Python:数据参数不能是迭代器

Question

我正在尝试复制此处提供的代码: https://github.com/IdoZehori/Credit-Score/blob/master/Credit%20score.ipynb

下面给出的函数无法运行并报错。谁能帮我解决一下

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

函数调用:

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:我知道之前有人问过这个问题，但我尝试使用这些技术，但错误仍然存​​在

Answer 1

zip 不能直接使用，你应该以列表的形式给出结果即:

x = pd.DataFrame(list(zip(data, vote)), columns=['annual_income', 'outlier'])

编辑(来自 bayethierno 答案):
从 0.24.0 版本开始，我们不再需要从 zip 生成列表，下面的语句是有效的:

x = pd.DataFrame(zip(data, vote), columns=['annual_income', 'outlier'])