I am reading file in R:
data <- read.delim ("file.fas", header=TRUE, sep="\t" )
However, after I have done some manipulations to the data, the output format is not same. It now contains commas "," like this all over.
write.table(x= data, file = "file_1.fas")
How can I avoid this? Maybe I should use some different function to write a file?
Hi I'm trying to import data from the URL:https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data but it always imports it as single line. I split the data by "\t" but it still not working. My R code;
bostonHousing <- read.table("https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data",
col.names= c("CRIM","ZN","INDUS","CHAS","NOX","RM","AGE","DIS","RAD","TAX","PTRATIO","B","LSTAT","MEDV"),
dec=",",sep = "\t")
The file isn't tab-separated, it's whitespace-separated. By default, read.table assumes columns are separated by one or more whitespace characters (tab or space). Specifying tab-delimiters (or using read.delim()) is only really necessary when columns are tab-delimited and the data columns may contain embedded spaces ...
url <- "https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data"
bostonHousing <- read.table(url)
seems to work fine (dec="," is also a bad idea)
I extracted data in R using the twitteR package and searchtwitter. I am then converting to a JSON file. It works, but when I view the JSON in notepad++ it is one long string. Is there a way to get it to separate so that each tweet with its specific information is separate.
testreal <- searchTwitteR('startup', n = 100, lang = 'en')
testrealdf <- do.call("rbind", lapply(testreal, as.data.frame))
write(exportJson, file = "testrealdf.json")
json_realdf <- fromJSON(file="testrealdf.json")
My file in notepad looks like.....
Use jsonlite::toJSON(x=yourDataFrame, pretty=TRUE). From ?toJSON:
pretty adds indentation whitespace to JSON output. Can be TRUE/FALSE
or a number specifying the number of spaces to indent. See prettify
This is just for cosmetics. The whitespace in JSON is not syntactically meaningful. For a serialization format with syntactically meaningful whitespace, check out R's yaml package, which can also read JSON.
I'm new, and I have a problem:
I got a dataset (csv file) with the 15 columns and 33,000 rows.
When I view the data in Excel it looks good, but when I try to load the data
into R- studio I have a problem:
I used the code:
x <- read.csv(file = "1energy.csv", head = TRUE, sep="")
View(x)
The result is that the columnnames are good, but the data (row 2 and further) are
all in my first column.
In the first column the data is separated with ; . But when i try the code:
x1 <- read.csv(file = "1energy.csv", head = TRUE, sep=";")
The next problem is: Error in read.table(file = file, header = header, sep = sep, quote = quote, :
duplicate 'row.names' are not allowed
So i made the code:
x1 <- read.csv(file = "1energy.csv", head = TRUE, sep=";", row.names = NULL)
And it looks liked it worked.... But now the data is in the wrong columns (for example, the "name" column contains now the "time" value, and the "time" column contains the "costs" value.
Does anybody know how to fix this? I can rename columns but i think that is not the best way.
Excel, in its English version at least, may use a comma as separator, so you may want to try
x1 <- read.csv(file = "1energy.csv", head = TRUE, sep=",")
I once had a similar problem where header had a long entry that contained a character that read.csv mistook for column separator. In reality, it was a part of a long name that wasn’t quoted properly.
Try skipping header and see if the problem persists
x1 <- read.csv(file = "1energy.csv", skip = 1, head = FALSE, sep=";")
In reply to your comment:
Two things you can do. Simplest one is to assign names manually:
myColNames <- c(“col1.name”,”col2.name”)
names(x1) <- myColNames
The other way is to read just the name row (the first line in your file)
read only the first line, split it into a character vector
nameLine <- readLines(con="1energy.csv", n=1)
fileColNames <- unlist(strsplit(nameLine,”;”))
then see how you can fix the problem, then assign names to your x1 data frame. I don’t know what exactly is wrong with your first line, so I can’t tell you how to fix it.
Yet another cruder option is to open your csv file using a text editor and edit column names.
It happens because of Exel's specifics. The easy solution is just to copy all your data Ctrl+C to Notepad and Save it again from Notepad as filename.csv (don't forget to remove .txt if necessary). It worked well for me. R opened this newly created csv file correctly, all data was separated at columns right.
Open your file in text edit and see if it really is separated with commas...
Sometimes .csv files are separated with tabs instead of commas or semicolon and when opening in excel it has no problem but in R you have to specify the separator like this:
x <- read.csv(file = "1energy.csv", head = TRUE, sep="\t")
I once had the same problem, this was my solution. Hope it works for you.
This problem can arise due to regional settings on the excel application where the .csv file was created.
While in most places a "," separates the columns in a COMMA separated file (which makes sense), in other places it is a ";"
Depending on your regional settings, you can experiment with:
x1 <- read.csv(file = "1energy.csv", head = TRUE, sep=",") #used in North America
or,
x1 <- read.csv(file = "1energy.csv", head = TRUE, sep=";") #used in some parts of Asia and Europe
You could use -
df <- read.csv("filename.csv", sep = ";", quote = "")
It solved one my problems similar to yours.
So i made the code:
x1 <- read.csv(file = "1energy.csv", head = TRUE, sep=";", row.names =
NULL) And it looks liked it worked.... But now the data is in the
wrong columns (for example, the "name" column contains now the "time"
value, and the "time" column contains the "costs" value.
Does anybody know how to fix this? I can rename columns but i think
that is not the best way.
I had the exact same issue. Did quite some research and found out, that the CSV was ill-formed.
In the header line of the CSV there were all the labels (separated by the separator) and then a line break.
Starting with line 2, there was an additional separator at the end of each line. So an example of such an ill-formed CSV file looks like this:
Field1;Field2 <-- see the *missing* semicolon at the end
12;23; <-- see the *trailing* semicolon in each of the data lines
34;67;
45;56;
Such ill-formatted files are even harder to spot for TAB-separated files.
Excel does not care about that, when importing CSV files.
But R does care.
When you use skip=1 you skip the header line that contains part of the mismatch. The data frame will be imported well, but there will be a column of "NA" at the end of each row. And obviously you will not have column names, as these were skipped.
Easiest solution: edit the CSV file and either add an additional separator at the end of the header line as well, or remove the trailing delimiters in the data lines. You can also use generic read and write functions in R for text files to automate that editing.
You can transform the data by arranging the data into many cells corresponding to columns.
1.Open your csv file
2.copy the content and paste it into txt file save and copy its content
3.open new excell file
4.in excell go to the section responsible for data . it is acually called "Data"
5.then on the left side go to external data query , in german "externe Daten abfragen"
6.go ahead step by step and seperate by commas
7. save your file as csv
I had the same problem and it was frustrating...
However, I found the ultimate solution
First take this (csv file) and then convert it online to Json file and download it ... then redo the whole thing backwards (re-convert Jason to csv) online... download the converted file... give it a name...
then put it on your Rstudio
file name <- read.csv(file='name your file.csv')
... took me 4 days to think out of the box... 🙂🙂🙂
I have a "csv" text file where each field is separated by \t&%$# which I'm now trying to import into R.
The sep= argument of read.table()instists on a single character. Is there a quick way to directly import this file?
Some of the data fields are user-submitted text which contain tabs, quotes, and other messy stuff, so changing the delimiter to something simpler seems like it could create other problems.
The following code will be able to handle multiple separator chars:
#fileName <- file name with fully qualified path
#separators <- each of them separated by '|'
read <- function(fileName, separators) {
data <- readLines(con <- file(fileName))
close(con)
records <- sapply(data, strsplit, split=separators)
dataFrame <- data.frame(t(sapply(records,c)))
rownames(dataFrame) <- 1: nrow(dataFrame)
return(as.data.frame(dataFrame,stringsAsFactors = FALSE))
}
As explained in this post, it is not possible in R without resorting to string parsing. You can pre-parse your file in another language (Awk, Perl, Python etc.) or read it line-by-line and parse the resulting strings in R.