getwd()
setwd("/Users/meridithlavelle/Desktop/Intro to R - Fall 2022") #make sure to set this
#to reflect the filepath on your own device 

1 + a
a <- 1
1 + a
a <- 4     
a.1 <- 1
a.4 <- 4

#installing and loading packages
install.packages("foreign")
library(foreign)
install.packages("readxl")
install.packages("readr")
install.packages("rio")

library(readxl)
library(readr)
library(rio)
library(carData)

help(package = "carData")
?WVS
?library

x <- 1
y <- 2
x * y

x/y
log(x)
exp(x)
class(x)

xvec <- c(1, 2, 3, 4, 5)
xvec
xvec <- c(1:5)

xvec2 <- seq(from = 1, to = 5, by = 1)
xvec2

yvec <- rep(1,5)
yvec
?rep

zvec_add <- xvec + yvec
zvec_add

mat1 <- matrix(data = c(1, 2, 3, 4, 5, 6), nrow = 3, byrow = TRUE)
mat1
mat2 <- matrix(data = c(1, 2, 3, 4, 5, 6), ncol = 3) 
mat2
# lines 51-52 not originally included on the pdf - this example was used to demonstrate
#that we can change the nrow specificatin to ncol 

mat3 <- matrix(data = seq(from = 6, to = 3.5, by = -0.5), nrow = 2, byrow = TRUE)
mat3

mat1 %*% mat2
rm(matx) #deleting a single object

#Data Frames
grade <- c("A", "D", "A-", "B+", "A", "A")
days_absent <- c(1, 9, 2, 3, 0, 1)
name <- c("Student 1", "Student 2", "Student 3", "Student 4", "Student 5",
          "Student 6")
mydata <- data.frame(name, grade, days_absent)
mydata

vec1 <- c(2, 4, 6, 8)
vec1[3]
mydata[1,]
mydata[,3]
mydata[2,2]
mydata[2:4, "days_absent"]
mydata$grade

draws <- rnorm(1000, mean = 5, sd = 10)
summary(draws)
plot(density(draws), main = "Title of plot", xlab = "X-axis", ylab = "Y-Axis")

draws <- rnorm(1000, mean = 5, sd = 10)
hist.plot <- hist(draws, main = "Histogram", xlab = "X-axis", ylab = "Y-axis")
hist.plot

#loading in data from your device
hr_conflict <- read.csv("hr_conflict.csv")
summary(hr_conflict)

sd(hr_conflict$population)
sd(hr_conflict$population, na.rm = TRUE)
quantile(hr_conflict$population, probs = c(0.05, 0.95), na.rm = TRUE)

#random draws/distrubutions
set.seed(321)
dist1 <- rnorm(n = 1000, mean = 0, sd = 1)
set.seed(321)
dist2 <- rnorm(n = 1000, mean = 0, sd = 2)
plot(density(dist1))
lines(density(dist2), col = "red")


set.seed(321)
x <- 1:50
y <- rnorm(n = 50, mean = 0, sd = 2)
plot(x, y, pch = 1, col = "blue")

set.seed(123)
x1 <- rnorm(100)
boxplot(x, col = "grey", main = "Box plot")
boxplot(x, col = "grey", main = "Box plot", xlab = "X", ylab = "Y")

#Exporting plots
set.seed(321)
dist1 <- rnorm(n = 1000, mean = 0, sd = 1)
set.seed(321)
dist2 <- rnorm(n = 1000, mean = 0, sd = 2)
pdf("density_plot.pdf", width = 5, height = 5)
plot(density(dist1))
lines(density(dist2), col = "red")
dev.off()

#ggplot
library(ggplot2)
library(reshape)
library(gapminder)
gapminder <- gapminder
summary(gapminder)

ggplot(gapminder, aes(x = gdpPercap, y = lifeExp)) +
  geom_point()

ggplot(gapminder, aes(x = gdpPercap, y = lifeExp)) +
  geom_point() +
  scale_x_log10()

ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent)) +
  geom_point()

ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent, size = pop)) +
  geom_point()

ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent, size = pop)) +
  geom_point() +
  scale_x_log10() +
  facet_wrap(~continent)

ggplot(gapminder, aes(x = continent, y = lifeExp)) +
  geom_col()

ggplot(gapminder, aes(x = continent, y = lifeExp, color = continent)) +
  geom_col()

set.seed(321)
dist1 <- rnorm(n = 1000, mean = 0, sd = 1)
set.seed(321)
dist2 <- rnorm(n = 1000, mean = 0, sd = 2)
dist.data <- data.frame(dist1, dist2)
ggplot(dist.data, aes(dist1)) +
  geom_density()

ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent, size = pop)) +
  geom_point() +
  scale_x_log10() +
  facet_wrap(~continent) +
  xlab("GDP per capita") +
  ylab("Life Expectancy") +
  ggtitle("GDP's effect on life expectancy by continent")

final.plot <- ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent, size = pop)) +
  geom_point() +
  scale_x_log10() +
  facet_wrap(~continent) +
  xlab("GDP per capita") +
  ylab("Life Expectancy") +
  ggtitle("GDP's Effect on Life Expectancy by Continent")
ggsave("final.plot.pdf")