python - TypeError : ufunc 'isnan' not supported for the input types, 对 NaN 值使用 Imputer

Question

我是 python 和 pandas 的新手。我正在尝试预处理一个由数字和分类特征组成的大数据框，并且在某些列中存在 NaN 值。首先，我尝试获取特征矩阵，然后使用 Imputer 放置 Nan 值的平均值或中值。

这是数据框

    MSSubClass MSZoning  LotFrontage  LotArea Street LotShape LandContour  \
0             60       RL         65.0     8450   Pave      Reg         Lvl   
1             20       RL         80.0     9600   Pave      Reg         Lvl   
2             60       RL         68.0    11250   Pave      IR1         Lvl   
3             70       RL         60.0     9550   Pave      IR1         Lvl   
4             60       RL         84.0    14260   Pave      IR1         Lvl   
5             50       RL         85.0    14115   Pave      IR1         Lvl   
6             20       RL         75.0    10084   Pave      Reg         Lvl   
7             60       RL          NaN    10382   Pave      IR1         Lvl   
8             50       RM         51.0     6120   Pave      Reg         Lvl   
9            190       RL         50.0     7420   Pave      Reg         Lvl   
10            20       RL         70.0    11200   Pave      Reg         Lvl   
11            60       RL         85.0    11924   Pave      IR1         Lvl

代码:只是将LotFrontage(索引号= 2)中的Nan值更改为列的平均值

imputer = Imputer(missing_values='Nan',strategy="mean",axis=0)
features = reduced_data.iloc[:,:-1].values
imputer.fit(features[:,2])

当我运行这个时，出现错误:

TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''    

首先:我的方法正确吗？第二:出现错误如何处理？

谢谢

Answer 1

试试这个，这是工作代码的示例

from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values = np.nan, strategy = 'mean', axis =0)
imputer = imputer.fit(X[:,1:3])
X[:,1:3] = imputer.transform(X[:,1:3])