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summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

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datakesehatan <- read.csv("data_kesehatan.csv")

zzz

library(readxl)
dataexcel <- read_xlsx("df_mahasiswa.xlsx")

zzz

databaru <- data.frame(datasets::Titanic)

zz

?Titanic
## starting httpd help server ... done
str(Titanic)
##  'table' num [1:4, 1:2, 1:2, 1:2] 0 0 35 0 0 0 17 0 118 154 ...
##  - attr(*, "dimnames")=List of 4
##   ..$ Class   : chr [1:4] "1st" "2nd" "3rd" "Crew"
##   ..$ Sex     : chr [1:2] "Male" "Female"
##   ..$ Age     : chr [1:2] "Child" "Adult"
##   ..$ Survived: chr [1:2] "No" "Yes"
summary(Titanic)
## Number of cases in table: 2201 
## Number of factors: 4 
## Test for independence of all factors:
##  Chisq = 1637.4, df = 25, p-value = 0
##  Chi-squared approximation may be incorrect

z

summary(datakesehatan)
##        X                id              umur         jenis_kelamin
##  Min.   :  1.00   Min.   :  1.00   Min.   :18.00   Length   :200  
##  1st Qu.: 50.75   1st Qu.: 50.75   1st Qu.:32.00   N.unique :  2  
##  Median :100.50   Median :100.50   Median :43.00   N.blank  :  0  
##  Mean   :100.50   Mean   :100.50   Mean   :44.31   Min.nchar:  9  
##  3rd Qu.:150.25   3rd Qu.:150.25   3rd Qu.:56.00   Max.nchar:  9  
##  Max.   :200.00   Max.   :200.00   Max.   :70.00                  
##   tinggi_badan    berat_badan      gula_darah     tekanan_sistolik
##  Min.   :143.1   Min.   :39.94   Min.   : 49.01   Min.   : 85.29  
##  1st Qu.:159.4   1st Qu.:57.82   1st Qu.: 86.74   1st Qu.:108.77  
##  Median :165.1   Median :63.35   Median :100.44   Median :119.92  
##  Mean   :165.8   Mean   :64.75   Mean   :101.01   Mean   :119.53  
##  3rd Qu.:171.7   3rd Qu.:72.17   3rd Qu.:111.90   3rd Qu.:129.62  
##  Max.   :186.9   Max.   :96.92   Max.   :163.68   Max.   :170.86  
##  tekanan_diastolik   kolesterol     skor_kesehatan  
##  Min.   : 53.05    Min.   : 98.56   Min.   : 45.45  
##  1st Qu.: 74.21    1st Qu.:172.44   1st Qu.: 84.30  
##  Median : 81.64    Median :190.25   Median : 92.92  
##  Mean   : 80.64    Mean   :191.80   Mean   : 89.61  
##  3rd Qu.: 87.18    3rd Qu.:216.47   3rd Qu.:100.00  
##  Max.   :102.84    Max.   :288.72   Max.   :100.00
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
databaru_selected <- select(databaru, Class, Sex, Survived)
databaru_selected
##    Class    Sex Survived
## 1    1st   Male       No
## 2    2nd   Male       No
## 3    3rd   Male       No
## 4   Crew   Male       No
## 5    1st Female       No
## 6    2nd Female       No
## 7    3rd Female       No
## 8   Crew Female       No
## 9    1st   Male       No
## 10   2nd   Male       No
## 11   3rd   Male       No
## 12  Crew   Male       No
## 13   1st Female       No
## 14   2nd Female       No
## 15   3rd Female       No
## 16  Crew Female       No
## 17   1st   Male      Yes
## 18   2nd   Male      Yes
## 19   3rd   Male      Yes
## 20  Crew   Male      Yes
## 21   1st Female      Yes
## 22   2nd Female      Yes
## 23   3rd Female      Yes
## 24  Crew Female      Yes
## 25   1st   Male      Yes
## 26   2nd   Male      Yes
## 27   3rd   Male      Yes
## 28  Crew   Male      Yes
## 29   1st Female      Yes
## 30   2nd Female      Yes
## 31   3rd Female      Yes
## 32  Crew Female      Yes
databaru_sorted_asc <- arrange(databaru, Freq)
head(databaru_sorted_asc)
##   Class    Sex   Age Survived Freq
## 1   1st   Male Child       No    0
## 2   2nd   Male Child       No    0
## 3  Crew   Male Child       No    0
## 4   1st Female Child       No    0
## 5   2nd Female Child       No    0
## 6  Crew Female Child       No    0
databaru_Child <- filter(databaru, Age == "Child")
head(databaru_Child)
##   Class    Sex   Age Survived Freq
## 1   1st   Male Child       No    0
## 2   2nd   Male Child       No    0
## 3   3rd   Male Child       No   35
## 4  Crew   Male Child       No    0
## 5   1st Female Child       No    0
## 6   2nd Female Child       No    0