Use the given code below to answer the questions.
## Load package
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis
## Import data
stocks <- tq_get("AAPL", get = "stock.prices", from = "2016-01-01")
stocks
## Visualize
stocks %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line()
## Import data
stocks <- tq_get("NFLX", get = "stock.prices", from = "2016-01-01")
stocks
## Visualize
stocks %>%
ggplot(aes(x = date, y = close)) +
geom_line()
For more information on the ggplot() function, refer to Ch2 Introduction to ggplot2 in one of our e-textbooks, Data Visualization with R.
The netflix stock has started off slow but then got better and more consistant throuout the year then dipped down a little.
## Import data
stocks <- tq_get("NFLX", "AMZN", get = "stock.prices", from = "2016-01-01")
stocks
## # A tibble: 1,032 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 109 110 105. 110. 20794800 110.
## 2 2016-01-05 110. 111. 106. 108. 17664600 108.
## 3 2016-01-06 105. 118. 105. 118. 33045700 118.
## 4 2016-01-07 116. 122. 112. 115. 33636700 115.
## 5 2016-01-08 116. 118. 111. 111. 18067100 111.
## 6 2016-01-11 112. 117. 111. 115. 21920400 115.
## 7 2016-01-12 116. 118. 115. 117. 15133500 117.
## 8 2016-01-13 114. 114. 105. 107. 24921600 107.
## 9 2016-01-14 106. 109. 101. 107. 23664800 107.
## 10 2016-01-15 102. 106. 102. 104. 19775100 104.
## # … with 1,022 more rows
Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.
Hint: Use echo and results in the chunk option. Note that this question only applies to the individual code chunk of Q6.