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relevant calculated fields are returning 0.00 when there is nothing to calculate and should be NULL

LynnBerni

In the following screenshot, the fields 5 & 6 are calculated based on data in fields 1-4. The whole group (fields1-6) is relevant as to whether or not a sample is collected. But, when no sample is collected, the calculated fields are returning 0.00. I would like them to be blank. Is there a way to control (cancel) the calculation when the relevant expression is not met?

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JamesTedrick

Hi Lynn,

I am seeing that calculate questions are submitting their calculations when not relevant. However, it I'm not seeing the effect when the items are in a group. Can you share the survey or the part of the survey experiencing the issue?

LynnBerni

Hi James,

Here's a link to the xls form. It's the "Sample Analysis" group.

Thanks!

JamesTedrick

Hi Lynn,

This doesn't appear to be the right survey- I'm not seeing the group you refer to.

markcain

You should be able to wrap the calculation in an if statement.

if(${no_sample}!='',calculation,'')

This basically means that if the field ${no_sample} is not empty, then the calculation is performed, otherwise the field is blank.

or if you want it to only calculate when a certain option is chosen

if(${no_sample}='option1',calculation,'')

LynnBerni

thanks Mark, tried the if statement and the field is still being populated with 0. This field just doesn't want to be NULL!

LynnBerni

Hi James,

That's the one, the group starts on line 19 of the sheet.

LynnBerni

Hello James Tedrick,

Have there been any updates on this issue? Or maybe other suggestions I could try? It continues to plague us.

Thanks!
Lynn

SteveLynch

is the table a .dbf or in a file geodatabase?

LynnBerni

dfb in egdb

SteveLynch

shapefile, which uses .dbf, converts null to zero.

To test, create a field in a fgdb that has nulls. Use CopyFeatures and save it to shapefile and you'll notice the zeros.

DanPatterson_Retired

Lynn, it sounds like relying on null values should be avoid in that case. If the data you are using are counts, put in a count value that isn't possible... you could go 'old school' and use -999 or some equivalent scaled variant. Any

observation which is a count cannot possibly have a negative number

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