Use the given code below to answer the questions.
Hint: Insert a new code chunk below and type in the code, using the tq_get() function above. Replace the ticker symbol for Walmart. You may find the ticker symbol for Microsoft from Yahoo Finance.
## # A tibble: 1,029 x 7
## date open high low close volume adjusted
## <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2016-01-04 60.5 61.5 60.4 61.5 11989200 55.7
## 2 2016-01-05 62.0 63.0 61.8 62.9 13326000 57.1
## 3 2016-01-06 62.5 64.0 62.5 63.5 16564600 57.6
## 4 2016-01-07 63.0 65.2 62.9 65.0 26430000 59.0
## 5 2016-01-08 65.1 65.4 63.4 63.5 17767900 57.6
## 6 2016-01-11 63.8 64.5 63.6 64.2 12653800 58.2
## 7 2016-01-12 64.4 64.7 63.4 63.6 12195900 57.7
## 8 2016-01-13 63.7 63.7 61.8 61.9 13725700 56.2
## 9 2016-01-14 62 63.6 61.8 63.1 12934900 57.2
## 10 2016-01-15 61.5 62.5 61.3 61.9 15174400 56.2
## # … with 1,019 more rows
There are 7 colums/variables
Walmart opened at 62.03, made a high of 63.05, made a low of 61.85, closed at 62.92, volume of 13326000, and adjusted 57.06602
Hint: Watch the video, “Basic Data Types”, in DataCamp: Introduction to R for Finance: Ch1 The Basics. There is numerical data, caracteristic data, and logical data
Hint: Insert a new code chunk below and type in the code, using the ggplot() function above. Revise the code so that it maps adjusted to the y-axis, instead of close.
For more information on the ggplot() function, refer to Ch2 Introduction to ggplot2 in one of our e-textbooks, Data Visualization with R.
Walmart started at about 85 at the begiining of 2019 or the end of 2018 over time it raised up to 112 and then back down to 105 to close out the year.
Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.
Hint: Use eval in the chunk option. Refer to the RMarkdown Reference Guide.