I'm trying to create a function that mines and exports association rules between item categories using the Apriori algorithm from mlxtend. While this works beautifully in jupyter notebooks. I get a type error when I copy the same function int my pycharm project.
In both cases I used mlxtend 0.15.0.0.
def apriori():
inputPath = inputPathField.get()
data = pd.read_csv(inputPath, usecols=['BillId', 'Level5'])
data['dummy'] = 1
matrix = data.pivot_table(values='dummy', index='BillId', columns='Level5').fillna(0)
frequent_itemsets = apriori(matrix, min_support=0.0005, use_colnames=True)
rules = association_rules(frequent_itemsets, metric="lift", min_threshold=1)
export = rules[(rules.antecedents.str.len() <= 3)]
export = export[(export.consequents.str.len() == 1)]
export = export[(export.confidence >= 0.15)]
outputPath = outputPathField.get()
export.to_csv(outputPath)
File "/home/scrybe/PycharmProjects/tkinter/Apriori.py", line 37, in apriori
frequent_itemsets = apriori(matrix, min_support=0.0005, use_colnames=True)
TypeError: apriori() got an unexpected keyword argument 'min_support'