import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
#Import Data set
dataset= pd.read_csv('Data.csv')
X = dataset.iloc[:,:-1].values
Y = dataset.iloc[:,3].values
#Taking Care of The Missing Data
from sklearn.preprocessing import Imputer
imputer = Imputer(missing_values='nan',strategy='mean',axis=0)
imputer = imputer.fit(X[:,1:3])
X[:,1:3] = imputer.transform(X[:,1:3])
我正在遵循本教程系列,并且完全按照他的导师对我所做的那样做,当然有代码中提到的此错误。一个潜在的解决方案当然会非常有帮助。提前谢谢。
Error : if value_to_mask == "NaN" or np.isnan(value_to_mask): 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''
试试:
imputer = Imputer(missing_values=np.nan,strategy='mean',axis=0)
或
imputer = Imputer(missing_values='NaN',strategy="mean",axis=0)
如文档中所述