week4

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##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
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##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
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##  Max.   :25.0   Max.   :120.00

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data("titanic")

## Warning in data("titanic"): data set 'titanic' not found

Titanic <- as.data.frame(Titanic)
Titanic

##    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
## 7    3rd Female Child       No   17
## 8   Crew Female Child       No    0
## 9    1st   Male Adult       No  118
## 10   2nd   Male Adult       No  154
## 11   3rd   Male Adult       No  387
## 12  Crew   Male Adult       No  670
## 13   1st Female Adult       No    4
## 14   2nd Female Adult       No   13
## 15   3rd Female Adult       No   89
## 16  Crew Female Adult       No    3
## 17   1st   Male Child      Yes    5
## 18   2nd   Male Child      Yes   11
## 19   3rd   Male Child      Yes   13
## 20  Crew   Male Child      Yes    0
## 21   1st Female Child      Yes    1
## 22   2nd Female Child      Yes   13
## 23   3rd Female Child      Yes   14
## 24  Crew Female Child      Yes    0
## 25   1st   Male Adult      Yes   57
## 26   2nd   Male Adult      Yes   14
## 27   3rd   Male Adult      Yes   75
## 28  Crew   Male Adult      Yes  192
## 29   1st Female Adult      Yes  140
## 30   2nd Female Adult      Yes   80
## 31   3rd Female Adult      Yes   76
## 32  Crew Female Adult      Yes   20

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

Titanic <- select(Titanic,Class,Sex,Survived)
head(Titanic)

##   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

pengeluaran <- data.frame(
  tanggal = as.Date(c("2026-09-01", "2026-09-02", "2026-09-02", "2026-09-03", "2026-09-04", "2026-09-05")),
  kategori = c("Makanan", "Transport", "Makanan", "Hiburan", "Transport", "Makanan"),
  jumlah = c(50000, 20000, 35000, 150000, 15000, 45000),
  metode_bayar = c("Cash", "E-wallet", "E-wallet", "Credit Card", "Cash", "E-wallet")
)

pengeluaran

##      tanggal  kategori jumlah metode_bayar
## 1 2026-09-01   Makanan  50000         Cash
## 2 2026-09-02 Transport  20000     E-wallet
## 3 2026-09-02   Makanan  35000     E-wallet
## 4 2026-09-03   Hiburan 150000  Credit Card
## 5 2026-09-04 Transport  15000         Cash
## 6 2026-09-05   Makanan  45000     E-wallet

pengeluaran <- filter(pengeluaran, kategori == "Makanan")
pengeluaran

##      tanggal kategori jumlah metode_bayar
## 1 2026-09-01  Makanan  50000         Cash
## 2 2026-09-02  Makanan  35000     E-wallet
## 3 2026-09-05  Makanan  45000     E-wallet

pengeluaran2 <- arrange(pengeluaran, jumlah)
pengeluaran2

##      tanggal kategori jumlah metode_bayar
## 1 2026-09-02  Makanan  35000     E-wallet
## 2 2026-09-05  Makanan  45000     E-wallet
## 3 2026-09-01  Makanan  50000         Cash