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Text file time series in r12/24/2023 ![]() ![]() The reason to follow this routine is that R saves objects in memory. Large files take up a lot of memory in R. ![]() Before importing data from files it better to free existing memory from unused objects. In your working directory create a folder named Data and in this folder create a RandomFile.txt with the following content. The column values would be separated by whitespaces. > getwd() # get current working directory Id Nameīefore importing this file into a data frame object one needs to verify the current working directory in R Environment. We need to set the current working directory in the R Environment with the following command > setwd(‘’) # set current working directory If this working directory differs from our project folder. The principal function for reading data into R is the read.table function. There are other convenience functions like read.csv and lim that provide arguments to read.table appropriate for CSV and tab-delimited files. read.table function: Reads a file and creates a data frame from it. For small size file, you can call the read.table function by just specifying the file argument. > data print(data) # display the data frame details R will pick up default values of arguments and load the data frame. On executing the above code we get the following result: V1 V2 There are two issues that are apparent with the data frame and that is TEXT FILE TIME SERIES IN R CODE ![]() The first line has not been considered as a header.The class of the columns has been taken default as factors instead of taking the first column as numeric and the second column as character.To test the class of the data frame object. ![]()
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