The ValueError: cannot convert float NaN to integer raised because of Pandas doesn't have the ability to store NaN values for integers.
From Pandas v0.24, introduces Nullable Integer Data Types which allows integers to coexist with NaNs. This does allow integer NaNs . This is the pandas integer, instead of the numpy integer. So, use Nullable Integer Data Types (e.g. Int64).
df['x'].astype('Int64')
NB: You have to go through numpy float first and then to nullable Int32, for some reason.
Another solution is Using numpy.nan_to_num(). The numpy.nan_to_num() returns an array or scalar replacing Not a Number ( Not A Number ) with zero, positive_infinity with a very large number and negative_infinity with a very small (or negative) number.
If you are not satisfied with the above solutions, you need to say what you want to do with NANs . You can either drop those rows df.dropna() or replace nans with something else (0 for instance: df.fillna(0) )
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MariMakes 208
Hey @widdershins,
Welcome to the Ultimaker Community 🎉
We have a known issue with crashes that happen with some models that are perfectly in the middle of the buildplate. If you move the model away slightly from the center of the buildplate you should be able to slice. Could it be that you are experiencing the same?
We are collecting cases here so the developers can solve the issue better.
https://github.com/Ultimaker/Cura/issues/13643
Do you have a project file for us? It contains the printer and settings we need for troubleshooting.
To save a project file go to File -> Save project.
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