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Install: R language, RTools40, and RStudio (see link below)
Packages: GGPLot2, dplyr, janitor.
Download code and data from Github.com (see link below).
Move R code and data to the working directory
library(ggplot2)
library(scales)
library(tidyr)
library(dplyr)
vegetable_consumption <- read.csv("./DATA/20-vegetable-consumption-per-capita.csv")
colnames(vegetable_consumption) <- c("Country","Code","Year","Vegetables")
vegetable_consumption %>% filter(Country == "World") %>%
ggplot() + geom_line(aes(x=Year,y=Vegetables)) +
scale_y_continuous(labels=comma) +
labs(title="Worldwide Vegetable Consumption Per Capita by Year",
subtitle = "(1961 - 2017)",
y="Kilogram/Person/Year")
vegie_top <- vegetable_consumption %>% filter(Year =="2017") %>% top_n(5,Vegetables) vegie_top <- as.data.frame(vegie_top) ggplot(vegie_top) + geom_col(aes(x=reorder(Country,Vegetables),y=Vegetables)) + coord_flip() + labs(title="Top Five Countries Rata by Per Capita Consumption")
vegie_bottom <- vegetable_consumption %>% filter(Year =="2017") %>% top_n(-5,Vegetables) vegie_bottom <- as.data.frame(vegie_bottom) ggplot(vegie_bottom) + geom_col(aes(x=reorder(Country,Vegetables),y=Vegetables)) + coord_flip() + labs(title="Bottom Five Countries Rata by Per Capita Consumption")
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