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
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, Pulse, Exer, Height, Smoke)
head(veri1)
##      Sex    Age Pulse Exer Height Smoke
## 1 Female 18.250    92 Some 173.00 Never
## 2   Male 17.583   104 None 177.80 Regul
## 3   Male 16.917    87 None     NA Occas
## 4   Male 20.333    NA None 160.00 Never
## 5   Male 23.667    35 Some 165.00 Never
## 6 Female 21.000    64 Some 172.72 Never
veri2<-veri1 %>% rename(cinsiyet=Sex, yas=Age, boy=Height,sigara= Smoke,egzersiz=Exer,nabiz=Pulse)
head(veri2)
##   cinsiyet    yas nabiz egzersiz    boy sigara
## 1   Female 18.250    92     Some 173.00  Never
## 2     Male 17.583   104     None 177.80  Regul
## 3     Male 16.917    87     None     NA  Occas
## 4     Male 20.333    NA     None 160.00  Never
## 5     Male 23.667    35     Some 165.00  Never
## 6   Female 21.000    64     Some 172.72  Never
names(veri2)
## [1] "cinsiyet" "yas"      "nabiz"    "egzersiz" "boy"      "sigara"
veri3<-veri2 %>% 
  mutate(cinsiyet= recode(cinsiyet, "Female"= "Kadın","Male"= "Erkek"),
         egzersiz=recode(egzersiz,
                         "None"="Yok",
                         "Some"="Bazen",
                         "Freq"="Sık"),
         sigara= recode(sigara,
                        "Never"= "Hiç",
                        "Occas"="Ara Sıra",
                        "Regul"="Düzenli",
                        "Heavy"="Fazla"))
head (veri3)
##   cinsiyet    yas nabiz egzersiz    boy   sigara
## 1    Kadın 18.250    92    Bazen 173.00      Hiç
## 2    Erkek 17.583   104      Yok 177.80  Düzenli
## 3    Erkek 16.917    87      Yok     NA Ara Sıra
## 4    Erkek 20.333    NA      Yok 160.00      Hiç
## 5    Erkek 23.667    35    Bazen 165.00      Hiç
## 6    Kadın 21.000    64    Bazen 172.72      Hiç
is.na(veri3)
##     cinsiyet   yas nabiz egzersiz   boy sigara
## 1      FALSE FALSE FALSE    FALSE FALSE  FALSE
## 2      FALSE FALSE FALSE    FALSE FALSE  FALSE
## 3      FALSE FALSE FALSE    FALSE  TRUE  FALSE
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## 227    FALSE FALSE FALSE    FALSE FALSE  FALSE
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any(is.na(veri3))
## [1] TRUE
colSums(is.na(veri3))
## cinsiyet      yas    nabiz egzersiz      boy   sigara 
##        1        0       45        0       28        1
veri_son<- na.omit(veri3)
summary(veri_son)
##   cinsiyet       yas            nabiz         egzersiz       boy       
##  Kadın:85   Min.   :16.92   Min.   : 35.00   Sık  :86   Min.   :152.0  
##  Erkek:85   1st Qu.:17.67   1st Qu.: 66.25   Yok  :14   1st Qu.:165.0  
##             Median :18.58   Median : 72.00   Bazen:70   Median :171.0  
##             Mean   :20.46   Mean   : 73.92              Mean   :172.5  
##             3rd Qu.:20.17   3rd Qu.: 80.00              3rd Qu.:180.0  
##             Max.   :70.42   Max.   :104.00              Max.   :200.0  
##       sigara   
##  Fazla   :  7  
##  Hiç     :136  
##  Ara Sıra: 13  
##  Düzenli : 14  
##                
## 
table(veri_son$cinsiyet)
## 
## Kadın Erkek 
##    85    85
prop.table(table(veri_son$cinsiyet))*100
## 
## Kadın Erkek 
##    50    50
table(veri_son$sigara)
## 
##    Fazla      Hiç Ara Sıra  Düzenli 
##        7      136       13       14
prop.table(table(veri_son$sigara))*100
## 
##     Fazla       Hiç  Ara Sıra   Düzenli 
##  4.117647 80.000000  7.647059  8.235294
veri_son %>% count(sigara) %>% mutate (yuzde=round((n/sum(n))*100,2))
##     sigara   n yuzde
## 1    Fazla   7  4.12
## 2      Hiç 136 80.00
## 3 Ara Sıra  13  7.65
## 4  Düzenli  14  8.24
veri_son %>% count(egzersiz) %>% mutate(yuzde=round((n/sum(n))*100,2))
##   egzersiz  n yuzde
## 1      Sık 86 50.59
## 2      Yok 14  8.24
## 3    Bazen 70 41.18
veri_son %>% group_by(egzersiz) %>% summarise(ortalama_nabiz=round(mean(nabiz),2))
## # A tibble: 3 × 2
##   egzersiz ortalama_nabiz
##   <fct>             <dbl>
## 1 Sık                71.4
## 2 Yok                75.9
## 3 Bazen              76.6
mean(veri_son$boy)
## [1] 172.5198
median(veri_son$boy)
## [1] 171
library(lsr)
modeOf(veri_son$boy)
## [1] 165