I am using R version 3.0.2 on Windows 7.
I load a CSV table into R and some of the column names have parentheses such as P(A) or P(A|B). If I try
whatever<- read.csv("C:/dir/name.csv", header=TRUE);
hist(whatever$P(A|B));
I get the error message
Error: unexpected symbol in "hist(whatever$P(A|B"
Is it possible, in R, to use column names with parentheses or must I change the column names to alphanumeric?
read.csv() will convert the special characters to '.' so the column 'P(A|B)' will be whatever$P.A.B..
However, as #Floo0 pointed out, if you can have column names like 'P(A|B)' which are accessed by whatever$"P(A|B)" or whatever[, "P(A|B)"].
Try
hist(whatever$"P(A|B)")
This should work fine.
Or use whatever[,i] where i is the number of column P(A|B)
Working example
whatever<-data.frame(test=rnorm(10))
colnames(whatever)<-"P(A|B)"
hist(whatever$"P(A|B)")
Related
Update 2020-5-14
Working with a different but similar dataset from here, I found read_csv seems to work fine. I haven't tried it with the original data yet though.
Although the replies didn't help solve the problem because my question was not correct, Shan's reply fits the original question I posted the most, so I accepted his answer.
Update 2020-5-12
I think my original question is not correct. Like mentioned in the comment, the data was quoted. Although changing the separator made the 11582 row in R look the same as the 11583 row in excel, it doesn't mean it's "right". Maybe there is some incorrect line switch due to inappropriate encoding or something, and thus causing some of the columns to be displaced. If I open the data with notepad++, the instance at row 11583 in excel is at the 11596 row.
Original question
I am trying to read the listings.csv from this dataset in kaggle into R. I downloaded the file and wrote the coderead.csv('listing.csv'). The first column, the column id, is supposed to be numeric. However, it shows:
listing$id[1:10]
[1] 2015 2695 3176 3309 7071 9991 14325 16401 16644 17409
13129 Levels: Ole Berl穩n!,16736423,Nerea,Mitte,Parkviertel,52.55554132116211,13.340658248460871,Entire home/apt,36,6,3,2018-01-26,0.16,1,279\n17312576,Great 2 floor apartment near Friederich Str MITTE,116829651,Selin,Mitte,Alexanderplatz,52.52349354926847,13.391003496971203,Entire home/apt,170,3,31,2018-10-13,1.63,1,92\n17316675,80簡 m of charm in 3 rooms with office space,116862833,Jon,Neuk繹lln,Schillerpromenade,52.47499080234379,13.427509313575928...
I think it is because there are values with commas in the second column. For example, opening the file with MiCrosoft excel, I can see one of the value in the second column is Ole,Ole...:
How can I read a csv file into R correctly when some values contain commas?
Since you have access to the data in Excel, you can 'Save As' in Excel with a seperator other than comma (,). First go in to Control Panel –> Region and Language -> Additional settings, you can change the "List Seperator". Most common one other than comma is pipe symbol (|). In R, when you read_csv, specify the seperator as '|'.
You could try this?
lsitings <- read.csv("listings.csv", stringsAsFactors = FALSE)
listings$name <- gsub(",","", listings$name) - This will remove the comma in Col name
If you don't need the information in the second column, then you can always delete it (in Excel) before importing into R. The read.csv function, which calls scan, can also omit unwanted columns using the colClasses argument. However, the fread function from the data.table package does this much more simply with the drop argument:
library(data.table)
listings <- fread("listings.csv", drop=2)
If you do need the information in that column, then other methods are needed (see other solutions).
Tried copying an old working code which substituted 2 values instead of 3. This isn't working though. Here it is:
Names <- c("Robert", "Mandy", "Mordecai")
Search <-function(find,relace,type){
gsub("find","relace",type)
}
Search("o","ooo", Names) #getting Names vector but no replacements
You need to remove the "'s from the line with the gsub call. Try:
gsub(find,relace,type)
I'm trying to read in a .csv file from the IRS and it doesn't appear to be formatted in any weird way.
I'm using the read.table() function, which I have used several times in the past but it isn't working this time; instead, I get this error:
data_0910<-read.table("/Users/blahblahblah/countyinflow0910.csv",header=T,stringsAsFactors=FALSE,colClasses="character")
Error in read.table("/Users/blahblahblah/countyinflow0910.csv", :
more columns than column names
Why is it doing this?
For reference, the .csv files can be found at:
http://www.irs.gov/uac/SOI-Tax-Stats-County-to-County-Migration-Data-Files
(The ones I need are under the county to county migration .csv section - either inflow or outflow.)
It uses commas as separators. So you can either set sep="," or just use read.csv:
x <- read.csv(file="http://www.irs.gov/file_source/pub/irs-soi/countyinflow1011.csv")
dim(x)
## [1] 113593 9
The error is caused by spaces in some of the values, and unmatched quotes. There are no spaces in the header, so read.table thinks that there is one column. Then it thinks it sees multiple columns in some of the rows. For example, the first two lines (header and first row):
State_Code_Dest,County_Code_Dest,State_Code_Origin,County_Code_Origin,State_Abbrv,County_Name,Return_Num,Exmpt_Num,Aggr_AGI
00,000,96,000,US,Total Mig - US & For,6973489,12948316,303495582
And unmatched quotes, for example on line 1336 (row 1335) which will confuse read.table with the default quote argument (but not read.csv):
01,089,24,033,MD,Prince George's County,13,30,1040
you have have strange characters in your heading # % -- or ,
For the Germans:
you have to change your decimal commas into a Full stop in your csv-file (in Excel:File -> Options -> Advanced -> "Decimal seperator") , then the error is solved.
Depending on the data (e.g. tsv extension) it may use tab as separators, so you may try sep = '\t' with read.csv.
This error can get thrown if your data frame has sf geometry columns.
I have a csv download of data from a Management Information system. There are some variables which are dates and are written in the csv as strings of the format "2012/11/16 00:00:00".
After reading in the csv file, I convert the date variables into a date using the function as.Date(). This works fine for all variables that do not contain any blank items.
For those which do contain blank items I get the following error message:
"character string is not in a standard unambiguous format"
How can I get R to replace blank items with something like "0000/00/00 00:00:00" so that the as.Date() function does not break? Are there other approaches you might recommend?
If they're strings, does something as simple as
mystr <- c("2012/11/16 00:00:00"," ","")
mystr[grepl("^ *$",mystr)] <- NA
as.Date(mystr)
work? (The regular expression "^ *$" looks for strings consisting of the start of the string (^), zero or more spaces (*), followed by the end of the string ($). More generally I think you could use "^[[:space:]]*$" to capture other kinds of whitespace (tabs etc.)
Even better, have the NAs correctly inserted when you read in the CSV:
read.csv(..., na.strings='')
or to specify a vector of all the values which should be read as NA...
read.csv(..., na.strings=c('',' ',' '))
I am trying to read this file (3.8mb) using its fixed-width structure as described in the following link.
This command:
a <- read.fwf('~/ccsl.txt',c(2,30,6,2,30,8,10,11,6,8))
Produces an error:
line 37 did not have 10 elements
After replicating the issue with different values of the skip option, I figured that the lines causing the problem all contain the "#" symbol.
Is there any way to get around it?
As #jverzani already commented, this problem is probably the fact that the # sign often used as a character to signal a comment. Setting the comment.char input argument of read.fwf to something other than # could fix the problem. I'll leave my answer below as a more general case that you can use on any character that causes problems (e.g. the 's in the Dutch city name 's Gravenhage).
I've had this problem occur with other symbols. The approach I took was to simply replace the # by either nothing, or by a character which does not generate the error. In my case it was no problem to simply replace the character, but this might not be possible in your case.
So my approach would be to delete the symbol that generates the error, or replace by another character. This can be done using a text editor (find and replace), in an R script, or using some linux tools called grep and sed. If you want to do this in an R script, use scan or readLines to read the lines. Once the text is in memory, you can use sub to replace the character.
If you cannot replace the character, I would try the following approach: replace the character by a character that does not generate an error, read it into R using read.fwf, and finally replace the character by the # character.
Following up on the answer above: to get all characters to be read as literals, use both comment.char="" and quote="" (the latter takes care of #PaulHiemstra's problem with single-quotes in Dutch proper nouns) in the call to read.fwf (this is documented in ?read.table).