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("AAPL", 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 2016-01-04 103.  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
## 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.

## # 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

Q2 How many shares of the stock were traded on January 13, 2016?

4126400

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.

Character: String types of data where each element in the code is a string of one or more characters. Consists of vectors that are letters.

Logical: Logical data is TRUE/FALSE data, or binary data with two possible options

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.

Since the beginning of 2019, Telsa has gradually decreased in value with an abrupt spike in value at the end of Q2. The value of the stock has not fully recovered since the beginning of 2019.

Q6 Import two stocks: Tesla and Netflix for the same time period.

## # 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.

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.