Week 2: Apply 1

Import stock prices

stocks <- tq_get(c("AAPL", "NVDA"),
                 get = "stock.prices",
                 from = "2023-01-01",
                 to = "2024-01-01")
stocks

## # A tibble: 500 × 8
##    symbol date        open  high   low close    volume adjusted
##    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
##  1 AAPL   2023-01-03  130.  131.  124.  125. 112117500     123.
##  2 AAPL   2023-01-04  127.  129.  125.  126.  89113600     125.
##  3 AAPL   2023-01-05  127.  128.  125.  125.  80962700     123.
##  4 AAPL   2023-01-06  126.  130.  125.  130.  87754700     128.
##  5 AAPL   2023-01-09  130.  133.  130.  130.  70790800     128.
##  6 AAPL   2023-01-10  130.  131.  128.  131.  63896200     129.
##  7 AAPL   2023-01-11  131.  134.  130.  133.  69458900     132.
##  8 AAPL   2023-01-12  134.  134.  131.  133.  71379600     132.
##  9 AAPL   2023-01-13  132.  135.  132.  135.  57809700     133.
## 10 AAPL   2023-01-17  135.  137.  134.  136.  63646600     134.
## # ℹ 490 more rows

Plot stock prices

stocks %>%
    
    ggplot(aes(x = date, y = adjusted, color = symbol)) +
    geom_line()