library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(MASS)##
## Attaching package: 'MASS'## The following object is masked from 'package:dplyr':
##
## selectdata("survey")
head(survey,10)## Sex Wr.Hnd NW.Hnd W.Hnd Fold Pulse Clap Exer Smoke Height M.I
## 1 Female 18.5 18.0 Right R on L 92 Left Some Never 173.00 Metric
## 2 Male 19.5 20.5 Left R on L 104 Left None Regul 177.80 Imperial
## 3 Male 18.0 13.3 Right L on R 87 Neither None Occas NA <NA>
## 4 Male 18.8 18.9 Right R on L NA Neither None Never 160.00 Metric
## 5 Male 20.0 20.0 Right Neither 35 Right Some Never 165.00 Metric
## 6 Female 18.0 17.7 Right L on R 64 Right Some Never 172.72 Imperial
## 7 Male 17.7 17.7 Right L on R 83 Right Freq Never 182.88 Imperial
## 8 Female 17.0 17.3 Right R on L 74 Right Freq Never 157.00 Metric
## 9 Male 20.0 19.5 Right R on L 72 Right Some Never 175.00 Metric
## 10 Male 18.5 18.5 Right R on L 90 Right Some Never 167.00 Metric
## Age
## 1 18.250
## 2 17.583
## 3 16.917
## 4 20.333
## 5 23.667
## 6 21.000
## 7 18.833
## 8 35.833
## 9 19.000
## 10 22.333tail(survey,10)## Sex Wr.Hnd NW.Hnd W.Hnd Fold Pulse Clap Exer Smoke Height M.I
## 228 Male 20.0 19.8 Right L on R 68 Right Freq Never 185.00 Metric
## 229 Female 18.6 18.8 Right L on R 70 Right Freq Regul 167.00 Metric
## 230 Male 18.6 19.6 Right L on R 71 Right Freq Occas 185.00 Metric
## 231 Female 18.8 18.5 Right R on L 80 Right Some Never 169.00 Metric
## 232 Male 18.0 16.0 Right R on L NA Right Some Never 180.34 Imperial
## 233 Female 18.0 18.0 Right L on R 85 Right Some Never 165.10 Imperial
## 234 Female 18.5 18.0 Right L on R 88 Right Some Never 160.00 Metric
## 235 Female 17.5 16.5 Right R on L NA Right Some Never 170.00 Metric
## 236 Male 21.0 21.5 Right R on L 90 Right Some Never 183.00 Metric
## 237 Female 17.6 17.3 Right R on L 85 Right Freq Never 168.50 Metric
## Age
## 228 17.417
## 229 20.333
## 230 19.333
## 231 18.167
## 232 20.750
## 233 17.667
## 234 16.917
## 235 18.583
## 236 17.167
## 237 17.750names(survey)## [1] "Sex" "Wr.Hnd" "NW.Hnd" "W.Hnd" "Fold" "Pulse" "Clap" "Exer"
## [9] "Smoke" "Height" "M.I" "Age"summary(survey)## Sex Wr.Hnd NW.Hnd W.Hnd Fold
## Female:118 Min. :13.00 Min. :12.50 Left : 18 L on R : 99
## Male :118 1st Qu.:17.50 1st Qu.:17.50 Right:218 Neither: 18
## NA's : 1 Median :18.50 Median :18.50 NA's : 1 R on L :120
## Mean :18.67 Mean :18.58
## 3rd Qu.:19.80 3rd Qu.:19.73
## Max. :23.20 Max. :23.50
## NA's :1 NA's :1
## Pulse Clap Exer Smoke Height
## Min. : 35.00 Left : 39 Freq:115 Heavy: 11 Min. :150.0
## 1st Qu.: 66.00 Neither: 50 None: 24 Never:189 1st Qu.:165.0
## Median : 72.50 Right :147 Some: 98 Occas: 19 Median :171.0
## Mean : 74.15 NA's : 1 Regul: 17 Mean :172.4
## 3rd Qu.: 80.00 NA's : 1 3rd Qu.:180.0
## Max. :104.00 Max. :200.0
## NA's :45 NA's :28
## M.I Age
## Imperial: 68 Min. :16.75
## Metric :141 1st Qu.:17.67
## NA's : 28 Median :18.58
## Mean :20.37
## 3rd Qu.:20.17
## Max. :73.00
## survey %>% count(Sex)## Sex n
## 1 Female 118
## 2 Male 118
## 3 <NA> 1survey %>% count(Pulse)## Pulse n
## 1 35 1
## 2 40 1
## 3 48 2
## 4 50 2
## 5 54 1
## 6 55 1
## 7 56 1
## 8 59 1
## 9 60 12
## 10 61 1
## 11 62 4
## 12 63 1
## 13 64 9
## 14 65 6
## 15 66 6
## 16 67 1
## 17 68 16
## 18 69 1
## 19 70 13
## 20 71 2
## 21 72 14
## 22 73 1
## 23 74 5
## 24 75 5
## 25 76 13
## 26 78 4
## 27 79 3
## 28 80 18
## 29 81 1
## 30 83 4
## 31 84 5
## 32 85 4
## 33 86 3
## 34 87 2
## 35 88 4
## 36 89 1
## 37 90 8
## 38 92 6
## 39 96 3
## 40 97 1
## 41 98 1
## 42 100 2
## 43 104 2
## 44 NA 45#İlgili sütunun frekans sayısını bulduk
survey %>%
group_by(Pulse)## # A tibble: 237 × 12
## # Groups: Pulse [44]
## Sex Wr.Hnd NW.Hnd W.Hnd Fold Pulse Clap Exer Smoke Height M.I Age
## <fct> <dbl> <dbl> <fct> <fct> <int> <fct> <fct> <fct> <dbl> <fct> <dbl>
## 1 Female 18.5 18 Right R on L 92 Left Some Never 173 Metr… 18.2
## 2 Male 19.5 20.5 Left R on L 104 Left None Regul 178. Impe… 17.6
## 3 Male 18 13.3 Right L on R 87 Neit… None Occas NA <NA> 16.9
## 4 Male 18.8 18.9 Right R on L NA Neit… None Never 160 Metr… 20.3
## 5 Male 20 20 Right Neither 35 Right Some Never 165 Metr… 23.7
## 6 Female 18 17.7 Right L on R 64 Right Some Never 173. Impe… 21
## 7 Male 17.7 17.7 Right L on R 83 Right Freq Never 183. Impe… 18.8
## 8 Female 17 17.3 Right R on L 74 Right Freq Never 157 Metr… 35.8
## 9 Male 20 19.5 Right R on L 72 Right Some Never 175 Metr… 19
## 10 Male 18.5 18.5 Right R on L 90 Right Some Never 167 Metr… 22.3
## # ℹ 227 more rowsyeni<-survey %>%
dplyr::select(Sex, Age, Smoke, Height, Exer, Pulse)yeni %>%
count(Sex, Age,Exer, Pulse
) %>%
na.omit(yeni)## Sex Age Exer Pulse n
## 1 Female 16.917 Freq 64 1
## 2 Female 16.917 Some 88 1
## 3 Female 17.000 Freq 80 1
## 5 Female 17.083 Freq 83 1
## 6 Female 17.083 Freq 87 1
## 7 Female 17.083 Some 68 2
## 8 Female 17.083 Some 72 1
## 11 Female 17.167 None 70 1
## 12 Female 17.167 Some 70 1
## 13 Female 17.167 Some 74 1
## 15 Female 17.250 Freq 65 1
## 16 Female 17.250 Freq 104 1
## 17 Female 17.250 Some 72 1
## 18 Female 17.250 Some 76 1
## 19 Female 17.250 Some 79 1
## 20 Female 17.250 Some 83 1
## 21 Female 17.333 Freq 70 1
## 22 Female 17.333 Freq 72 1
## 23 Female 17.417 Freq 40 1
## 24 Female 17.417 Freq 60 1
## 25 Female 17.417 Freq 70 1
## 26 Female 17.417 Some 76 1
## 27 Female 17.500 Freq 70 1
## 28 Female 17.500 Freq 92 1
## 29 Female 17.500 Some 66 1
## 30 Female 17.500 Some 80 2
## 31 Female 17.500 Some 84 1
## 33 Female 17.583 Freq 64 1
## 34 Female 17.583 Some 92 1
## 35 Female 17.667 Freq 68 1
## 36 Female 17.667 Freq 98 1
## 37 Female 17.667 Some 68 1
## 38 Female 17.667 Some 80 1
## 39 Female 17.667 Some 85 1
## 40 Female 17.750 Freq 68 1
## 41 Female 17.750 Freq 85 1
## 42 Female 17.750 Some 88 1
## 43 Female 18.000 Freq 74 1
## 44 Female 18.000 Some 70 1
## 46 Female 18.167 Freq 80 1
## 48 Female 18.167 Some 70 1
## 49 Female 18.167 Some 80 1
## 50 Female 18.167 Some 88 1
## 51 Female 18.250 Some 80 1
## 52 Female 18.250 Some 92 1
## 53 Female 18.333 Some 90 1
## 54 Female 18.417 None 80 1
## 55 Female 18.417 Some 60 1
## 56 Female 18.417 Some 80 1
## 57 Female 18.500 Freq 80 1
## 58 Female 18.500 Freq 85 1
## 60 Female 18.500 Some 50 1
## 61 Female 18.500 Some 81 1
## 62 Female 18.583 Freq 64 1
## 63 Female 18.583 Some 76 1
## 65 Female 18.667 Freq 48 1
## 66 Female 18.667 None 68 1
## 67 Female 18.667 Some 96 1
## 68 Female 18.750 Freq 75 1
## 70 Female 18.917 Some 100 1
## 72 Female 19.083 Freq 68 1
## 73 Female 19.083 Some 86 1
## 74 Female 19.167 Freq 68 1
## 76 Female 19.167 Some 64 1
## 77 Female 19.167 Some 80 1
## 80 Female 19.250 Some 61 1
## 81 Female 19.333 Freq 89 1
## 82 Female 19.667 Some 70 1
## 85 Female 20.000 Freq 92 1
## 86 Female 20.167 Freq 64 1
## 87 Female 20.167 Freq 72 1
## 88 Female 20.167 None 86 1
## 89 Female 20.333 Freq 70 1
## 90 Female 20.500 None 70 1
## 91 Female 20.667 Freq 68 1
## 94 Female 21.000 Some 64 1
## 96 Female 21.167 Freq 75 1
## 97 Female 22.917 Some 70 1
## 98 Female 23.083 Freq 84 1
## 99 Female 23.250 Freq 60 1
## 100 Female 23.500 Some 92 1
## 101 Female 23.583 Some 76 1
## 102 Female 24.167 Freq 76 1
## 103 Female 24.667 Some 79 1
## 104 Female 26.500 Some 76 1
## 105 Female 28.500 Freq 80 1
## 106 Female 29.083 Freq 60 1
## 108 Female 30.750 None 50 1
## 109 Female 32.750 Some 65 1
## 110 Female 35.833 Freq 74 1
## 111 Female 39.750 Freq 72 1
## 112 Female 41.583 None 76 1
## 113 Female 44.250 Some 74 1
## 115 Male 16.750 Some 66 1
## 116 Male 16.917 None 87 1
## 117 Male 17.167 Freq 71 1
## 118 Male 17.167 Freq 90 1
## 119 Male 17.167 Some 60 1
## 120 Male 17.167 Some 70 1
## 121 Male 17.167 Some 90 1
## 122 Male 17.333 Freq 72 1
## 123 Male 17.417 Freq 56 1
## 124 Male 17.417 Freq 59 1
## 125 Male 17.417 Freq 68 1
## 126 Male 17.417 Freq 72 1
## 128 Male 17.500 Freq 68 1
## 129 Male 17.500 Freq 78 2
## 130 Male 17.500 Freq 80 1
## 131 Male 17.500 Some 72 1
## 132 Male 17.500 Some 90 1
## 133 Male 17.583 None 104 1
## 134 Male 17.583 Some 90 1
## 135 Male 17.667 Freq 62 1
## 136 Male 17.750 None 60 1
## 137 Male 17.750 Some 54 1
## 138 Male 17.750 Some 67 1
## 139 Male 17.833 Freq 64 1
## 141 Male 17.917 Freq 60 1
## 142 Male 17.917 Freq 72 2
## 143 Male 17.917 Freq 78 1
## 144 Male 17.917 Freq 84 1
## 145 Male 18.000 Freq 66 1
## 147 Male 18.083 Freq 62 1
## 148 Male 18.083 Freq 66 1
## 150 Male 18.167 Freq 72 1
## 151 Male 18.167 None 80 1
## 152 Male 18.250 Freq 68 1
## 153 Male 18.250 Freq 76 1
## 154 Male 18.250 Some 62 1
## 156 Male 18.333 None 80 1
## 157 Male 18.333 Some 74 1
## 158 Male 18.333 Some 78 1
## 160 Male 18.417 Some 85 1
## 161 Male 18.500 Freq 55 1
## 163 Male 18.500 None 65 1
## 164 Male 18.583 Freq 64 1
## 165 Male 18.583 Some 84 1
## 166 Male 18.667 Some 80 2
## 168 Male 18.750 Some 60 1
## 169 Male 18.750 Some 90 1
## 170 Male 18.833 Freq 83 1
## 171 Male 18.917 Freq 75 1
## 172 Male 18.917 Freq 84 1
## 173 Male 18.917 None 68 1
## 174 Male 18.917 Some 83 1
## 175 Male 18.917 Some 92 1
## 177 Male 19.000 Some 72 1
## 178 Male 19.000 Some 75 1
## 179 Male 19.000 Some 96 1
## 180 Male 19.167 Some 90 1
## 181 Male 19.250 Some 79 1
## 182 Male 19.333 Freq 71 1
## 183 Male 19.333 Freq 72 1
## 184 Male 19.333 Freq 88 1
## 185 Male 19.417 Freq 68 1
## 186 Male 19.417 None 96 1
## 187 Male 19.500 None 97 1
## 189 Male 19.667 Some 75 1
## 194 Male 20.000 Freq 65 1
## 195 Male 20.000 Freq 86 1
## 196 Male 20.083 Freq 63 1
## 197 Male 20.083 Freq 100 1
## 198 Male 20.167 Freq 76 1
## 199 Male 20.333 Freq 62 1
## 200 Male 20.333 Freq 66 1
## 202 Male 20.417 Some 65 1
## 205 Male 21.000 Freq 66 1
## 207 Male 21.167 Some 72 1
## 210 Male 21.333 Freq 48 1
## 212 Male 21.583 Freq 60 1
## 213 Male 21.917 Freq 76 1
## 214 Male 22.333 Some 90 1
## 215 Male 22.833 Freq 65 1
## 216 Male 23.000 Freq 64 1
## 217 Male 23.417 Freq 68 1
## 218 Male 23.583 Freq 76 1
## 219 Male 23.667 Some 35 1
## 220 Male 23.833 Freq 70 1
## 221 Male 25.500 Freq 76 1
## 222 Male 27.333 Some 60 1
## 223 Male 28.583 Some 60 1
## 224 Male 32.667 Freq 60 1
## 225 Male 35.500 Some 80 1
## 226 Male 36.583 Freq 76 1
## 227 Male 43.833 None 68 1
## 228 Male 70.417 Freq 69 1mean(yeni$ Age)## [1] 20.37451yeni %>%
group_by(Sex) %>%
summarise(ortalama_Age= round(mean(Age),2))## # A tibble: 3 × 2
## Sex ortalama_Age
## <fct> <dbl>
## 1 Female 20.4
## 2 Male 20.3
## 3 <NA> 21.5#kadınlarda ortalama yaş 20.41 iken erkeklerde 20.33
yeni2<-yeni %>%
mutate(Sex, Age, Smoke, Height, Exer, Pulse)head(yeni2)## Sex Age Smoke Height Exer Pulse
## 1 Female 18.250 Never 173.00 Some 92
## 2 Male 17.583 Regul 177.80 None 104
## 3 Male 16.917 Occas NA None 87
## 4 Male 20.333 Never 160.00 None NA
## 5 Male 23.667 Never 165.00 Some 35
## 6 Female 21.000 Never 172.72 Some 64veri_son <- na.omit(yeni2)#ortalama hesaplarken hata vermemesi için NA ların temizlenmesi gerekir. bunun için önce bu kodla na içermeyen bir tablo haline getirmek gerek
veri_son %>%
count(Pulse) %>%
mutate(yuzde=round((n/sum(n)))*100,2)## Pulse n yuzde 2
## 1 35 1 0 2
## 2 40 1 0 2
## 3 48 2 0 2
## 4 50 1 0 2
## 5 55 1 0 2
## 6 56 1 0 2
## 7 59 1 0 2
## 8 60 11 0 2
## 9 61 1 0 2
## 10 62 4 0 2
## 11 63 1 0 2
## 12 64 7 0 2
## 13 65 6 0 2
## 14 66 5 0 2
## 15 67 1 0 2
## 16 68 15 0 2
## 17 69 1 0 2
## 18 70 13 0 2
## 19 71 2 0 2
## 20 72 13 0 2
## 21 74 5 0 2
## 22 75 5 0 2
## 23 76 10 0 2
## 24 78 3 0 2
## 25 79 3 0 2
## 26 80 16 0 2
## 27 81 1 0 2
## 28 83 4 0 2
## 29 84 5 0 2
## 30 85 3 0 2
## 31 86 2 0 2
## 32 87 1 0 2
## 33 88 4 0 2
## 34 89 1 0 2
## 35 90 7 0 2
## 36 92 5 0 2
## 37 96 2 0 2
## 38 97 1 0 2
## 39 100 2 0 2
## 40 104 2 0 2mean(veri_son$Pulse)## [1] 73.91765