code-100.R

# import data and inspect
#
library(tidyverse)
library(caret)
library(dslabs)
data(us_contagious_diseases)
str(us_contagious_diseases)

# assign dat to the per 10,000 rate of measles, removing Alaska and Hawaii and adjusting for weeks reporting
#
the_disease <- "Measles"
dat <- us_contagious_diseases %>%
  filter(!state %in% c("Hawaii", "Alaska") & disease == the_disease) %>%
  mutate(rate = count / population * 10000 * 52/weeks_reporting) %>%
  mutate(state = reorder(state, rate))

# plot disease rates per year in California
#
dat %>% filter(state == "California" & !is.na(rate)) %>%
  ggplot(aes(year, rate)) +
  geom_line() +
  ylab("Cases per 10,000") +
  geom_vline(xintercept=1963, col = "blue")

# tile plot of disease rate by state and year
#
dat %>% ggplot(aes(year, state, fill=rate)) +
        geom_tile(color = "grey50") +
        scale_x_continuous(expand = c(0,0)) +
        scale_fill_gradientn(colors = RColorBrewer::brewer.pal(9, "PuRd"), trans = "sqrt") +
        geom_vline(xintercept = 1963, col = "cyan") +
        theme_minimal() + theme(panel.grid = element_blank()) +
        ggtitle(the_disease) +
        ylab("") +
        xlab("")


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# geom_tile(color = "#C6DC67") +                                                        #
# scale_fill_gradientn(colors = RColorBrewer::brewer.pal(9, "Reds"), trans = "sqrt") +  #
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