I was trying to remove all columns with a zero variance from my data, using this command
file <- file[,sapply(file, function(v) var(v, na.rm=TRUE)!=0)]
This command was working perfectly for my previous datasets, now I am trying to use on a new dataset and it gives me the following error:
Error in `[.data.frame`(file, , sapply(file, function(v) var(v, na.rm = TRUE) != :
undefined columns selected
In addition: Warning message:
In var(v, na.rm = TRUE) : NAs introduced by coercion
The problem is I did not select any columns, I just applied the function to all columns! How come I get an error telling me undefined columns selected!
Any idea what could have gone wrong??
The data looks exactly this way
col1 col2 col3 col4
1 FIA 3.5 2.4 NA
2 DWF 2.1 NA 3.7
3 LIK 0.25 2.3 1.38
4 JUW 2.1 4.0 3.2
The input file was a CSV file and read via the read.csv command, it had an extra empty column at the end of the table that was causing this problem, removing this last column via this command, solved the issue.
lastcol <- ncol(file)
file[,lastcol] <- NULL
Related
When I use R data.table(fread) to read dat file (3GB) a problem occurs:
Stopped early on line 3169933. Expected 136 fields but found 138. Consider fill=TRUE and comment.char=. First discarded non-empty line:
My code:
library(data.table)
file_path = 'data.dat' # 3GB
fread(file_path,fill=TRUE)
The problem is that my file has ~ 5 million rows. In detail:
From row 1 to row 3169933 it has 136 columns
From row 3169933 to row 5000000 it has 138 columns
fread() only reads my file to row 3169933 due to this error. fill = TRUE did not help in this case. Could anyone help me ?
R version: 3.6.3
data.table version: 1.13.2
Note about fill=TRUE in this case:
[Case 1- not my case] if part 1 of my file (50% rows) have 138 columns and part 2 have 136 columns then the fill=TRUE will help (it will fill two column in part 2 with NA)
[Case 2- my case] if part 1 of my file (50% rows) have 136 columns and part 2 have 138 columns then the fill =TRUE will not help in this case.
Not sure why you still have the problem even with fill=T... But if nothing helps, you can try playing with something like this:
tryCatch(
expr = {dt1 <<- fread(file_path)},
warning = function(w){
cat('Warning: ', w$message, '\n\n');
n_line <- as.numeric(gsub('Stopped early on line (\\d+)\\..*','\\1',w$message))
if (!is.na(n_line)) {
cat('Found ', n_line,'\n')
dt1_part1 <- fread(file_path, nrows=n_line)
dt1_part2 <- fread(file_path, skip=n_line)
dt1 <<- rbind(dt1_part1, dt1_part2, fill=T)
}
},
finally = cat("\nFinished. \n")
);
tryCatch() construct catches warning message so you can extract the line number and process it accordingly.
Try to read them separately, combine them after creating two extra columns for the first part.
first_part = fread('data.dat', nrows = 3169933) %>%
mutate(extra_1 = NA, extra_2 = NA)
second_part = fread('data.dat', skip = 3169933)
df = bind_rows(first_part, second_part)
I'm trying to write an xlsx file from a list of dataframes that I created but I'm getting an error due to missing data (I couldn't download it). I just want to write the xlsx file besides having this lacking data. Any help is appreciated.
For replication of the problem:
library(quantmod)
name_of_symbols <- c("AKER","YECO","SNOA")
research_dates <- c("2018-11-19","2018-11-19","2018-11-14")
my_symbols_df <- lapply(name_of_symbols, function(x) tryCatch(getSymbols(x, auto.assign = FALSE),error = function(e) { }))
my_stocks_OHLCV <- list()
for (i in 1:3) {
trade_date <- paste(as.Date(research_dates[i]))
OHLCV_data <- my_symbols_df[[i]][trade_date]
my_stocks_OHLCV[[i]] <- data.frame(OHLCV_data)
}
And you can see the missing data down here in my_stocks_OHLCV[[2]] and the write.xlsx error I'm getting:
print(my_stocks_OHLCV)
[[1]]
AKER.Open AKER.High AKER.Low AKER.Close AKER.Volume AKER.Adjusted
2018-11-19 2.67 3.2 1.56 1.75 15385800 1.75
[[2]]
data frame with 0 columns and 0 rows
[[3]]
SNOA.Open SNOA.High SNOA.Low SNOA.Close SNOA.Volume SNOA.Adjusted
2018-11-14 1.1 1.14 1.01 1.1 107900 1.1
write.xlsx(my_stocks_OHLCV, "C:/Users/MICRO/Downloads/Datasets_stocks/dux_OHLCV.xlsx")
Error in (function (..., row.names = NULL, check.rows = FALSE,
check.names = TRUE,:arguments imply differing number of rows: 1, 0
How do I run write.xlsx even though I have this missing data?
The main question you need to ask is, what do you want instead?
As you are working with stock data, the best idea, is that if you don't have data for a stock, then remove it. Something like this should work,
my_stocks_OHLCV[lapply(my_stocks_OHLCV,nrow)>0]
If you want a row full of NA or 0
Then use the lapply function and for each element of the list, of length 0, replace with either NA's, vector of 0's (c(0,0,0,0,0,0)) etc...
Something like this,
condition <- !lapply(my_stocks_OHLCV,nrow)>0
my_stocks_OHLCV[condition] <- data.frame(rep(NA,6))
Here we define the condition variable, to be the elements in the list where you don't have any data. We can then replace those by NA or swap the NA for 0. However, I can't think of a reason to do this.
A variation on your question, and one you could handle inside your for loop, is to check if you have data, and if you don't, replace the values there, with NAs, and you could given it the correct headers, as you know which stock it relates to.
Hope this helps.
I am trying to assign values to a dataframe variable defined by the user. The user specifies the name of the variable, let's call this x, in the dataframe df. For simplicity I want to assign a value of 3 to everything in the column the user specifies. The simplified code is:
variableName <- paste("df$", x, sep="")
eval(parse(text=variableName)) <- 3
But I get an error:
Error in file(filename, "r") : cannot open the connection
In addition: Warning message:
In file(filename, "r") :
cannot open file 'df$x': No such file or directory
I've tried all kinds of remedies to no avail. If I simply try to print the values of the column.
eval(parse(text=variableName))
I get no errors and it prints out ok. It's only when I try to give that column a value that I get the error. Any help would be appreciated.
I believe the issue is that there is no way to use the result of eval() on the LHS of an assignment.
df = data.frame(foo = 1:5,
bar = -3)
x = "bar"
variableName <- paste("df$", x, sep="")
eval(parse(text=variableName)) <- 3
#> Warning in file(filename, "r"): cannot open file 'df$bar': No such file or
#> directory
#> Error in file(filename, "r"): cannot open the connection
## This error is a bit misleading. Breaking it apart I get a different error.
eval(expression(df$bar)) <- 3
#> Error in eval(expression(df$bar)) <- 3: could not find function "eval<-"
## And it works if you put it all in the string to be parsed.
ex1 <- paste0("df$", x, "<-3")
eval(parse(text=ex1))
df
#> foo bar
#> 1 1 3
#> 2 2 3
#> 3 3 3
#> 4 4 3
#> 5 5 3
## But I doubt that's the best way to do it!
I have lot's of files in my directoy and I want to read all files and select the second columns of them and put those columns as rows of a matrix, but I face with strange error.
would anybody help me to figure out, what's going wrong with my code ?
Here is my effort:
#read all files in one directoy into R and select desired column
nm <- list.files(path="April/mRNA_expression/")
Gene_exp<-do.call(rbind, lapply(nm, function(x) read.table(file=x,header=TRUE, sep= ",")[, 2]))
save(Gene_exp, file="Path to folder")
The error I get is :
## Error in `[.data.frame`(read.table(file = x, header = TRUE, sep = ""), :
## undefined columns selected*
To check that, really my files have 2 columns I did this :
b <- read.table("A.genes.normalized_results", sep="")
dim(b)
## [1] 20532 2
My text file Looks like this :
gene_id normalized_count
?|100130426 0.0000
?|100133144 10.6340
?|100134869 5.6790
?|10357 106.4628
?|10431 710.8902
?|136542 0.0000
?|155060 132.2883
?|26823 0.5098
?|280660 0.0000
?|317712 0.0000
?|340602 0.0000
?|388795 1.2745
?|390284 5.3527
?|391343 2.5489
?|391714 0.7647
?|404770 0.0000
?|441362 0.0000
The better solution would be to only import the second column when reading it. Use the colClasses argument to completely skip the first:
Gene_exp<-do.call(rbind, lapply(nm, function(x) read.delim(file=x,header=TRUE, colClasses=c('NULL', 'character'))))
I am assuming the second column is character. Change it to the appropriate class if you need to.
I am trying to input a large (> 70 MB) fixed format text file into r. For a smaller file (< 1MB), I can use the read.fwf() function as shown below.
condodattest1a <- read.fwf(impfile1,widths=testcsv3$Varlen,col.names=testcsv3$Varname)
When I try to run the line of code below,
condodattest1 <- read.fwf(impfile,widths=testcsv3$Varlen,col.names=testcsv3$Varname)
I get the following error message:
Error: cannot allocate vector of size 2 Kb
The only difference between the 2 lines is the size of the input file.
The formatting for the file I want to import is given in the dataframe called testcsv3. I show a small snippet of the dataframe below:
> head(testcsv3)
Varlen Varname Varclass Varsep Varforfmt
1 2 "V1" "character" 2 "A2.0"
2 15 "V2" "character" 17 "A15.0"
3 28 "V3" "character" 45 "A28.0"
4 3 "V4" "character" 48 "F3.0"
5 1 "V5" "character" 49 "A1.0"
6 3 "V6" "character" 52 "A3.0"
At least part of my problem is that I am reading in all the data as factors when I use read.fwf() and I end up exceeding the memory limit on my computer.
I tried to use read.table() as a way of formatting each variable but it seems I need a text delimiter with that function. There is a suggestion in section 3.3 in the link below that I could use sep to identify the column where every variable starts.
http://data.princeton.edu/R/readingData.html
However, when I use the command below:
condodattest1b <- read.table(impfile1,sep=testcsv3$Varsep,col.names=testcsv3$Varname, colClasses=testcsv3$Varclass)
I get the following error message:
Error in read.table(impfile1, sep = testcsv3$Varsep, col.names = testcsv3$Varname, : invalid 'sep' argument
Finally, I tried to use:
condodattest1c <- read.fortran(impfile1,lengths=testcsv3$Varlen, format=testcsv3$Varforfmt, col.names=testcsv3$Varname)
but I get the following message:
Error in processFormat(format) : missing lengths for some fields
In addition: Warning messages:
1: In processFormat(format) : NAs introduced by coercion
2: In processFormat(format) : NAs introduced by coercion
3: In processFormat(format) : NAs introduced by coercion
All I am trying to do at this point is format the data when they come into r as something other than factors. I am hoping this will limit the amount of memory I am using and allow me to actually input the file. I would appreciate any suggestions about how I can do this. I know the Fortran formats for all the variables and the column at which each variable begins.
Thank you,
Warren
Maybe this code works for you. You have to fill varlen with the field sizes and add the corresponding type strings (e.g. numeric, character, integer) to colclasses
my.readfwf <- function(filename,varlen,colclasses) {
sidx <- cumsum(c(1,varlen[1:(length(varlen)-1)]))
eidx <- sidx+varlen-1
filecontent <- scan(filename,character(0),sep="\n")
if (any(diff(nchar(filecontent))!=0))
stop("line lengths differ!")
nlines <- length(filecontent)
res <- list()
for (i in seq_along(varlen)) {
res[[i]] <- sapply(filecontent,substring,first=sidx[i],last=eidx[i])
mode(res[[i]]) <- colclasses[i]
}
attributes(res) <- list(names=paste("V",seq_along(res),sep=""),row.names=seq_along(res[[1]]),class="data.frame")
return(res)
}