## If necessary
## install.packages(c('ggplot2','cowplot'))
## load packages
library(ggplot2)
## Cowplot is just to join together the four graphs at the end
library(cowplot)

## load data (the Economics dataset comes with ggplot2) 
eco_df <- economics

## basic plot
p1 <- ggplot() +
  geom_line(aes(x=date, y = uempmed), data = eco_df)
p1

## Change line color and chart labels 
## Note here that color is *outside* of the aes() argument, and so this will color the line
## If color were instead *inside* aes() and set to a factor variable, ggplot would create
## a different line for each value of the factor variable, colored differently.
p2 <- ggplot() +
  ## choose a color of preference
  geom_line(aes(x=date, y = uempmed), color = "navyblue", data = eco_df) +
  ## add chart title and change axes labels
  labs(
    title = "Median Duration of Unemployment", 
    x = "Date",
    y = "") +
  ## Add a ggplot theme
  theme_light()
  ## center the chart title
  theme(plot.title = element_text(hjust = 0.5)) +

p2

## plotting multiple charts (of different line types and sizes)
p3 <-ggplot() +
  geom_line(aes(x=date, y = uempmed), color = "navyblue", 
            size = 1.5, data = eco_df) +
  geom_line(aes(x=date, y = psavert), color = "red2", 
            linetype = "dotted", size = 0.8, data = eco_df) +
  labs(
    title = "Unemployment Duration (Blue) and Savings Rate (Red)", 
    x = "Date",
    y = "") +
  theme_light() +
  theme(plot.title = element_text(hjust = 0.5))
  
p3

## Plotting a different line type for each group
## There isn't a natural factor in this data so let's just duplicate the data and make one up
eco_df$fac <- factor(1, levels = c(1,2))
eco_df2 <- eco_df
eco_df2$fac <- 2
eco_df2$uempmed <- eco_df2$uempmed - 2 + rnorm(nrow(eco_df2))
eco_df <- rbind(eco_df, eco_df2)
p4 <- ggplot() +
  ## This time, color goes inside aes
  geom_line(aes(x=date, y = uempmed, color = fac), data = eco_df) +
  ## add chart title and change axes labels
  labs(
    title = "Median Duration of Unemployment", 
    x = "Date",
    y = "") +
  ## Add a ggplot theme
  theme_light() +
  ## center the chart title
  theme(plot.title = element_text(hjust = 0.5),
        ## Move the legend onto some blank space on the diagram
        legend.position = c(.25,.8),
        ## And put a box around it
        legend.background = element_rect(color="black")) +
  ## Retitle the legend that pops up to explain the discrete (factor) difference in colors
  ## (note if we just want a name change we could do guides(color = guide_legend(title = 'Random Factor')) instead)
  scale_color_manual(name = "Random Factor",
                     # And specify the colors for the factor levels (1 and 2) by hand if we like
                     values = c("1" = "red", "2" = "blue"))
p4

# Put them all together with cowplot for LOST upload
plot_grid(p1,p2,p3,p4, nrow=2)