Hi, I have a really strange error and I was not able to fix it till now. A have a python script, which takes a dataframe and returns a pandas dataframe with 3 columns. Each element in every column is a list itself. The script worked totally fine, but know I’m getting a completely random error: [image] I know this kind of error and know what it means, but it makes no sense, because the script is running completely fine when I click on execute in the node. [image] Furthermore if I just swap my return df final_df with the input_table df_invoices there is no error anymore. Which makes no sense, because the script is doing essentially the same but is just returning the old not altered dataframe. And what does this have to do with the error above? Why is there even an error outside of the node but not inside? Can someone please help me. EDIT: If I comment everything out and just return a pandas DF with numbers I get the following error: [image] It is so weird because it worked fine before. Best regards Armin

Hi @ArminFan , Do the individual elements (numbers) of the data frame happen to be wrapped in numpy arrays? I can reproduce the “non-byte type passed to CreateByteArray” error like this: import pandas as pd import numpy as np output_table = pd.DataFrame({"my_test_column": [ np.array([1]) ]}) whereas this version works: import pandas as pd output_table = pd.DataFrame({"my_test_column": [ 1 ]}) Similarly, I can reproduce the “The truth value…” error like this: import pandas as pd import numpy as np output_table = pd.DataFrame({"my_test_column": [ np.array([1, 2, 3]) ]}) whereas this works: import pandas as pd output_table = pd.DataFrame({"my_test_column": [ [1, 2, 3] ]}) numpy arrays as data frame elements are (currently) not supported by KNIME because KNIME does not have any builtin n-dimensional array types. Still, we should definitely produce more helpful error messages in such cases + potentially treat numpy arrays that contain only a single element or are 1-dimensional separately (the latter should be representable in KNIME in the form of collection cells). Marcel

Strange behaviour of Knime Python (1=>1) Node

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mlauber71 May 28, 2021, 6:43pm 7

@ArminFan for what it is worth: you could still combine KNIME and Python and numpy arrays, just not use them inside KNIME but save them separately and re-use them whenever needed:

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