install.packages("tidyverse")
library(tidyverse)
## -- Attaching packages --------------------------------------- tidyverse 1.3.0 --
## v ggplot2 3.3.3 v purrr 0.3.4
## v tibble 3.0.5 v dplyr 1.0.3
## v tidyr 1.1.2 v stringr 1.4.0
## v readr 1.4.0 v forcats 0.5.0
## -- Conflicts ------------------------------------------ tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
??tidyverse
tictoc::tic()
cars1<-utils::read.csv("https://github.com/tidyverse/readr/raw/master/inst/extdata/mtcars.csv")
class(cars1)
## [1] "data.frame"
tictoc::toc()
## 1.22 sec elapsed
tictoc::tic()
cars2<-readr::read_csv("https://github.com/tidyverse/readr/raw/master/inst/extdata/mtcars.csv")
##
## -- Column specification --------------------------------------------------------
## cols(
## mpg = col_double(),
## cyl = col_double(),
## disp = col_double(),
## hp = col_double(),
## drat = col_double(),
## wt = col_double(),
## qsec = col_double(),
## vs = col_double(),
## am = col_double(),
## gear = col_double(),
## carb = col_double()
## )
class(cars2)
## [1] "spec_tbl_df" "tbl_df" "tbl" "data.frame"
tictoc::toc()
## 1.52 sec elapsed
cars2
## # A tibble: 32 x 11
## mpg cyl disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4
## 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4
## 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1
## 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1
## 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2
## 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1
## 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4
## 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2
## 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2
## 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4
## # ... with 22 more rows
# Contoh mengimpor data yang berukuran besar
system.time(accident<-read_csv("https://vincentarelbundock.github.io/Rdatasets/csv/DAAG/nassCDS.csv"))
## Warning: Missing column names filled in: 'X1' [1]
##
## -- Column specification --------------------------------------------------------
## cols(
## X1 = col_double(),
## dvcat = col_character(),
## weight = col_double(),
## dead = col_character(),
## airbag = col_character(),
## seatbelt = col_character(),
## frontal = col_double(),
## sex = col_character(),
## ageOFocc = col_double(),
## yearacc = col_double(),
## yearVeh = col_double(),
## abcat = col_character(),
## occRole = col_character(),
## deploy = col_double(),
## injSeverity = col_double(),
## caseid = col_character()
## )
## user system elapsed
## 0.15 0.00 0.52
system.time(accident<-read.csv("https://vincentarelbundock.github.io/Rdatasets/csv/DAAG/nassCDS.csv"))
## user system elapsed
## 2.64 0.03 2.94
library(datasets)
data(iris)
#iris<-tibble::as_tibble(iris)
mean(iris$Sepal.Length)
## [1] 5.843333
iris$Sepal.Length %>% mean()
## [1] 5.843333
x <- c(0.109, 0.359, 0.63, 0.996, 0.515, 0.142, 0.017, 0.829, 0.907)
round(exp(diff(log(x))), 1)
## [1] 3.3 1.8 1.6 0.5 0.3 0.1 48.8 1.1
x %>% log() %>%
diff() %>%
exp() %>%
round(1)
## [1] 3.3 1.8 1.6 0.5 0.3 0.1 48.8 1.1
#menghitung rata-rata Sepal length setiap species
iris %>% group_by(Species) %>% summarise(mean=mean(Sepal.Length), .groups='drop')
## # A tibble: 3 x 2
## Species mean
## * <fct> <dbl>
## 1 setosa 5.01
## 2 versicolor 5.94
## 3 virginica 6.59
#mengurutkan berdasarkan peubah Sepal.Length dari nilai terkecil
iris %>% arrange(Sepal.Length)
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 4.3 3.0 1.1 0.1 setosa
## 2 4.4 2.9 1.4 0.2 setosa
## 3 4.4 3.0 1.3 0.2 setosa
## 4 4.4 3.2 1.3 0.2 setosa
## 5 4.5 2.3 1.3 0.3 setosa
## 6 4.6 3.1 1.5 0.2 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 4.6 3.6 1.0 0.2 setosa
## 9 4.6 3.2 1.4 0.2 setosa
## 10 4.7 3.2 1.3 0.2 setosa
## 11 4.7 3.2 1.6 0.2 setosa
## 12 4.8 3.4 1.6 0.2 setosa
## 13 4.8 3.0 1.4 0.1 setosa
## 14 4.8 3.4 1.9 0.2 setosa
## 15 4.8 3.1 1.6 0.2 setosa
## 16 4.8 3.0 1.4 0.3 setosa
## 17 4.9 3.0 1.4 0.2 setosa
## 18 4.9 3.1 1.5 0.1 setosa
## 19 4.9 3.1 1.5 0.2 setosa
## 20 4.9 3.6 1.4 0.1 setosa
## 21 4.9 2.4 3.3 1.0 versicolor
## 22 4.9 2.5 4.5 1.7 virginica
## 23 5.0 3.6 1.4 0.2 setosa
## 24 5.0 3.4 1.5 0.2 setosa
## 25 5.0 3.0 1.6 0.2 setosa
## 26 5.0 3.4 1.6 0.4 setosa
## 27 5.0 3.2 1.2 0.2 setosa
## 28 5.0 3.5 1.3 0.3 setosa
## 29 5.0 3.5 1.6 0.6 setosa
## 30 5.0 3.3 1.4 0.2 setosa
## 31 5.0 2.0 3.5 1.0 versicolor
## 32 5.0 2.3 3.3 1.0 versicolor
## 33 5.1 3.5 1.4 0.2 setosa
## 34 5.1 3.5 1.4 0.3 setosa
## 35 5.1 3.8 1.5 0.3 setosa
## 36 5.1 3.7 1.5 0.4 setosa
## 37 5.1 3.3 1.7 0.5 setosa
## 38 5.1 3.4 1.5 0.2 setosa
## 39 5.1 3.8 1.9 0.4 setosa
## 40 5.1 3.8 1.6 0.2 setosa
## 41 5.1 2.5 3.0 1.1 versicolor
## 42 5.2 3.5 1.5 0.2 setosa
## 43 5.2 3.4 1.4 0.2 setosa
## 44 5.2 4.1 1.5 0.1 setosa
## 45 5.2 2.7 3.9 1.4 versicolor
## 46 5.3 3.7 1.5 0.2 setosa
## 47 5.4 3.9 1.7 0.4 setosa
## 48 5.4 3.7 1.5 0.2 setosa
## 49 5.4 3.9 1.3 0.4 setosa
## 50 5.4 3.4 1.7 0.2 setosa
## 51 5.4 3.4 1.5 0.4 setosa
## 52 5.4 3.0 4.5 1.5 versicolor
## 53 5.5 4.2 1.4 0.2 setosa
## 54 5.5 3.5 1.3 0.2 setosa
## 55 5.5 2.3 4.0 1.3 versicolor
## 56 5.5 2.4 3.8 1.1 versicolor
## 57 5.5 2.4 3.7 1.0 versicolor
## 58 5.5 2.5 4.0 1.3 versicolor
## 59 5.5 2.6 4.4 1.2 versicolor
## 60 5.6 2.9 3.6 1.3 versicolor
## 61 5.6 3.0 4.5 1.5 versicolor
## 62 5.6 2.5 3.9 1.1 versicolor
## 63 5.6 3.0 4.1 1.3 versicolor
## 64 5.6 2.7 4.2 1.3 versicolor
## 65 5.6 2.8 4.9 2.0 virginica
## 66 5.7 4.4 1.5 0.4 setosa
## 67 5.7 3.8 1.7 0.3 setosa
## 68 5.7 2.8 4.5 1.3 versicolor
## 69 5.7 2.6 3.5 1.0 versicolor
## 70 5.7 3.0 4.2 1.2 versicolor
## 71 5.7 2.9 4.2 1.3 versicolor
## 72 5.7 2.8 4.1 1.3 versicolor
## 73 5.7 2.5 5.0 2.0 virginica
## 74 5.8 4.0 1.2 0.2 setosa
## 75 5.8 2.7 4.1 1.0 versicolor
## 76 5.8 2.7 3.9 1.2 versicolor
## 77 5.8 2.6 4.0 1.2 versicolor
## 78 5.8 2.7 5.1 1.9 virginica
## 79 5.8 2.8 5.1 2.4 virginica
## 80 5.8 2.7 5.1 1.9 virginica
## 81 5.9 3.0 4.2 1.5 versicolor
## 82 5.9 3.2 4.8 1.8 versicolor
## 83 5.9 3.0 5.1 1.8 virginica
## 84 6.0 2.2 4.0 1.0 versicolor
## 85 6.0 2.9 4.5 1.5 versicolor
## 86 6.0 2.7 5.1 1.6 versicolor
## 87 6.0 3.4 4.5 1.6 versicolor
## 88 6.0 2.2 5.0 1.5 virginica
## 89 6.0 3.0 4.8 1.8 virginica
## 90 6.1 2.9 4.7 1.4 versicolor
## 91 6.1 2.8 4.0 1.3 versicolor
## 92 6.1 2.8 4.7 1.2 versicolor
## 93 6.1 3.0 4.6 1.4 versicolor
## 94 6.1 3.0 4.9 1.8 virginica
## 95 6.1 2.6 5.6 1.4 virginica
## 96 6.2 2.2 4.5 1.5 versicolor
## 97 6.2 2.9 4.3 1.3 versicolor
## 98 6.2 2.8 4.8 1.8 virginica
## 99 6.2 3.4 5.4 2.3 virginica
## 100 6.3 3.3 4.7 1.6 versicolor
## 101 6.3 2.5 4.9 1.5 versicolor
## 102 6.3 2.3 4.4 1.3 versicolor
## 103 6.3 3.3 6.0 2.5 virginica
## 104 6.3 2.9 5.6 1.8 virginica
## 105 6.3 2.7 4.9 1.8 virginica
## 106 6.3 2.8 5.1 1.5 virginica
## 107 6.3 3.4 5.6 2.4 virginica
## 108 6.3 2.5 5.0 1.9 virginica
## 109 6.4 3.2 4.5 1.5 versicolor
## 110 6.4 2.9 4.3 1.3 versicolor
## 111 6.4 2.7 5.3 1.9 virginica
## 112 6.4 3.2 5.3 2.3 virginica
## 113 6.4 2.8 5.6 2.1 virginica
## 114 6.4 2.8 5.6 2.2 virginica
## 115 6.4 3.1 5.5 1.8 virginica
## 116 6.5 2.8 4.6 1.5 versicolor
## 117 6.5 3.0 5.8 2.2 virginica
## 118 6.5 3.2 5.1 2.0 virginica
## 119 6.5 3.0 5.5 1.8 virginica
## 120 6.5 3.0 5.2 2.0 virginica
## 121 6.6 2.9 4.6 1.3 versicolor
## 122 6.6 3.0 4.4 1.4 versicolor
## 123 6.7 3.1 4.4 1.4 versicolor
## 124 6.7 3.0 5.0 1.7 versicolor
## 125 6.7 3.1 4.7 1.5 versicolor
## 126 6.7 2.5 5.8 1.8 virginica
## 127 6.7 3.3 5.7 2.1 virginica
## 128 6.7 3.1 5.6 2.4 virginica
## 129 6.7 3.3 5.7 2.5 virginica
## 130 6.7 3.0 5.2 2.3 virginica
## 131 6.8 2.8 4.8 1.4 versicolor
## 132 6.8 3.0 5.5 2.1 virginica
## 133 6.8 3.2 5.9 2.3 virginica
## 134 6.9 3.1 4.9 1.5 versicolor
## 135 6.9 3.2 5.7 2.3 virginica
## 136 6.9 3.1 5.4 2.1 virginica
## 137 6.9 3.1 5.1 2.3 virginica
## 138 7.0 3.2 4.7 1.4 versicolor
## 139 7.1 3.0 5.9 2.1 virginica
## 140 7.2 3.6 6.1 2.5 virginica
## 141 7.2 3.2 6.0 1.8 virginica
## 142 7.2 3.0 5.8 1.6 virginica
## 143 7.3 2.9 6.3 1.8 virginica
## 144 7.4 2.8 6.1 1.9 virginica
## 145 7.6 3.0 6.6 2.1 virginica
## 146 7.7 3.8 6.7 2.2 virginica
## 147 7.7 2.6 6.9 2.3 virginica
## 148 7.7 2.8 6.7 2.0 virginica
## 149 7.7 3.0 6.1 2.3 virginica
## 150 7.9 3.8 6.4 2.0 virginica
#mengurutkan berdasarkan peubah Sepal.Length dari nilai terbesar
iris %>% arrange(desc(Sepal.Length))
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 7.9 3.8 6.4 2.0 virginica
## 2 7.7 3.8 6.7 2.2 virginica
## 3 7.7 2.6 6.9 2.3 virginica
## 4 7.7 2.8 6.7 2.0 virginica
## 5 7.7 3.0 6.1 2.3 virginica
## 6 7.6 3.0 6.6 2.1 virginica
## 7 7.4 2.8 6.1 1.9 virginica
## 8 7.3 2.9 6.3 1.8 virginica
## 9 7.2 3.6 6.1 2.5 virginica
## 10 7.2 3.2 6.0 1.8 virginica
## 11 7.2 3.0 5.8 1.6 virginica
## 12 7.1 3.0 5.9 2.1 virginica
## 13 7.0 3.2 4.7 1.4 versicolor
## 14 6.9 3.1 4.9 1.5 versicolor
## 15 6.9 3.2 5.7 2.3 virginica
## 16 6.9 3.1 5.4 2.1 virginica
## 17 6.9 3.1 5.1 2.3 virginica
## 18 6.8 2.8 4.8 1.4 versicolor
## 19 6.8 3.0 5.5 2.1 virginica
## 20 6.8 3.2 5.9 2.3 virginica
## 21 6.7 3.1 4.4 1.4 versicolor
## 22 6.7 3.0 5.0 1.7 versicolor
## 23 6.7 3.1 4.7 1.5 versicolor
## 24 6.7 2.5 5.8 1.8 virginica
## 25 6.7 3.3 5.7 2.1 virginica
## 26 6.7 3.1 5.6 2.4 virginica
## 27 6.7 3.3 5.7 2.5 virginica
## 28 6.7 3.0 5.2 2.3 virginica
## 29 6.6 2.9 4.6 1.3 versicolor
## 30 6.6 3.0 4.4 1.4 versicolor
## 31 6.5 2.8 4.6 1.5 versicolor
## 32 6.5 3.0 5.8 2.2 virginica
## 33 6.5 3.2 5.1 2.0 virginica
## 34 6.5 3.0 5.5 1.8 virginica
## 35 6.5 3.0 5.2 2.0 virginica
## 36 6.4 3.2 4.5 1.5 versicolor
## 37 6.4 2.9 4.3 1.3 versicolor
## 38 6.4 2.7 5.3 1.9 virginica
## 39 6.4 3.2 5.3 2.3 virginica
## 40 6.4 2.8 5.6 2.1 virginica
## 41 6.4 2.8 5.6 2.2 virginica
## 42 6.4 3.1 5.5 1.8 virginica
## 43 6.3 3.3 4.7 1.6 versicolor
## 44 6.3 2.5 4.9 1.5 versicolor
## 45 6.3 2.3 4.4 1.3 versicolor
## 46 6.3 3.3 6.0 2.5 virginica
## 47 6.3 2.9 5.6 1.8 virginica
## 48 6.3 2.7 4.9 1.8 virginica
## 49 6.3 2.8 5.1 1.5 virginica
## 50 6.3 3.4 5.6 2.4 virginica
## 51 6.3 2.5 5.0 1.9 virginica
## 52 6.2 2.2 4.5 1.5 versicolor
## 53 6.2 2.9 4.3 1.3 versicolor
## 54 6.2 2.8 4.8 1.8 virginica
## 55 6.2 3.4 5.4 2.3 virginica
## 56 6.1 2.9 4.7 1.4 versicolor
## 57 6.1 2.8 4.0 1.3 versicolor
## 58 6.1 2.8 4.7 1.2 versicolor
## 59 6.1 3.0 4.6 1.4 versicolor
## 60 6.1 3.0 4.9 1.8 virginica
## 61 6.1 2.6 5.6 1.4 virginica
## 62 6.0 2.2 4.0 1.0 versicolor
## 63 6.0 2.9 4.5 1.5 versicolor
## 64 6.0 2.7 5.1 1.6 versicolor
## 65 6.0 3.4 4.5 1.6 versicolor
## 66 6.0 2.2 5.0 1.5 virginica
## 67 6.0 3.0 4.8 1.8 virginica
## 68 5.9 3.0 4.2 1.5 versicolor
## 69 5.9 3.2 4.8 1.8 versicolor
## 70 5.9 3.0 5.1 1.8 virginica
## 71 5.8 4.0 1.2 0.2 setosa
## 72 5.8 2.7 4.1 1.0 versicolor
## 73 5.8 2.7 3.9 1.2 versicolor
## 74 5.8 2.6 4.0 1.2 versicolor
## 75 5.8 2.7 5.1 1.9 virginica
## 76 5.8 2.8 5.1 2.4 virginica
## 77 5.8 2.7 5.1 1.9 virginica
## 78 5.7 4.4 1.5 0.4 setosa
## 79 5.7 3.8 1.7 0.3 setosa
## 80 5.7 2.8 4.5 1.3 versicolor
## 81 5.7 2.6 3.5 1.0 versicolor
## 82 5.7 3.0 4.2 1.2 versicolor
## 83 5.7 2.9 4.2 1.3 versicolor
## 84 5.7 2.8 4.1 1.3 versicolor
## 85 5.7 2.5 5.0 2.0 virginica
## 86 5.6 2.9 3.6 1.3 versicolor
## 87 5.6 3.0 4.5 1.5 versicolor
## 88 5.6 2.5 3.9 1.1 versicolor
## 89 5.6 3.0 4.1 1.3 versicolor
## 90 5.6 2.7 4.2 1.3 versicolor
## 91 5.6 2.8 4.9 2.0 virginica
## 92 5.5 4.2 1.4 0.2 setosa
## 93 5.5 3.5 1.3 0.2 setosa
## 94 5.5 2.3 4.0 1.3 versicolor
## 95 5.5 2.4 3.8 1.1 versicolor
## 96 5.5 2.4 3.7 1.0 versicolor
## 97 5.5 2.5 4.0 1.3 versicolor
## 98 5.5 2.6 4.4 1.2 versicolor
## 99 5.4 3.9 1.7 0.4 setosa
## 100 5.4 3.7 1.5 0.2 setosa
## 101 5.4 3.9 1.3 0.4 setosa
## 102 5.4 3.4 1.7 0.2 setosa
## 103 5.4 3.4 1.5 0.4 setosa
## 104 5.4 3.0 4.5 1.5 versicolor
## 105 5.3 3.7 1.5 0.2 setosa
## 106 5.2 3.5 1.5 0.2 setosa
## 107 5.2 3.4 1.4 0.2 setosa
## 108 5.2 4.1 1.5 0.1 setosa
## 109 5.2 2.7 3.9 1.4 versicolor
## 110 5.1 3.5 1.4 0.2 setosa
## 111 5.1 3.5 1.4 0.3 setosa
## 112 5.1 3.8 1.5 0.3 setosa
## 113 5.1 3.7 1.5 0.4 setosa
## 114 5.1 3.3 1.7 0.5 setosa
## 115 5.1 3.4 1.5 0.2 setosa
## 116 5.1 3.8 1.9 0.4 setosa
## 117 5.1 3.8 1.6 0.2 setosa
## 118 5.1 2.5 3.0 1.1 versicolor
## 119 5.0 3.6 1.4 0.2 setosa
## 120 5.0 3.4 1.5 0.2 setosa
## 121 5.0 3.0 1.6 0.2 setosa
## 122 5.0 3.4 1.6 0.4 setosa
## 123 5.0 3.2 1.2 0.2 setosa
## 124 5.0 3.5 1.3 0.3 setosa
## 125 5.0 3.5 1.6 0.6 setosa
## 126 5.0 3.3 1.4 0.2 setosa
## 127 5.0 2.0 3.5 1.0 versicolor
## 128 5.0 2.3 3.3 1.0 versicolor
## 129 4.9 3.0 1.4 0.2 setosa
## 130 4.9 3.1 1.5 0.1 setosa
## 131 4.9 3.1 1.5 0.2 setosa
## 132 4.9 3.6 1.4 0.1 setosa
## 133 4.9 2.4 3.3 1.0 versicolor
## 134 4.9 2.5 4.5 1.7 virginica
## 135 4.8 3.4 1.6 0.2 setosa
## 136 4.8 3.0 1.4 0.1 setosa
## 137 4.8 3.4 1.9 0.2 setosa
## 138 4.8 3.1 1.6 0.2 setosa
## 139 4.8 3.0 1.4 0.3 setosa
## 140 4.7 3.2 1.3 0.2 setosa
## 141 4.7 3.2 1.6 0.2 setosa
## 142 4.6 3.1 1.5 0.2 setosa
## 143 4.6 3.4 1.4 0.3 setosa
## 144 4.6 3.6 1.0 0.2 setosa
## 145 4.6 3.2 1.4 0.2 setosa
## 146 4.5 2.3 1.3 0.3 setosa
## 147 4.4 2.9 1.4 0.2 setosa
## 148 4.4 3.0 1.3 0.2 setosa
## 149 4.4 3.2 1.3 0.2 setosa
## 150 4.3 3.0 1.1 0.1 setosa
iris %>% filter(Species=="setosa")
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 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
iris %>% select(Species,Petal.Width,Petal.Length)
## Species Petal.Width Petal.Length
## 1 setosa 0.2 1.4
## 2 setosa 0.2 1.4
## 3 setosa 0.2 1.3
## 4 setosa 0.2 1.5
## 5 setosa 0.2 1.4
## 6 setosa 0.4 1.7
## 7 setosa 0.3 1.4
## 8 setosa 0.2 1.5
## 9 setosa 0.2 1.4
## 10 setosa 0.1 1.5
## 11 setosa 0.2 1.5
## 12 setosa 0.2 1.6
## 13 setosa 0.1 1.4
## 14 setosa 0.1 1.1
## 15 setosa 0.2 1.2
## 16 setosa 0.4 1.5
## 17 setosa 0.4 1.3
## 18 setosa 0.3 1.4
## 19 setosa 0.3 1.7
## 20 setosa 0.3 1.5
## 21 setosa 0.2 1.7
## 22 setosa 0.4 1.5
## 23 setosa 0.2 1.0
## 24 setosa 0.5 1.7
## 25 setosa 0.2 1.9
## 26 setosa 0.2 1.6
## 27 setosa 0.4 1.6
## 28 setosa 0.2 1.5
## 29 setosa 0.2 1.4
## 30 setosa 0.2 1.6
## 31 setosa 0.2 1.6
## 32 setosa 0.4 1.5
## 33 setosa 0.1 1.5
## 34 setosa 0.2 1.4
## 35 setosa 0.2 1.5
## 36 setosa 0.2 1.2
## 37 setosa 0.2 1.3
## 38 setosa 0.1 1.4
## 39 setosa 0.2 1.3
## 40 setosa 0.2 1.5
## 41 setosa 0.3 1.3
## 42 setosa 0.3 1.3
## 43 setosa 0.2 1.3
## 44 setosa 0.6 1.6
## 45 setosa 0.4 1.9
## 46 setosa 0.3 1.4
## 47 setosa 0.2 1.6
## 48 setosa 0.2 1.4
## 49 setosa 0.2 1.5
## 50 setosa 0.2 1.4
## 51 versicolor 1.4 4.7
## 52 versicolor 1.5 4.5
## 53 versicolor 1.5 4.9
## 54 versicolor 1.3 4.0
## 55 versicolor 1.5 4.6
## 56 versicolor 1.3 4.5
## 57 versicolor 1.6 4.7
## 58 versicolor 1.0 3.3
## 59 versicolor 1.3 4.6
## 60 versicolor 1.4 3.9
## 61 versicolor 1.0 3.5
## 62 versicolor 1.5 4.2
## 63 versicolor 1.0 4.0
## 64 versicolor 1.4 4.7
## 65 versicolor 1.3 3.6
## 66 versicolor 1.4 4.4
## 67 versicolor 1.5 4.5
## 68 versicolor 1.0 4.1
## 69 versicolor 1.5 4.5
## 70 versicolor 1.1 3.9
## 71 versicolor 1.8 4.8
## 72 versicolor 1.3 4.0
## 73 versicolor 1.5 4.9
## 74 versicolor 1.2 4.7
## 75 versicolor 1.3 4.3
## 76 versicolor 1.4 4.4
## 77 versicolor 1.4 4.8
## 78 versicolor 1.7 5.0
## 79 versicolor 1.5 4.5
## 80 versicolor 1.0 3.5
## 81 versicolor 1.1 3.8
## 82 versicolor 1.0 3.7
## 83 versicolor 1.2 3.9
## 84 versicolor 1.6 5.1
## 85 versicolor 1.5 4.5
## 86 versicolor 1.6 4.5
## 87 versicolor 1.5 4.7
## 88 versicolor 1.3 4.4
## 89 versicolor 1.3 4.1
## 90 versicolor 1.3 4.0
## 91 versicolor 1.2 4.4
## 92 versicolor 1.4 4.6
## 93 versicolor 1.2 4.0
## 94 versicolor 1.0 3.3
## 95 versicolor 1.3 4.2
## 96 versicolor 1.2 4.2
## 97 versicolor 1.3 4.2
## 98 versicolor 1.3 4.3
## 99 versicolor 1.1 3.0
## 100 versicolor 1.3 4.1
## 101 virginica 2.5 6.0
## 102 virginica 1.9 5.1
## 103 virginica 2.1 5.9
## 104 virginica 1.8 5.6
## 105 virginica 2.2 5.8
## 106 virginica 2.1 6.6
## 107 virginica 1.7 4.5
## 108 virginica 1.8 6.3
## 109 virginica 1.8 5.8
## 110 virginica 2.5 6.1
## 111 virginica 2.0 5.1
## 112 virginica 1.9 5.3
## 113 virginica 2.1 5.5
## 114 virginica 2.0 5.0
## 115 virginica 2.4 5.1
## 116 virginica 2.3 5.3
## 117 virginica 1.8 5.5
## 118 virginica 2.2 6.7
## 119 virginica 2.3 6.9
## 120 virginica 1.5 5.0
## 121 virginica 2.3 5.7
## 122 virginica 2.0 4.9
## 123 virginica 2.0 6.7
## 124 virginica 1.8 4.9
## 125 virginica 2.1 5.7
## 126 virginica 1.8 6.0
## 127 virginica 1.8 4.8
## 128 virginica 1.8 4.9
## 129 virginica 2.1 5.6
## 130 virginica 1.6 5.8
## 131 virginica 1.9 6.1
## 132 virginica 2.0 6.4
## 133 virginica 2.2 5.6
## 134 virginica 1.5 5.1
## 135 virginica 1.4 5.6
## 136 virginica 2.3 6.1
## 137 virginica 2.4 5.6
## 138 virginica 1.8 5.5
## 139 virginica 1.8 4.8
## 140 virginica 2.1 5.4
## 141 virginica 2.4 5.6
## 142 virginica 2.3 5.1
## 143 virginica 1.9 5.1
## 144 virginica 2.3 5.9
## 145 virginica 2.5 5.7
## 146 virginica 2.3 5.2
## 147 virginica 1.9 5.0
## 148 virginica 2.0 5.2
## 149 virginica 2.3 5.4
## 150 virginica 1.8 5.1
iris %>% mutate(sepal=Sepal.Length+Sepal.Width)
## Sepal.Length Sepal.Width Petal.Length Petal.Width Species sepal
## 1 5.1 3.5 1.4 0.2 setosa 8.6
## 2 4.9 3.0 1.4 0.2 setosa 7.9
## 3 4.7 3.2 1.3 0.2 setosa 7.9
## 4 4.6 3.1 1.5 0.2 setosa 7.7
## 5 5.0 3.6 1.4 0.2 setosa 8.6
## 6 5.4 3.9 1.7 0.4 setosa 9.3
## 7 4.6 3.4 1.4 0.3 setosa 8.0
## 8 5.0 3.4 1.5 0.2 setosa 8.4
## 9 4.4 2.9 1.4 0.2 setosa 7.3
## 10 4.9 3.1 1.5 0.1 setosa 8.0
## 11 5.4 3.7 1.5 0.2 setosa 9.1
## 12 4.8 3.4 1.6 0.2 setosa 8.2
## 13 4.8 3.0 1.4 0.1 setosa 7.8
## 14 4.3 3.0 1.1 0.1 setosa 7.3
## 15 5.8 4.0 1.2 0.2 setosa 9.8
## 16 5.7 4.4 1.5 0.4 setosa 10.1
## 17 5.4 3.9 1.3 0.4 setosa 9.3
## 18 5.1 3.5 1.4 0.3 setosa 8.6
## 19 5.7 3.8 1.7 0.3 setosa 9.5
## 20 5.1 3.8 1.5 0.3 setosa 8.9
## 21 5.4 3.4 1.7 0.2 setosa 8.8
## 22 5.1 3.7 1.5 0.4 setosa 8.8
## 23 4.6 3.6 1.0 0.2 setosa 8.2
## 24 5.1 3.3 1.7 0.5 setosa 8.4
## 25 4.8 3.4 1.9 0.2 setosa 8.2
## 26 5.0 3.0 1.6 0.2 setosa 8.0
## 27 5.0 3.4 1.6 0.4 setosa 8.4
## 28 5.2 3.5 1.5 0.2 setosa 8.7
## 29 5.2 3.4 1.4 0.2 setosa 8.6
## 30 4.7 3.2 1.6 0.2 setosa 7.9
## 31 4.8 3.1 1.6 0.2 setosa 7.9
## 32 5.4 3.4 1.5 0.4 setosa 8.8
## 33 5.2 4.1 1.5 0.1 setosa 9.3
## 34 5.5 4.2 1.4 0.2 setosa 9.7
## 35 4.9 3.1 1.5 0.2 setosa 8.0
## 36 5.0 3.2 1.2 0.2 setosa 8.2
## 37 5.5 3.5 1.3 0.2 setosa 9.0
## 38 4.9 3.6 1.4 0.1 setosa 8.5
## 39 4.4 3.0 1.3 0.2 setosa 7.4
## 40 5.1 3.4 1.5 0.2 setosa 8.5
## 41 5.0 3.5 1.3 0.3 setosa 8.5
## 42 4.5 2.3 1.3 0.3 setosa 6.8
## 43 4.4 3.2 1.3 0.2 setosa 7.6
## 44 5.0 3.5 1.6 0.6 setosa 8.5
## 45 5.1 3.8 1.9 0.4 setosa 8.9
## 46 4.8 3.0 1.4 0.3 setosa 7.8
## 47 5.1 3.8 1.6 0.2 setosa 8.9
## 48 4.6 3.2 1.4 0.2 setosa 7.8
## 49 5.3 3.7 1.5 0.2 setosa 9.0
## 50 5.0 3.3 1.4 0.2 setosa 8.3
## 51 7.0 3.2 4.7 1.4 versicolor 10.2
## 52 6.4 3.2 4.5 1.5 versicolor 9.6
## 53 6.9 3.1 4.9 1.5 versicolor 10.0
## 54 5.5 2.3 4.0 1.3 versicolor 7.8
## 55 6.5 2.8 4.6 1.5 versicolor 9.3
## 56 5.7 2.8 4.5 1.3 versicolor 8.5
## 57 6.3 3.3 4.7 1.6 versicolor 9.6
## 58 4.9 2.4 3.3 1.0 versicolor 7.3
## 59 6.6 2.9 4.6 1.3 versicolor 9.5
## 60 5.2 2.7 3.9 1.4 versicolor 7.9
## 61 5.0 2.0 3.5 1.0 versicolor 7.0
## 62 5.9 3.0 4.2 1.5 versicolor 8.9
## 63 6.0 2.2 4.0 1.0 versicolor 8.2
## 64 6.1 2.9 4.7 1.4 versicolor 9.0
## 65 5.6 2.9 3.6 1.3 versicolor 8.5
## 66 6.7 3.1 4.4 1.4 versicolor 9.8
## 67 5.6 3.0 4.5 1.5 versicolor 8.6
## 68 5.8 2.7 4.1 1.0 versicolor 8.5
## 69 6.2 2.2 4.5 1.5 versicolor 8.4
## 70 5.6 2.5 3.9 1.1 versicolor 8.1
## 71 5.9 3.2 4.8 1.8 versicolor 9.1
## 72 6.1 2.8 4.0 1.3 versicolor 8.9
## 73 6.3 2.5 4.9 1.5 versicolor 8.8
## 74 6.1 2.8 4.7 1.2 versicolor 8.9
## 75 6.4 2.9 4.3 1.3 versicolor 9.3
## 76 6.6 3.0 4.4 1.4 versicolor 9.6
## 77 6.8 2.8 4.8 1.4 versicolor 9.6
## 78 6.7 3.0 5.0 1.7 versicolor 9.7
## 79 6.0 2.9 4.5 1.5 versicolor 8.9
## 80 5.7 2.6 3.5 1.0 versicolor 8.3
## 81 5.5 2.4 3.8 1.1 versicolor 7.9
## 82 5.5 2.4 3.7 1.0 versicolor 7.9
## 83 5.8 2.7 3.9 1.2 versicolor 8.5
## 84 6.0 2.7 5.1 1.6 versicolor 8.7
## 85 5.4 3.0 4.5 1.5 versicolor 8.4
## 86 6.0 3.4 4.5 1.6 versicolor 9.4
## 87 6.7 3.1 4.7 1.5 versicolor 9.8
## 88 6.3 2.3 4.4 1.3 versicolor 8.6
## 89 5.6 3.0 4.1 1.3 versicolor 8.6
## 90 5.5 2.5 4.0 1.3 versicolor 8.0
## 91 5.5 2.6 4.4 1.2 versicolor 8.1
## 92 6.1 3.0 4.6 1.4 versicolor 9.1
## 93 5.8 2.6 4.0 1.2 versicolor 8.4
## 94 5.0 2.3 3.3 1.0 versicolor 7.3
## 95 5.6 2.7 4.2 1.3 versicolor 8.3
## 96 5.7 3.0 4.2 1.2 versicolor 8.7
## 97 5.7 2.9 4.2 1.3 versicolor 8.6
## 98 6.2 2.9 4.3 1.3 versicolor 9.1
## 99 5.1 2.5 3.0 1.1 versicolor 7.6
## 100 5.7 2.8 4.1 1.3 versicolor 8.5
## 101 6.3 3.3 6.0 2.5 virginica 9.6
## 102 5.8 2.7 5.1 1.9 virginica 8.5
## 103 7.1 3.0 5.9 2.1 virginica 10.1
## 104 6.3 2.9 5.6 1.8 virginica 9.2
## 105 6.5 3.0 5.8 2.2 virginica 9.5
## 106 7.6 3.0 6.6 2.1 virginica 10.6
## 107 4.9 2.5 4.5 1.7 virginica 7.4
## 108 7.3 2.9 6.3 1.8 virginica 10.2
## 109 6.7 2.5 5.8 1.8 virginica 9.2
## 110 7.2 3.6 6.1 2.5 virginica 10.8
## 111 6.5 3.2 5.1 2.0 virginica 9.7
## 112 6.4 2.7 5.3 1.9 virginica 9.1
## 113 6.8 3.0 5.5 2.1 virginica 9.8
## 114 5.7 2.5 5.0 2.0 virginica 8.2
## 115 5.8 2.8 5.1 2.4 virginica 8.6
## 116 6.4 3.2 5.3 2.3 virginica 9.6
## 117 6.5 3.0 5.5 1.8 virginica 9.5
## 118 7.7 3.8 6.7 2.2 virginica 11.5
## 119 7.7 2.6 6.9 2.3 virginica 10.3
## 120 6.0 2.2 5.0 1.5 virginica 8.2
## 121 6.9 3.2 5.7 2.3 virginica 10.1
## 122 5.6 2.8 4.9 2.0 virginica 8.4
## 123 7.7 2.8 6.7 2.0 virginica 10.5
## 124 6.3 2.7 4.9 1.8 virginica 9.0
## 125 6.7 3.3 5.7 2.1 virginica 10.0
## 126 7.2 3.2 6.0 1.8 virginica 10.4
## 127 6.2 2.8 4.8 1.8 virginica 9.0
## 128 6.1 3.0 4.9 1.8 virginica 9.1
## 129 6.4 2.8 5.6 2.1 virginica 9.2
## 130 7.2 3.0 5.8 1.6 virginica 10.2
## 131 7.4 2.8 6.1 1.9 virginica 10.2
## 132 7.9 3.8 6.4 2.0 virginica 11.7
## 133 6.4 2.8 5.6 2.2 virginica 9.2
## 134 6.3 2.8 5.1 1.5 virginica 9.1
## 135 6.1 2.6 5.6 1.4 virginica 8.7
## 136 7.7 3.0 6.1 2.3 virginica 10.7
## 137 6.3 3.4 5.6 2.4 virginica 9.7
## 138 6.4 3.1 5.5 1.8 virginica 9.5
## 139 6.0 3.0 4.8 1.8 virginica 9.0
## 140 6.9 3.1 5.4 2.1 virginica 10.0
## 141 6.7 3.1 5.6 2.4 virginica 9.8
## 142 6.9 3.1 5.1 2.3 virginica 10.0
## 143 5.8 2.7 5.1 1.9 virginica 8.5
## 144 6.8 3.2 5.9 2.3 virginica 10.0
## 145 6.7 3.3 5.7 2.5 virginica 10.0
## 146 6.7 3.0 5.2 2.3 virginica 9.7
## 147 6.3 2.5 5.0 1.9 virginica 8.8
## 148 6.5 3.0 5.2 2.0 virginica 9.5
## 149 6.2 3.4 5.4 2.3 virginica 9.6
## 150 5.9 3.0 5.1 1.8 virginica 8.9
install.packages("Lahman")
library(Lahman)
data("Teams")
#Teams<-tibble::as_tibble(Teams)
??Teams
dim(Teams)
## [1] 2925 48
head(Teams)
## yearID lgID teamID franchID divID Rank G Ghome W L DivWin WCWin LgWin
## 1 1871 NA BS1 BNA <NA> 3 31 NA 20 10 <NA> <NA> N
## 2 1871 NA CH1 CNA <NA> 2 28 NA 19 9 <NA> <NA> N
## 3 1871 NA CL1 CFC <NA> 8 29 NA 10 19 <NA> <NA> N
## 4 1871 NA FW1 KEK <NA> 7 19 NA 7 12 <NA> <NA> N
## 5 1871 NA NY2 NNA <NA> 5 33 NA 16 17 <NA> <NA> N
## 6 1871 NA PH1 PNA <NA> 1 28 NA 21 7 <NA> <NA> Y
## WSWin R AB H X2B X3B HR BB SO SB CS HBP SF RA ER ERA CG SHO SV
## 1 <NA> 401 1372 426 70 37 3 60 19 73 16 NA NA 303 109 3.55 22 1 3
## 2 <NA> 302 1196 323 52 21 10 60 22 69 21 NA NA 241 77 2.76 25 0 1
## 3 <NA> 249 1186 328 35 40 7 26 25 18 8 NA NA 341 116 4.11 23 0 0
## 4 <NA> 137 746 178 19 8 2 33 9 16 4 NA NA 243 97 5.17 19 1 0
## 5 <NA> 302 1404 403 43 21 1 33 15 46 15 NA NA 313 121 3.72 32 1 0
## 6 <NA> 376 1281 410 66 27 9 46 23 56 12 NA NA 266 137 4.95 27 0 0
## IPouts HA HRA BBA SOA E DP FP name
## 1 828 367 2 42 23 243 24 0.834 Boston Red Stockings
## 2 753 308 6 28 22 229 16 0.829 Chicago White Stockings
## 3 762 346 13 53 34 234 15 0.818 Cleveland Forest Citys
## 4 507 261 5 21 17 163 8 0.803 Fort Wayne Kekiongas
## 5 879 373 7 42 22 235 14 0.840 New York Mutuals
## 6 747 329 3 53 16 194 13 0.845 Philadelphia Athletics
## park attendance BPF PPF teamIDBR teamIDlahman45
## 1 South End Grounds I NA 103 98 BOS BS1
## 2 Union Base-Ball Grounds NA 104 102 CHI CH1
## 3 National Association Grounds NA 96 100 CLE CL1
## 4 Hamilton Field NA 101 107 KEK FW1
## 5 Union Grounds (Brooklyn) NA 90 88 NYU NY2
## 6 Jefferson Street Grounds NA 102 98 ATH PH1
## teamIDretro
## 1 BS1
## 2 CH1
## 3 CL1
## 4 FW1
## 5 NY2
## 6 PH1
glimpse(Teams)
## Rows: 2,925
## Columns: 48
## $ yearID <int> 1871, 1871, 1871, 1871, 1871, 1871, 1871, 1871, 1871...
## $ lgID <fct> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ teamID <fct> BS1, CH1, CL1, FW1, NY2, PH1, RC1, TRO, WS3, BL1, BR...
## $ franchID <fct> BNA, CNA, CFC, KEK, NNA, PNA, ROK, TRO, OLY, BLC, EC...
## $ divID <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ Rank <int> 3, 2, 8, 7, 5, 1, 9, 6, 4, 2, 9, 6, 1, 7, 8, 3, 4, 5...
## $ G <int> 31, 28, 29, 19, 33, 28, 25, 29, 32, 58, 29, 37, 48, ...
## $ Ghome <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ W <int> 20, 19, 10, 7, 16, 21, 4, 13, 15, 35, 3, 9, 39, 6, 5...
## $ L <int> 10, 9, 19, 12, 17, 7, 21, 15, 15, 19, 26, 28, 8, 16,...
## $ DivWin <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ WCWin <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ LgWin <chr> "N", "N", "N", "N", "N", "Y", "N", "N", "N", "N", "N...
## $ WSWin <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ R <int> 401, 302, 249, 137, 302, 376, 231, 351, 310, 617, 15...
## $ AB <int> 1372, 1196, 1186, 746, 1404, 1281, 1036, 1248, 1353,...
## $ H <int> 426, 323, 328, 178, 403, 410, 274, 384, 375, 753, 24...
## $ X2B <int> 70, 52, 35, 19, 43, 66, 44, 51, 54, 106, 29, 35, 107...
## $ X3B <int> 37, 21, 40, 8, 21, 27, 25, 34, 26, 31, 9, 10, 30, 5,...
## $ HR <int> 3, 10, 7, 2, 1, 9, 3, 6, 6, 14, 0, 1, 7, 0, 2, 4, 4,...
## $ BB <int> 60, 60, 26, 33, 33, 46, 38, 49, 48, 29, 18, 19, 29, ...
## $ SO <int> 19, 22, 25, 9, 15, 23, 30, 19, 13, 28, 40, 25, 26, 1...
## $ SB <int> 73, 69, 18, 16, 46, 56, 53, 62, 48, 53, 8, 19, 48, 1...
## $ CS <int> 16, 21, 8, 4, 15, 12, 10, 24, 13, 18, 13, 16, 14, 3,...
## $ HBP <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ SF <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ RA <int> 303, 241, 341, 243, 313, 266, 287, 362, 303, 434, 41...
## $ ER <int> 109, 77, 116, 97, 121, 137, 108, 153, 137, 166, 160,...
## $ ERA <dbl> 3.55, 2.76, 4.11, 5.17, 3.72, 4.95, 4.30, 5.51, 4.37...
## $ CG <int> 22, 25, 23, 19, 32, 27, 23, 28, 32, 48, 28, 37, 41, ...
## $ SHO <int> 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 4, 0, 0, 3, 1, 2...
## $ SV <int> 3, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 4, 0, 0, 1, 0, 1...
## $ IPouts <int> 828, 753, 762, 507, 879, 747, 678, 750, 846, 1548, 7...
## $ HA <int> 367, 308, 346, 261, 373, 329, 315, 431, 371, 573, 48...
## $ HRA <int> 2, 6, 13, 5, 7, 3, 3, 4, 4, 3, 7, 6, 0, 6, 6, 2, 3, ...
## $ BBA <int> 42, 28, 53, 21, 42, 53, 34, 75, 45, 63, 36, 21, 27, ...
## $ SOA <int> 23, 22, 34, 17, 22, 16, 16, 12, 13, 77, 13, 13, 29, ...
## $ E <int> 243, 229, 234, 163, 235, 194, 220, 198, 218, 432, 27...
## $ DP <int> 24, 16, 15, 8, 14, 13, 14, 22, 20, 22, 9, 15, 44, 17...
## $ FP <dbl> 0.834, 0.829, 0.818, 0.803, 0.840, 0.845, 0.821, 0.8...
## $ name <chr> "Boston Red Stockings", "Chicago White Stockings", "...
## $ park <chr> "South End Grounds I", "Union Base-Ball Grounds", "N...
## $ attendance <int> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ BPF <int> 103, 104, 96, 101, 90, 102, 97, 101, 94, 106, 87, 11...
## $ PPF <int> 98, 102, 100, 107, 88, 98, 99, 100, 98, 102, 96, 122...
## $ teamIDBR <chr> "BOS", "CHI", "CLE", "KEK", "NYU", "ATH", "ROK", "TR...
## $ teamIDlahman45 <chr> "BS1", "CH1", "CL1", "FW1", "NY2", "PH1", "RC1", "TR...
## $ teamIDretro <chr> "BS1", "CH1", "CL1", "FW1", "NY2", "PH1", "RC1", "TR...
mets<-Teams %>% filter(teamID=="NYN")
nrow(mets)
## [1] 58
head(mets)
## yearID lgID teamID franchID divID Rank G Ghome W L DivWin WCWin LgWin
## 1 1962 NL NYN NYM <NA> 10 161 80 40 120 <NA> <NA> N
## 2 1963 NL NYN NYM <NA> 10 162 81 51 111 <NA> <NA> N
## 3 1964 NL NYN NYM <NA> 10 163 82 53 109 <NA> <NA> N
## 4 1965 NL NYN NYM <NA> 10 164 82 50 112 <NA> <NA> N
## 5 1966 NL NYN NYM <NA> 9 161 81 66 95 <NA> <NA> N
## 6 1967 NL NYN NYM <NA> 10 162 78 61 101 <NA> <NA> N
## WSWin R AB H X2B X3B HR BB SO SB CS HBP SF RA ER ERA CG SHO SV
## 1 N 617 5492 1318 166 40 139 616 991 59 48 NA NA 948 801 5.04 43 4 10
## 2 N 501 5336 1168 156 35 96 457 1078 41 52 NA NA 774 653 4.12 42 5 12
## 3 N 569 5566 1372 195 31 103 353 932 36 31 NA NA 776 679 4.25 40 10 15
## 4 N 495 5441 1202 203 27 107 392 1129 28 42 NA NA 752 656 4.06 29 11 14
## 5 N 587 5371 1286 187 35 98 446 992 55 46 NA NA 761 661 4.17 37 9 22
## 6 N 498 5417 1288 178 23 83 362 981 58 44 NA NA 672 594 3.73 36 10 19
## IPouts HA HRA BBA SOA E DP FP name park
## 1 4290 1577 192 571 772 210 167 0.967 New York Mets Polo Grounds IV
## 2 4281 1452 162 529 806 208 151 0.967 New York Mets Polo Grounds IV
## 3 4314 1511 130 466 717 166 154 0.974 New York Mets Shea Stadium
## 4 4362 1462 147 498 776 169 153 0.974 New York Mets Shea Stadium
## 5 4281 1497 166 521 773 159 171 0.975 New York Mets Shea Stadium
## 6 4299 1369 124 536 893 157 147 0.975 New York Mets Shea Stadium
## attendance BPF PPF teamIDBR teamIDlahman45 teamIDretro
## 1 922530 100 105 NYM NYN NYN
## 2 1080108 100 105 NYM NYN NYN
## 3 1732597 97 100 NYM NYN NYN
## 4 1768389 96 99 NYM NYN NYN
## 5 1932693 97 100 NYM NYN NYN
## 6 1565492 98 100 NYM NYN NYN
myMets<-mets %>% filter(yearID %in% 2004:2012)
myMets %>% select(yearID, teamID, W, L)
## yearID teamID W L
## 1 2004 NYN 71 91
## 2 2005 NYN 83 79
## 3 2006 NYN 97 65
## 4 2007 NYN 88 74
## 5 2008 NYN 89 73
## 6 2009 NYN 70 92
## 7 2010 NYN 79 83
## 8 2011 NYN 77 85
## 9 2012 NYN 74 88
Teams %>%
select(yearID, teamID, W, L) %>%
filter(teamID=="NYN" & yearID %in% 2004:2012)
## yearID teamID W L
## 1 2004 NYN 71 91
## 2 2005 NYN 83 79
## 3 2006 NYN 97 65
## 4 2007 NYN 88 74
## 5 2008 NYN 89 73
## 6 2009 NYN 70 92
## 7 2010 NYN 79 83
## 8 2011 NYN 77 85
## 9 2012 NYN 74 88
metsBen <- Teams %>% select(yearID, teamID, W, L, R, RA) %>%
filter(teamID == "NYN" & yearID %in% 2004:2012)
metsBen
## yearID teamID W L R RA
## 1 2004 NYN 71 91 684 731
## 2 2005 NYN 83 79 722 648
## 3 2006 NYN 97 65 834 731
## 4 2007 NYN 88 74 804 750
## 5 2008 NYN 89 73 799 715
## 6 2009 NYN 70 92 671 757
## 7 2010 NYN 79 83 656 652
## 8 2011 NYN 77 85 718 742
## 9 2012 NYN 74 88 650 709
metsBen <- metsBen %>% rename(RS = R) # new name = old name
metsBen
## yearID teamID W L RS RA
## 1 2004 NYN 71 91 684 731
## 2 2005 NYN 83 79 722 648
## 3 2006 NYN 97 65 834 731
## 4 2007 NYN 88 74 804 750
## 5 2008 NYN 89 73 799 715
## 6 2009 NYN 70 92 671 757
## 7 2010 NYN 79 83 656 652
## 8 2011 NYN 77 85 718 742
## 9 2012 NYN 74 88 650 709
metsBen <- metsBen %>% mutate(WPct = W / (W + L))
metsBen
## yearID teamID W L RS RA WPct
## 1 2004 NYN 71 91 684 731 0.4382716
## 2 2005 NYN 83 79 722 648 0.5123457
## 3 2006 NYN 97 65 834 731 0.5987654
## 4 2007 NYN 88 74 804 750 0.5432099
## 5 2008 NYN 89 73 799 715 0.5493827
## 6 2009 NYN 70 92 671 757 0.4320988
## 7 2010 NYN 79 83 656 652 0.4876543
## 8 2011 NYN 77 85 718 742 0.4753086
## 9 2012 NYN 74 88 650 709 0.4567901
metsBen <- metsBen %>% mutate(WPct_hat = 1 / (1 +(RA/RS)^2))
metsBen
## yearID teamID W L RS RA WPct WPct_hat
## 1 2004 NYN 71 91 684 731 0.4382716 0.4668211
## 2 2005 NYN 83 79 722 648 0.5123457 0.5538575
## 3 2006 NYN 97 65 834 731 0.5987654 0.5655308
## 4 2007 NYN 88 74 804 750 0.5432099 0.5347071
## 5 2008 NYN 89 73 799 715 0.5493827 0.5553119
## 6 2009 NYN 70 92 671 757 0.4320988 0.4399936
## 7 2010 NYN 79 83 656 652 0.4876543 0.5030581
## 8 2011 NYN 77 85 718 742 0.4753086 0.4835661
## 9 2012 NYN 74 88 650 709 0.4567901 0.4566674
metsBen <- metsBen %>% mutate(W_hat = WPct_hat * (W + L))
metsBen
## yearID teamID W L RS RA WPct WPct_hat W_hat
## 1 2004 NYN 71 91 684 731 0.4382716 0.4668211 75.62501
## 2 2005 NYN 83 79 722 648 0.5123457 0.5538575 89.72491
## 3 2006 NYN 97 65 834 731 0.5987654 0.5655308 91.61600
## 4 2007 NYN 88 74 804 750 0.5432099 0.5347071 86.62255
## 5 2008 NYN 89 73 799 715 0.5493827 0.5553119 89.96053
## 6 2009 NYN 70 92 671 757 0.4320988 0.4399936 71.27896
## 7 2010 NYN 79 83 656 652 0.4876543 0.5030581 81.49541
## 8 2011 NYN 77 85 718 742 0.4753086 0.4835661 78.33771
## 9 2012 NYN 74 88 650 709 0.4567901 0.4566674 73.98012
filter(metsBen, W >= W_hat)
## yearID teamID W L RS RA WPct WPct_hat W_hat
## 1 2006 NYN 97 65 834 731 0.5987654 0.5655308 91.61600
## 2 2007 NYN 88 74 804 750 0.5432099 0.5347071 86.62255
## 3 2012 NYN 74 88 650 709 0.4567901 0.4566674 73.98012
arrange(metsBen, desc(WPct))
## yearID teamID W L RS RA WPct WPct_hat W_hat
## 1 2006 NYN 97 65 834 731 0.5987654 0.5655308 91.61600
## 2 2008 NYN 89 73 799 715 0.5493827 0.5553119 89.96053
## 3 2007 NYN 88 74 804 750 0.5432099 0.5347071 86.62255
## 4 2005 NYN 83 79 722 648 0.5123457 0.5538575 89.72491
## 5 2010 NYN 79 83 656 652 0.4876543 0.5030581 81.49541
## 6 2011 NYN 77 85 718 742 0.4753086 0.4835661 78.33771
## 7 2012 NYN 74 88 650 709 0.4567901 0.4566674 73.98012
## 8 2004 NYN 71 91 684 731 0.4382716 0.4668211 75.62501
## 9 2009 NYN 70 92 671 757 0.4320988 0.4399936 71.27896
metsBen %>%
summarize(num_years = n(), total_W = sum(W), total_L = sum(L),
total_WPct = sum(W) / sum(W + L), sum_resid = sum(W - W_hat))
## num_years total_W total_L total_WPct sum_resid
## 1 9 728 730 0.4993141 -10.64119