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("AMZN", get = "stock.prices", from = "2016-01-01")
stocks
## # A tibble: 1,025 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 656. 658. 628. 637. 9314500 637.
## 2 2016-01-05 647. 647. 628. 634. 5822600 634.
## 3 2016-01-06 622 640. 620. 633. 5329200 633.
## 4 2016-01-07 622. 630 605. 608. 7074900 608.
## 5 2016-01-08 620. 624. 606 607. 5512900 607.
## 6 2016-01-11 612. 620. 599. 618. 4891600 618.
## 7 2016-01-12 625. 626. 612. 618. 4724100 618.
## 8 2016-01-13 621. 621. 579. 582. 7655200 582.
## 9 2016-01-14 580. 602. 570. 593 7238000 593
## 10 2016-01-15 572. 585. 565. 570. 7784500 570.
## # … with 1,015 more rows
There are 7 variables.
date, open, high, low, close, volume, adjusted
These variables are numeric. The other types are character and logical.
There are 1,025 rows.
The row represents daily stock prices.
## Visualize
stocks %>%
ggplot(aes(x = date, y = close)) +
geom_line()
Hint: Change message, warning, collapse, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.