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
## # 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
character data is referred to as string types. logical data describes it in as much detail as possible.
Teslas stock has been on the decline since the start of 2019. it went up alittle bit during Q2 but dropped shortly after.
## # 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.