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⬅️ Previous capture (2021-12-04)
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library(ggplot2)
library(scales)
library(dplyr)
library(tidyr)
rm(list=ls())
vegetable_consumption <- read.csv("./DATA/20-vegetable-consumption-per-capita.csv")
colnames(vegetable_consumption) <- c("Country","Code","Year","Vegetables")
vegetable_consumption %>% filter(Country == "United States") %>%
ggplot() + geom_line(aes(x=Year,y=Vegetables),lwd=2,col="red") +
scale_y_continuous(labels=comma) +
labs(title="United States Vegetable Consumption Per Capita by Year",
subtitle = "(1961 - 2017)",
y="Kilogram/Person/Year")
US Veggie Consumption Per-Capita
vegie_top <- vegetable_consumption %>% filter(Year =="2017") %>% top_n(5,Vegetables)
vegie_top <- as.data.frame(vegie_top)
countries_top_five <- vegie_top %>% select(Country) %>% left_join(vegetable_consumption,by="Country")
head(countries_top_five)
tail(countries_top_five)
ggplot(countries_top_five) + geom_line(aes(x=Year,y=Vegetables,col=Country)) +
labs(title = "Vegetables Consumption Kg/Person/Year",subtitle = "( Top 5 countries)",
y="Vegetables Consumed per person Kg")
ggplot(countries_top_five) + geom_col(aes(x=Year,y=Vegetables)) +
facet_wrap(~Country) + labs(title="Top Five Countries by Per Capita ",
subtitle = "(Vegetable Consumption per Capita)",
y="Vegetables by Kg/Person/Year")
