## ---- eval=FALSE--------------------------------------------------------- library('gapminder') ## ------------------------------------------------------------------------ gapminder <- readRDS('data/gapminder.rds') ## ------------------------------------------------------------------------ head(gapminder) ## ------------------------------------------------------------------------ gapminder$country ## ------------------------------------------------------------------------ countries <- gapminder$country countries ## ------------------------------------------------------------------------ head(gapminder) ## ------------------------------------------------------------------------ gapminder[3, ] ## ------------------------------------------------------------------------ gapminder[2, 3] ## ------------------------------------------------------------------------ gapminder[-(1:1650), 3] ## ------------------------------------------------------------------------ gapminder[c(2,4), -3] ## ------------------------------------------------------------------------ gapminder[c(2,4), c("country", "pop")] ## ------------------------------------------------------------------------ gapminder[gapminder$lifeExp>82, c("country", "pop")] ## ------------------------------------------------------------------------ subset(gapminder, pop>1000000000) ## ------------------------------------------------------------------------ subset(gapminder, pop>1000000000 & country=='India') ## ------------------------------------------------------------------------ subset(gapminder, pop>1000000000 | continent=='Oceania') ## ------------------------------------------------------------------------ africa <- subset(gapminder, continent=='Africa') africa ## ------------------------------------------------------------------------ year_2007 <- gapminder[gapminder$year==2007, ] year_2007 ## ---- eval=FALSE--------------------------------------------------------- gapminder[2, 1] gapminder[1, 3] gapminder[, 1] gapminder[1] gapminder[1, ] gapminder[0, 3] gapminder[-2, ] gapminder[, -1] gapminder[c(1,5,7), ] gapminder[, c(1,2)] gapminder[gapminder$pop<100000, ] gapminder[gapminder$year==1952, c(4)] ## ---- eval=FALSE--------------------------------------------------------- gapminder$lifeExp ## ---- echo=FALSE--------------------------------------------------------- head(gapminder$lifeExp) ## ---- eval=FALSE--------------------------------------------------------- gapminder$continent ## ---- echo=FALSE--------------------------------------------------------- head(gapminder$continent) ## ------------------------------------------------------------------------ # install.packages('dplyr') # devtools::install_github("tidyverse/dplyr") library('dplyr') ## ------------------------------------------------------------------------ gapminder_sel1 <- select(gapminder, country, year, pop) ## ------------------------------------------------------------------------ gapminder_sel2 <- select(gapminder, -continent) ## ------------------------------------------------------------------------ gapminder_arr1 <- arrange(gapminder, lifeExp) ## ------------------------------------------------------------------------ gapminder_arr1 <- arrange(gapminder, desc(lifeExp)) ## ------------------------------------------------------------------------ gapminder_fil1 <- filter(gapminder, year == 2007) ## ------------------------------------------------------------------------ gapminder_fil2 <- filter(gapminder, year == 2007 & pop <= 999999) ## ------------------------------------------------------------------------ gapminder_fil2 <- filter(gapminder, continent != 'Asia' | lifeExp < 30) ## ------------------------------------------------------------------------ gapminder_mut1 <- mutate(gapminder, gdp_mil = (gdpPercap * pop) / 1000000) ## ------------------------------------------------------------------------ gapminder_sum1 <- summarize(gapminder, mean_le = mean(lifeExp)) ## ---- echo=FALSE--------------------------------------------------------- gapminder_sum1 ## ------------------------------------------------------------------------ gapminder_sum2 <- summarize(gapminder, mean_le = mean(lifeExp), min_le = min(lifeExp), max_le = max(lifeExp)) ## ---- echo=FALSE--------------------------------------------------------- gapminder_sum2 ## ------------------------------------------------------------------------ gapminder2007 <- filter(gapminder, year == 2007) gapminder_grp1 <- group_by(gapminder2007, continent) ## ---- echo=FALSE--------------------------------------------------------- head(gapminder_grp1) ## ------------------------------------------------------------------------ gapminder_grp1 <- summarize(gapminder_grp1, mean_lifeExp = mean(lifeExp)) ## ------------------------------------------------------------------------ # install.packages('tidyr') library('tidyr') ## ------------------------------------------------------------------------ gapminder_sel <- select(gapminder, -continent, -lifeExp, -gdpPercap) gapminder_spread <- spread(gapminder_sel, country, pop) ## ------------------------------------------------------------------------ gapminder_gather <- gather(gapminder_spread, country, pop, -year) ## ------------------------------------------------------------------------ gapminder_sel <- select(gapminder, country, continent, pop) gapminder_africa <- filter(gapminder_sel, continent=='Africa') ## ------------------------------------------------------------------------ gapminder_africa <- filter(select(gapminder, country, continent, pop), continent=='Africa') ## ------------------------------------------------------------------------ gapminder_africa <- gapminder %>% select(country, continent, pop) %>% filter(continent=='Africa') ## ------------------------------------------------------------------------ gapminder_proc <- gapminder %>% filter(continent=='Europe', year==2007) %>% mutate(pop_in_thousands=pop/1000) %>% select(country, gdpPercap, pop_in_thousands) %>% gather(key, value, gdpPercap, pop_in_thousands)