setwd("C:/Users/asus4/OneDrive/Desktop/TUGAS/VDE")
dataorg = read.csv("C:/Users/asus4/Downloads/organdata.csv", header=T, sep=",")
head(dataorg)
## country year donors pop pop_dens gdp gdp_lag health health_lag
## 1 Australia <NA> NA 17065 0.2204433 16774 16591 1300 1224
## 2 Australia 1/1/91 12.09 17284 0.2232723 17171 16774 1379 1300
## 3 Australia 1/1/92 12.35 17495 0.2259980 17914 17171 1455 1379
## 4 Australia 1/1/93 12.51 17667 0.2282198 18883 17914 1540 1455
## 5 Australia 1/1/94 10.25 17855 0.2306484 19849 18883 1626 1540
## 6 Australia 1/1/95 10.18 18072 0.2334516 21079 19849 1737 1626
## pubhealth roads cerebvas assault external txp_pop world opt
## 1 4.8 136.5954 682 21 444 0.9375916 Liberal In
## 2 5.4 122.2518 647 19 425 0.9257116 Liberal In
## 3 5.4 112.8322 630 17 406 0.9145470 Liberal In
## 4 5.4 110.5451 611 18 376 0.9056433 Liberal In
## 5 5.4 107.9810 631 17 387 0.8961075 Liberal In
## 6 5.5 111.6091 592 16 371 0.8853475 Liberal In
## consent_law consent_practice consistent ccode
## 1 Informed Informed Yes Oz
## 2 Informed Informed Yes Oz
## 3 Informed Informed Yes Oz
## 4 Informed Informed Yes Oz
## 5 Informed Informed Yes Oz
## 6 Informed Informed Yes Oz
tail(dataorg)
## country year donors pop pop_dens gdp gdp_lag health health_lag
## 233 United States 1/1/98 21.00 275854 2.864798 31612 30283 4096 3939
## 234 United States 1/1/99 20.87 279040 2.897885 33016 31612 4298 4096
## 235 United States 1/1/00 21.21 282224 2.930952 34590 33016 4538 4298
## 236 United States 1/1/01 21.31 285318 2.963084 35118 34590 4869 4538
## 237 United States 1/1/02 21.47 288369 2.994769 36006 35118 5267 4869
## 238 United States <NA> NA NA NA NA 36006 5665 5267
## pubhealth roads cerebvas assault external txp_pop world opt
## 233 5.8 150.4455 428 68 519 0.9932791 Liberal In
## 234 5.8 149.5019 440 64 514 0.9819381 Liberal In
## 235 5.8 148.6231 432 61 499 0.9708600 Liberal In
## 236 6.2 147.8911 424 58 484 0.9603320 Liberal In
## 237 6.6 148.4730 416 55 469 0.9501715 Liberal In
## 238 NA NA NA NA NA NA Liberal In
## consent_law consent_practice consistent ccode
## 233 Informed Informed Yes USA
## 234 Informed Informed Yes USA
## 235 Informed Informed Yes USA
## 236 Informed Informed Yes USA
## 237 Informed Informed Yes USA
## 238 Informed Informed Yes USA
nrow(dataorg)
## [1] 238
summary(dataorg)
## country year donors pop
## Length:238 Length:238 Min. : 5.20 Min. : 3514
## Class :character Class :character 1st Qu.:13.00 1st Qu.: 6938
## Mode :character Mode :character Median :15.10 Median : 15531
## Mean :16.48 Mean : 39921
## 3rd Qu.:19.60 3rd Qu.: 57301
## Max. :33.90 Max. :288369
## NA's :34 NA's :17
## pop_dens gdp gdp_lag health
## Min. : 0.2204 Min. :12917 Min. :11434 Min. : 791
## 1st Qu.: 1.9377 1st Qu.:19546 1st Qu.:19034 1st Qu.:1581
## Median : 9.4908 Median :22756 Median :22158 Median :1956
## Mean :12.0011 Mean :22986 Mean :22575 Mean :2074
## 3rd Qu.:19.1106 3rd Qu.:26180 3rd Qu.:25887 3rd Qu.:2408
## Max. :38.8851 Max. :36554 Max. :36554 Max. :5665
## NA's :17 NA's :17
## health_lag pubhealth roads cerebvas
## Min. : 727 Min. :4.30 Min. : 58.21 Min. :300.0
## 1st Qu.:1542 1st Qu.:5.50 1st Qu.: 83.46 1st Qu.:500.0
## Median :1850 Median :6.00 Median :111.22 Median :604.0
## Mean :1973 Mean :6.19 Mean :113.04 Mean :610.8
## 3rd Qu.:2290 3rd Qu.:6.90 3rd Qu.:139.57 3rd Qu.:698.0
## Max. :5267 Max. :8.80 Max. :232.48 Max. :957.0
## NA's :21 NA's :17 NA's :17
## assault external txp_pop world
## Min. : 4.00 Min. :258.0 Min. :0.2204 Length:238
## 1st Qu.: 9.00 1st Qu.:367.0 1st Qu.:0.6268 Class :character
## Median : 11.00 Median :421.0 Median :0.7116 Mode :character
## Mean : 16.53 Mean :450.1 Mean :0.7214
## 3rd Qu.: 16.00 3rd Qu.:534.0 3rd Qu.:0.8313
## Max. :103.00 Max. :853.0 Max. :1.1191
## NA's :17 NA's :17 NA's :17
## opt consent_law consent_practice consistent
## Length:238 Length:238 Length:238 Length:238
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## ccode
## Length:238
## Class :character
## Mode :character
##
##
##
##
unique(dataorg$country)
## [1] "Australia" "Austria" "Belgium" "Canada"
## [5] "Denmark" "Finland" "France" "Germany"
## [9] "Italy" "Ireland" "Netherlands" "Norway"
## [13] "Spain" "Sweden" "Switzerland" "United Kingdom"
## [17] "United States"
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.3.3
p1 <- ggplot(data = dataorg, mapping = aes(x = year, y = donors))
p1 + geom_point()
## Warning: Removed 34 rows containing missing values or values outside the scale range
## (`geom_point()`).
p2 <- ggplot(data = dataorg, mapping = aes(x = year, y = donors))
p2 + geom_line(aes(group = country)) + facet_wrap(~country)
## Warning: Removed 34 rows containing missing values or values outside the scale range
## (`geom_line()`).
p3 <- ggplot(data = dataorg, mapping = aes(x = country, y = donors))
p3 + geom_boxplot()
## Warning: Removed 34 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
p3 <- ggplot(data = dataorg, mapping = aes(x = country, y = donors))
p3 + geom_boxplot() + coord_flip()
## Warning: Removed 34 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
p3 <- ggplot(data = dataorg, mapping = aes(x = reorder(country, donors, na.rm = TRUE), y = donors))
p3 + geom_boxplot() + coord_flip() + labs(x = NULL, y = "Donors")
## Warning: Removed 34 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
p3 <- ggplot(data = dataorg, mapping = aes(x = reorder(country, donors, na.rm = TRUE), y = donors, fill=world))
p3 + geom_boxplot() + coord_flip() + labs(x = NULL, y = "Donors") + theme(legend.position = "top")
## Warning: Removed 34 rows containing non-finite outside the scale range
## (`stat_boxplot()`).
p4 <- ggplot(data = dataorg,
mapping = aes(x = reorder(country, donors, na.rm=TRUE),
y = donors, color = world))
p4 + geom_jitter(position = position_jitter(width=0.15)) + labs(x=NULL, y = "Donors") + coord_flip() + theme(legend.position = "top")
## Warning: Removed 34 rows containing missing values or values outside the scale range
## (`geom_point()`).
