Quote:
Originally Posted by capink
The author field is not mandatory. While you cannot get rid of the author control when mapping columns, you can simply set the column value to zero.
The title field is mandatory and I have no intention of changing that. If you must import lists without titles, you can simply map the title column to an arbitrary column (you can map a single csv to more than one field), and clean it after importing using the bulk metadata edit tool.
But note that whatever column you map to the title, it must contain value for each row for it to succeed. So you can map the identifier to the title field. If your csv don't have a column with values for each row, you can simply insert the same value for your title column in your spreadsheet editor.
I don't understand this, if they have different title/author and have no identifiers, they are not going to match anyway.
Edit: does you mean matching books using columns other than title/author/identifiers? If so, this is a lot of work and and will end up being far from perfect for variety of reasons. Beside the work it would take, one of the main worries here is false matches ruining users metadata. I am not ruling this out altogether, but not right now.
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I have titles that are for the books I sent to my Kindle. These titles are formatted series first. When Amazon or I download the list of books, their titles show up in my 'send to Kindle" format. I have a column with this title.
Regarding the authors, it's not a big deal but the Goodreads library export .csv separates multiple authors. So if a book is by K Webster, and Ker Dukey
Calibre might have them both as the author, but the Goodreads is only going to have one of those authors. The same with anthologies. Goodreads has just the first author and then another column with every other author.
I have a column with just the Goodreads authors.
So that is a possible reason.