chicks_plot.R

library(ggplot2)
library(ggsci) # for cool palettes

# read data
my_data <- read.csv("data/chickengrowthdiet.csv")
str(my_data)
# Diet should not be numeric but factor (or categorical)
my_data$Diet <- factor(my_data$Diet)

# -------------------------------------
# make plot 1
# -------------------------------------
our_plot_1 <- 
  ggplot(data = my_data,
         aes(x = Time,
             y = weight,
             fill = Diet,
             color = Diet)) +
  # add the points
  geom_point(shape = 1, cex = 1, alpha = 0.7, position = "jitter") +
  # add CI ribbon and the fit lines
  geom_smooth(method='loess', size = 1) + # or method='loess'
  # set axis labels
  labs(x = "Days", 
       y = "Weight (g)") +
  theme_bw(base_size = 10) # base font size
  # theme(panel.grid = element_blank()) # eliminate grids

# display the plot
our_plot_1

# save the plot as PDF
ggsave(filename = "chicks_loess_default_col.pdf", 
       plot = our_plot_1, 
       width = 15, 
       height = 10, 
       units = "cm", 
       scale = 1)

# -------------------------------------
# plot 2
# -------------------------------------
our_plot_2 <- 
  ggplot(data = my_data,
         aes(x = Time,
             y = weight,
             color = Diet)) +
  # add the points
  geom_point(shape = 1, cex = 1, alpha = 0.7, position = "jitter") +
  # add CI ribbon and the fit lines
  geom_smooth(method='loess', size = 1, alpha = 0.2) + # or method='loess'
  scale_color_npg() +
  # set axis labels
  labs(x = "Days", 
       y = "Weight (g)") +
  theme_bw(base_size = 10) # base font size
# theme(panel.grid = element_blank()) # eliminate grids

# display the plot
our_plot_2

# save the plot as PDF
ggsave(filename = "chicks_loess_npg.pdf", 
       plot = our_plot_2, 
       width = 15, 
       height = 10, 
       units = "cm", 
       scale = 1)