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, union
library(MASS)
## 
## Attaching package: 'MASS'
## The following object is masked from 'package:dplyr':
## 
##     select
data("survey")
head(survey)
##      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
##      Age
## 1 18.250
## 2 17.583
## 3 16.917
## 4 20.333
## 5 23.667
## 6 21.000
tail(survey)
##        Sex Wr.Hnd NW.Hnd W.Hnd   Fold Pulse  Clap Exer Smoke Height      M.I
## 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
## 232 20.750
## 233 17.667
## 234 16.917
## 235 18.583
## 236 17.167
## 237 17.750
names(survey)
##  [1] "Sex"    "Wr.Hnd" "NW.Hnd" "W.Hnd"  "Fold"   "Pulse"  "Clap"   "Exer"  
##  [9] "Smoke"  "Height" "M.I"    "Age"
veri1 <-survey %>% 
 dplyr::select(Sex,Age,Smoke,Height,Exer,Pulse)
veri2 <-veri1 %>% 
  rename(yaş=Age,
         cinsiyet=Sex,
         sigara=Smoke,
         nabız=Pulse,
         egzersiz=Exer,
         boy=Height)
veri2 %>% 
  count(egzersiz)
##   egzersiz   n
## 1     Freq 115
## 2     None  24
## 3     Some  98
veri2 %>% 
  count(boy) %>% 
  mutate(yuzde=
round((n/sum(n))*100,2))
##       boy  n yuzde
## 1  150.00  1  0.42
## 2  152.00  1  0.42
## 3  152.40  1  0.42
## 4  153.50  1  0.42
## 5  154.94  2  0.84
## 6  155.00  2  0.84
## 7  156.00  1  0.42
## 8  156.20  1  0.42
## 9  157.00  3  1.27
## 10 157.48  3  1.27
## 11 158.00  1  0.42
## 12 159.00  2  0.84
## 13 160.00  5  2.11
## 14 160.02  3  1.27
## 15 162.50  1  0.42
## 16 162.56  4  1.69
## 17 163.00  3  1.27
## 18 164.00  4  1.69
## 19 165.00 14  5.91
## 20 165.10  4  1.69
## 21 166.40  1  0.42
## 22 166.50  1  0.42
## 23 167.00  7  2.95
## 24 167.64  5  2.11
## 25 168.00  8  3.38
## 26 168.50  1  0.42
## 27 168.90  1  0.42
## 28 169.00  2  0.84
## 29 169.20  1  0.42
## 30 170.00 14  5.91
## 31 170.18  4  1.69
## 32 171.00  5  2.11
## 33 171.50  1  0.42
## 34 172.00  7  2.95
## 35 172.72  6  2.53
## 36 173.00  4  1.69
## 37 174.00  1  0.42
## 38 175.00  5  2.11
## 39 175.26  5  2.11
## 40 176.00  2  0.84
## 41 176.50  2  0.84
## 42 177.00  3  1.27
## 43 177.80  2  0.84
## 44 178.00  2  0.84
## 45 178.50  1  0.42
## 46 179.00  3  1.27
## 47 179.10  2  0.84
## 48 180.00  8  3.38
## 49 180.34  9  3.80
## 50 182.00  1  0.42
## 51 182.50  1  0.42
## 52 182.88  4  1.69
## 53 183.00  3  1.27
## 54 184.00  2  0.84
## 55 185.00  6  2.53
## 56 185.42  2  0.84
## 57 187.00  3  1.27
## 58 187.96  3  1.27
## 59 188.00  1  0.42
## 60 189.00  2  0.84
## 61 190.00  3  1.27
## 62 190.50  3  1.27
## 63 191.80  1  0.42
## 64 193.04  1  0.42
## 65 195.00  1  0.42
## 66 196.00  1  0.42
## 67 200.00  1  0.42
## 68     NA 28 11.81
#not:öğrencilerin %3.38'i (n=8) boyu 180'dir.