Quiz 1
Daniel Lee
8/28/2019
- Q1 Import Tesla stock prices, instead of Apple.
- Q2 How many shares of the stock were traded on January 13, 2016?
- 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 Tesla stock has performed since the beginning of 2019.
- Q6 Import two stocks: Tesla and Netflix for the same time period.
- Q7 Hide the messages, but display the code and results of the code from the webpage.
- Q8 Hide the code in Q6 but display 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("TSLA", get = "stock.prices", from = "2016-01-01")
stocks## # A tibble: 928 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 231. 231. 219 223. 6827100 223.
## 2 2016-01-05 226. 227. 220 223. 3186800 223.
## 3 2016-01-06 220 220. 216. 219. 3779100 219.
## 4 2016-01-07 214. 218. 214. 216. 3554300 216.
## 5 2016-01-08 218. 220. 211. 211 3628100 211
## 6 2016-01-11 214. 214. 203 208. 4089700 208.
## 7 2016-01-12 212. 214. 205. 210. 3091900 210.
## 8 2016-01-13 212. 213. 200 200. 4126400 200.
## 9 2016-01-14 202. 210 193. 206. 6490700 206.
## 10 2016-01-15 199. 205. 197. 205. 5578600 205.
## # … with 918 more rows## Visualize
stocks %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line()
Q1 Import Tesla stock prices, instead of Apple.
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("TSLA", get = "stock.prices", from = "2016-01-01")
stocks## # A tibble: 928 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 231. 231. 219 223. 6827100 223.
## 2 2016-01-05 226. 227. 220 223. 3186800 223.
## 3 2016-01-06 220 220. 216. 219. 3779100 219.
## 4 2016-01-07 214. 218. 214. 216. 3554300 216.
## 5 2016-01-08 218. 220. 211. 211 3628100 211
## 6 2016-01-11 214. 214. 203 208. 4089700 208.
## 7 2016-01-12 212. 214. 205. 210. 3091900 210.
## 8 2016-01-13 212. 213. 200 200. 4126400 200.
## 9 2016-01-14 202. 210 193. 206. 6490700 206.
## 10 2016-01-15 199. 205. 197. 205. 5578600 205.
## # … with 918 more rows## Visualize
stocks %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line()
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.
Hint: Watch the video, “Basic Data Types”, in DataCamp: Introduction to R for Finance: Ch1 The Basics.
Anything writtin in letters is Character data and Logical data are the options True or False
Q4 Plot the closing price in a line chart.
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.
## Load package
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis
## Import data
stocks <- tq_get("TSLA", get = "stock.prices", from = "2016-01-01")
stocks## # A tibble: 928 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 231. 231. 219 223. 6827100 223.
## 2 2016-01-05 226. 227. 220 223. 3186800 223.
## 3 2016-01-06 220 220. 216. 219. 3779100 219.
## 4 2016-01-07 214. 218. 214. 216. 3554300 216.
## 5 2016-01-08 218. 220. 211. 211 3628100 211
## 6 2016-01-11 214. 214. 203 208. 4089700 208.
## 7 2016-01-12 212. 214. 205. 210. 3091900 210.
## 8 2016-01-13 212. 213. 200 200. 4126400 200.
## 9 2016-01-14 202. 210 193. 206. 6490700 206.
## 10 2016-01-15 199. 205. 197. 205. 5578600 205.
## # … with 918 more rows## Visualize
stocks %>%
ggplot(aes(x = date, y = close)) +
geom_line()
Q5 From the chart you created in Q4, briefly describe how the Tesla stock has performed since the beginning of 2019.
The stocks has plummeted since the begining of 2019. Lower than usual
Q6 Import two stocks: Tesla and Netflix for the same time period.
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.
## # A tibble: 928 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 231. 231. 219 223. 6827100 223.
## 2 2016-01-05 226. 227. 220 223. 3186800 223.
## 3 2016-01-06 220 220. 216. 219. 3779100 219.
## 4 2016-01-07 214. 218. 214. 216. 3554300 216.
## 5 2016-01-08 218. 220. 211. 211 3628100 211
## 6 2016-01-11 214. 214. 203 208. 4089700 208.
## 7 2016-01-12 212. 214. 205. 210. 3091900 210.
## 8 2016-01-13 212. 213. 200 200. 4126400 200.
## 9 2016-01-14 202. 210 193. 206. 6490700 206.
## 10 2016-01-15 199. 205. 197. 205. 5578600 205.
## # … with 918 more rows## # A tibble: 928 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 918 more rows
Q7 Hide the messages, but display the code and results of the code from the webpage.
Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.
## Load package
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis
## Import data
stocks <- tq_get("TSLA", get = "stock.prices", from = "2016-01-01")
stocks## # A tibble: 928 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 231. 231. 219 223. 6827100 223.
## 2 2016-01-05 226. 227. 220 223. 3186800 223.
## 3 2016-01-06 220 220. 216. 219. 3779100 219.
## 4 2016-01-07 214. 218. 214. 216. 3554300 216.
## 5 2016-01-08 218. 220. 211. 211 3628100 211
## 6 2016-01-11 214. 214. 203 208. 4089700 208.
## 7 2016-01-12 212. 214. 205. 210. 3091900 210.
## 8 2016-01-13 212. 213. 200 200. 4126400 200.
## 9 2016-01-14 202. 210 193. 206. 6490700 206.
## 10 2016-01-15 199. 205. 197. 205. 5578600 205.
## # … with 918 more rows## Import data
stocks <- tq_get("NFLX", get = "stock.prices", from = "2016-01-01")
stocks## # A tibble: 928 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 918 more rows## Visualize
stocks %>%
ggplot(aes(x = date, y = adjusted)) +
geom_line()
Q8 Hide the code in Q6 but display its results.
Hint: Use echo and results in the chunk option. Note that this question only applies to the individual code chunk of Q6.