Python中的数据预处理

Question

Heyy, I am new to data science and here I am trying to find missing data in one of the columns.But, I am encountering an error which states that "X is not defined". Can someone help me?

#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])

Answer 1

The "X" denotes an numpy.ndarray of your primary DataFrame, minus the target variable.

X = df.iloc[:, :-1].values

Try this. Should be working.

Answer 2

To find the missing data for a single column, the below code is must worked.

dataset_name['column_name'].isnull().sum()

Note: if we need to find the missing data then not bother about X variable. X and y variables are needed when you try to fill the missing data with some mean/median/mode values.