Question

After Loading the .csv file into your R session (it could be any CSV file), and how can we do the following commands to find information

(a)List column names of .csv file

(b) change the name of the last two column respectively. Leave first column name as Year.

(c)Confirm that column names have changed as expected.

(d) Eliminate all rows with NA fields, if any.

(e) Set "Year" as a factor.

(f) Verify (e) has worked.

Answer 1

Reading csv file is very simple as that using read.csv

example:

# Read "comma separated value" files (".csv")

read.csv(file, header = TRUE, sep = ",", dec = ".", ...)

Here you need to understand that if your file is in same folder you need to give the fileName Directly and if it is in another directory you need to give the full path.

a) Reading colomNames from csv

In my system i had a csv file named as Data.csv, first i need to take the data of the csv file to a variable as shown below.
Dt_1 = read.csv("Data.csv", header = TRUE , sep = "," )

names(DT_1)

output : [1] "Name" "Address" "Phone_Number"

b)changing  the name of the last two column respectively.

Dt_1%>% rename( Address = Area , Phone _Number = Mobile)

c)To get the expected answer again run the above code i.e, names(DT_1) you will be seeing the changes as follows

output : [1] "Name" " Area" "Mobile"

d) To drop rows or fields which has 'NA' as the field we have many ways but following code works perfect

using library(tidyr)
Dt_1 %>% drop_na()

e)we use following query

ft<-factor(year, levels, labels = levels,
       exclude = NA, ordered = is.ordered(year), nmax = NA)

f)
is.factor(ft)
is.ordered(ft)

If you have given the data has clear i have been upload with snapshots

as of now this will work .