Week 2: Apply 1

Import stock prices

stocks <- tq_get(c("NVDA", "SHOP" , "TTD"),
                 get = "stock.prices",
                 from = "2023-01-01")
stocks

## # A tibble: 1,257 × 8
##    symbol date        open  high   low close    volume adjusted
##    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>     <dbl>    <dbl>
##  1 NVDA   2023-01-03  14.9  15.0  14.1  14.3 401277000     14.3
##  2 NVDA   2023-01-04  14.6  14.9  14.2  14.7 431324000     14.7
##  3 NVDA   2023-01-05  14.5  14.6  14.1  14.3 389168000     14.3
##  4 NVDA   2023-01-06  14.5  15.0  14.0  14.9 405044000     14.9
##  5 NVDA   2023-01-09  15.3  16.1  15.1  15.6 504231000     15.6
##  6 NVDA   2023-01-10  15.5  16.0  15.5  15.9 384101000     15.9
##  7 NVDA   2023-01-11  15.8  16.0  15.6  16.0 353285000     16.0
##  8 NVDA   2023-01-12  16.1  16.6  15.5  16.5 551409000     16.5
##  9 NVDA   2023-01-13  16.3  16.9  16.2  16.9 447287000     16.9
## 10 NVDA   2023-01-17  16.9  17.7  16.9  17.7 511102000     17.7
## # ℹ 1,247 more rows

Plot stock prices

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

Import stock prices

stocks <- tq_get(c("GOOG", "UPST" , "AAPL"),
                 get = "stock.prices",
                 from = "2023-01-01")
stocks

## # A tibble: 1,257 × 8
##    symbol date        open  high   low close   volume adjusted
##    <chr>  <date>     <dbl> <dbl> <dbl> <dbl>    <dbl>    <dbl>
##  1 GOOG   2023-01-03  89.8  91.6  89.0  89.7 20738500     89.6
##  2 GOOG   2023-01-04  91.0  91.2  87.8  88.7 27046500     88.6
##  3 GOOG   2023-01-05  88.1  88.2  86.6  86.8 23136100     86.7
##  4 GOOG   2023-01-06  87.4  88.5  85.6  88.2 26612600     88.1
##  5 GOOG   2023-01-09  89.2  90.8  88.6  88.8 22996700     88.7
##  6 GOOG   2023-01-10  86.7  89.5  86.7  89.2 22855600     89.1
##  7 GOOG   2023-01-11  90.1  92.4  89.7  92.3 25998800     92.2
##  8 GOOG   2023-01-12  92.4  92.6  90.6  91.9 22754200     91.8
##  9 GOOG   2023-01-13  91.5  93.0  90.9  92.8 18630700     92.7
## 10 GOOG   2023-01-17  92.8  93.0  90.8  92.2 22935800     92.1
## # ℹ 1,247 more rows

Plot stock prices

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