Python Learning Experience

# Data Preprocessing Template

# Importing the Libraries
Import NumPy as NP
Import Matplotlib.pyplot as Plt
Import Pandas as PD

#Importing the DataSet
Dataest = pd.read_csv (' data.csv ')
X = dataest.iloc[:,:-1].values #自变量 0 To-1 columns, so output to 2 columns
y = dataest.iloc[:,3].values # variable here 3 for fourth column
# Taking care of 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])

Achieve the filling of missing data in one data, and put an average value in the missing place.

Python Learning Experience