Answer all questions fully and include all requested answern and output onto a single pdf$,$ doc, or docx file. All written work for the report will need to be typed, and all requested plots need to be generated through R$.$ All plots need to be correctly labeled and easy to read$/$understand$.$ In addition to the typed project, upload the $$ source file used to perform all requested statisticul operations and the final cleaned dataset as a csv file. Failure to upload the $.$ R source file and the cleaned dataset will result in a substantial loss of points. Data for completing this project may be found under the "FilevProject$/$Project $1^11$ page on Canvas. Cleaning and Inspecting data: The file Stocks.csv contains data on the closing stock price on a single day for a larpe number of companies, For each company, the dataset provides the name $($Name$),$ stock market ticker symbol $($Symbol$),$ sector $($Sectot$),$ Mock price $($Price$),$ dividend as a percentage of stock price $($Dividend$),$ price$-$to$-$camings ratio $($PE$),$ earaings per share $($EPS$),$ book value in billions of dollars $($Book Value$),$ lowest and highest share price over the last $52$ weeks $(52$ week low and $52$ weck high$),$ market value of the company's shares in billions of dollars $($Market Cap$),$ and earnings before interest, taxes, depreciation, and amortization in billions of dollars $($EBITDA$).1.$ Data Cleaning: $($a$)(2$pts$)$ How many companies are included in the Stocks.csy dataset? $($b$)(4$pts$)$ How many missing values are there for each variable? Hox many incomplete observations are there? $($c$)(8$pts$)$ Clean up the missing data by cither remewing all incomplete observations or by imputing values for the missing data. Which opeion did you choose? Why? $($d$)(2$pts$)$ Add a column to this dataset obtained by taking the log base $10$ of the beok value. $($c$)(2$pts$)$ Add a column to this dataset obtained by taking the log base $10$ of the market cap. $($f$)(2$pts$)$ Add a columa to this dataset obtained by taking the log hase $10$ of the EBITDA. $($g$)(4$pts$)$ Create a variable that is $1$ if the company has a price$-$to$-$earnings ratio greater than $15$ and is $0$ otherwise. Add this variable as a column ia the dataset. $($Hint: The $1$felse$()$ function can do this fairly easily. Try looking at the help tile to see how to do this.$)($b$)(3$pts$)$ Replace the $3$rd entry of the Name variable with your full name. $1($i$)(3$pts$)$ Save this cleaned dataset as a csv file.