Use the given code below to answer the questions.
## # A tibble: 928 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 103. 105. 102 105. 67649400 98.7
## 2 2016-01-05 106. 106. 102. 103. 55791000 96.3
## 3 2016-01-06 101. 102. 99.9 101. 68457400 94.4
## 4 2016-01-07 98.7 100. 96.4 96.4 81094400 90.4
## 5 2016-01-08 98.6 99.1 96.8 97.0 70798000 90.9
## 6 2016-01-11 99.0 99.1 97.3 98.5 49739400 92.4
## 7 2016-01-12 101. 101. 98.8 100.0 49154200 93.7
## 8 2016-01-13 100. 101. 97.3 97.4 62439600 91.3
## 9 2016-01-14 98.0 100. 95.7 99.5 63170100 93.3
## 10 2016-01-15 96.2 97.7 95.4 97.1 79833900 91.0
## # … with 918 more rows
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.
## # 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
Hint: Watch the video, “Basic Data Types”, in DataCamp: Introduction to R for Finance: Ch1 The Basics.
Logical data is usually either true or false, “yes, no, true, false” character data is written in letters, “clothing, popsicle, etc.”
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.
At the start of 2019 the Tesla stock had a low starting point and has been working it’s way up ever since the start of the year. There hasn’t been many downfalls or dips in the graph.
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
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.