R version 4.2.3 (2023-03-15 ucrt) -- "Shortstop Beagle"
Copyright (C) 2023 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> help.start()
starting httpd help server ... done
If nothing happens, you should open
âhttp://127.0.0.1:24922/doc/html/index.htmlâ yourself
> help.search(plot)
Error in help.search(plot) :
argument âpatternâ must be a single character string
> help.search("plot")
> ?plot
> 2+3
[1] 5
> a <- 2+3
> a
[1] 5
> 2^3 -> b
> b
[1] 8
> c <- b
> b <- 6
> b
[1] 6
> c
[1] 8
> 3.14 -> d
> d
[1] 3.14
> Inf
[1] Inf
> NaN
[1] NaN
> 5/0
[1] Inf
> Inf-Inf
[1] NaN
> 2+3i
[1] 2+3i
> "ABC"
[1] "ABC"
> TRUE
[1] TRUE
> T
[1] TRUE
> FALSE
[1] FALSE
> F
[1] FALSE
> t
function (x)
UseMethod("t")
<bytecode: 0x000001a92ebc0858>
<environment: namespace:base>
> TRUE & FALSE
[1] FALSE
> TRUE | FALSE
[1] TRUE
> all(T,T,F)
[1] FALSE
> any(T,T,F)
[1] TRUE
> a == b
[1] FALSE
> a > 2
[1] TRUE
> a >= 2
[1] TRUE
> a
[1] 5
> a %% 2
[1] 1
> a %/% 2
[1] 2
> a
[1] 5
> mode(a)
[1] "numeric"
> s <- "abc"
> mode(s)
[1] "character"
> L <- T
> mode(L)
[1] "logical"
> NAĹą
Error: object 'NAĹą' not found
> NA
[1] NA
> NULL
NULL
> is.numeric(a)
[1] TRUE
> is.numeric(s)
[1] FALSE
> as.numeric("123")
[1] 123
> as.character(3.14)
[1] "3.14"
> f <- c(3,0,-2.5)
> f
[1] 3.0 0.0 -2.5
> g <- c(2, "abc")
> g
[1] "2" "abc"
> 1:5
[1] 1 2 3 4 5
> 5:1
[1] 5 4 3 2 1
> seq(1,5)
[1] 1 2 3 4 5
> seq(1,5,2)
[1] 1 3 5
> seq(1,5,length=10)
[1] 1.000000 1.444444 1.888889 2.333333 2.777778
[6] 3.222222 3.666667 4.111111 4.555556 5.000000
> seq(1,by=2,length=10)
[1] 1 3 5 7 9 11 13 15 17 19
> seq(by=2,length=10,to=4)
[1] -14 -12 -10 -8 -6 -4 -2 0 2 4
> ?seq
> ?distributions
> rnorm(10)
[1] 1.0450519 1.1096217 1.6411432 -1.1841482
[5] 0.9457732 -1.1974559 2.7096923 2.3471129
[9] 0.1451879 0.9871264
> v <- 2:4
> w <- c(3,0,-2)
> v; w
[1] 2 3 4
[1] 3 0 -2
> v + w
[1] 5 3 2
> 2 * v
[1] 4 6 8
> v * w
[1] 6 0 -8
> v ^w
[1] 8.0000 1.0000 0.0625
> x <- c(2,-2)
> v
[1] 2 3 4
> x + v
[1] 4 1 6
Warning message:
In x + v : longer object length is not a multiple of shorter object length
> y <- 1:6
> y + x
[1] 3 0 5 2 7 4
> y
[1] 1 2 3 4 5 6
> x
[1] 2 -2
> x[1]
[1] 2
> x[0]
numeric(0)
> y[-1]
[1] 2 3 4 5 6
> y
[1] 1 2 3 4 5 6
> y[8]
[1] NA
> y[c(1,3,4)]
[1] 1 3 4
> y
[1] 1 2 3 4 5 6
> y[c(1,3,4]
Error: unexpected ']' in "y[c(1,3,4]"
>
> y[2:4]
[1] 2 3 4
> y[-2:4]
Error in y[-2:4] : only 0's may be mixed with negative subscripts
> y[-(2:4)]
[1] 1 5 6
> 2:4*2
[1] 4 6 8
> y[c(1,3,1,3)]
[1] 1 3 1 3
> y[c(1,3,1,3,1,3,1,3,1,3)]
[1] 1 3 1 3 1 3 1 3 1 3
> x
[1] 2 -2
> y
[1] 1 2 3 4 5 6
> L <- c(T,T,F,F,F,T)
> y[L]
[1] 1 2 6
> y[c(T,F)]
[1] 1 3 5
> y > 2
[1] FALSE FALSE TRUE TRUE TRUE TRUE
> y[y>2]
[1] 3 4 5 6
> y[(y>2)&(y %% 2 == 1)]
[1] 3 5
> A <- y
> A
[1] 1 2 3 4 5 6
> dim(A)
NULL
> dim(A) <- c(2,3)
> A
[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6
> B <- matrix(-3:2,2,3)
> B
[,1] [,2] [,3]
[1,] -3 -1 1
[2,] -2 0 2
> C <- matrix(-3:2,2,3,byrow=TRUE)
> C
[,1] [,2] [,3]
[1,] -3 -2 -1
[2,] 0 1 2
> C[1,2]
[1] -2
> C[1,]
[1] -3 -2 -1
> C[,2]
[1] -2 1
> C[1,1:2]
[1] -3 -2
> C[-1,-2]
[1] 0 2
> C[2]
[1] 0
> C
[,1] [,2] [,3]
[1,] -3 -2 -1
[2,] 0 1 2
> C[6]
[1] 2
> C[2,]
[1] 0 1 2
> D <- matrix(1:4,2,2)
> D
[,1] [,2]
[1,] 1 3
[2,] 2 4
> t(A)
[,1] [,2]
[1,] 1 2
[2,] 3 4
[3,] 5 6
> A
[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6
> t(A) %*% D
[,1] [,2]
[1,] 5 11
[2,] 11 25
[3,] 17 39
> v
[1] 2 3 4
> A %*% v
[,1]
[1,] 31
[2,] 40
> v %*% t(A)
[,1] [,2]
[1,] 31 40
> w
[1] 3 0 -2
> v %*% w
[,1]
[1,] -2
> crossprod(v,w)
[,1]
[1,] -2
> outer(v,w)
[,1] [,2] [,3]
[1,] 6 0 -4
[2,] 9 0 -6
[3,] 12 0 -8
> det(D)
[1] -2
> x
[1] 2 -2
> solve(D,x)
[1] -7 3
> solve(D)
[,1] [,2]
[1,] -2 1.5
[2,] 1 -0.5
> solve(D) %*% D
[,1] [,2]
[1,] 1 0
[2,] 0 1
> F <- matrix(c(1,2,1,2),2,2)
> F
[,1] [,2]
[1,] 1 1
[2,] 2 2
> det(F)
[1] 0
> solve(F)
Error in solve.default(F) :
Lapack routine dgesv: system is exactly singular: U[2,2] = 0
> A
[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6
> lista <- list("abc", 23, TRUE)
> lista
[[1]]
[1] "abc"
[[2]]
[1] 23
[[3]]
[1] TRUE
> lista[4] <- x
Warning message:
In lista[4] <- x :
number of items to replace is not a multiple of replacement length
> lista[[4]] <- x
> lista
[[1]]
[1] "abc"
[[2]]
[1] 23
[[3]]
[1] TRUE
[[4]]
[1] 2 -2
> names(lista)
NULL
> names(lista) <- c(str,num,logical,vekt)
Error: object 'num' not found
> names(lista) <- c("str","num","logical","vekt")
> lista
$str
[1] "abc"
$num
[1] 23
$logical
[1] TRUE
$vekt
[1] 2 -2
> names(lista)[3] <- NA
> lista
$str
[1] "abc"
$num
[1] 23
$<NA>
[1] TRUE
$vekt
[1] 2 -2
> names(lista)[3] <- NULL
Error in names(lista)[3] <- NULL : replacement has length zero
> lista
$str
[1] "abc"
$num
[1] 23
$<NA>
[1] TRUE
$vekt
[1] 2 -2
> lista[2]
$num
[1] 23
> lista[[2]]
[1] 23
> lista$num
[1] 23
> lista$vekt[2]
[1] -2
> lista$vekt
[1] 2 -2
> lista[4]
$vekt
[1] 2 -2
> lista[4][2]
$<NA>
NULL
> lista[[4]][2]
[1] -2
> data()
> iris
Sepal.Length Sepal.Width Petal.Length
1 5.1 3.5 1.4
2 4.9 3.0 1.4
3 4.7 3.2 1.3
4 4.6 3.1 1.5
5 5.0 3.6 1.4
6 5.4 3.9 1.7
7 4.6 3.4 1.4
8 5.0 3.4 1.5
9 4.4 2.9 1.4
10 4.9 3.1 1.5
11 5.4 3.7 1.5
12 4.8 3.4 1.6
13 4.8 3.0 1.4
14 4.3 3.0 1.1
15 5.8 4.0 1.2
16 5.7 4.4 1.5
17 5.4 3.9 1.3
18 5.1 3.5 1.4
19 5.7 3.8 1.7
20 5.1 3.8 1.5
21 5.4 3.4 1.7
22 5.1 3.7 1.5
23 4.6 3.6 1.0
24 5.1 3.3 1.7
25 4.8 3.4 1.9
26 5.0 3.0 1.6
27 5.0 3.4 1.6
28 5.2 3.5 1.5
29 5.2 3.4 1.4
30 4.7 3.2 1.6
31 4.8 3.1 1.6
32 5.4 3.4 1.5
33 5.2 4.1 1.5
34 5.5 4.2 1.4
35 4.9 3.1 1.5
36 5.0 3.2 1.2
37 5.5 3.5 1.3
38 4.9 3.6 1.4
39 4.4 3.0 1.3
40 5.1 3.4 1.5
41 5.0 3.5 1.3
42 4.5 2.3 1.3
43 4.4 3.2 1.3
44 5.0 3.5 1.6
45 5.1 3.8 1.9
46 4.8 3.0 1.4
47 5.1 3.8 1.6
48 4.6 3.2 1.4
49 5.3 3.7 1.5
50 5.0 3.3 1.4
51 7.0 3.2 4.7
52 6.4 3.2 4.5
53 6.9 3.1 4.9
54 5.5 2.3 4.0
55 6.5 2.8 4.6
56 5.7 2.8 4.5
57 6.3 3.3 4.7
58 4.9 2.4 3.3
59 6.6 2.9 4.6
60 5.2 2.7 3.9
61 5.0 2.0 3.5
62 5.9 3.0 4.2
63 6.0 2.2 4.0
64 6.1 2.9 4.7
65 5.6 2.9 3.6
66 6.7 3.1 4.4
67 5.6 3.0 4.5
68 5.8 2.7 4.1
69 6.2 2.2 4.5
70 5.6 2.5 3.9
71 5.9 3.2 4.8
72 6.1 2.8 4.0
73 6.3 2.5 4.9
74 6.1 2.8 4.7
75 6.4 2.9 4.3
76 6.6 3.0 4.4
77 6.8 2.8 4.8
78 6.7 3.0 5.0
79 6.0 2.9 4.5
80 5.7 2.6 3.5
81 5.5 2.4 3.8
82 5.5 2.4 3.7
83 5.8 2.7 3.9
84 6.0 2.7 5.1
85 5.4 3.0 4.5
86 6.0 3.4 4.5
87 6.7 3.1 4.7
88 6.3 2.3 4.4
89 5.6 3.0 4.1
90 5.5 2.5 4.0
91 5.5 2.6 4.4
92 6.1 3.0 4.6
93 5.8 2.6 4.0
94 5.0 2.3 3.3
95 5.6 2.7 4.2
96 5.7 3.0 4.2
97 5.7 2.9 4.2
98 6.2 2.9 4.3
99 5.1 2.5 3.0
100 5.7 2.8 4.1
101 6.3 3.3 6.0
102 5.8 2.7 5.1
103 7.1 3.0 5.9
104 6.3 2.9 5.6
105 6.5 3.0 5.8
106 7.6 3.0 6.6
107 4.9 2.5 4.5
108 7.3 2.9 6.3
109 6.7 2.5 5.8
110 7.2 3.6 6.1
111 6.5 3.2 5.1
112 6.4 2.7 5.3
113 6.8 3.0 5.5
114 5.7 2.5 5.0
115 5.8 2.8 5.1
116 6.4 3.2 5.3
117 6.5 3.0 5.5
118 7.7 3.8 6.7
119 7.7 2.6 6.9
120 6.0 2.2 5.0
121 6.9 3.2 5.7
122 5.6 2.8 4.9
123 7.7 2.8 6.7
124 6.3 2.7 4.9
125 6.7 3.3 5.7
126 7.2 3.2 6.0
127 6.2 2.8 4.8
128 6.1 3.0 4.9
129 6.4 2.8 5.6
130 7.2 3.0 5.8
131 7.4 2.8 6.1
132 7.9 3.8 6.4
133 6.4 2.8 5.6
134 6.3 2.8 5.1
135 6.1 2.6 5.6
136 7.7 3.0 6.1
137 6.3 3.4 5.6
138 6.4 3.1 5.5
139 6.0 3.0 4.8
140 6.9 3.1 5.4
141 6.7 3.1 5.6
142 6.9 3.1 5.1
143 5.8 2.7 5.1
144 6.8 3.2 5.9
145 6.7 3.3 5.7
146 6.7 3.0 5.2
147 6.3 2.5 5.0
148 6.5 3.0 5.2
149 6.2 3.4 5.4
150 5.9 3.0 5.1
Petal.Width Species
1 0.2 setosa
2 0.2 setosa
3 0.2 setosa
4 0.2 setosa
5 0.2 setosa
6 0.4 setosa
7 0.3 setosa
8 0.2 setosa
9 0.2 setosa
10 0.1 setosa
11 0.2 setosa
12 0.2 setosa
13 0.1 setosa
14 0.1 setosa
15 0.2 setosa
16 0.4 setosa
17 0.4 setosa
18 0.3 setosa
19 0.3 setosa
20 0.3 setosa
21 0.2 setosa
22 0.4 setosa
23 0.2 setosa
24 0.5 setosa
25 0.2 setosa
26 0.2 setosa
27 0.4 setosa
28 0.2 setosa
29 0.2 setosa
30 0.2 setosa
31 0.2 setosa
32 0.4 setosa
33 0.1 setosa
34 0.2 setosa
35 0.2 setosa
36 0.2 setosa
37 0.2 setosa
38 0.1 setosa
39 0.2 setosa
40 0.2 setosa
41 0.3 setosa
42 0.3 setosa
43 0.2 setosa
44 0.6 setosa
45 0.4 setosa
46 0.3 setosa
47 0.2 setosa
48 0.2 setosa
49 0.2 setosa
50 0.2 setosa
51 1.4 versicolor
52 1.5 versicolor
53 1.5 versicolor
54 1.3 versicolor
55 1.5 versicolor
56 1.3 versicolor
57 1.6 versicolor
58 1.0 versicolor
59 1.3 versicolor
60 1.4 versicolor
61 1.0 versicolor
62 1.5 versicolor
63 1.0 versicolor
64 1.4 versicolor
65 1.3 versicolor
66 1.4 versicolor
67 1.5 versicolor
68 1.0 versicolor
69 1.5 versicolor
70 1.1 versicolor
71 1.8 versicolor
72 1.3 versicolor
73 1.5 versicolor
74 1.2 versicolor
75 1.3 versicolor
76 1.4 versicolor
77 1.4 versicolor
78 1.7 versicolor
79 1.5 versicolor
80 1.0 versicolor
81 1.1 versicolor
82 1.0 versicolor
83 1.2 versicolor
84 1.6 versicolor
85 1.5 versicolor
86 1.6 versicolor
87 1.5 versicolor
88 1.3 versicolor
89 1.3 versicolor
90 1.3 versicolor
91 1.2 versicolor
92 1.4 versicolor
93 1.2 versicolor
94 1.0 versicolor
95 1.3 versicolor
96 1.2 versicolor
97 1.3 versicolor
98 1.3 versicolor
99 1.1 versicolor
100 1.3 versicolor
101 2.5 virginica
102 1.9 virginica
103 2.1 virginica
104 1.8 virginica
105 2.2 virginica
106 2.1 virginica
107 1.7 virginica
108 1.8 virginica
109 1.8 virginica
110 2.5 virginica
111 2.0 virginica
112 1.9 virginica
113 2.1 virginica
114 2.0 virginica
115 2.4 virginica
116 2.3 virginica
117 1.8 virginica
118 2.2 virginica
119 2.3 virginica
120 1.5 virginica
121 2.3 virginica
122 2.0 virginica
123 2.0 virginica
124 1.8 virginica
125 2.1 virginica
126 1.8 virginica
127 1.8 virginica
128 1.8 virginica
129 2.1 virginica
130 1.6 virginica
131 1.9 virginica
132 2.0 virginica
133 2.2 virginica
134 1.5 virginica
135 1.4 virginica
136 2.3 virginica
137 2.4 virginica
138 1.8 virginica
139 1.8 virginica
140 2.1 virginica
141 2.4 virginica
142 2.3 virginica
143 1.9 virginica
144 2.3 virginica
145 2.5 virginica
146 2.3 virginica
147 1.9 virginica
148 2.0 virginica
149 2.3 virginica
150 1.8 virginica
> ?iris
> head(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width
1 5.1 3.5 1.4 0.2
2 4.9 3.0 1.4 0.2
3 4.7 3.2 1.3 0.2
4 4.6 3.1 1.5 0.2
5 5.0 3.6 1.4 0.2
6 5.4 3.9 1.7 0.4
Species
1 setosa
2 setosa
3 setosa
4 setosa
5 setosa
6 setosa
> edit(iris)
Sepal.Length Sepal.Width Petal.Length Petal.Width
1 5.1 3.5 1.4 0.2
2 4.9 3.0 1.4 0.2
3 4.7 3.2 1.3 0.2
4 4.6 3.1 1.5 0.2
5 5.0 3.6 1.4 0.2
6 5.4 3.9 1.7 0.4
7 4.6 3.4 1.4 0.3
8 5.0 3.4 1.5 0.2
9 4.4 2.9 1.4 0.2
10 4.9 3.1 1.5 0.1
11 5.4 3.7 1.5 0.2
12 4.8 3.4 1.6 0.2
13 4.8 3.0 1.4 0.1
14 4.3 3.0 1.1 0.1
15 5.8 4.0 1.2 0.2
16 5.7 4.4 1.5 0.4
17 5.4 3.9 1.3 0.4
18 5.1 3.5 1.4 0.3
19 5.7 3.8 1.7 0.3
20 5.1 3.8 1.5 0.3
21 5.4 3.4 1.7 0.2
22 5.1 3.7 1.5 0.4
23 4.6 3.6 1.0 0.2
24 5.1 3.3 1.7 0.5
25 4.8 3.4 1.9 0.2
26 5.0 3.0 1.6 0.2
27 5.0 3.4 1.6 0.4
28 5.2 3.5 1.5 0.2
29 5.2 3.4 1.4 0.2
30 4.7 3.2 1.6 0.2
31 4.8 3.1 1.6 0.2
32 5.4 3.4 1.5 0.4
33 5.2 4.1 1.5 0.1
34 5.5 4.2 1.4 0.2
35 4.9 3.1 1.5 0.2
36 5.0 3.2 1.2 0.2
37 5.5 3.5 1.3 0.2
38 4.9 3.6 1.4 0.1
39 4.4 3.0 1.3 0.2
40 5.1 3.4 1.5 0.2
41 5.0 3.5 1.3 0.3
42 4.5 2.3 1.3 0.3
43 4.4 3.2 1.3 0.2
44 5.0 3.5 1.6 0.6
45 5.1 3.8 1.9 0.4
46 4.8 3.0 1.4 0.3
47 5.1 3.8 1.6 0.2
48 4.6 3.2 1.4 0.2
49 5.3 3.7 1.5 0.2
50 5.0 3.3 1.4 0.2
51 7.0 3.2 4.7 1.4
52 6.4 3.2 4.5 1.5
53 6.9 3.1 4.9 1.5
54 5.5 2.3 4.0 1.3
55 6.5 2.8 4.6 1.5
56 5.7 2.8 4.5 1.3
57 6.3 3.3 4.7 1.6
58 4.9 2.4 3.3 1.0
59 6.6 2.9 4.6 1.3
60 5.2 2.7 3.9 1.4
61 5.0 2.0 3.5 1.0
62 5.9 3.0 4.2 1.5
63 6.0 2.2 4.0 1.0
64 6.1 2.9 4.7 1.4
65 5.6 2.9 3.6 1.3
66 6.7 3.1 4.4 1.4
67 5.6 3.0 4.5 1.5
68 5.8 2.7 4.1 1.0
69 6.2 2.2 4.5 1.5
70 5.6 2.5 3.9 1.1
71 5.9 3.2 4.8 1.8
72 6.1 2.8 4.0 1.3
73 6.3 2.5 4.9 1.5
74 6.1 2.8 4.7 1.2
75 6.4 2.9 4.3 1.3
76 6.6 3.0 4.4 1.4
77 6.8 2.8 4.8 1.4
78 6.7 3.0 5.0 1.7
79 6.0 2.9 4.5 1.5
80 5.7 2.6 3.5 1.0
81 5.5 2.4 3.8 1.1
82 5.5 2.4 3.7 1.0
83 5.8 2.7 3.9 1.2
84 6.0 2.7 5.1 1.6
85 5.4 3.0 4.5 1.5
86 6.0 3.4 4.5 1.6
87 6.7 3.1 4.7 1.5
88 6.3 2.3 4.4 1.3
89 5.6 3.0 4.1 1.3
90 5.5 2.5 4.0 1.3
91 5.5 2.6 4.4 1.2
92 6.1 3.0 4.6 1.4
93 5.8 2.6 4.0 1.2
94 5.0 2.3 3.3 1.0
95 5.6 2.7 4.2 1.3
96 5.7 3.0 4.2 1.2
97 5.7 2.9 4.2 1.3
98 6.2 2.9 4.3 1.3
99 5.1 2.5 3.0 1.1
100 5.7 2.8 4.1 1.3
101 6.3 3.3 6.0 2.5
102 5.8 2.7 5.1 1.9
103 7.1 3.0 5.9 2.1
104 6.3 2.9 5.6 1.8
105 6.5 3.0 5.8 2.2
106 7.6 3.0 6.6 2.1
107 4.9 2.5 4.5 1.7
108 7.3 2.9 6.3 1.8
109 6.7 2.5 5.8 1.8
110 7.2 3.6 6.1 2.5
111 6.5 3.2 5.1 2.0
112 6.4 2.7 5.3 1.9
113 6.8 3.0 5.5 2.1
114 5.7 2.5 5.0 2.0
115 5.8 2.8 5.1 2.4
116 6.4 3.2 5.3 2.3
117 6.5 3.0 5.5 1.8
118 7.7 3.8 6.7 2.2
119 7.7 2.6 6.9 2.3
120 6.0 2.2 5.0 1.5
121 6.9 3.2 5.7 2.3
122 5.6 2.8 4.9 2.0
123 7.7 2.8 6.7 2.0
124 6.3 2.7 4.9 1.8
125 6.7 3.3 5.7 2.1
126 7.2 3.2 6.0 1.8
127 6.2 2.8 4.8 1.8
128 6.1 3.0 4.9 1.8
129 6.4 2.8 5.6 2.1
130 7.2 3.0 5.8 1.6
131 7.4 2.8 6.1 1.9
132 7.9 3.8 6.4 2.0
133 6.4 2.8 5.6 2.2
134 6.3 2.8 5.1 1.5
135 6.1 2.6 5.6 1.4
136 7.7 3.0 6.1 2.3
137 6.3 3.4 5.6 2.4
138 6.4 3.1 5.5 1.8
139 6.0 3.0 4.8 1.8
140 6.9 3.1 5.4 2.1
141 6.7 3.1 5.6 2.4
142 6.9 3.1 5.1 2.3
143 5.8 2.7 5.1 1.9
144 6.8 3.2 5.9 2.3
145 6.7 3.3 5.7 2.5
146 6.7 3.0 5.2 2.3
147 6.3 2.5 5.0 1.9
148 6.5 3.0 5.2 2.0
149 6.2 3.4 5.4 2.3
150 5.9 3.0 5.1 1.8
Species
1 setosa
2 setosa
3 setosa
4 setosa
5 setosa
6 setosa
7 setosa
8 setosa
9 setosa
10 setosa
11 setosa
12 setosa
13 setosa
14 setosa
15 setosa
16 setosa
17 setosa
18 setosa
19 setosa
20 setosa
21 setosa
22 setosa
23 setosa
24 setosa
25 setosa
26 setosa
27 setosa
28 setosa
29 setosa
30 setosa
31 setosa
32 setosa
33 setosa
34 setosa
35 setosa
36 setosa
37 setosa
38 setosa
39 setosa
40 setosa
41 setosa
42 setosa
43 setosa
44 setosa
45 setosa
46 setosa
47 setosa
48 setosa
49 setosa
50 setosa
51 versicolor
52 versicolor
53 versicolor
54 versicolor
55 versicolor
56 versicolor
57 versicolor
58 versicolor
59 versicolor
60 versicolor
61 versicolor
62 versicolor
63 versicolor
64 versicolor
65 versicolor
66 versicolor
67 versicolor
68 versicolor
69 versicolor
70 versicolor
71 versicolor
72 versicolor
73 versicolor
74 versicolor
75 versicolor
76 versicolor
77 versicolor
78 versicolor
79 versicolor
80 versicolor
81 versicolor
82 versicolor
83 versicolor
84 versicolor
85 versicolor
86 versicolor
87 versicolor
88 versicolor
89 versicolor
90 versicolor
91 versicolor
92 versicolor
93 versicolor
94 versicolor
95 versicolor
96 versicolor
97 versicolor
98 versicolor
99 versicolor
100 versicolor
101 virginica
102 virginica
103 virginica
104 virginica
105 virginica
106 virginica
107 virginica
108 virginica
109 virginica
110 virginica
111 virginica
112 virginica
113 virginica
114 virginica
115 virginica
116 virginica
117 virginica
118 virginica
119 virginica
120 virginica
121 virginica
122 virginica
123 virginica
124 virginica
125 virginica
126 virginica
127 virginica
128 virginica
129 virginica
130 virginica
131 virginica
132 virginica
133 virginica
134 virginica
135 virginica
136 virginica
137 virginica
138 virginica
139 virginica
140 virginica
141 virginica
142 virginica
143 virginica
144 virginica
145 virginica
146 virginica
147 virginica
148 virginica
149 virginica
150 virginica
> iris[2,3]
[1] 1.4
> iris[2]
Sepal.Width
1 3.5
2 3.0
3 3.2
4 3.1
5 3.6
6 3.9
7 3.4
8 3.4
9 2.9
10 3.1
11 3.7
12 3.4
13 3.0
14 3.0
15 4.0
16 4.4
17 3.9
18 3.5
19 3.8
20 3.8
21 3.4
22 3.7
23 3.6
24 3.3
25 3.4
26 3.0
27 3.4
28 3.5
29 3.4
30 3.2
31 3.1
32 3.4
33 4.1
34 4.2
35 3.1
36 3.2
37 3.5
38 3.6
39 3.0
40 3.4
41 3.5
42 2.3
43 3.2
44 3.5
45 3.8
46 3.0
47 3.8
48 3.2
49 3.7
50 3.3
51 3.2
52 3.2
53 3.1
54 2.3
55 2.8
56 2.8
57 3.3
58 2.4
59 2.9
60 2.7
61 2.0
62 3.0
63 2.2
64 2.9
65 2.9
66 3.1
67 3.0
68 2.7
69 2.2
70 2.5
71 3.2
72 2.8
73 2.5
74 2.8
75 2.9
76 3.0
77 2.8
78 3.0
79 2.9
80 2.6
81 2.4
82 2.4
83 2.7
84 2.7
85 3.0
86 3.4
87 3.1
88 2.3
89 3.0
90 2.5
91 2.6
92 3.0
93 2.6
94 2.3
95 2.7
96 3.0
97 2.9
98 2.9
99 2.5
100 2.8
101 3.3
102 2.7
103 3.0
104 2.9
105 3.0
106 3.0
107 2.5
108 2.9
109 2.5
110 3.6
111 3.2
112 2.7
113 3.0
114 2.5
115 2.8
116 3.2
117 3.0
118 3.8
119 2.6
120 2.2
121 3.2
122 2.8
123 2.8
124 2.7
125 3.3
126 3.2
127 2.8
128 3.0
129 2.8
130 3.0
131 2.8
132 3.8
133 2.8
134 2.8
135 2.6
136 3.0
137 3.4
138 3.1
139 3.0
140 3.1
141 3.1
142 3.1
143 2.7
144 3.2
145 3.3
146 3.0
147 2.5
148 3.0
149 3.4
150 3.0
> iris[2,]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
2 4.9 3 1.4 0.2 setosa
> iris$Species
[1] setosa setosa setosa setosa setosa
[6] setosa setosa setosa setosa setosa
[11] setosa setosa setosa setosa setosa
[16] setosa setosa setosa setosa setosa
[21] setosa setosa setosa setosa setosa
[26] setosa setosa setosa setosa setosa
[31] setosa setosa setosa setosa setosa
[36] setosa setosa setosa setosa setosa
[41] setosa setosa setosa setosa setosa
[46] setosa setosa setosa setosa setosa
[51] versicolor versicolor versicolor versicolor versicolor
[56] versicolor versicolor versicolor versicolor versicolor
[61] versicolor versicolor versicolor versicolor versicolor
[66] versicolor versicolor versicolor versicolor versicolor
[71] versicolor versicolor versicolor versicolor versicolor
[76] versicolor versicolor versicolor versicolor versicolor
[81] versicolor versicolor versicolor versicolor versicolor
[86] versicolor versicolor versicolor versicolor versicolor
[91] versicolor versicolor versicolor versicolor versicolor
[96] versicolor versicolor versicolor versicolor versicolor
[101] virginica virginica virginica virginica virginica
[106] virginica virginica virginica virginica virginica
[111] virginica virginica virginica virginica virginica
[116] virginica virginica virginica virginica virginica
[121] virginica virginica virginica virginica virginica
[126] virginica virginica virginica virginica virginica
[131] virginica virginica virginica virginica virginica
[136] virginica virginica virginica virginica virginica
[141] virginica virginica virginica virginica virginica
[146] virginica virginica virginica virginica virginica
Levels: setosa versicolor virginica
> mode(iris$Species)
[1] "numeric"
> class(iris$Species)
[1] "factor"
> names(iris)
[1] "Sepal.Length" "Sepal.Width" "Petal.Length" "Petal.Width"
[5] "Species"
> row.names(iris)
[1] "1" "2" "3" "4" "5" "6" "7" "8" "9"
[10] "10" "11" "12" "13" "14" "15" "16" "17" "18"
[19] "19" "20" "21" "22" "23" "24" "25" "26" "27"
[28] "28" "29" "30" "31" "32" "33" "34" "35" "36"
[37] "37" "38" "39" "40" "41" "42" "43" "44" "45"
[46] "46" "47" "48" "49" "50" "51" "52" "53" "54"
[55] "55" "56" "57" "58" "59" "60" "61" "62" "63"
[64] "64" "65" "66" "67" "68" "69" "70" "71" "72"
[73] "73" "74" "75" "76" "77" "78" "79" "80" "81"
[82] "82" "83" "84" "85" "86" "87" "88" "89" "90"
[91] "91" "92" "93" "94" "95" "96" "97" "98" "99"
[100] "100" "101" "102" "103" "104" "105" "106" "107" "108"
[109] "109" "110" "111" "112" "113" "114" "115" "116" "117"
[118] "118" "119" "120" "121" "122" "123" "124" "125" "126"
[127] "127" "128" "129" "130" "131" "132" "133" "134" "135"
[136] "136" "137" "138" "139" "140" "141" "142" "143" "144"
[145] "145" "146" "147" "148" "149" "150"
> mode(iris$Sepal.Width)
[1] "numeric"
> iris[2:5,c(1,3,5)]
Sepal.Length Petal.Length Species
2 4.9 1.4 setosa
3 4.7 1.3 setosa
4 4.6 1.5 setosa
5 5.0 1.4 setosa
> iris2 <- iris[5:10,]
> iris2
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
5 5.0 3.6 1.4 0.2 setosa
6 5.4 3.9 1.7 0.4 setosa
7 4.6 3.4 1.4 0.3 setosa
8 5.0 3.4 1.5 0.2 setosa
9 4.4 2.9 1.4 0.2 setosa
10 4.9 3.1 1.5 0.1 setosa
> iris2[2,]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
6 5.4 3.9 1.7 0.4 setosa
> iris2["6",]
Sepal.Length Sepal.Width Petal.Length Petal.Width Species
6 5.4 3.9 1.7 0.4 setosa
> x <- rnorm(10)
> y <- rnorm(10)
> runif[10]
Error in runif[10] : object of type 'closure' is not subsettable
> runif(10)
[1] 0.6792710 0.7309148 0.5484440 0.8403378 0.8734246
[6] 0.6797834 0.2015283 0.5208646 0.4451908 0.1930728
> round(1 + runif(10))
[1] 2 1 2 2 1 1 2 2 2 2
> .Last.value
[1] 2 1 2 2 1 1 2 2 2 2
> .Last.value -> halmaz
> pontok <- data.frame(xkoord = x, ykoord = y, halmaz = halmaz)
> pontok
xkoord ykoord halmaz
1 0.1829699 0.3702491 2
2 0.3649382 -0.7408059 1
3 -0.2073121 -0.6979016 2
4 -1.7441663 -0.4389299 2
5 1.3119190 1.7016581 1
6 0.9769963 1.6276354 1
7 0.6187861 0.6406041 2
8 0.2507825 -1.3344828 2
9 1.6436978 -0.9704997 2
10 -0.8417565 -0.3048665 2
> pontok[1]
xkoord
1 0.1829699
2 0.3649382
3 -0.2073121
4 -1.7441663
5 1.3119190
6 0.9769963
7 0.6187861
8 0.2507825
9 1.6436978
10 -0.8417565
> pontok$xkoord
[1] 0.1829699 0.3649382 -0.2073121 -1.7441663 1.3119190
[6] 0.9769963 0.6187861 0.2507825 1.6436978 -0.8417565
> pontok$tav <- sqrt(pontok$xkoord^2+pontok$ykoord^2)
> pontok
xkoord ykoord halmaz tav
1 0.1829699 0.3702491 2 0.4129920
2 0.3649382 -0.7408059 1 0.8258167
3 -0.2073121 -0.6979016 2 0.7280419
4 -1.7441663 -0.4389299 2 1.7985482
5 1.3119190 1.7016581 1 2.1486674
6 0.9769963 1.6276354 1 1.8983463
7 0.6187861 0.6406041 2 0.8906569
8 0.2507825 -1.3344828 2 1.3578425
9 1.6436978 -0.9704997 2 1.9088248
10 -0.8417565 -0.3048665 2 0.8952640
> class(pontok$halmaz)
[1] "numeric"
> pontok$halmaz <- factor(pontok$halmaz)
> class(pontok$halmaz)
[1] "factor"
> pontok$halmaz
[1] 2 1 2 2 1 1 2 2 2 2
Levels: 1 2
> halmaz
[1] 2 1 2 2 1 1 2 2 2 2
> class(halmaz)
[1] "numeric"
> plot(halmaz)
> plot(pontok$halmaz)
> mean(pontok$tav)
[1] 1.2865
> length(pontok$tav)
[1] 10
> sum(pontok$tav)
[1] 12.865
> tapply(pontok$tav,pontok$halmaz,mean)
1 2
1.624277 1.141739
> ls()
[1] "a" "A" "b" "B" "c" "C"
[7] "d" "D" "f" "F" "g" "halmaz"
[13] "iris2" "L" "lista" "pontok" "s" "v"
[19] "w" "x" "y"
> rm(A,B,g,f,F)
> ls()
[1] "a" "b" "c" "C" "d" "D"
[7] "halmaz" "iris2" "L" "lista" "pontok" "s"
[13] "v" "w" "x" "y"
> pontok$koord
NULL
> pontok$xkoord
[1] 0.1829699 0.3649382 -0.2073121 -1.7441663 1.3119190
[6] 0.9769963 0.6187861 0.2507825 1.6436978 -0.8417565
> attach(pontok)
The following object is masked _by_ .GlobalEnv:
halmaz
> xkoord
[1] 0.1829699 0.3649382 -0.2073121 -1.7441663 1.3119190
[6] 0.9769963 0.6187861 0.2507825 1.6436978 -0.8417565
> plot(xkoord,ykoord)
> pontok
xkoord ykoord halmaz tav
1 0.1829699 0.3702491 2 0.4129920
2 0.3649382 -0.7408059 1 0.8258167
3 -0.2073121 -0.6979016 2 0.7280419
4 -1.7441663 -0.4389299 2 1.7985482
5 1.3119190 1.7016581 1 2.1486674
6 0.9769963 1.6276354 1 1.8983463
7 0.6187861 0.6406041 2 0.8906569
8 0.2507825 -1.3344828 2 1.3578425
9 1.6436978 -0.9704997 2 1.9088248
10 -0.8417565 -0.3048665 2 0.8952640
> xkoord <- rnorm(10) + 2
> xkoord
[1] 1.3251152 0.8270475 -0.4877544 3.9717239 1.3021074
[6] 2.1701846 2.4353841 4.1954699 1.8175215 1.3981023
> pontok$xkoord
[1] 0.1829699 0.3649382 -0.2073121 -1.7441663 1.3119190
[6] 0.9769963 0.6187861 0.2507825 1.6436978 -0.8417565
> ls()
[1] "a" "b" "c" "C" "d" "D"
[7] "halmaz" "iris2" "L" "lista" "pontok" "s"
[13] "v" "w" "x" "xkoord" "y"
> ykoord
[1] 0.3702491 -0.7408059 -0.6979016 -0.4389299 1.7016581
[6] 1.6276354 0.6406041 -1.3344828 -0.9704997 -0.3048665
> detach(pontok)
> ykoord
Error: object 'ykoord' not found
> pontok$ykoord
[1] 0.3702491 -0.7408059 -0.6979016 -0.4389299 1.7016581
[6] 1.6276354 0.6406041 -1.3344828 -0.9704997 -0.3048665
> attach(pontok)
The following objects are masked _by_ .GlobalEnv:
halmaz, xkoord
> xkoord
[1] 1.3251152 0.8270475 -0.4877544 3.9717239 1.3021074
[6] 2.1701846 2.4353841 4.1954699 1.8175215 1.3981023
> pontok$xkoord
[1] 0.1829699 0.3649382 -0.2073121 -1.7441663 1.3119190
[6] 0.9769963 0.6187861 0.2507825 1.6436978 -0.8417565
> detach(pontok)
> rm(xkoord,halmaz)
> attach(pontok)
> plot(xkoord,ykoord)
> plot(xkoord,ykoord,col="red")
> ?colors
> colors()
[1] "white" "aliceblue"
[3] "antiquewhite" "antiquewhite1"
[5] "antiquewhite2" "antiquewhite3"
[7] "antiquewhite4" "aquamarine"
[9] "aquamarine1" "aquamarine2"
[11] "aquamarine3" "aquamarine4"
[13] "azure" "azure1"
[15] "azure2" "azure3"
[17] "azure4" "beige"
[19] "bisque" "bisque1"
[21] "bisque2" "bisque3"
[23] "bisque4" "black"
[25] "blanchedalmond" "blue"
[27] "blue1" "blue2"
[29] "blue3" "blue4"
[31] "blueviolet" "brown"
[33] "brown1" "brown2"
[35] "brown3" "brown4"
[37] "burlywood" "burlywood1"
[39] "burlywood2" "burlywood3"
[41] "burlywood4" "cadetblue"
[43] "cadetblue1" "cadetblue2"
[45] "cadetblue3" "cadetblue4"
[47] "chartreuse" "chartreuse1"
[49] "chartreuse2" "chartreuse3"
[51] "chartreuse4" "chocolate"
[53] "chocolate1" "chocolate2"
[55] "chocolate3" "chocolate4"
[57] "coral" "coral1"
[59] "coral2" "coral3"
[61] "coral4" "cornflowerblue"
[63] "cornsilk" "cornsilk1"
[65] "cornsilk2" "cornsilk3"
[67] "cornsilk4" "cyan"
[69] "cyan1" "cyan2"
[71] "cyan3" "cyan4"
[73] "darkblue" "darkcyan"
[75] "darkgoldenrod" "darkgoldenrod1"
[77] "darkgoldenrod2" "darkgoldenrod3"
[79] "darkgoldenrod4" "darkgray"
[81] "darkgreen" "darkgrey"
[83] "darkkhaki" "darkmagenta"
[85] "darkolivegreen" "darkolivegreen1"
[87] "darkolivegreen2" "darkolivegreen3"
[89] "darkolivegreen4" "darkorange"
[91] "darkorange1" "darkorange2"
[93] "darkorange3" "darkorange4"
[95] "darkorchid" "darkorchid1"
[97] "darkorchid2" "darkorchid3"
[99] "darkorchid4" "darkred"
[101] "darksalmon" "darkseagreen"
[103] "darkseagreen1" "darkseagreen2"
[105] "darkseagreen3" "darkseagreen4"
[107] "darkslateblue" "darkslategray"
[109] "darkslategray1" "darkslategray2"
[111] "darkslategray3" "darkslategray4"
[113] "darkslategrey" "darkturquoise"
[115] "darkviolet" "deeppink"
[117] "deeppink1" "deeppink2"
[119] "deeppink3" "deeppink4"
[121] "deepskyblue" "deepskyblue1"
[123] "deepskyblue2" "deepskyblue3"
[125] "deepskyblue4" "dimgray"
[127] "dimgrey" "dodgerblue"
[129] "dodgerblue1" "dodgerblue2"
[131] "dodgerblue3" "dodgerblue4"
[133] "firebrick" "firebrick1"
[135] "firebrick2" "firebrick3"
[137] "firebrick4" "floralwhite"
[139] "forestgreen" "gainsboro"
[141] "ghostwhite" "gold"
[143] "gold1" "gold2"
[145] "gold3" "gold4"
[147] "goldenrod" "goldenrod1"
[149] "goldenrod2" "goldenrod3"
[151] "goldenrod4" "gray"
[153] "gray0" "gray1"
[155] "gray2" "gray3"
[157] "gray4" "gray5"
[159] "gray6" "gray7"
[161] "gray8" "gray9"
[163] "gray10" "gray11"
[165] "gray12" "gray13"
[167] "gray14" "gray15"
[169] "gray16" "gray17"
[171] "gray18" "gray19"
[173] "gray20" "gray21"
[175] "gray22" "gray23"
[177] "gray24" "gray25"
[179] "gray26" "gray27"
[181] "gray28" "gray29"
[183] "gray30" "gray31"
[185] "gray32" "gray33"
[187] "gray34" "gray35"
[189] "gray36" "gray37"
[191] "gray38" "gray39"
[193] "gray40" "gray41"
[195] "gray42" "gray43"
[197] "gray44" "gray45"
[199] "gray46" "gray47"
[201] "gray48" "gray49"
[203] "gray50" "gray51"
[205] "gray52" "gray53"
[207] "gray54" "gray55"
[209] "gray56" "gray57"
[211] "gray58" "gray59"
[213] "gray60" "gray61"
[215] "gray62" "gray63"
[217] "gray64" "gray65"
[219] "gray66" "gray67"
[221] "gray68" "gray69"
[223] "gray70" "gray71"
[225] "gray72" "gray73"
[227] "gray74" "gray75"
[229] "gray76" "gray77"
[231] "gray78" "gray79"
[233] "gray80" "gray81"
[235] "gray82" "gray83"
[237] "gray84" "gray85"
[239] "gray86" "gray87"
[241] "gray88" "gray89"
[243] "gray90" "gray91"
[245] "gray92" "gray93"
[247] "gray94" "gray95"
[249] "gray96" "gray97"
[251] "gray98" "gray99"
[253] "gray100" "green"
[255] "green1" "green2"
[257] "green3" "green4"
[259] "greenyellow" "grey"
[261] "grey0" "grey1"
[263] "grey2" "grey3"
[265] "grey4" "grey5"
[267] "grey6" "grey7"
[269] "grey8" "grey9"
[271] "grey10" "grey11"
[273] "grey12" "grey13"
[275] "grey14" "grey15"
[277] "grey16" "grey17"
[279] "grey18" "grey19"
[281] "grey20" "grey21"
[283] "grey22" "grey23"
[285] "grey24" "grey25"
[287] "grey26" "grey27"
[289] "grey28" "grey29"
[291] "grey30" "grey31"
[293] "grey32" "grey33"
[295] "grey34" "grey35"
[297] "grey36" "grey37"
[299] "grey38" "grey39"
[301] "grey40" "grey41"
[303] "grey42" "grey43"
[305] "grey44" "grey45"
[307] "grey46" "grey47"
[309] "grey48" "grey49"
[311] "grey50" "grey51"
[313] "grey52" "grey53"
[315] "grey54" "grey55"
[317] "grey56" "grey57"
[319] "grey58" "grey59"
[321] "grey60" "grey61"
[323] "grey62" "grey63"
[325] "grey64" "grey65"
[327] "grey66" "grey67"
[329] "grey68" "grey69"
[331] "grey70" "grey71"
[333] "grey72" "grey73"
[335] "grey74" "grey75"
[337] "grey76" "grey77"
[339] "grey78" "grey79"
[341] "grey80" "grey81"
[343] "grey82" "grey83"
[345] "grey84" "grey85"
[347] "grey86" "grey87"
[349] "grey88" "grey89"
[351] "grey90" "grey91"
[353] "grey92" "grey93"
[355] "grey94" "grey95"
[357] "grey96" "grey97"
[359] "grey98" "grey99"
[361] "grey100" "honeydew"
[363] "honeydew1" "honeydew2"
[365] "honeydew3" "honeydew4"
[367] "hotpink" "hotpink1"
[369] "hotpink2" "hotpink3"
[371] "hotpink4" "indianred"
[373] "indianred1" "indianred2"
[375] "indianred3" "indianred4"
[377] "ivory" "ivory1"
[379] "ivory2" "ivory3"
[381] "ivory4" "khaki"
[383] "khaki1" "khaki2"
[385] "khaki3" "khaki4"
[387] "lavender" "lavenderblush"
[389] "lavenderblush1" "lavenderblush2"
[391] "lavenderblush3" "lavenderblush4"
[393] "lawngreen" "lemonchiffon"
[395] "lemonchiffon1" "lemonchiffon2"
[397] "lemonchiffon3" "lemonchiffon4"
[399] "lightblue" "lightblue1"
[401] "lightblue2" "lightblue3"
[403] "lightblue4" "lightcoral"
[405] "lightcyan" "lightcyan1"
[407] "lightcyan2" "lightcyan3"
[409] "lightcyan4" "lightgoldenrod"
[411] "lightgoldenrod1" "lightgoldenrod2"
[413] "lightgoldenrod3" "lightgoldenrod4"
[415] "lightgoldenrodyellow" "lightgray"
[417] "lightgreen" "lightgrey"
[419] "lightpink" "lightpink1"
[421] "lightpink2" "lightpink3"
[423] "lightpink4" "lightsalmon"
[425] "lightsalmon1" "lightsalmon2"
[427] "lightsalmon3" "lightsalmon4"
[429] "lightseagreen" "lightskyblue"
[431] "lightskyblue1" "lightskyblue2"
[433] "lightskyblue3" "lightskyblue4"
[435] "lightslateblue" "lightslategray"
[437] "lightslategrey" "lightsteelblue"
[439] "lightsteelblue1" "lightsteelblue2"
[441] "lightsteelblue3" "lightsteelblue4"
[443] "lightyellow" "lightyellow1"
[445] "lightyellow2" "lightyellow3"
[447] "lightyellow4" "limegreen"
[449] "linen" "magenta"
[451] "magenta1" "magenta2"
[453] "magenta3" "magenta4"
[455] "maroon" "maroon1"
[457] "maroon2" "maroon3"
[459] "maroon4" "mediumaquamarine"
[461] "mediumblue" "mediumorchid"
[463] "mediumorchid1" "mediumorchid2"
[465] "mediumorchid3" "mediumorchid4"
[467] "mediumpurple" "mediumpurple1"
[469] "mediumpurple2" "mediumpurple3"
[471] "mediumpurple4" "mediumseagreen"
[473] "mediumslateblue" "mediumspringgreen"
[475] "mediumturquoise" "mediumvioletred"
[477] "midnightblue" "mintcream"
[479] "mistyrose" "mistyrose1"
[481] "mistyrose2" "mistyrose3"
[483] "mistyrose4" "moccasin"
[485] "navajowhite" "navajowhite1"
[487] "navajowhite2" "navajowhite3"
[489] "navajowhite4" "navy"
[491] "navyblue" "oldlace"
[493] "olivedrab" "olivedrab1"
[495] "olivedrab2" "olivedrab3"
[497] "olivedrab4" "orange"
[499] "orange1" "orange2"
[501] "orange3" "orange4"
[503] "orangered" "orangered1"
[505] "orangered2" "orangered3"
[507] "orangered4" "orchid"
[509] "orchid1" "orchid2"
[511] "orchid3" "orchid4"
[513] "palegoldenrod" "palegreen"
[515] "palegreen1" "palegreen2"
[517] "palegreen3" "palegreen4"
[519] "paleturquoise" "paleturquoise1"
[521] "paleturquoise2" "paleturquoise3"
[523] "paleturquoise4" "palevioletred"
[525] "palevioletred1" "palevioletred2"
[527] "palevioletred3" "palevioletred4"
[529] "papayawhip" "peachpuff"
[531] "peachpuff1" "peachpuff2"
[533] "peachpuff3" "peachpuff4"
[535] "peru" "pink"
[537] "pink1" "pink2"
[539] "pink3" "pink4"
[541] "plum" "plum1"
[543] "plum2" "plum3"
[545] "plum4" "powderblue"
[547] "purple" "purple1"
[549] "purple2" "purple3"
[551] "purple4" "red"
[553] "red1" "red2"
[555] "red3" "red4"
[557] "rosybrown" "rosybrown1"
[559] "rosybrown2" "rosybrown3"
[561] "rosybrown4" "royalblue"
[563] "royalblue1" "royalblue2"
[565] "royalblue3" "royalblue4"
[567] "saddlebrown" "salmon"
[569] "salmon1" "salmon2"
[571] "salmon3" "salmon4"
[573] "sandybrown" "seagreen"
[575] "seagreen1" "seagreen2"
[577] "seagreen3" "seagreen4"
[579] "seashell" "seashell1"
[581] "seashell2" "seashell3"
[583] "seashell4" "sienna"
[585] "sienna1" "sienna2"
[587] "sienna3" "sienna4"
[589] "skyblue" "skyblue1"
[591] "skyblue2" "skyblue3"
[593] "skyblue4" "slateblue"
[595] "slateblue1" "slateblue2"
[597] "slateblue3" "slateblue4"
[599] "slategray" "slategray1"
[601] "slategray2" "slategray3"
[603] "slategray4" "slategrey"
[605] "snow" "snow1"
[607] "snow2" "snow3"
[609] "snow4" "springgreen"
[611] "springgreen1" "springgreen2"
[613] "springgreen3" "springgreen4"
[615] "steelblue" "steelblue1"
[617] "steelblue2" "steelblue3"
[619] "steelblue4" "tan"
[621] "tan1" "tan2"
[623] "tan3" "tan4"
[625] "thistle" "thistle1"
[627] "thistle2" "thistle3"
[629] "thistle4" "tomato"
[631] "tomato1" "tomato2"
[633] "tomato3" "tomato4"
[635] "turquoise" "turquoise1"
[637] "turquoise2" "turquoise3"
[639] "turquoise4" "violet"
[641] "violetred" "violetred1"
[643] "violetred2" "violetred3"
[645] "violetred4" "wheat"
[647] "wheat1" "wheat2"
[649] "wheat3" "wheat4"
[651] "whitesmoke" "yellow"
[653] "yellow1" "yellow2"
[655] "yellow3" "yellow4"
[657] "yellowgreen"
> plot(xkoord,ykoord,col=3)
> plot(1:12,1:12,col=1:12)
> plot(xkoord,ykoord,col=halmaz)
> plot(xkoord,ykoord,pch="+")
> plot(xkoord,ykoord,pch=4)
> plot(1:12,1:12,pch=1:12)
> plot(xkoord,ykoord,pch=halmaz)
Error in plot.xy(xy, type, ...) : invalid plotting symbol
> plot(xkoord,ykoord,pch=halmaz+2)
Warning message:
In Ops.factor(halmaz, 2) : â+â not meaningful for factors
> plot(xkoord,ykoord,pch=as.numeric(halmaz))
> plot(xkoord,ykoord,pch=as.numeric(halmaz),col=halmaz)
> pontok
xkoord ykoord halmaz tav
1 0.1829699 0.3702491 2 0.4129920
2 0.3649382 -0.7408059 1 0.8258167
3 -0.2073121 -0.6979016 2 0.7280419
4 -1.7441663 -0.4389299 2 1.7985482
5 1.3119190 1.7016581 1 2.1486674
6 0.9769963 1.6276354 1 1.8983463
7 0.6187861 0.6406041 2 0.8906569
8 0.2507825 -1.3344828 2 1.3578425
9 1.6436978 -0.9704997 2 1.9088248
10 -0.8417565 -0.3048665 2 0.8952640
> pontok[12,] <- list(rnorm(1),rnorm(1),2)
> pontok
xkoord ykoord halmaz tav
1 0.1829699 0.3702491 2 0.4129920
2 0.3649382 -0.7408059 1 0.8258167
3 -0.2073121 -0.6979016 2 0.7280419
4 -1.7441663 -0.4389299 2 1.7985482
5 1.3119190 1.7016581 1 2.1486674
6 0.9769963 1.6276354 1 1.8983463
7 0.6187861 0.6406041 2 0.8906569
8 0.2507825 -1.3344828 2 1.3578425
9 1.6436978 -0.9704997 2 1.9088248
10 -0.8417565 -0.3048665 2 0.8952640
11 NA NA <NA> NA
12 0.1595688 1.8862897 2 0.1595688
> pontok[14,] <- 1
> pontok
xkoord ykoord halmaz tav
1 0.1829699 0.3702491 2 0.4129920
2 0.3649382 -0.7408059 1 0.8258167
3 -0.2073121 -0.6979016 2 0.7280419
4 -1.7441663 -0.4389299 2 1.7985482
5 1.3119190 1.7016581 1 2.1486674
6 0.9769963 1.6276354 1 1.8983463
7 0.6187861 0.6406041 2 0.8906569
8 0.2507825 -1.3344828 2 1.3578425
9 1.6436978 -0.9704997 2 1.9088248
10 -0.8417565 -0.3048665 2 0.8952640
11 NA NA <NA> NA
12 0.1595688 1.8862897 2 0.1595688
13 NA NA <NA> NA
14 1.0000000 1.0000000 1 1.0000000
> pontok[6] <- pontok$xkoord
Error in `[<-.data.frame`(`*tmp*`, 6, value = c(0.182969913021711, 0.364938174325596, :
new columns would leave holes after existing columns
> x <- 3
> y <- 4
> x+y
[1] 7
> save.image("C:\\Users\\aa002221\\Documents\\R\\elso\\.RData")
>