小编Mar*_*cel的帖子

我有一个数据框，其中包含一个名为 ProjectSubject 的列。数据框大约有 1,000,000 行长。

在 ProjectSubject 列中，我有很多不同的字符串。下面是一个例子：

>unique(unlist(projectdf$ProjectSubject))

[1] "Applied Learning"                           "Applied Learning, Literacy 
& Language"     
[3] "Literacy & Language"                        "Special Needs"                             
[5] "Literacy & Language, History & Civics"      "Math & Science"                            
[7] "History & Civics, Math & Science"           "Literacy & Language, 
Special Needs"        
[9] "Applied Learning, Special Needs"            "Health & Sports, Special 
Needs"            
[11] "Math & Science, Literacy & Language"        "Literacy & Language, Math 
& Science"       
[13] "Literacy & Language, Music & The Arts"      "Math & Science, Special …

我有一个 Pandas 数据框，它在特定列中有一些 NaN 值：

1291   NaN
1841   NaN
2049   NaN
Name: some column, dtype: float64

我已经制作了以下管道来处理它：

from sklearn.preprocessing import StandardScaler
from sklearn.impute import SimpleImputer
from sklearn.pipeline import Pipeline

scaler = StandardScaler(with_mean = True)
imputer = SimpleImputer(strategy = 'median')
logistic = LogisticRegression()

pipe = Pipeline([('imputer', imputer),
                 ('scaler', scaler), 
                 ('logistic', logistic)])

现在，当我将此管道传递给 a 时RandomizedSearchCV，出现以下错误：

ValueError: Input contains NaN, infinity or a value too large for dtype('float64').

它实际上比那要长得多 - 如果需要，我可以在编辑中发布整个错误。无论如何，我很确定此列是唯一包含 NaN 的列。此外，如果我从管道中切换SimpleImputer到（现已弃用）Imputer，管道在我的RandomizedSearchCV. 我检查了文档，但似乎它的SimpleImputer …