Quiz 1
Andrew Wasilefsky
8/28/2019
- Q1 Import Netflix stock prices, instead of Apple.
- Q2 How many shares of the stock were traded on January 13, 2017?
- Q3 Stock prices in this data would be a good example of numeric data. Character and logical are two other basic data types in R. List one example of character data and one example of logical data.
- Q4 Plot the closing price in a line chart.
- Q5 From the chart you created in Q4, briefly describe how the Netflix stock has performed since the beginning of 2019.
- Q6 Import two stocks: Netflix and Amazon for the same time period.
- Q7 Hide the messages and the results of the code, but display the code on the webpage.
- Q8 Make an exception to the code chunk in Q6 by displaying both the code and its results.
- Q9 Display the title and your name correctly at the top of the webpage.
- Q10 Use the correct slug.
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()
Q1 Import Netflix stock prices, instead of Apple.
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis
stocks <- tq_get("NFLX", get = "stock.prices", from = "2017-01-01")
stocksQ3 Stock prices in this data would be a good example of numeric data. Character and logical are two other basic data types in R. List one example of character data and one example of logical data.
One example of character data would be (“one” or “two”). Logical data is represented in a true or false scenario, such as (false, false, true, true, false)
Q4 Plot the closing price in a line chart.
stocks %>%
ggplot(aes(x = date, y = close)) +
geom_line()
Q5 From the chart you created in Q4, briefly describe how the Netflix stock has performed since the beginning of 2019.
Netflix has done well, but hit a hiccup around the middle of 2019. But overall, it grew from $250 to $400.Q6 Import two stocks: Netflix and Amazon for the same time period.
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis
stocks <- tq_get("NFLX", "AMZN", get = "stock.prices", from = "2017-01-01")
stocks## # A tibble: 781 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2017-01-03 125. 128. 124. 127. 9437900 127.
## 2 2017-01-04 127. 130. 127. 129. 7843600 129.
## 3 2017-01-05 129. 133. 129. 132. 10185500 132.
## 4 2017-01-06 132. 134. 130. 131. 10657900 131.
## 5 2017-01-09 131. 132. 130. 131. 5771800 131.
## 6 2017-01-10 131. 132. 129. 130. 5985800 130.
## 7 2017-01-11 131. 132. 129. 130. 5615100 130.
## 8 2017-01-12 131. 131. 128. 129. 5388900 129.
## 9 2017-01-13 131. 134. 131. 134. 10515000 134.
## 10 2017-01-17 135. 135. 132. 133. 12220200 133.
## # … with 771 more rows