This is my code:
import numpy as np
import pandas as pd
from sklearn.preprocessing import LabelEncoder
from sklearn.pipeline import Pipeline
le = LabelEncoder()
df = pd.read_csv(‘Train_Data.csv’)
#df = pd.get_dummies(x_tran, drop_first=True)
df3 = pd.read_csv(‘Test_Data.csv’)
df1 = df.iloc[:,1:80]
df2 = df.iloc[:,-1:]
print(df1.shape)
df1.iloc[:,1:80] = df1.iloc[:,1:80].fillna(0)
df3.iloc[:,:80] = df3.iloc[:,:80].fillna(0)
#df1.info()
dfx = pd.get_dummies(df1, drop_first=True)
dfy = pd.get_dummies(df2, drop_first=True)
dfz = pd.get_dummies(df3, drop_first=True)
#print(dfx)
#dfx.info()
df1.apply(le.fit_transform)