Can I make another suggestion?
Do you often have multiple missing audits?
If not, then you can very easily create a column that replaces zero values by the average of the value before and after (and retains the correct value if it is not zero)
Then create a third column that contains zero except when the original value is zero. If the original value is zero, it should contain some conveniently large value such as 10.
Now plot your graph using the interpolated data, and add error-bars using the zero-or-ten column.
This gives you a plot without misleading spikes, but marks each missing audit with a short vertical bar.
It is harder to adapt to multiple interpolations where several audits were missed in a row.
Incidentally, I'd recommend using a score such as -1 as a marker of a missing audit, rather than zero, just on the off-chance that one day someone is so awful that they really deserve zero. Markers should be values that cannot arise in any other way.