Question: How I can check my Working Directory so that I would be able to import my data in R.
Answer: To find the working directory, the command getwd() can be used, that is
Question: How I can change the working directory to my own path.
Answer: Use function setwd(), that is
Question: I have data set stored in text format (ASCII) that contain rectangular data. How I can read this data in tabular form. I have already set my working directory.
Answer: As data is already in a directory, which is set as the working directory, use following command
> mydata <- read.table(“data.dat”)
> mydata <- read.table(“data.txt”)
mydata is named object that will have data from file “data.dat” or “data.txt” in data frame format. Each variable in the data file will be named by default V1, V2,…
Question: How this stored data can be to accessed?
Answer: To access the stored data, write data frame object name (“mydata”) with $ sign and name of the variable. That is,
> mydata[ , 1]
Question: My data file has variables names in first row of the data file. In previous Question, variables names were V1, V2, V3, … How I can get actual names of the variable store in first row of data.dat file.
Answer: Instead of reading a data file with default values of arguments, use
> read.table(“data.dat”, header = TRUE)
Question: I want to read a data file which is not stored in the working directory?
Answer: To access the data file which is not stored in the working directory, provide complete path of the file, such as.
> read.table(“d:/data.dat” , header = TRUE)
> read.table(“d:/Rdata/data.txt” , header = TRUE)
Note that read.table() is used to read the data from external files that has a normally a special form:
- The first line of the file should have a name for each variable in the data frame. However, if the first row does not contain the name of a variable then header argument should not be set to FALSE.
- Each additional line of the file has its first item a row label and the values for each variable.
In R it is strongly suggested that variables need to be held in the data frame. For this purpose read.table() function can be used. For further details about read.table() function use,