Use the given code below to answer the questions.

## Load package
library(tidyverse) # for cleaning, plotting, etc
## ── Attaching packages ────────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.2.1     ✓ purrr   0.3.3
## ✓ tibble  2.1.3     ✓ dplyr   0.8.4
## ✓ tidyr   1.0.2     ✓ stringr 1.4.0
## ✓ readr   1.3.1     ✓ forcats 0.4.0
## ── Conflicts ───────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
library(tidyquant) # for financial analysis
## Loading required package: lubridate
## 
## Attaching package: 'lubridate'
## The following object is masked from 'package:base':
## 
##     date
## Loading required package: PerformanceAnalytics
## Loading required package: xts
## Loading required package: zoo
## 
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric
## 
## Attaching package: 'xts'
## The following objects are masked from 'package:dplyr':
## 
##     first, last
## 
## Attaching package: 'PerformanceAnalytics'
## The following object is masked from 'package:graphics':
## 
##     legend
## Loading required package: quantmod
## Loading required package: TTR
## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo
## Version 0.4-0 included new data defaults. See ?getSymbols.
## ══ Need to Learn tidyquant? ═══════════════════════════════════════════════════════
## Business Science offers a 1-hour course - Learning Lab #9: Performance Analysis & Portfolio Optimization with tidyquant!
## </> Learn more at: https://university.business-science.io/p/learning-labs-pro </>
## Import data
stocks <- tq_get("AAPL", get = "stock.prices", from = "2016-01-01")
stocks
## # A tibble: 1,035 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     98.2
##  2 2016-01-05 106.  106.  102.  103.  55791000     95.8
##  3 2016-01-06 101.  102.   99.9 101.  68457400     93.9
##  4 2016-01-07  98.7 100.   96.4  96.4 81094400     89.9
##  5 2016-01-08  98.6  99.1  96.8  97.0 70798000     90.4
##  6 2016-01-11  99.0  99.1  97.3  98.5 49739400     91.9
##  7 2016-01-12 101.  101.   98.8 100.  49154200     93.2
##  8 2016-01-13 100.  101.   97.3  97.4 62439600     90.8
##  9 2016-01-14  98.0 100.   95.7  99.5 63170100     92.8
## 10 2016-01-15  96.2  97.7  95.4  97.1 79833900     90.6
## # … with 1,025 more rows
## Visualize
stocks %>%
  ggplot(aes(x = date, y = adjusted)) +
  geom_line()

Q1 Import Netflix 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. ## Import data stocks <- tq_get(“NFLX”, get = “stock.prices”, from = “2016-01-01”) stocks

Q2 How many shares of the stock were traded on January 13, 2017?

150 stocks were shared

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.

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.

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.

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.

Q7 Hide the messages and the results of the code, but display the code on the webpage.

Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.

Q8 Make an exception to the code chunk in Q6 by displaying both the code and its results.

Hint: Use echo and results in the chunk option. Note that this question only applies to the individual code chunk of Q6.

Q9 Display the title and your name correctly at the top of the webpage.

Q10 Use the correct slug.