Read worksheet with only one row

[tidyverse]

Read worksheet with only one row

[wdkrnls]

Could it give a warning instead of an error?

[byzheng]

Warning could be a better idea.

[hadley]

I think the correct behaviour would be a zero row output

[TAwosanya]

Dear Hadley,
Please what do you suggest one can do to solve this problem? My own case is that I have several excel files with several worksheets in each one. I set up the data loading parameters and I use lapply() to read all worksheets across all files so it might be a little difficult to know which worksheet or files that brings the error. Thanks in advance for your VERY QUICK reply

[hadley]

I will resolve this when I'm next working on readxl, which is unlikely to be in the next six weeks.

[soodoku]

Dear Hadley,

One more thing, which appears not to have been covered in the comments above: It appears that after the "Error: Skipped over all data", data from subsequent sheets in the file (which have more data) --- is not read in. I suppose it is kind of obvious behavior after the error. But I wanted to make a note of it in the off chance it had escaped your notice.

[mehmetaergun]

I got hit by this one too, while trying to import a workbook with 30+ sheets. Happens at
bd63ea5#commitcomment-19697741

I'm not fluent in Rcpp nor C++ otherwise I'd gladly provide a pull request.

When/if you get a chance, would it be possible to turn the stop to warning and also output the name or the index number of the sheet, so this

this.sheet <- "my sheet" # second sheet

read_excel(load.file, sheet = this.sheet)

would output something like

Rcpp::warning("No data found in sheet: ", sheet_)

No data found in sheet 'my sheet'
or
No data found in sheet 2

My workaround for now was to insert a row with all NAs to the single-row sheet but that of course is bad in terms of data integrity and workflow/automation.

Also, thank you so much for writing this! So happy not to have to depend on java!

[jennybc]

This is slight variation of #222, where there's a header row but no data rows.
Duplicate of #144