my data frame has a column A with strings in character form
> df$A
[1] "2-60", "2-61", "2-62", "2-63" etc
I saved the table using write.csv, but when I open it with Excel column A appears formatted as date:
Feb-60
Feb-61
Feb-62
Feb-63
etc
Anyone knows what can I do to avoid this?
I tweaked the arguments of write.csv but nothing worked, and I can't seem to find an example in Stack Overflow that helps solve this problem.
As said in the comments, this is an excel behaviour, not R's. And that can't be deactivated:
Microsoft Excel is preprogrammed to make it easier to enter dates. For
example, 12/2 changes to 2-Dec. This is very frustrating when you
enter something that you don't want changed to a date. Unfortunately
there is no way to turn this off. But there are ways to get around it.
Microsoft Office Article
The first suggested way around it according to the article is not helpful, because it relies on changing the cell formatting, but that's too late when you open the .csv file in excel (it's already converted to an integer representing the date).
There is, however, a useful tip:
If you only have a few numbers to enter, you can stop Excel from
changing them into dates by entering:
An apostrophe (‘) before you enter a number, such as ’11-53 or ‘1/47. The apostrophe isn’t displayed in the cell after you press
Enter.
So you can make the data display as original by using
vec <- c("2-60", "2-61", "2-62", "2-63")
vec <- paste0("'", vec)
Just remember the values will still have the apostrophe if you read them again in R, so you might have to use
vec <- sub("'", "", vec)
This might not be ideal but at least it works.
One alternative is enclosing the text in =" ", as an excel formula, but that has the same end result and uses more characters.
Another solution - a bit tedious, Use Import Text File in Excel, click thru the dialog boxes and in Step 3 of 3 of the Text Import Wizard, you will have an option of setting the column data format, use "Text" for the column that has "2-60", "2-61", "2-62", "2-63". If you use General (the default), Excel tries to be smart and converts the answer for you.
I solved the problem by saving the file using the .xlsx format by using the function
write.xlsx()
from the package xlsx (https://www.rdocumentation.org/packages/xlsx/versions/0.6.5)
Related
I came across a strange problem when trying to export an R dataframe to a csv file.
The dataframe contains some big numbers, but when they are written to the csv file, they "lose" the decimal part and are instead written without it.
But not like one would expect, but like this:
Say 3224571816.5649 is the correct value in R. When written to csv, it becomes 32245718165649.
I am using the write.csv2 function to write the csv. The separators are correct, as it works normally for smaller values. Is the problem occurring because the number (with decimals) is bigger than 32bit?
And more importantly, how can I solve this, as I have a whole dataframe with values as big (or bigger) than this? Also, it has to be written in to a csv.
write.csv2 is intended for a different standard of csv (Western European styling, which based on your use of a "." as a decimal indicator, I am guessing you are not looking for). write.csv2 uses a comma as a decimal indicator and a semicolon as the field delimiter, so if you are trying to read the result in as a comma separated file, it will look strange indeed.
I suggest you use write.csv (or even better, write.table) to output your file. write.csv assumes a comma separator and period for decimal marker.
both write.csv and write.csv2 are just wrappers for write.table, which is the underlying method. In general, I recommend use of write.table because it does not assume your region and you can explicitly pass it sep = ",", dec = ".", etc. This not only lets you know what you are using for sure, but it also makes your code a lot more readable.
for more, check the rdocumentation.org site for write.table: https://www.rdocumentation.org/packages/utils/versions/3.5.3/topics/write.table
I have a relatively simple issue when writing out in R with fwrite from the data.table package I am getting a character vector interpreted as scientific notation by Excel. You can run the following code to create the data issue:
#create example
samp = data.table(id = c("7E39", "7G32","5D99999"))
fwrite(samp,"test.csv",row.names = F)
When you read this back into R you get values back no problem if you have scinote disable. My less code capable colleagues work with the csv directly in excel and they see this:
They can attempt to change the variable to text but excel then interprets all the zeros. I want them to see the original "7E39" from the data table created. Any ideas how to avoid this issue?
PS: I'm working with millions of rows so write.csv is not really an option
EDIT:
One workaround I've found is to just create a mock variable with quotes:
samp = data.table(id = c("7E39", "7G32","5D99999"))[,id2:=shQuote(id)]
I prefer a tidyr solution (pun intended), as I hate unnecessary columns
EDIT2:
Following R2Evan's solution I adapted it to data table with the following (factoring another numerical column, to see if any changes occured):
#create example
samp = data.table(id = c("7E39", "7G32","5D99999"))[,second_var:=c(1,2,3)]
fwrite(samp[,id:=sprintf("=%s", shQuote(id))],
"foo.csv", row.names=FALSE)
It's a kludge, and dang-it for Excel to force this (I've dealt with it before).
write.csv(data.frame(id=sprintf("=%s", shQuote(c("7E39", "7G32","5D99999")))),
"foo.csv", row.names=FALSE)
This is forcing Excel to consider that column a formula, and interpret it as such. You'll see that in Excel, it is a literal formula that assigns a static string.
This is obviously not portable and prone to all sorts of problems, but that is Excel's way in this regard.
(BTW: I used write.csv here, but frankly it doesn't matter which function you use, as long as it passes the string through.)
Another option, but one that your consumers will need to do, not you.
If you export the file "as is", meaning the cell content is just "7E39", then an auto-import within Excel will always try to be smart about that cell's content. However, you can manually import the data.
Using Excel 2016 (32bit, on win10_64bit, if it matters):
Open Excel (first), have an (optionally empty) worksheet already open
On the ribbon: Data > Get External Data > From Text
Navigate to the appropriate file (CSV)
Select "Delimited" (file type), click Next, select "Comma" (and optionally deselect any others that may default to selected), Next
Click on the specific column(s) and set the "Default data format" to "Text" (this will need to be done for any/all columns where this is a problem). Multiple columns can be Shift-selected (for a range of columns), but not Ctrl-selected. Finish.
Choose the top-left cell to import/paste the data (or a new worksheet)
Select Properties..., and deselect "Save query definition". Without this step, the data is considered a query into an external data source, which may not be a problem but makes some things a little annoying. (For example, try to highlight all data and delete it ... Excel really wants to make sure you know what you're doing there.)
This method provides a portable solution. It "punishes" the Excel users, but anybody/anything else will still be able to consume the files directly without change. The biggest disadvantage with this method is that you won't know if somebody loads it incorrectly unless/until they get odd results when the try to use the data and some fields are silently converted.
I am using a shiney interface under R to read in a CSV file and load it into one sheet of an excel xlsm file. The file then allows user input and preforms calculations based on VBA macros.
The R xlsx package is working well for preserving the VBA and formatting in the original excel sheet. However some of the data is being converted to a different data type than intended. For example a cell containing the string "F" is causing the column containing it to be converted to type boolean, or a miss-entered number in one cell is causing the entire column to be converted to string.
Can this behavior be controlled so that, for example, cells with valid numbers are not converted to string type? Is there a work-around? Or can someone just help me to understand what is happening in the guts of the package to cause this effect so I can try to find a way around it?
Here are the calls in question:
#excelType() points to an excel xlsm template
data = read.csv("results.csv")
excelForm = loadWorkbook(excelType())
sheets = getSheets(excelForm)
addDataFrame(data, sheets[[1]], col.names = FALSE, row.names = FALSE, startRow=2, colStyle = NULL)
saveWorkbook(excelForm, "results.xlsm")
Thanks!
I hope this is the correct protocol for explaining the outcome which worked for me. I hope it will be of help to others if they end up doing something similar, though the solution is not very elegant!
I tried r2evans's suggestion of forcing column types I could not get that to work in this case. Using readxls gave the same problem, and also broke my VBA. Given lebelionz's comment suggesting that this is an R thing and not a package thing I followed his advice to deal with it after the fact. (I do not see how to credit a comment rather than an answer, but for the record this was very helpful, as were the others).
I therefore altered the program producing the CSV that was being loaded through R. I appended "::" to each cell produced, so that R saw all cells as strings, regardless of the original content. Thus "F" was stored as "::F", and therefore was not altered by R.
I added an autorun macro to the excel sheet thus created, so that when opened it automatically performed a global search and replace to remove the prefix "::" from the whole of the data. This forces Excel to choose a data type for each cell after it was restored, resulting in the types being detected cell by cell and in the correct format for my purposes.
It feels kludgy, but it works and is relatively transparent to the user. One hazard is that if the user data intentionally contained the string "::" it would be lost (I am confident this cannot arise in my particular application, but if someone would like to suggest a better prefix I would be interested). I still hope for an eventual solution rather than a work-around.
And here I thought it was only the movie industry that had to "fix it in post"!
I have a dataframe in R which has one row of utf-8 encoded special characters and one integer row.
If I display both rows, or go into the view(), I do not see the characters displayed correctly.
However, if I only select the row with the special characters, it works. Any ideas?
This is the output (if I paste it, the encoding disappears):
This looks like a bug in R. I've worked around a number of these in the corpus package. Try the following
library(corpus)
print.corpus_frame(WW_mapping[1:3,])
Alternatively, do
library(corpus)
class(WW_mapping) <- c("corpus_frame", "data.frame")
WW_mapping[1:3,]
Adding the "corpus_frame" class to the data frame changes the print and format methods; otherwise, it does not change the behavior of the object.
If that doesn't work, please report your sessionInfo() along with dput(WW_mapping). (Actually, even if this fix does work, please report this information so that we can let the R core developers know about the problem.)
I have this sql server query that I am running in my .net app.
(CONVERT(VARCHAR(8), EventDate, 112)+ substring(RequestedBy,1,1)+right( '0000000' + convert( varchar( 7 ), ContactID ), 7 )) as Contacts
It produces the following results in the following format:
20120731e0000001
20120731f0000002
20120731p0000003
This is the result and format that we want.
Problem is when we click on export icon to export these results to excel, the first one changes to the scientific format like 2.01E+08.
Any date that has e in the middle such as 20120731*e*0000001 turns into scientific data.
The rest is just fine.
Any ideas how to fix this?
I want to apologize in advance if I stick the wrong tag in the Tags section since I am not sure where the fix could come from.
The formatting is happening when Excel opens your exported file. Simply change the column to have "formatted text" of string so that it displays as the original format.
When you open the exported data file directly with Excel, all formats are set as General. In General format, Excel applies formatting to what it recognizes as numbers and dates. So, to be clear, the issue is not with your export, but rather with how Excel is reading your data by default. Try the following to get around this issue.
Export to CSV. Then, rather than opening the CSV in Excel, use Excel's 'Get External Data From Text' tool to import the data into an empty workbook. Here you can specify to treat this field as TEXT rather than as GENERAL.
Note that once Excel applies number (or date) format to a cell, the data in the cell has been changed. No application of a new format will bring back your desired data. For this reason you must specify the format before Excel opens the file.