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⬅️ Previous capture (2021-12-04)
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library(ggplot2) library(scales) library(dplyr) library(janitor) ## Read Data rm(list=ls()) df <- read.csv("./prevalence-of-drug-use-disorders-by-age.csv") df <- clean_names(df) colnames(df) <- c("County","Code","Year","age_14","age_19","age_24", "age_29","age_34","all_age_percent","male_14","age_49", "age_70","standard_percent") US <- df %>% filter(Code=="USA") %>% select(Year:standard_percent) str(df) ## ggplot(US) + geom_line(aes(x=Year,y=standard_percent)) + labs(title="Standard Percent") ## ggplot(US) + geom_line(aes(x=Year,y=age_14,col="age_14")) + geom_line(aes(x=Year,y=age_19,col="age_19")) + geom_line(aes(x=Year,y=age_24,col="age_24")) + geom_line(aes(x=Year,y=age_24,col="age_24")) + geom_line(aes(x=Year,y=age_29,col="age_29")) + geom_line(aes(x=Year,y=age_34,col="age_34")) + geom_line(aes(x=Year,y=age_49,col="age_49")) + labs(title = "prevalence-of-drug-use-disorders-by-age: 10-49 Years", y="prevalence (%) ") + guides(color = guide_legend(override.aes = list(size = 2)))
Plot: