R read.csv "More columns than column names" error

r import

108,139

Solution 1

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

Solution 2

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.

Solution 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.

Solution 4

try read.table() instead of read.csv()

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108,139

Author by

Vicki1227

Updated on July 09, 2022

Comments

Vicki1227 almost 2 years
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！
hrbrmstr over 9 years

Should be colClasses=, and the CSV file is really wonky. That particular method does not produce a viable data frame for that data.
mgriebe over 9 years

Can you skip the header row?
hrbrmstr over 9 years

The problem is there is not just a single header row, there are 10 interspersed throughout the whole file
mgriebe over 9 years

Then remove them. Presumably you do not want any duplicates. You can use unique to remove duplicates.
hrbrmstr over 9 years

It's not my data and that's what my code does. With your last revision, the poster can use the data once they remove the all NA columns.
mgriebe over 9 years

readlines + grep to filter is a good idea. I'll give you a +1.
mgriebe over 9 years

Remember, the OP wanted to get past the error. header=F does that.
Waseem Ahmad Naeem almost 6 years

This is way better then other but how to tackle with null values in table, then?
Admin over 5 years

i am not sure whether you mean this : df [is.na(df)] <- 0 ?
Kon Ath over 2 years

You just saved me!