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: 922 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 912 more rows
## Examine data
glimpse(stocks)
## Observations: 922
## Variables: 7
## $ date     <date> 2016-01-04, 2016-01-05, 2016-01-06, 2016-01-07, 2016-0…
## $ open     <dbl> 102.61, 105.75, 100.56, 98.68, 98.55, 98.97, 100.55, 10…
## $ high     <dbl> 105.37, 105.85, 102.37, 100.13, 99.11, 99.06, 100.69, 1…
## $ low      <dbl> 102.00, 102.41, 99.87, 96.43, 96.76, 97.34, 98.84, 97.3…
## $ close    <dbl> 105.35, 102.71, 100.70, 96.45, 96.96, 98.53, 99.96, 97.…
## $ volume   <dbl> 67649400, 55791000, 68457400, 81094400, 70798000, 49739…
## $ adjusted <dbl> 98.74225, 96.26781, 94.38389, 90.40047, 90.87848, 92.35…
## Visualize
stocks %>%
  ggplot(aes(x = date, y = close)) +
  geom_line()

Q1 Get Microsoft 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 for Microsoft. You may find the ticker symbol for Microsoft from Yahoo Finance.

## Load package
library(tidyverse) # for cleaning, plotting, etc
library(tidyquant) # for financial analysis

## Import data
stocks <- tq_get("MFST", get = "stock.prices", from = "2016-01-01")
stocks
## # A tibble: 922 x 7
##    date        open  high   low close volume adjusted
##    <date>     <dbl> <dbl> <dbl> <dbl>  <dbl>    <dbl>
##  1 2016-01-04   7.3   7.3   7.3  7.3       1     7.3 
##  2 2016-01-05   6     6     6    6        40     6   
##  3 2016-01-06   6     6     6    6         0     6   
##  4 2016-01-07   6     6     6    6         1     6   
##  5 2016-01-08   6.8   6.8   6.8  6.8      35     6.8 
##  6 2016-01-11   6.8   9.5   6.3  8.86     84     8.86
##  7 2016-01-12   7     7     7    7        46     7   
##  8 2016-01-13   7     7     7    7         0     7   
##  9 2016-01-14   9.2   9.2   7    7         2     7   
## 10 2016-01-15   7     8.8   6.1  6.1      73     6.1 
## # … with 912 more rows

Q2 How many columns (variables) are there?

Hint: Insert a new code chunk below and type in the code, using the glimpse() function above.

## Examine data
glimpse(stocks)
## Observations: 922
## Variables: 7
## $ date     <date> 2016-01-04, 2016-01-05, 2016-01-06, 2016-01-07, 2016-0…
## $ open     <dbl> 7.3, 6.0, 6.0, 6.0, 6.8, 6.8, 7.0, 7.0, 9.2, 7.0, 6.1, …
## $ high     <dbl> 7.3, 6.0, 6.0, 6.0, 6.8, 9.5, 7.0, 7.0, 9.2, 8.8, 6.1, …
## $ low      <dbl> 7.3, 6.0, 6.0, 6.0, 6.8, 6.3, 7.0, 7.0, 7.0, 6.1, 6.1, …
## $ close    <dbl> 7.30, 6.00, 6.00, 6.00, 6.80, 8.86, 7.00, 7.00, 7.00, 6…
## $ volume   <dbl> 1, 40, 0, 1, 35, 84, 46, 0, 2, 73, 0, 1021, 224, 213, 1…
## $ adjusted <dbl> 7.30, 6.00, 6.00, 6.00, 6.80, 8.86, 7.00, 7.00, 7.00, 6…

Q3 What are the variables?

open high low close volume adjusted

Q4 What type of data are they? What are other basic data types?

Hint: Watch the video, “Basic Data Types”, in DataCamp: Introduction to R for Finance: Ch1 The Basics. numeric logical and charachter

Q5 How many rows are there?

922

Q6 What does the row represent?

daily information on stock prices

Q7 Create a line plot for the data.

Hint: Insert a new code chunk below and type in the code, using the ggplot() function above. For more information on the ggplot() function, refer to Ch2 Introduction to ggplot2 in one of our e-textbooks, Data Visualization with R.

## Visualize
stocks %>%
  ggplot(aes(x = date, y = close)) +
  geom_line()

```

Q8 Hide the messages and warings but display the code and results of the code on the webpage.

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

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

Q10 Use the correct slug.