I'm trying to replicate the code that is provided here: https://github.com/IdoZehori/Credit-Score/blob/master/Credit%20score.ipynb
The function given below fails to run and give error. Can someone help me resolving it
def replaceOutlier(data, method = outlierVote, replace='median'):
'''replace: median (auto)
'minUpper' which is the upper bound of the outlier detection'''
vote = outlierVote(data)
x = pd.DataFrame(zip(data, vote), columns=['annual_income', 'outlier'])
if replace == 'median':
replace = x.debt.median()
elif replace == 'minUpper':
replace = min([val for (val, vote) in list(zip(data, vote)) if vote == True])
if replace < data.mean():
return 'There are outliers lower than the sample mean'
debtNew = []
for i in range(x.shape[0]):
if x.iloc[i][1] == True:
debtNew.append(replace)
else:
debtNew.append(x.iloc[i][0])
return debtNew
Function Call:
incomeNew = replaceOutlier(df.annual_income, replace='minUpper')
Error: x = pd.DataFrame(zip(data, vote), columns=['annual_income', 'outlier']) TypeError: data argument can't be an iterator
PS: I understand this has been asked before, but I tried using the techniques however the error still remains
zip cannot be used directly, you should give the result as a list i.e.:
x = pd.DataFrame(list(zip(data, vote)), columns=['annual_income', 'outlier'])
Edit (from bayethierno answer) :
Since the release 0.24.0, we don't need to generate the list from the zip
anymore, the following statement is valid :
x = pd.DataFrame(zip(data, vote), columns=['annual_income', 'outlier'])
This actually works in pandas version 0.24.2 without having to use list around zip
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