ValueError: invalid literal for int() with base 10: '#SUP:'

[nhamzehn]

Thank you for writing this wrapper.
I have an issue when using to_pandas_dataframe() method with 'Apriori_with_hash_tree'.
The following error is appear: ValueError: invalid literal for int() with base 10: '#SUP:'

from spmf import Spmf
spmf = Spmf("Apriori_with_hash_tree",
            input_filename="contextPasquier99_name.txt",
            output_filename="output.txt",
            arguments=[0.40, 30, 2])

spmf.run()
print(spmf.to_pandas_dataframe())
spmf.to_csv("output.csv")

contextPasquier99_name.txt

Regards.

[LoLei]

Could you please post the entire stacktrace? The to_pandas_dataframe method may assume that a different algorithm was used, which may interfere with some others. https://github.com/LoLei/spmf-py/blob/master/spmf/__init__.py#L142

[vanderson-rocha]

Hi guys. I made some changes to resolve this issue. Can I post the code here?

[LoLei]

@vanderson-rocha Cool, feel free to open a pull request with the changes!