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()
Hint: Insert a new code chunk below and type in the code, using the tq_get() function above. Replace the ticker symbol. Find ticker symbols from Yahoo Finance.
## Load package
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis
## Import data
stocks <- tq_get("NFLX", get = "stock.prices", from = "2016-01-01")
stocks
## Visualize
stocks %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line()
Hint: Watch the video, “Basic Data Types”, in DataCamp: Introduction to R for Finance: Ch1 The Basics.
Character Data: ticker symbol Logical Data: Something being true or false
Hint: Insert a new code chunk below and type in the code, using the ggplot() function above. Revise the code so that it maps close to the y-axis, instead of adjusted.
For more information on the ggplot() function, refer to Ch2 Introduction to ggplot2 in one of our e-textbooks, Data Visualization with R.
## Visualize
stocks %>%
ggplot(aes(x = date, y = close)) +
geom_line()
The Netflix stock started out low then by 2018 it exploded upwards for a closing price. In 2019 it dropped a lot maybe could be from disney + coming out or other company’s coming into the market. Right at the end of 2020 it looks like its starting back to grow up.
Hint: Insert a new code chunk below and type in the code, using the tq_get() function above. You may refer to the manual of the tidyquant r package. Or, simply Google the tq_get function and see examples of the function’s usage.
## Load package
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis
## Import data
stocks <- tq_get(c("AMZN", "NFLX"), get = "stock.prices", from = "2016-01-01")
stocks
## # A tibble: 2,066 x 8
## symbol date open high low close volume adjusted
## <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 AMZN 2016-01-04 656. 658. 628. 637. 9314500 637.
## 2 AMZN 2016-01-05 647. 647. 628. 634. 5822600 634.
## 3 AMZN 2016-01-06 622 640. 620. 633. 5329200 633.
## 4 AMZN 2016-01-07 622. 630 605. 608. 7074900 608.
## 5 AMZN 2016-01-08 620. 624. 606 607. 5512900 607.
## 6 AMZN 2016-01-11 612. 620. 599. 618. 4891600 618.
## 7 AMZN 2016-01-12 625. 626. 612. 618. 4724100 618.
## 8 AMZN 2016-01-13 621. 621. 579. 582. 7655200 582.
## 9 AMZN 2016-01-14 580. 602. 570. 593 7238000 593
## 10 AMZN 2016-01-15 572. 585. 565. 570. 7784500 570.
## # … with 2,056 more rows
## Visualize
stocks %>%
ggplot(aes(x = date, y = close, col = symbol)) +
geom_line()
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.