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.
Related
I am working an uploaded document originally from google docs downloaded to an xlsx file. This data has been hand entered & formatted to be DD-MM-YY, however this data has uploaded inconsistently (see example below). I've tried a few different things (kicking myself for not saving the code) and it left me with just removing the incorrectly formatted dates.
Any suggestions for fixing this in excel or (preferably) in R? This is longitudinal data so it would be frustrating to have to go back into every excel sheet to update. Thanks!
data <- read_excel("DescriptiveStats.xlsx")
ex:
22/04/13
43168.0
43168.0
is a correct date value
22/04/13
is not a valid date. it is a text string. to convert it into date you will need to change it into 04/13/2022
there are a few options. one is to change the locale so the 22/04/13 would be valid. see more over here: locale differences in google sheets (documentation missing pages)
2nd option is to use regex to convert it. see examples:
https://stackoverflow.com/a/72410817/5632629
https://stackoverflow.com/a/73722854/5632629
however, it is very likely that 43168 is also not the correct date. if your date before import was 01/02/2022 then after import it could be: 44563 which is actually 02/01/2022 so be careful. you can check it with:
=TO_DATE(43168)
and date can be checked with:
=ISDATE("22/04/13")
I have some data points (gene id) that are like "dates" for example MAR1 but when i export it to csv it keeps changing it to 1.Mar as if it's an actual date.
How can I keep it as MAR1 not keep changing it as date format?
When i try to fix this on excel it trying to change it into txt format it changes into cell number.
You should look into PowerQuery if you are working with CSV format.
Open a blank workbook, instead of opening the file go to the Data Tab -> Get Data -> From Text/CSV and locate the file.
(You can also pick Excel file if you plan to use writexl)
Click "Transform Data" and from there you can pick which formats you want by clicking on the small icons in the columns (in your case set the column to text). You can also do many other things such as sort or convert a data to a week number.
Click "Close & Load" and it will appear in a new tab as a table.
What's nice about PowerQuery if you are doing any post analysis in Excel is that next time you export in R, you only have to hit "Refresh All" in the data tab and it will pull your new data in and apply transformations provided you haven't changed any of the column/names.
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.
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)
How do i extract a number formatted column when i spool to a csv file from unix when the column is varchar in database?
Number format in CSV is 5.05291E+12
should actually be 5052909272618
This problem is not a Unix or ksh problem, but an Excel problem. Assuming Excel is the default application for a .csv file, When you double-click to open in Excel, it makes the column type "General" by default and you get the scientific notation instead of the text value as expected. If your numeric data has leading zeroes they will be removed also.
One way to fix is to start Excel (this example in the 2010 version), the go to Data/get external data/from text, follow the wizard making sure to set the "column data format" to "text" for the column that contains your large number (click on the column in the "data preview" section first). Leading zeroes will be preserved also.
You could code a vba macro that would open with all columns as text (a little searching will show you some examples) but there seems to be no place to tell Excel to treat columns as "text" by default.
There was need to develop report and I was also facing the same issue.i found that there is one workaround/solution. e.g.
your table name --> EMPLOYEE
contains 3 columns colA,colB,colC. the problem is with colB. after connecting to sqlplus you can save the the data in spool file as :
select colA|| ','''||colB||''',' ||colC from employee
sample result:
3603342979,'8938190128981938262',142796283 .
when excel opens the file it displays the result "as-it-is"