library(ggplot2) library(scales) library(dplyr) library(tidyr) ## Import Fruit Consumption data rm(list=ls()) fruit <- read.csv("./DATA/1-fruit-consumption-per-capita.csv") fruit <- fruit %>%select(-Code) colnames(fruit) <- c("Country","Year","Fruits") fruits_top <- fruit %>% filter(Year =="2017") %>% top_n(5,Fruits) fruits_top <- as.data.frame(fruits_top) ggplot(fruits_top) + geom_col(aes(x=reorder(Country,Fruits),y=Fruits)) + coord_flip() + labs(title="Top 5 countries by per Capita Fruit Production") countries_five <- fruits_top %>% select(Country) %>% left_join(fruit,by="Country") head(countries_five) tail(countries_five) ### Plot Top % Countries by Kg cosummed per year per person. ## ggplot(countries_five) + geom_line(aes(x=Year,y=Fruits,col=Country)) + labs(title = "Fruit Consumption Kg/Person/Year",subtitle = "( Top 5 countries)", y="Fruit Consumed per person Kg") ### Plot of US Fruit consumption fruit %>% filter(Country =="United States") %>% ggplot() + geom_line(aes(x=Year,y=Fruits)) + labs(title="US Fruit Consumption: Kg/Year/Person (1960-2017)", y="Kilograms Per Person")
countries_five %>% filter(Year >="2010") %>% ggplot() + geom_col(aes(x=Country,y=Fruits)) + facet_wrap(~Year,ncol=2) + coord_flip() + labs(title="Fruit Consumption by Country by Year/Kg/Person") ggplot(countries_five) + geom_line(aes(x=Year,y=Fruits,col=Country)) + labs(title = "Fruit Consumption Kg/Person/Year",subtitle = "( Top 5 countries)", y="Fruit Consumed per person Kg") + facet_wrap(~Country,scale="free_y",ncol=2) + geom_smooth(aes(x=Year, y= Fruits),method="lm")
Fruit Comsumption by Country/Year
R Language and Rtools40 (click and "base" and "Rtools")