Frost

library(ggplot2)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(patchwork)
library(hrbrthemes)

## NOTE: Either Arial Narrow or Roboto Condensed fonts are required to use these themes.

##       Please use hrbrthemes::import_roboto_condensed() to install Roboto Condensed and

##       if Arial Narrow is not on your system, please see https://bit.ly/arialnarrow

library(readr)
Frost <- read_csv("Frost.csv")

## Warning: Missing column names filled in: 'X1' [1]

## Parsed with column specification:
## cols(
##   X1 = col_double(),
##   gen = col_double(),
##   new = col_double(),
##   sus = col_double()
## )

View(Frost)

head(Frost)

## # A tibble: 6 x 4
##      X1   gen   new   sus
##   <dbl> <dbl> <dbl> <dbl>
## 1     1     0     0   100
## 2     2     1     1    99
## 3     3     2     2    97
## 4     4     3     4    93
## 5     5     4     6    87
## 6     6     5    11    76

Frost <- Frost %>%
  rename(gen, Generation_of_Epidemic = gen,
         new, New_Cases_in_Generation = new,
         sus, Remaining_Susceptibles = sus)

P1 <- ggplot(Frost, aes(x=Generation_of_Epidemic, y=New_Cases_in_Generation)) + geom_line(color="69b3a2", size=2) + ggtitle("New Cases in Generation") + theme_ipsum() 

P2 <-ggplot(Frost, aes(x=Generation_of_Epidemic, y=Remaining_Susceptibles)) + geom_line(color="grey", size=2) + ggtitle("Remaining Susceptibles") + theme_ipsum()

ggplot(Frost, aes(x=Generation_of_Epidemic, y=New_Cases_in_Generation)) +
  
scale_y_continuous(name = "New Cases in Generation", 
sec.axis = sec_axis (trans=~.*10, name = "Remaining Susceptibles")) + theme_ipsum()