA>
## [25] <NA> <NA> <NA> <NA>
## [29] <NA> <NA> <NA> <NA>
## [33] <NA> <NA> <NA> <NA>
## [37] <NA> <NA> <NA> <NA>
## [41] <NA> <NA>
## <0 rows> (or 0-length row.names)5th Day Class on R
Idetnify the Length of a String
nchar("Ravitej")## [1] 7Extracts the Place of which we Requires by Position Number
substr("Ravitej", 1 ,3) ## [1] "Rav"Replacing Functions
S<-"RavitejKarvy Analytics Limited KAL"
sub("Ravitej", "Karvy", S)## [1] "KarvyKarvy Analytics Limited KAL"gsub("Ravitej", "Karvy", S)## [1] "KarvyKarvy Analytics Limited KAL"Concatnating Two Vectors Using Outer Function & Paste Function
locations<-c("NY","LA","CHI","HOU")
treatment<-c("T1","T2","T3")
outer(locations,treatment,paste, sep="/")## [,1] [,2] [,3]
## [1,] "NY/T1" "NY/T2" "NY/T3"
## [2,] "LA/T1" "LA/T2" "LA/T3"
## [3,] "CHI/T1" "CHI/T2" "CHI/T3"
## [4,] "HOU/T1" "HOU/T2" "HOU/T3"paste("Ravi", "tej ",sep=" ")## [1] "Ravi tej "Displaying the System Date & its Class
y<-Sys.Date()
y<-2015-10-06
class(Sys.Date())## [1] "Date"as.Date("10/06/2015", format = "%m/%d/%Y")## [1] "2015-10-06"International Standardization of Organization
s1<-ISOdate(2015,6,10)
s2<-as.Date(ISOdate(2015,10,6))
class(s2)## [1] "Date"ISOdatetime(2015, 10, 06, 3, 33, 50, tz = "GMT")## [1] "2015-10-06 03:33:50 GMT"Ploting Mean MEdian Mode
X<-c(1,1,2,2,2,3,4,9,15)
mean(X)## [1] 4.333333mode(X)## [1] "numeric"median(X)## [1] 2sd(X)## [1] 4.690416hist(X)
Plotting The Graph of the Data in R
data()
View(cars)
plot(cars)
plot(cars$speed, cars$dist)
plot(cars, main ="The Tittle", xlab="Speed in KM/H", ylab="distance in KM")
grid()
lines(cars)
pairs(cars)
## Ploting of Iris
data(iris)
with(iris,plot(Petal.Length,Petal.Width,pch=as.integer(Species)))
f<-factor(iris$Species)
legend(1.5,2.4,as.character(levels(f)),pch=1:length(levels(f)))
grid()
data(Cars93, package="MASS")
View(Cars93)
coplot(Horsepower ~ MPG.city | Origin, data = Cars93)
adult<-read.csv("C:\\Users\\localadmin\\Desktop\\R\\adult.csv")
write.csv(adult, "C:\\Users\\localadmin\\Desktop\\R\\adult.csv")
adult<-read.csv("C:\\Users\\localadmin\\Desktop\\R\\adult.csv")
View(adult)
attach(adult)## The following object is masked _by_ .GlobalEnv:
##
## X
##
## The following objects are masked from Adult (pos = 3):
##
## V1, V10, V11, V12, V13, V14, V15, V2, V3, V4, V5, V6, V7, V8,
## V9, X, X.1, X.10, X.11, X.12, X.13, X.14, X.15, X.16, X.17,
## X.18, X.19, X.2, X.20, X.21, X.22, X.23, X.24, X.25, X.26,
## X.3, X.4, X.5, X.6, X.7, X.8, X.9
##
## The following objects are masked from Adult (pos = 4):
##
## V1, V10, V11, V12, V13, V14, V15, V2, V3, V4, V5, V6, V7, V8,
## V9, X, X.1, X.10, X.11, X.12, X.13, X.14, X.15, X.16, X.17,
## X.18, X.19, X.2, X.20, X.21, X.22, X.23, X.24, X.25, X.26,
## X.3, X.4, X.5, X.6, X.7, X.8, X.9plot(adult$V14,adult$V10)
plot(adult$V1, adult$V4)
plot(adult$V4,adult$V1)
plot(adult$V9,adult$V15)
plot(adult$V7,adult$V6)
Day 6
replace names
k<-c(1:5,NA)is.na(k)## [1] FALSE FALSE FALSE FALSE FALSE TRUEcomplete.cases(k)## [1] TRUE TRUE TRUE TRUE TRUE FALSE
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