Dünya bankasından veri indirmek

library(WDI)

DT.DOD.DECT.GN.ZS “Stocks de la dette extérieure (% du RNB)” TX.VAL.FUEL.ZS.UN “Yakıt ihracatı (mal ihracatının yüzdesi)”

data <- WDI(indicator = c("DT.DOD.DECT.GN.ZS","TX.VAL.FUEL.ZS.UN"))

Kesit veri

2000

library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
data2000 <- data %>% filter(year==2000)
dataSO <- data %>% filter(country=="Somalia")
library(ggplot2)
ggplot(dataSO,aes(year,DT.DOD.DECT.GN.ZS)) +geom_line()
## Warning: Removed 11 rows containing missing values or values outside the scale range
## (`geom_line()`).

ggplot(dataSO,aes(year,DT.DOD.DECT.GN.ZS)) +geom_point()
## Warning: Removed 33 rows containing missing values or values outside the scale range
## (`geom_point()`).

data2000 <- data %>% filter(year==2000)
view(data2000)
data2000 <- data2000 %>% filter(year==2000)
data2000 <- data2000 %>% aes(!is.na(DT.DOD.DECT.GN.ZS))
data2000 <- data2000 %>% aes(!is.na(TX.VAL.FUEL.ZS.UN))
library(ggplot2)
ggplot(data, aes(DT.DOD.DECT.GN.ZS)) + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 11284 rows containing non-finite outside the scale range
## (`stat_bin()`).

ggplot(dataSO,aes(year,TX.VAL.FUEL.ZS.UN)) +geom_line()
## Warning: Removed 43 rows containing missing values or values outside the scale range
## (`geom_line()`).

ggplot(dataSO,aes(year,TX.VAL.FUEL.ZS.UN)) +geom_point()
## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).

library(ggplot2)
ggplot(data, aes(TX.VAL.FUEL.ZS.UN)) + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 7883 rows containing non-finite outside the scale range
## (`stat_bin()`).

Regresyon

model <- lm(DT.DOD.DECT.GN.ZS ~ TX.VAL.FUEL.ZS.UN, data = dataSO)
summary(model)
## 
## Call:
## lm(formula = DT.DOD.DECT.GN.ZS ~ TX.VAL.FUEL.ZS.UN, data = dataSO)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -30.98 -28.55 -22.67  11.07  79.55 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)   
## (Intercept)         53.652     13.783   3.893    0.003 **
## TX.VAL.FUEL.ZS.UN   12.463      9.351   1.333    0.212   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 42.58 on 10 degrees of freedom
##   (52 observations effacées parce que manquantes)
## Multiple R-squared:  0.1509, Adjusted R-squared:  0.06594 
## F-statistic: 1.776 on 1 and 10 DF,  p-value: 0.2122