Home/ Questions/The easy way to handle error - duplicate 'row.names' are not allowed.
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Everly Miller
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Asked: 2022-05-18T21:35:30+00:00 In:

The easy way to handle error – duplicate ‘row.names’ are not allowed.

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As advised, I used some code samples in another forum, but it could not improve the problem. My question is the “duplicate ‘row.names’ are not allowed” in R – how to solve it? The command line is:

StartDate, var1, var2, var3, ..., var14
systems <- read.table("http://getfile.pl?test.csv", header = TRUE, sep = ",")

and the result:

duplicate row.names are not allowed

What does the message mean? Can you advise me to fix it? If you have other better answers, leave them in the answer box below.

duplicate row.names
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2 Answers

  1. Best Answer
    Expert

    The cause:

    After looking over your problem, I find that except for the header row, each row in the file ends with a comma. This makes R misunderstand that the row names are in the 1st values column.

    Solution:

    The easiest way to solve this error is require read.table not to apply row.names:

    systems <- read.table("http://getfile.pl?test.csv",
header=TRUE, sep=",", row.names=NULL)

    You can see all your numbered rows after doing this.

    Then let’s check out read.csv, a wrapper for read.table that has the sep=',' and header=TRUE arguments configured previously, making your call easier to:

    systems <- read.csv("http://getfile.pl?test.csv", row.names=NULL)
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  2. The related question highlights a section of ?read.table documentation that answers your problem.

    If there is a header and the first row contains one fewer field
    than the number of columns, the first column in the input is used
    for the row names. Otherwise if row.names is missing, the rows are numbered.

    The header row is likely to have 1 less column than the rest of your file. Therefore read.table assumes the first column is the one.names (which must be unique), and not a column (which may contain duplicated value). This can be fixed by one of these two solutions:

    1. Add a delimiter (ie, \t or , to the front or the end of your header row within the source file.
    2. Remove trailing delimiters from your data

    Your data structure will determine which option you make.

    Example: The header row is taken to mean that there is one less column than the data, because the delimiters aren’t compatible: 

    v1,v2,v3 # 3 items!!
a1,a2,a3, # 4 items
b1,b2,b3, # 4 items

    This is how it’s interpreted by default 

     v1,v2,v3 # 3 items!!
a1,a2,a3, # 4 items
b1,b2,b3, # 4 items

    The values of the first column (without headers) are interpreted as row.names a1 or b1. This error can be caused by duplicates in this column, which is possible.

    You can set row.names = FALSE to make the shift not occur, but there is still a mismatch between the items in the header, and the data, because the delimiters aren’t compatible.

    Solution 1 Add trailing separator to header 

    v1,v2,v3, # 4 items!!
a1,a2,a3, # 4 items
b1,b2,b3, # 4 items

    Solution 2 Removing trailing delimiter in non-header rows 

    v1,v2,v3 # 3 items
a1,a2,a3 # 3 items!!
b1,b2,b3 # 3 items!!
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