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## extract請用 select() 從資料 movies中 (ggplot2movies), 選出欄位名稱從 title 到 votes, 以及 Action 到 Short的資料
library(pacman)
p_load(ggplot2movies)
head(movies)## # A tibble: 6 x 24
## title year length budget rating votes r1 r2 r3 r4 r5 r6
## <chr> <int> <int> <int> <dbl> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 $ 1971 121 NA 6.4 348 4.5 4.5 4.5 4.5 14.5 24.5
## 2 $100… 1939 71 NA 6 20 0 14.5 4.5 24.5 14.5 14.5
## 3 $21 … 1941 7 NA 8.2 5 0 0 0 0 0 24.5
## 4 $40,… 1996 70 NA 8.2 6 14.5 0 0 0 0 0
## 5 $50,… 1975 71 NA 3.4 17 24.5 4.5 0 14.5 14.5 4.5
## 6 $pent 2000 91 NA 4.3 45 4.5 4.5 4.5 14.5 14.5 14.5
## # … with 12 more variables: r7 <dbl>, r8 <dbl>, r9 <dbl>, r10 <dbl>,
## # mpaa <chr>, Action <int>, Animation <int>, Comedy <int>, Drama <int>,
## # Documentary <int>, Romance <int>, Short <int>str(movies)## Classes 'tbl_df', 'tbl' and 'data.frame': 58788 obs. of 24 variables:
## $ title : chr "$" "$1000 a Touchdown" "$21 a Day Once a Month" "$40,000" ...
## $ year : int 1971 1939 1941 1996 1975 2000 2002 2002 1987 1917 ...
## $ length : int 121 71 7 70 71 91 93 25 97 61 ...
## $ budget : int NA NA NA NA NA NA NA NA NA NA ...
## $ rating : num 6.4 6 8.2 8.2 3.4 4.3 5.3 6.7 6.6 6 ...
## $ votes : int 348 20 5 6 17 45 200 24 18 51 ...
## $ r1 : num 4.5 0 0 14.5 24.5 4.5 4.5 4.5 4.5 4.5 ...
## $ r2 : num 4.5 14.5 0 0 4.5 4.5 0 4.5 4.5 0 ...
## $ r3 : num 4.5 4.5 0 0 0 4.5 4.5 4.5 4.5 4.5 ...
## $ r4 : num 4.5 24.5 0 0 14.5 14.5 4.5 4.5 0 4.5 ...
## $ r5 : num 14.5 14.5 0 0 14.5 14.5 24.5 4.5 0 4.5 ...
## $ r6 : num 24.5 14.5 24.5 0 4.5 14.5 24.5 14.5 0 44.5 ...
## $ r7 : num 24.5 14.5 0 0 0 4.5 14.5 14.5 34.5 14.5 ...
## $ r8 : num 14.5 4.5 44.5 0 0 4.5 4.5 14.5 14.5 4.5 ...
## $ r9 : num 4.5 4.5 24.5 34.5 0 14.5 4.5 4.5 4.5 4.5 ...
## $ r10 : num 4.5 14.5 24.5 45.5 24.5 14.5 14.5 14.5 24.5 4.5 ...
## $ mpaa : chr "" "" "" "" ...
## $ Action : int 0 0 0 0 0 0 1 0 0 0 ...
## $ Animation : int 0 0 1 0 0 0 0 0 0 0 ...
## $ Comedy : int 1 1 0 1 0 0 0 0 0 0 ...
## $ Drama : int 1 0 0 0 0 1 1 0 1 0 ...
## $ Documentary: int 0 0 0 0 0 0 0 1 0 0 ...
## $ Romance : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Short : int 0 0 1 0 0 0 0 1 0 0 ...select(iris,Sepal.Length:Petal.Width)## 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 1.8select(movies,title:votes,Action:Short)## # A tibble: 58,788 x 13
## title year length budget rating votes Action Animation Comedy Drama
## <chr> <int> <int> <int> <dbl> <int> <int> <int> <int> <int>
## 1 $ 1971 121 NA 6.4 348 0 0 1 1
## 2 $100… 1939 71 NA 6 20 0 0 1 0
## 3 $21 … 1941 7 NA 8.2 5 0 1 0 0
## 4 $40,… 1996 70 NA 8.2 6 0 0 1 0
## 5 $50,… 1975 71 NA 3.4 17 0 0 0 0
## 6 $pent 2000 91 NA 4.3 45 0 0 0 1
## 7 $win… 2002 93 NA 5.3 200 1 0 0 1
## 8 '15' 2002 25 NA 6.7 24 0 0 0 0
## 9 '38 1987 97 NA 6.6 18 0 0 0 1
## 10 '49-… 1917 61 NA 6 51 0 0 0 0
## # … with 58,778 more rows, and 3 more variables: Documentary <int>,
## # Romance <int>, Short <int>movies %>% select(starts_with("r"))## # A tibble: 58,788 x 12
## rating r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 Romance
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 6.4 4.5 4.5 4.5 4.5 14.5 24.5 24.5 14.5 4.5 4.5 0
## 2 6 0 14.5 4.5 24.5 14.5 14.5 14.5 4.5 4.5 14.5 0
## 3 8.2 0 0 0 0 0 24.5 0 44.5 24.5 24.5 0
## 4 8.2 14.5 0 0 0 0 0 0 0 34.5 45.5 0
## 5 3.4 24.5 4.5 0 14.5 14.5 4.5 0 0 0 24.5 0
## 6 4.3 4.5 4.5 4.5 14.5 14.5 14.5 4.5 4.5 14.5 14.5 0
## 7 5.3 4.5 0 4.5 4.5 24.5 24.5 14.5 4.5 4.5 14.5 0
## 8 6.7 4.5 4.5 4.5 4.5 4.5 14.5 14.5 14.5 4.5 14.5 0
## 9 6.6 4.5 4.5 4.5 0 0 0 34.5 14.5 4.5 24.5 0
## 10 6 4.5 0 4.5 4.5 4.5 44.5 14.5 4.5 4.5 4.5 0
## # … with 58,778 more rowsmovies %>% select(starts_with("m"))## # A tibble: 58,788 x 1
## mpaa
## <chr>
## 1 ""
## 2 ""
## 3 ""
## 4 ""
## 5 ""
## 6 ""
## 7 "R"
## 8 ""
## 9 ""
## 10 ""
## # … with 58,778 more rows從資料 movies中，找出欄位名稱開頭為 r or m的欄位
movies %>%
select(starts_with("r"),starts_with("m"))## # A tibble: 58,788 x 13
## rating r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 Romance
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
## 1 6.4 4.5 4.5 4.5 4.5 14.5 24.5 24.5 14.5 4.5 4.5 0
## 2 6 0 14.5 4.5 24.5 14.5 14.5 14.5 4.5 4.5 14.5 0
## 3 8.2 0 0 0 0 0 24.5 0 44.5 24.5 24.5 0
## 4 8.2 14.5 0 0 0 0 0 0 0 34.5 45.5 0
## 5 3.4 24.5 4.5 0 14.5 14.5 4.5 0 0 0 24.5 0
## 6 4.3 4.5 4.5 4.5 14.5 14.5 14.5 4.5 4.5 14.5 14.5 0
## 7 5.3 4.5 0 4.5 4.5 24.5 24.5 14.5 4.5 4.5 14.5 0
## 8 6.7 4.5 4.5 4.5 4.5 4.5 14.5 14.5 14.5 4.5 14.5 0
## 9 6.6 4.5 4.5 4.5 0 0 0 34.5 14.5 4.5 24.5 0
## 10 6 4.5 0 4.5 4.5 4.5 44.5 14.5 4.5 4.5 4.5 0
## # … with 58,778 more rows, and 1 more variable: mpaa <chr>請將iris資料中數值欄位，全部改為英吋(即除以2.5)，以及將Species欄位的資料全部轉為英文大寫， 並輸出資料集為irisImperial
iris %>%
mutate(Sepal.Length=Sepal.Length/2.5,
Sepal.Width=Sepal.Width/2.5,
Petal.Length=Petal.Length/2.5,
Petal.Width=Petal.Width/2.5)## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 2.04 1.40 0.56 0.08 setosa
## 2 1.96 1.20 0.56 0.08 setosa
## 3 1.88 1.28 0.52 0.08 setosa
## 4 1.84 1.24 0.60 0.08 setosa
## 5 2.00 1.44 0.56 0.08 setosa
## 6 2.16 1.56 0.68 0.16 setosa
## 7 1.84 1.36 0.56 0.12 setosa
## 8 2.00 1.36 0.60 0.08 setosa
## 9 1.76 1.16 0.56 0.08 setosa
## 10 1.96 1.24 0.60 0.04 setosa
## 11 2.16 1.48 0.60 0.08 setosa
## 12 1.92 1.36 0.64 0.08 setosa
## 13 1.92 1.20 0.56 0.04 setosa
## 14 1.72 1.20 0.44 0.04 setosa
## 15 2.32 1.60 0.48 0.08 setosa
## 16 2.28 1.76 0.60 0.16 setosa
## 17 2.16 1.56 0.52 0.16 setosa
## 18 2.04 1.40 0.56 0.12 setosa
## 19 2.28 1.52 0.68 0.12 setosa
## 20 2.04 1.52 0.60 0.12 setosa
## 21 2.16 1.36 0.68 0.08 setosa
## 22 2.04 1.48 0.60 0.16 setosa
## 23 1.84 1.44 0.40 0.08 setosa
## 24 2.04 1.32 0.68 0.20 setosa
## 25 1.92 1.36 0.76 0.08 setosa
## 26 2.00 1.20 0.64 0.08 setosa
## 27 2.00 1.36 0.64 0.16 setosa
## 28 2.08 1.40 0.60 0.08 setosa
## 29 2.08 1.36 0.56 0.08 setosa
## 30 1.88 1.28 0.64 0.08 setosa
## 31 1.92 1.24 0.64 0.08 setosa
## 32 2.16 1.36 0.60 0.16 setosa
## 33 2.08 1.64 0.60 0.04 setosa
## 34 2.20 1.68 0.56 0.08 setosa
## 35 1.96 1.24 0.60 0.08 setosa
## 36 2.00 1.28 0.48 0.08 setosa
## 37 2.20 1.40 0.52 0.08 setosa
## 38 1.96 1.44 0.56 0.04 setosa
## 39 1.76 1.20 0.52 0.08 setosa
## 40 2.04 1.36 0.60 0.08 setosa
## 41 2.00 1.40 0.52 0.12 setosa
## 42 1.80 0.92 0.52 0.12 setosa
## 43 1.76 1.28 0.52 0.08 setosa
## 44 2.00 1.40 0.64 0.24 setosa
## 45 2.04 1.52 0.76 0.16 setosa
## 46 1.92 1.20 0.56 0.12 setosa
## 47 2.04 1.52 0.64 0.08 setosa
## 48 1.84 1.28 0.56 0.08 setosa
## 49 2.12 1.48 0.60 0.08 setosa
## 50 2.00 1.32 0.56 0.08 setosa
## 51 2.80 1.28 1.88 0.56 versicolor
## 52 2.56 1.28 1.80 0.60 versicolor
## 53 2.76 1.24 1.96 0.60 versicolor
## 54 2.20 0.92 1.60 0.52 versicolor
## 55 2.60 1.12 1.84 0.60 versicolor
## 56 2.28 1.12 1.80 0.52 versicolor
## 57 2.52 1.32 1.88 0.64 versicolor
## 58 1.96 0.96 1.32 0.40 versicolor
## 59 2.64 1.16 1.84 0.52 versicolor
## 60 2.08 1.08 1.56 0.56 versicolor
## 61 2.00 0.80 1.40 0.40 versicolor
## 62 2.36 1.20 1.68 0.60 versicolor
## 63 2.40 0.88 1.60 0.40 versicolor
## 64 2.44 1.16 1.88 0.56 versicolor
## 65 2.24 1.16 1.44 0.52 versicolor
## 66 2.68 1.24 1.76 0.56 versicolor
## 67 2.24 1.20 1.80 0.60 versicolor
## 68 2.32 1.08 1.64 0.40 versicolor
## 69 2.48 0.88 1.80 0.60 versicolor
## 70 2.24 1.00 1.56 0.44 versicolor
## 71 2.36 1.28 1.92 0.72 versicolor
## 72 2.44 1.12 1.60 0.52 versicolor
## 73 2.52 1.00 1.96 0.60 versicolor
## 74 2.44 1.12 1.88 0.48 versicolor
## 75 2.56 1.16 1.72 0.52 versicolor
## 76 2.64 1.20 1.76 0.56 versicolor
## 77 2.72 1.12 1.92 0.56 versicolor
## 78 2.68 1.20 2.00 0.68 versicolor
## 79 2.40 1.16 1.80 0.60 versicolor
## 80 2.28 1.04 1.40 0.40 versicolor
## 81 2.20 0.96 1.52 0.44 versicolor
## 82 2.20 0.96 1.48 0.40 versicolor
## 83 2.32 1.08 1.56 0.48 versicolor
## 84 2.40 1.08 2.04 0.64 versicolor
## 85 2.16 1.20 1.80 0.60 versicolor
## 86 2.40 1.36 1.80 0.64 versicolor
## 87 2.68 1.24 1.88 0.60 versicolor
## 88 2.52 0.92 1.76 0.52 versicolor
## 89 2.24 1.20 1.64 0.52 versicolor
## 90 2.20 1.00 1.60 0.52 versicolor
## 91 2.20 1.04 1.76 0.48 versicolor
## 92 2.44 1.20 1.84 0.56 versicolor
## 93 2.32 1.04 1.60 0.48 versicolor
## 94 2.00 0.92 1.32 0.40 versicolor
## 95 2.24 1.08 1.68 0.52 versicolor
## 96 2.28 1.20 1.68 0.48 versicolor
## 97 2.28 1.16 1.68 0.52 versicolor
## 98 2.48 1.16 1.72 0.52 versicolor
## 99 2.04 1.00 1.20 0.44 versicolor
## 100 2.28 1.12 1.64 0.52 versicolor
## 101 2.52 1.32 2.40 1.00 virginica
## 102 2.32 1.08 2.04 0.76 virginica
## 103 2.84 1.20 2.36 0.84 virginica
## 104 2.52 1.16 2.24 0.72 virginica
## 105 2.60 1.20 2.32 0.88 virginica
## 106 3.04 1.20 2.64 0.84 virginica
## 107 1.96 1.00 1.80 0.68 virginica
## 108 2.92 1.16 2.52 0.72 virginica
## 109 2.68 1.00 2.32 0.72 virginica
## 110 2.88 1.44 2.44 1.00 virginica
## 111 2.60 1.28 2.04 0.80 virginica
## 112 2.56 1.08 2.12 0.76 virginica
## 113 2.72 1.20 2.20 0.84 virginica
## 114 2.28 1.00 2.00 0.80 virginica
## 115 2.32 1.12 2.04 0.96 virginica
## 116 2.56 1.28 2.12 0.92 virginica
## 117 2.60 1.20 2.20 0.72 virginica
## 118 3.08 1.52 2.68 0.88 virginica
## 119 3.08 1.04 2.76 0.92 virginica
## 120 2.40 0.88 2.00 0.60 virginica
## 121 2.76 1.28 2.28 0.92 virginica
## 122 2.24 1.12 1.96 0.80 virginica
## 123 3.08 1.12 2.68 0.80 virginica
## 124 2.52 1.08 1.96 0.72 virginica
## 125 2.68 1.32 2.28 0.84 virginica
## 126 2.88 1.28 2.40 0.72 virginica
## 127 2.48 1.12 1.92 0.72 virginica
## 128 2.44 1.20 1.96 0.72 virginica
## 129 2.56 1.12 2.24 0.84 virginica
## 130 2.88 1.20 2.32 0.64 virginica
## 131 2.96 1.12 2.44 0.76 virginica
## 132 3.16 1.52 2.56 0.80 virginica
## 133 2.56 1.12 2.24 0.88 virginica
## 134 2.52 1.12 2.04 0.60 virginica
## 135 2.44 1.04 2.24 0.56 virginica
## 136 3.08 1.20 2.44 0.92 virginica
## 137 2.52 1.36 2.24 0.96 virginica
## 138 2.56 1.24 2.20 0.72 virginica
## 139 2.40 1.20 1.92 0.72 virginica
## 140 2.76 1.24 2.16 0.84 virginica
## 141 2.68 1.24 2.24 0.96 virginica
## 142 2.76 1.24 2.04 0.92 virginica
## 143 2.32 1.08 2.04 0.76 virginica
## 144 2.72 1.28 2.36 0.92 virginica
## 145 2.68 1.32 2.28 1.00 virginica
## 146 2.68 1.20 2.08 0.92 virginica
## 147 2.52 1.00 2.00 0.76 virginica
## 148 2.60 1.20 2.08 0.80 virginica
## 149 2.48 1.36 2.16 0.92 virginica
## 150 2.36 1.20 2.04 0.72 virginicairis %>%
transmute(Sepal.Width=floor(Sepal.Width),
Species = case_when(
Species == "setosa" ~toupper(Species),
Species == "versicolor" ~toupper(Species),
Species == "virginica" ~toupper(Species),
TRUE ~ as.character(Species)
))## Sepal.Width Species
## 1 3 SETOSA
## 2 3 SETOSA
## 3 3 SETOSA
## 4 3 SETOSA
## 5 3 SETOSA
## 6 3 SETOSA
## 7 3 SETOSA
## 8 3 SETOSA
## 9 2 SETOSA
## 10 3 SETOSA
## 11 3 SETOSA
## 12 3 SETOSA
## 13 3 SETOSA
## 14 3 SETOSA
## 15 4 SETOSA
## 16 4 SETOSA
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## 18 3 SETOSA
## 19 3 SETOSA
## 20 3 SETOSA
## 21 3 SETOSA
## 22 3 SETOSA
## 23 3 SETOSA
## 24 3 SETOSA
## 25 3 SETOSA
## 26 3 SETOSA
## 27 3 SETOSA
## 28 3 SETOSA
## 29 3 SETOSA
## 30 3 SETOSA
## 31 3 SETOSA
## 32 3 SETOSA
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## 37 3 SETOSA
## 38 3 SETOSA
## 39 3 SETOSA
## 40 3 SETOSA
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## 45 3 SETOSA
## 46 3 SETOSA
## 47 3 SETOSA
## 48 3 SETOSA
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## 51 3 VERSICOLOR
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## 150 3 VIRGINICA