Data manipulation in R to plot active covid19 cases and Apple stock price. See comment in https://statsandr.com/blog/data-manipulation-in-r/

stock_price_covid19.R

# install.packages("quantmod")
library(quantmod)
# devtools::install_github("RamiKrispin/coronavirus", force = TRUE)
library(coronavirus)

# coronavirus dataset
`%>%` <- magrittr::`%>%`
df <- coronavirus %>%
  # dplyr::filter(date == max(date)) %>%
  dplyr::filter(country == "Indonesia") %>%
  dplyr::group_by(country, type) %>%
  dplyr::summarise(total = sum(cases)) %>%
  tidyr::pivot_wider(
    names_from = type,
    values_from = total
  ) %>%
  # dplyr::mutate(unrecovered = confirmed - ifelse(is.na(recovered), 0, recovered) - ifelse(is.na(death), 0, death)) %>%
  dplyr::mutate(unrecovered = confirmed - ifelse(is.na(death), 0, death)) %>%
  dplyr::arrange(-confirmed) %>%
  dplyr::ungroup() %>%
  dplyr::mutate(country = dplyr::if_else(country == "United Arab Emirates", "UAE", country)) %>%
  dplyr::mutate(country = dplyr::if_else(country == "Mainland China", "China", country)) %>%
  dplyr::mutate(country = dplyr::if_else(country == "North Macedonia", "N.Macedonia", country)) %>%
  dplyr::mutate(country = trimws(country)) %>%
  dplyr::mutate(country = factor(country, levels = country))

df_daily <- coronavirus %>%
  dplyr::filter(country == "Indonesia") %>%
  dplyr::group_by(date, type) %>%
  dplyr::summarise(total = sum(cases, na.rm = TRUE)) %>%
  tidyr::pivot_wider(
    names_from = type,
    values_from = total
  ) %>%
  dplyr::arrange(date) %>%
  dplyr::ungroup() %>%
  # dplyr::mutate(active = confirmed - death - recovered) %>%
  dplyr::mutate(active = confirmed - death) %>%
  dplyr::mutate(
    confirmed_cum = cumsum(confirmed),
    death_cum = cumsum(death),
    # recovered_cum = cumsum(recovered),
    active_cum = cumsum(active)
  )

View(df_daily)

# stock dataset
getSymbols("AAPL", src = "yahoo")
View(AAPL)
str(AAPL)
AAPL <- as.data.frame(AAPL)
AAPL$date <- as.Date(rownames(AAPL))
AAPL <- subset(AAPL, date >= min(df_daily$date))

# create plot
plot(
  x = AAPL$date, y = AAPL$AAPL.Close, ylim = c(0, max(df_daily$active)),
  type = "l", ylab = NA, xlab = "Date", main = "Apple stock price and active Covid19 cases"
)
lines(x = df_daily$date, y = df_daily$active, col = "red")