Değişken Açıklamaları: -
NY.GDP.MKTP.KD.ZG = GSYH büyüme oranı (yıllık %) -
NE.EXP.GNFS.ZS = Mal ve hizmet ihracatının GSYH içindeki
payı (%)
library(WDI)
library(tidyverse)
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## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.0.4
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(explore)
library(ggplot2)
data <- WDI(indicator = c("NY.GDP.MKTP.KD.ZG", "NE.EXP.GNFS.ZS"), extra = TRUE)
str(data)
## 'data.frame': 17024 obs. of 14 variables:
## $ country : chr "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
## $ iso2c : chr "AF" "AF" "AF" "AF" ...
## $ iso3c : chr "AFG" "AFG" "AFG" "AFG" ...
## $ year : int 1967 1962 1963 1961 1966 1996 1960 1998 1999 2000 ...
## $ status : chr "" "" "" "" ...
## $ lastupdated : chr "2025-01-28" "2025-01-28" "2025-01-28" "2025-01-28" ...
## $ NY.GDP.MKTP.KD.ZG: num NA NA NA NA NA NA NA NA NA NA ...
## ..- attr(*, "label")= chr "GDP growth (annual %)"
## $ NE.EXP.GNFS.ZS : num NA NA NA NA NA NA NA NA NA NA ...
## ..- attr(*, "label")= chr "Exports of goods and services (% of GDP)"
## $ region : chr "South Asia" "South Asia" "South Asia" "South Asia" ...
## $ capital : chr "Kabul" "Kabul" "Kabul" "Kabul" ...
## $ longitude : chr "69.1761" "69.1761" "69.1761" "69.1761" ...
## $ latitude : chr "34.5228" "34.5228" "34.5228" "34.5228" ...
## $ income : chr "Low income" "Low income" "Low income" "Low income" ...
## $ lending : chr "IDA" "IDA" "IDA" "IDA" ...
data %>% summarise_all(~ sum(is.na(.)))
## country iso2c iso3c year status lastupdated NY.GDP.MKTP.KD.ZG NE.EXP.GNFS.ZS
## 1 0 0 0 0 0 0 3141 5977
## region capital longitude latitude income lending
## 1 448 448 448 448 448 448
df_turkiye <- data %>% filter(country == "Turkey")
GSYH büyüme oranı grafiği:
ggplot(data = df_turkiye, aes(x = year, y = NY.GDP.MKTP.KD.ZG)) +
geom_line() +
labs(title = "Türkiye GSYH Büyüme Oranı", x = "Yıl", y = "Büyüme (%)") +
theme_minimal()
df_turkiye <- df_turkiye %>%
mutate(devletinpayi = NE.EXP.GNFS.ZS - NY.GDP.MKTP.KD.ZG)
ggplot(df_turkiye, aes(x = year, y = devletinpayi)) +
geom_line() +
labs(title = "Türkiye'de Devletin Payı", x = "Yıl", y = "Pay (%)") +
theme_minimal()
data_world <- data %>% filter(country == "World") %>%
select(year, NY.GDP.MKTP.KD.ZG) %>%
rename(W_gsyih = NY.GDP.MKTP.KD.ZG)
bos_data <- data %>% group_by(country) %>% summarise(toplam_bos = sum(is.na(NE.EXP.GNFS.ZS)))
kalacak_ulkeler <- bos_data %>% filter(toplam_bos == 0) %>% pull(country)
df_tam <- data %>% filter(country %in% kalacak_ulkeler)
df_tam <- df_tam %>%
left_join(data_world, by = "year") %>%
mutate(ulke_orani = NY.GDP.MKTP.KD.ZG / W_gsyih,
MvHI = NE.EXP.GNFS.ZS / W_gsyih,
devletinpayi = ulke_orani - MvHI)
df_Germany <- df_tam %>% filter(country == "Germany")
ggplot(df_Germany, aes(x = year, y = NY.GDP.MKTP.KD.ZG)) +
geom_line() +
labs(title = "Almanya GSYH Büyüme Oranı", x = "Yıl", y = "Büyüme (%)") +
theme_minimal()
data <- data.frame(
Year = 2010:2020,
Germany = c(40, 41, 42, 42, 43, 43, 44, 45, 46, 46, 47),
Turkey = c(30, 30, 30, 30, 30, 30, 30, 31, 32, 33, 34)
)
data_long <- data %>% pivot_longer(cols = c(Germany, Turkey), names_to = "Country", values_to = "Tax_Rate")
ggplot(data_long, aes(x = Year, y = Tax_Rate, color = Country)) +
geom_line(size = 1) +
geom_point(size = 3) +
labs(title = "Alamanya ve Türkiye GSYH Oranı Karşılaştırması (2010-2020)",
x = "Yıl", y = "Oran (%)", color = "Ülke") +
theme_minimal()
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.