ValueError: invalid literal for int() with base 10: '#SUP:'
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")
Regards.
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
Hi guys. I made some changes to resolve this issue. Can I post the code here?
@vanderson-rocha Cool, feel free to open a pull request with the changes!