Use the given code below to answer the questions.
Character data would consist of words, such as house color. Logical data would be true or false data, such as medication test success/failure.
Netflix stock increased sharply at the start of 2019, but has remained stable since then.
## Import data
stocksNFAM <- tq_get(c("NFLX", "AMZN"), get = "stock.prices", from = "2016-01-01")
stocksNFAM
## # A tibble: 2,066 x 8
## symbol date open high low close volume adjusted
## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 NFLX 2016-01-04 109 110 105. 110. 20794800 110.
## 2 NFLX 2016-01-05 110. 111. 106. 108. 17664600 108.
## 3 NFLX 2016-01-06 105. 118. 105. 118. 33045700 118.
## 4 NFLX 2016-01-07 116. 122. 112. 115. 33636700 115.
## 5 NFLX 2016-01-08 116. 118. 111. 111. 18067100 111.
## 6 NFLX 2016-01-11 112. 117. 111. 115. 21920400 115.
## 7 NFLX 2016-01-12 116. 118. 115. 117. 15133500 117.
## 8 NFLX 2016-01-13 114. 114. 105. 107. 24921600 107.
## 9 NFLX 2016-01-14 106. 109. 101. 107. 23664800 107.
## 10 NFLX 2016-01-15 102. 106. 102. 104. 19775100 104.
## # … with 2,056 more rows
## Visualize
stocksNFAM %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line()