An Architect's vision

Use read.table() It actually reads data into RAM. This is not good practice to use this for big data set. Use read.csv() or read.csv2() Assign to a variable nedat <- b="" data.csv="" orkingdirectory="" read.table=""> nedat    V1                                  V2 1  NA ,"EmpNo","EmpName","Location","Age" 2   1                  ,1,"AAAA","KOL",20 3   2                  ,2,"BBBB","MUM",23 4   3                  ,3,"CCCC","DEL",24 5   4                  ,4,"DDDD","CHE",45 6   5                  ,5,"EEEE","KOL",67 7   6                  ,6,"FFFF","MUM",54 8   7                  ,7,"GGGG","DEL",34 9   8                  ,8,"HHHH","CHE",65 10  9                  ,9,"IIII","KOL",45 11 10                 ,

Copy to a variable MyData <- file="D:/Workingdirectory/data.csv" header="TRUE," p="" read.csv="" sep=","> Create new file write.csv(MyData, file = "NewData.csv")

Identify current working directory getwd() Set working directory setwd() setwd("D:/Workingdirectory") Download file to your local directory URL <- https:="" p="" s3-xxxx="" testr.csv="" xxxxxx=""> download.file(URL, destfile = "data.csv", method="curl")