Question

Name	Gender	Designation	SSN	Age
Wlliam Johnson	M	Officer	222-22-1111	25
Mike Smith	M	Intern	333-33-1111	22
Tom Walker	M	Accountant	200-20-2000	23
Jared Smith	M	CEO	211-11-2111	20
Walker Johnson	M	CFO	300-00-0122	21
William Smith	M	Supervisor	123-12-1234	28
Haley Smith	F	Asst. Supervisor	234-23-2345	29
Sheley Homes	F	Safety Mngr	555-55-5656	22
Kate Winslate	F	Receptionist	258-25-8888	24
Jack Dawson	M	Operator 1	235-21-0000	27
Beth Kenyatta	F	Operator 2	411-33-2546	30
Simba Wetu	M	Inspector	365-25-1234	23
Jane Sams	F	Driver	100-45-2150	34
Joshua Knowles	M	Shipping Clerk	300-16-7140	31
Martha Stewart	F	Shipping Mngr	100-15-1324	25
Ashley Thompson	F	Janator	300-56-4123	26
Asha Williams	F	Trainer	201-23-1235	30
Jared Walker	M	IT Manager	450-47-2354	25
Taylor Homes	F	R&D Intern	532-11-2563	33
Mike Weber	M	Analyst	325-00-1254	31

Copy and Paste data to excel and using RStudio help with the following

2. Output all the employee genders.

3. Output all the details of employees 12:20

4. Output the summary of the data frame.

5. Add a new employee row to the data frame.

6. Output all the details of the employees whose designation belongs to a category you prefer. For example, clerk.

7. Output all the details of the employees whose age is greater than a particular number. For example, age>20.

8. Write the data frame to a csv file.

9. Read this csv file into R with and without default headers.

10. Change the SSN number of an employee to a new number you like. For example, if it was 300-16-7140 initially, change it to 200-45-2150.

Answer 1

Firstly reading csv into dataframe using read.csv() function

data<-read.csv(file="C:/Users/keerthi raja/Desktop/Book1.csv")
new<-data.frame(data)
new

the initial output is:

2) simply to display all the genders use $symbol to select particula column from the data frame

new$Gender

output:

3) now to display 12:20 all employees data use indexing of data frames

  new[12:20,] //which means select 12:20 rows with all columns

output:

  

4)summary() function will give following results:

output:

5) we add a new row using rbind() function

  newemployee<-data.frame(Name="Jonathan",Gender="M",Designation="CEO",SSN="100-101-224",Age=22)
rbind(new,newemployee)

output:

6) to subset a dataframe using a specific condition we use subset() function

  Ceo<-subset(new,Designation == "CEO")
print(Ceo)

output:

7)  newdata<-subset(new, age > 20)
newdata

8) For writing we have write.csv() function

  write.csv(new,"myname.csv")