ValueError: invalid literal for int() with base 10: '#SUP:'
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- Dominant language
- Python
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Description
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.
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Research direction
Run the supplied Apriori_with_hash_tree example with contextPasquier99_name.txt and start at the to_pandas_dataframe() conversion path. Trace how the algorithm output containing '#SUP:' is parsed; done means the example converts to a pandas DataFrame without the reported ValueError.
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Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100