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I am trying to use pandas DataFrame.to_sql to insert values in a table of my Postgres database. I have some nan values in a column of integers that does not belong to any constraint.

I get the following error : 

sqlalchemy.exc.DataError: (DataError) integer out of range

When I substitute nan values with zéros, insertion happens as wanted, so it is really nan values that are to blame for my error.

I have tried converting nan values to None and to np.nan , but I get the same error. So the question is: what nan format do I need so that pd.to_sql handles it correctly?

My restrictions are : python 2.7 pandas 0.14.1 , sqlalchemy 0.9.8 , Postgres 9.2

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  • similar problem here: "Incorrect decimal value: 'NaN' for column XYZ". XYZ in my case is a DECIMAL column. Commented Jan 13, 2020 at 6:10

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The problem is with your pandas version: 0.14.1.

Starting with pandas 0.15, to_sql supports writing NaN values.

You can try upgrading your pandas.

Also, for now you can convert NAN to NONE like:

df = df.astype(object).where(pd.notnull(df), None)
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Thank you for your answer. I can unfortunately not upgrage pandas since it is on a server I use, and the administrator does not wish to proceed to an upgrade.. I have already tried replacing by None but it won't work, I get the same error..
Please refer to this.

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