RaySteam

你可以用 np.isnan 创建遮罩并过滤掉 NaN 价值观 outlier :

result = df[~np.isnan(df.outlier)].values.tolist()
print(result)

输出

[['12:28:31', 3, 3, 3.0], ['14:28:31', 6, 7, 7.0], ['14:28:31', 4, 9, 9.0]]

您需要删除逗号,例如:

lists=['111,222','121,121']
result = [int(s.replace(',', '')) for s in lists]
print(result)

输出

[111222, 121121]