R read.csv“列多于列名”错误

Question

I have a problem when importing .csv file into R. With my code:

t <- read.csv("C:\\N0_07312014.CSV", na.string=c("","null","NaN","X"),
          header=T, stringsAsFactors=FALSE,check.names=F)

R reports an error and does not do what I want:

Error in read.table(file = file, header = header, sep = sep, quote = quote,  : 
  more columns than column names

I guess the problem is because my data is not well formatted. I only need data from [,1:32] . All others should be deleted.

Data can be downloaded from: https://drive.google.com/file/d/0B86_a8ltyoL3VXJYM3NVdmNPMUU/edit?usp=sharing

Thanks so much！

Answer 1

Open the .csv as a text file (for example, use TextEdit on a Mac) and check to see if columns are being separated with commas.

csv is "comma separated vectors". For some reason when Excel saves my csv's it uses semicolons instead.

When opening your csv use:

read.csv("file_name.csv",sep=";")

Semi colon is just an example but as someone else previously suggested don't assume that because your csv looks good in Excel that it's so.

Answer 2

That's one wonky CSV file. Multiple headers tossed about (try pasting it to CSV Fingerprint ) to see what I mean.

Since I don't know the data, it's impossible to be sure the following produces accurate results for you, but it involves using readLines and other R functions to pre-process the text:

# use readLines to get the data
dat <- readLines("N0_07312014.CSV")

# i had to do this to fix grep errors
Sys.setlocale('LC_ALL','C')

# filter out the repeating, and wonky headers
dat_2 <- grep("Node Name,RTC_date", dat, invert=TRUE, value=TRUE)

# turn that vector into a text connection for read.csv
dat_3 <- read.csv(textConnection(paste0(dat_2, collapse="\n")),
                  header=FALSE, stringsAsFactors=FALSE)

str(dat_3)
## 'data.frame':    308 obs. of  37 variables:
##  $ V1 : chr  "Node 0" "Node 0" "Node 0" "Node 0" ...
##  $ V2 : chr  "07/31/2014" "07/31/2014" "07/31/2014" "07/31/2014" ...
##  $ V3 : chr  "08:58:18" "08:59:22" "08:59:37" "09:00:06" ...
##  $ V4 : chr  "" "" "" "" ...
## .. more
##  $ V36: chr  "" "" "" "" ...
##  $ V37: chr  "0" "0" "0" "0" ...

# grab the headers
headers <- strsplit(dat[1], ",")[[1]]

# how many of them are there?
length(headers)
## [1] 32

# limit it to the 32 columns you want (Which matches)
dat_4 <- dat_3[,1:32]

# and add the headers
colnames(dat_4) <- headers

str(dat_4)
## 'data.frame':    308 obs. of  32 variables:
##  $ Node Name         : chr  "Node 0" "Node 0" "Node 0" "Node 0" ...
##  $ RTC_date          : chr  "07/31/2014" "07/31/2014" "07/31/2014" "07/31/2014" ...
##  $ RTC_time          : chr  "08:58:18" "08:59:22" "08:59:37" "09:00:06" ...
##  $ N1 Bat (VDC)      : chr  "" "" "" "" ...
##  $ N1 Shinyei (ug/m3): chr  "" "" "0.23" "null" ...
##  $ N1 CC (ppb)       : chr  "" "" "null" "null" ...
##  $ N1 Aeroq (ppm)    : chr  "" "" "null" "null" ...
## ... continues

Answer 3

If you only need the first 32 columns, and you know how many columns there are, you can set the other columns classes to NULL.

read.csv("C:\\N0_07312014.CSV", na.string=c("","null","NaN","X"),
      header=T, stringsAsFactors=FALSE,
      colClasses=c(rep("character",32),rep("NULL",10)))

If you do not want to code up each colClass and you like the guesses read.csv then just save that csv and open it again.

Alternatively, you can skip the header and name the columns yourself and remove the misbehaved rows.

A<-data.frame(read.csv("N0_07312014.CSV",
                        header=F,stringsAsFactors=FALSE,
                        colClasses=c(rep("character",32),rep("NULL",5)),
                        na.string=c("","null","NaN","X")))
Yournames<-as.character(A[1,])
names(A)<-Yournames
yourdata<-unique(A)[-1,]

The code above assumes you do not want any duplicate rows. You can alternatively remove rows that have the first entry equal to the first column name, but I'll leave that to you.

Answer 4

尝试 read.table() 而不是 read.csv()

Answer 5

I was also facing the same issue. Now solved.

Just use header = FALSE

read.csv("data.csv", header = FALSE) -> mydata

Answer 6

I had the same problem. I opened my data in textfile and double expressions are separated by semicolons, you should replace them with a period

Answer 7

I was having this error that was caused by multiple rows of meta data at the top of the file. I was able to use read.csv by doing skip= and skipping those rows.

data <- read.csv('/blah.csv',skip=3)

Answer 8

对我来说，解决方案是使用 csv2 而不是 csv。

Answer 9

read.csv("file_name.csv", header=F);

Setting the HEADER to be FALSE will do the job perfectly for you...