edit_features null values becoming 0s

Question

I am trying to use edit_features to update a hosted table with data from a pandas dataframe. The process runs without error, but the null values in the dataframe are automatically converted to 0s in the table as shown below. Is there a way to prevent this because 0s in these fields have an inherent meaning and they should be missing, not 0.

Thanks!

MackWood · Answer

Gotcha, I will try to figure out how to have the python script mask them as they are handled when manually updating then. Because the maps that are pointing to this data use the missing values as a specific symbology for census tracts with no data and I'm trying to not have to mess with the map too much.

danretired · Answer

they are handled internally ... masking if you will, just like they are in ArcGIS Pro. There are real NaNs for floats, just not integers.  Your first table has the columns as floats in the dataframe, hence NaNs, your second table is integers hence no NaNs (NaInt not an integer doesn't exist)

So either make sure that they are floats on transfer, deal with the zeros or exclude the records that are NaN is pretty well your options

NaN - Wikipedia

MackWood · Answer

How does the current hosted table have nulls as integers?