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If I do not add arguments dec and sep columns are right, but quoted numeric data appears to be char. If I only specify dec = ",", columns are wrong (it separates by \t or blanks, instead of commas). If I try to specify dec = ",", sep = ",", then I get
sep== dec (',') isnotallowed
I'm conscious of the ambiguity of this instruction, since 13800,10864 could be just a decimal number, but then, I would set as assumption that the dec = "," only would apply to data inside quotes
The text was updated successfully, but these errors were encountered:
Well, then I think you are asking too much here. You have quoted strings but don't want to parse these as strings, which is against common convention. Ignoring that issue, you would have commas both as column separator and as decimal separator, which simply isn't a valid file format. I suggest, you post-process after importing, i.e., as.numeric(sub(",", ".", "27,03", fixed = TRUE)).
Found a csv file with data formatted as follows:
If I do not add arguments
dec
andsep
columns are right, but quoted numeric data appears to be char. If I only specifydec = ","
, columns are wrong (it separates by \t or blanks, instead of commas). If I try to specifydec = ",", sep = ","
, then I getI'm conscious of the ambiguity of this instruction, since
13800,10864
could be just a decimal number, but then, I would set as assumption that thedec = ","
only would apply to data inside quotesThe text was updated successfully, but these errors were encountered: