I know this question has probably been asked quite often, but I am still having a lot of trouble with it.
So far what I have is week1.txt. I am able to load the data into R with
week1 = read.csv("week1.txt")
but the file is created so that the values for all six columns are in the first column, with each new column that I need being separated by a space. How would I separate the first column into six columns with each new column starting at the space? I have tried and tried but just can't get it.
You need to explicitly specify space as a separator:
week1 = read.csv("week1.txt", sep=" ")
The default separator for read.csv() is a comma, which wasn't helping to separate the columns in your input file.
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 stumped. My issue is that I want to grab specific names from a given column. However, when I try and filter them I get most of the names except for a few, even though I can clearly see their names in the original excel file. I think it has to do what some sort of special characters or spacing in the name column. I am confused on how I can fix this.
I have tried using excels clean() function to apply that to the given column. I have tried working an Alteryx flow to clean the data. All of these steps haven't helped any. I am starting to wonder if this is an r issue.
surveyData %>% filter(`Completed By` == "Spencer,(redbox with whitedot in middle)Amy")
surveyData %>% filter(`Completed By` == "Spencer, Amy")
in r the first line had this redbox with white dot in between the comma and the first name. I got this red box with white dot by copy the name from the data frame and copying it into notepad and then pasting it in r. This actually works and returns what I want. Now the second case is a standard space which doesn't return what I want. So how can I fix this issue by not having to copy a name from the data frame and copy to notepad then copying the results from notepad to r, which has the redbox with a white dot in between the comma(,) and first name.
Expected results is that I get the rows that are attached to what ever name I filter by.
I was able to find the answer, it turns out the space is actually a break space with unicode of (U+00A0) compared to the normal space unicode (U+0020). The break space is not apart of the American Standard Code for Information Interchange(ACSII). Thus r filter() couldn't grab some names because they had break spaces. I fixed this by subbing the Unicode of the break space with the Unicode for a normal space and applying that to my given column. Example below:
space_fix = gsub("\u00A0", " ", surveyData$`Completed By`, fixed = TRUE) #subbing break space unicode with space unicode for the given column I am interested in
surveyData$`Completed By Clean` = space_fix
Once, I applied this I could easily filter any name!
Thanks everyone!
I have a 2.8gb text file that I'm trying to import into R.
1) I used fread(file='file.txt',sep = ';',header = T,nrows = 1000,stringsAsFactors = F,fill=T) to take a quick look, and I saw that some rows happen to show some columns with NA's and in the row below are the values that should be in the NA's place.
2) Next, I used HJSplit to see a part of the file in a notepad and noticed that there are linebreaks in the middle of some rows, making these rows occupy two rows. Here's an ilustration of what's happening (example of ';' separated file with 4 columns):
id;name;age;sex
150;bob;40;F
151;luke;20;M
152;mary
20;F
153;larry;30;M
Question: Is there a way that I can solve this problem?
One thing that came to my mind was to use the fact that the number of columns are defined, but I don't know how.
I have a large CSV file (170k rows), which I'm importing into R. Each entry in the file is comma-delimited - however, in some of the columns (particularly those with a collection of URLs stuck together), there are commas in the strings. An example below:
Will Smith,25/09/68,null,male,08/10/14,450109,TRUE,http://commons.wikimedia.org/wiki/Special:FilePath/Will_Smith_2011,_2.jpg?width=300http://upload.wikimedia.org/wikipedia/commons/thumb/5/51/Will_Smith_2011,_2.jpg/200px-Will_Smith_2011,_2.jpghttp:.....
The added comma has a knock-on effect - it makes R (and Excel) think that it is a separate column, which then extends out over other columns and destroying the formatting. Given that there are roughly ~10% of the data affected, is there a quick way to get around this?
If the rule suggested by this limited example is to remove the commas that appear before underscores, then this succeeds:
gsub("[,][_]", "_", s)
Without some rule for when commas should be ignored, no.
If you have some consistant rule then use str_replace_all with regex to find the exceptions.
If you're the one making the csv I'd suggest you delimit with a different character.