I am aware that there are similar questions on this site, however, none of them seem to answer my question sufficiently.
This is what I have done so far:
I have a csv file which I open in excel. I manipulate the columns algebraically to obtain a new column "A". I import the file into R using read.csv()
and the entries in column A are stored as factors - I want them to be stored as numeric. I find this question on the topic:
Imported a csv-dataset to R but the values becomes factors
Following the advice, I include stringsAsFactors = FALSE
as an argument in read.csv()
, however, as Hong Ooi suggested in the page linked above, this doesn't cause the entries in column A to be stored as numeric values.
A possible solution is to use the advice given in the following page:
How to convert a factor to an integer\numeric without a loss of information?
however, I would like a cleaner solution i.e. a way to import the file so that the entries of column entries are stored as numeric values.
Cheers for any help!
It's likely because they were originally factor s. You need as. numeric(as. character(........))
The contents of a CSV file can be read as a data frame in R using the read. csv(…) function. The CSV file to be read should be either present in the current working directory or the directory should be set accordingly using the setwd(…)
csv() Function. read. csv() function in R Language is used to read “comma separated value” files. It imports data in the form of a data frame.
Whatever algebra you are doing in Excel to create the new column could probably be done more effectively in R.
Please try the following: Read the raw file (before any excel manipulation) into R using read.csv(... stringsAsFactors=FALSE)
. [If that does not work, please take a look at ?read.table
(which read.csv
wraps), however there may be some other underlying issue].
For example:
delim = "," # or is it "\t" ? dec = "." # or is it "," ? myDataFrame <- read.csv("path/to/file.csv", header=TRUE, sep=delim, dec=dec, stringsAsFactors=FALSE)
Then, let's say your numeric columns is column 4
myDataFrame[, 4] <- as.numeric(myDataFrame[, 4]) # you can also refer to the column by "itsName"
In read.table
(and its relatives) it is the na.strings
argument which specifies which strings are to be interpreted as missing values NA
. The default value is na.strings = "NA"
If missing values in an otherwise numeric variable column are coded as something else than "NA
", e.g. ".
" or "N/A
", these rows will be interpreted as character
, and then the whole column is converted to character
.
Thus, if your missing values are some else than "NA
", you need to specify them in na.strings
.
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