library(tidyverse)
isikud=read_csv("http://www.tlu.ee/~jaagup/andmed/muu/estonia_reisijad.txt") 
isikud %>% ggplot(aes(Age)) + geom_histogram(binwidth = 10) + 
        facet_wrap(~Category, nrow = 2)

isikud %>% ggplot(aes(Age)) + geom_histogram(binwidth = 10) + 
  facet_grid(Sex~Category)

isikud %>% filter(Country %in% c("Estonia", "Sweden")) %>%
  ggplot(aes(Age)) + geom_histogram(binwidth = 10) + 
  facet_grid(Sex~Country)

isikud %>% filter(Country %in% c("Estonia", "Sweden")) %>%
  ggplot(aes(Age, fill=Sex)) + geom_histogram(binwidth = 10, position = "dodge") + 
  facet_grid(Category~Country)

isikud %>% group_by(Sex) %>% summarise(kogus=n())
#Koostage facet_wrap eesti, soome ja rootsi isikute vanuste histogrammi kohta

#Koostage facet_grid eesti, soome ja rootsi isikute 
  #vanuste ja sugude histogrammi kohta

#Koostage sugude sektordiagramm vastavalt kodakondsusele (4 levinumat (+ muud))
#Lisage facet_wrap kategooria kaupa
#Lisage facet_grid soo kaupa


isikud %>% filter(Country %in% c("Estonia", "Sweden")) %>%
  ggplot(aes(x="", y=length(Country), fill=Country)) + 
   geom_col( position = "fill")+coord_polar("y")+
   theme(axis.text = element_blank(), 
        axis.ticks = element_blank(),
        panel.grid = element_blank())+
    xlab("")+ylab("") +
    facet_grid(Sex~Category)



sonad=read_csv("http://www.tlu.ee/~jaagup/andmed/keel/kunglarahvas_lambipirn_pikkused_haalikud.txt")

ecom <- readr::read_csv('https://raw.githubusercontent.com/rsquaredacademy/datasets/master/web.csv')

ggplot(ecom, aes(x = n_pages, y = duration)) + 
  geom_point() + geom_abline(slope=20, intercept=0)+
  geom_abline(slope=0, intercept=300) +
  geom_smooth(method="lm")

ecom %>% filter(n_pages>1) %>%
ggplot(aes(x = n_pages, y = duration)) + 
  geom_point() + geom_abline(slope=20, intercept=0)+
  geom_abline(slope=0, intercept=300) +
  geom_smooth(se=FALSE)

ecom %>% group_by(device) %>% summarise(kogus=n()) %>%
   ggplot(aes(device, kogus)) +
   geom_col() + coord_flip()



ecom %>% group_by(device) %>% summarise(kogus=n()) %>%
  ggplot(aes(device, kogus)) +
  geom_col() + geom_hline(yintercept = c(150, 200, 250)) + 
  geom_vline(xintercept = 1.7, color="red")+coord_flip()

ggplot(mtcars, aes(disp, mpg, label = rownames(mtcars))) +
  geom_label()

ggplot(mtcars, aes(disp, mpg, label = rownames(mtcars))) +
  geom_text( check_overlap = TRUE)

ggplot(mtcars, aes(x = disp, y = mpg, size = disp)) +
  geom_point()


Joonise katsetus

Pange eri tunnused näitama suurust, kuju, värvi
Katsetage pealkirjade teksti omadustega

ecom %>% filter(n_pages>1) %>% 
   ggplot(aes(n_pages, duration)) + geom_point()


ecom %>% filter(n_pages>1) %>% 
  ggplot(aes(n_pages, duration, shape=device, color=referrer)) +
  geom_point()+
  ggtitle("Veebikasutus", subtitle = "eelmisel aastal")+
  theme(plot.title=element_text(face = "italic")) +
  scale_shape_manual("Seade", values=c("laptop"=12, "mobile"=22, "tablet"=25))