I am trying to export a table to CSV format, but one of my columns is special - it's like a number string except that the length of the string needs to be the same every time, so I add trailing spaces to shorter numbers to get it to a certain length (in this case I make it length 5).
library(dplyr)
library(readr)
df <- read.table(text="ID Something
22 Red
55555 Red
123 Blue
",header=T)
df <- mutate(df,ID=str_pad(ID,5,"right"," "))
df
ID Something
1 22 Red
2 55555 Red
3 123 Blue
Unfortunately, when I try to do write_csv somewhere, the trailing spaces disappear which is not good for what I want to use this for. I think it's because I am downloading the csv from the R server and then opening it in Excel, which messes around with the data. Any tips?
str_pad() appears to be a function from stringr package, which is not currently available for R 3.5.0 which I am using - this may be the cause of your issues as well. If it the function actually works for you, please ignore the next step and skip straight to my Excel comments below
Adding spaces. Here is how I have accomplished this task with base R
# a custom function to add arbitrary number of trailing spaces
SpaceAdd <- function(x, desiredLength = 5) {
additionalSpaces <- ifelse(nchar(x) < desiredLength,
paste(rep(" ", desiredLength - nchar(x)), collapse = ""), "")
paste(x, additionalSpaces, sep="")
}
# use the function on your df
df$ID <- mapply(df$ID, FUN = SpaceAdd)
# write csv normally
write.csv(df, "df.csv")
NOTE When you import to Excel, you should be using the 'import from text' wizard rather than just opening the .csv. This is because you need marking your 'ID' column as text in order to keep the spaces
NOTE 2 I have learned today, that having your first column named 'ID' might actually cause further problems with excel, since it may misinterpret the nature of the file, and treat it as SYLK file instead. So it may be best avoiding this column name if possible.
Here is a wiki tl;dr:
A commonly encountered (and spurious) 'occurrence' of the SYLK file happens when a comma-separated value (CSV) format is saved with an unquoted first field name of 'ID', that is the first two characters match the first two characters of the SYLK file format. Microsoft Excel (at least to Office 2016) will then emit misleading error messages relating to the format of the file, such as "The file you are trying to open, 'x.csv', is in a different format than specified by the file extension..."
details: https://en.wikipedia.org/wiki/SYmbolic_LinK_(SYLK)
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).
I have got this .txt file outputed by a microscope to process.
#read the .txt file generated by microscope, skipping the first 9 lines of garbage information
df <- read.csv("Objects_Population - AllCells.txt", sep="\t", skip = 9,header=TRUE, fill = T)
Then I started looking at the structure of the dataframe, everything seems fine except I now found an extra column in the end of the data frame named "x.1" and all rows of it are NA values. I don't see this column when I open the .txt file in excel. I suspect the problem has something to do with the column names generated by microscope, they contain quite some special characters
Below is the dataframe read by Excel(only showing the last 2 columns since I have 132 columns, and their names are disgustingly long):
AllCells - Cell Contact Area with Neighbors [%] AllCells - Nucleus Nearest Neighbor Distance [µm]
0 4.82083
21.9512 0
15.7895 0
29.4118 0.584611
0 4.21569
0 1.99599
0 3.50767
...
This has happened to me before but I never took it too serious as I was always interested in a subset of my data frame. Now I'm looking at all columns then this starts to bothering me.
Is there any way I can read them correctly without R attaching that additional "X.1" column in the end? Preferably not manually delete or subset out the last column...
Cheers,
ML
If all other column names are correct, you have probably a trailing \t in the text file. R tries to include it and gives it the generic column name X.1.
You could try and read the file first as 'plain text' and remove the trailing \t and only then use read.csv:
file_connection <- file("Objects_Population - AllCells.txt")
content <- readLines(file_connection )
close(file_connection)
Now we try to get rid of these trailing \t (this might need some testing to fit your needs)
sanitized <- gsub("\\t$", "", content)
And then we read this sanitized string as if it was a file (using the argument text)
df <- read.csv(text=paste0(sanitized, collapse="\n"), sep="\t", skip = 9,header=TRUE, fill = T)
Had that problem too. Fixed it by saving the file as "CSV (MS-DOS (*csv)" instead of what I originally had as "CSV (Comma delimited)(*csv)".
This is almost certainly because you've got an extra empty column in your spreadsheet.
In Excel, open your sheet and press Ctrl-End. If you end up in an empty cell outside the range of your data, there's the problem. Select the column (Ctrl-Space), right-click, and choose Delete.
I also encountered similar problem. I found that three extra columns were created (X, X.1, X.2), after I loaded dataset from excel sheet to R studio.
Steps Followed by me:
a) I went to the excel sheet and selected those three extra columns after last column with actual values in excel sheet. Selected extra 3 columns by keeping cursor on top of columns and then right click the mouse and select delete.
b) Again loaded that excel sheet in R. I did not find those 3 columns.
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 would like to direct output to a file, using a write.csv statement. I am wanting to write 16 different output files, labeling each one with the extension 1 through 16.
Example as written now:
trackfilenums=1:16
for (i in trackfilenums){
calculations etc
write.csv(max.hsi, 'Severity_Index.csv', row.names=F)
}
I would like for the output csv files to be labeled 'Severity_Index_1.csv', 'Severity_Index_2.csv', etc. Not sure how to do this in R language.
Thanks!
Kimberly
You will want to use the paste command:
write.csv(max.hsi, paste0("Severity_Index_", i,".csv"), row.names=F)
Some people like to have file names like Name_01 Name_02 etc instead of Name_1 Name_2 etc. This may, for example, make the alphabetical order more reasonable: with some software, otherwise, 10 would come after 1, 20 after 2, etc.
This kind of numbering can be achieved with sprintf:
sprintf("Severity_Index_%02d.csv", 7)
The interesting part is %02d -- this says that i is an integer value (could actually use %02i as well) that will take at least 2 positions, and leading zero will be used if necessary.
# try also
sprintf("Severity_Index_%03d.csv", 7)
sprintf("Severity_Index_%2d.csv", 7)
To add to the other answers here, I find it's also a good idea to sanitise the pasted string to make sure it is ok for the file system. For that purpose I have the following function:
fsSafe <- function(string) {
safeString <- gsub("[^[:alnum:]]", "_", string)
safeString <- gsub("_+", "_", safeString)
safeString
}
This simply strips out all non-alphabetic and non-numeric characters and replacing them with an underscore.
I am trying to read a flat file into R.
It is separated by ';' and has 12 leading lines of comments to describe the content.
I want to read the file and exlude the comments.
The problem however is that the commented line 11 contains the data headers as follows:
# Fields: labno; name; dob; sex; location; date
Is there a way that I can extract the headers form the comments and apply them to the data. The way I thought of doing it was to read the first 11 lines only and store everything from labno as a vector. The I would read everything from line 13 and use the store vector as column names for the the date.
Is there a way to read the first 11 lines and remove everything before labno
Thanks.
Step1: (read only the eleventh row containing column names. )
hdrs <- read.table("somefile.txt", nrows=1, skip=10, comment.char="")
Step2: (read the rest of the file, allowing default automatic names)
dat <- read.table("somefile.txt", skip=12)
Step3: (remove extraneous characters before applying the ‘fields’ as column names)
names(dat) <- scan(textConnection(sub("# Fields\\:", "", hdrs)),
what="character", sep=";")
Later versions of R allow ‘scan’ to have a ‘text’ argument rather than requiring the awkward textConnection function.