### Þarft bara að keyra þetta einu sinni.
#install.packages("patchwork")
#install.packages("hrbrthemes")
#install.packages("Quandl")
#install.packages("openair")
#install.packages("imputeTS")
#install.packages("tidyverse")
#install.packages("Rcpp")


library(tidyverse)
library(dplyr)
library(ggplot2)
library(Rcpp)
library(TTR)
library(forecast)
library(patchwork)
library(lubridate)
library(hrbrthemes)
library(tidyr)
library(Quandl)
library(openair)
library(imputeTS)

# read the data
options(stringsAsFactors = FALSE)
mydata <- read.csv("exercise_data.csv", header = TRUE)
mydata1 <- na.omit(mydata)


## Ex1
subdata <- subset(mydata, month<4)
subdata <- mutate(subdata, temperature_as_vector = as.vector(temperature))
subdata <- mutate(subdata, so2_as_vector = as.vector(so2))
interpolated.temp <- na_ma(subdata$temperature, k = 4, weighting = "simple", maxgap = Inf)
subdata <- mutate(subdata, interpolated.temp)
interpolated.so2 <- na_ma(subdata$so2, k = 4, weighting = "simple", maxgap = Inf)
subdata <- mutate(subdata, interpolated.so2)
grouped.month.day <- group_by(subdata, month, day)
mean_temp <- summarise(grouped.month.day, mean_day_temp = mean(interpolated.temp))
mean_SO2 <- summarise(grouped.month.day, mean_day_so2 = mean(interpolated.so2))
averaged_data <- data.frame(mean_temp$mean_day_temp, mean_SO2$mean_day_so2)
averaged_data <- mutate(averaged_data, ID = row_number())
coeff <- 0.3
plot1 <- ggplot(averaged_data, aes(x=ID)) + geom_line(aes(y=mean_temp.mean_day_temp), col = 
                                                        "green") +geom_line(aes(y=mean_SO2.mean_day_so2/coeff), col ="red") + 
  scale_y_continuous(name = "Temperature(°C)", sec.axis = sec_axis(~.*coeff, name = "Concentration 
of SO2"))
theme <- theme(axis.title.y.right = element_text(colour = "red"),
               axis.title.y.left = element_text(colour = "green"),
               axis.line.y.left = element_line(colour ="green"),
               axis.line.y.right = element_line(colour = "red"),
               axis.ticks.y.left = element_line(colour = "green"),
               axis.ticks.y.right = element_line(colour = "red")) 

#print(plot1+theme+ggtitle("Daily averaged SO2 concentration and temperature during 1 January 2006 – 31 March 2006")) + labs(x="Day of 2006")
plot1 + 
  theme + 
  ggtitle("Daily averaged SO2 concentration and temperature during 1 January 2006 – 31 March 2006") + 
  labs(x="Day of 2006")



################# EX2

ex2 <- read.csv("exercise_data.csv", header = TRUE)
ex2.1 <- na.omit(ex2)
ex2.1%>%group_by(day)
temp <- ex2.1%>%group_by(day)%>%summarise(mean_temp=mean(temperature))
so2 <- ex2.1%>%group_by(day)%>%summarise(mean_SO2=mean(so2))
mydata2 <- data.frame(temp, so2)
df <- subset(mydata2, select = -c(day.1))
sub1 <- mydata1[c(1:24), c(7:8)]
sub2 <- mydata1[c(25:48), c(7:8)]
sub3 <- mydata1[c(49:72), c(7:8)]
sub4 <- mydata1[c(73:96), c(7:8)]
sub5 <- mydata1[c(97:120), c(7:8)]
sub6 <- mydata1[c(121:144), c(7:8)]
sub7 <- mydata1[c(145:168), c(7:8)]
sub8 <- mydata1[c(169:192), c(7:8)]
sub9 <- mydata1[c(193:216), c(7:8)]
sub10 <- mydata1[c(217:240), c(7:8)]
sub11 <- mydata1[c(241:264), c(7:8)]
sub12 <- mydata1[c(265:288), c(7:8)]
ggplot(df, aes(x = mean_temp, y = mean_SO2)) + geom_point() +
  geom_point(data = sub1, aes(x = temperature, y = so2), color = "yellow") +
  geom_point(data = sub2, aes(x = temperature, y = so2, color = "red"))+
  geom_point(data = sub3, aes(x = temperature, y = so2, color = "green"))+
  geom_point(data = sub4, aes(x = temperature, y = so2), color = "blue")+
  geom_point(data = sub5, aes(x = temperature, y = so2, color = "black"))+
  geom_point(data = sub6, aes(x = temperature, y = so2, color = "white"))+
  geom_point(data = sub7, aes(x = temperature, y = so2, color = "purple"))+
  geom_point(data = sub8, aes(x = temperature, y = so2, color = "brown"))+
  geom_point(data = sub9, aes(x = temperature, y = so2, color = "pink"))+
  geom_point(data = sub10, aes(x = temperature, y = so2, color = "orange"))+
  geom_point(data = sub11, aes(x = temperature, y = so2, color = "dark grey"))+
  geom_point(data = sub12, aes(x = temperature, y = so2, color = "light blue"))+
  xlab("Averaged temperature (°C)")+
  ylab("Averaged SO2 concentration")+
  ggtitle("Daily averaged SO2 concentration against daily averaged temperature at 67.2m height")