Join Predicted values with test dataset

[bhuwan]

Thank you for the reply.
This is how I get the y_pred.

# split data 
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.25, random_state=0, shuffle=True)

# Feature Scaling
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)	

# Fitting SVM
from sklearn.svm import SVC
classifier = SVC(kernel = 'linear', random_state = 0)
classifier.fit(X_train, y_train)

# Predicting the Test
y_pred = classifier.predict(X_test)

This is my desired result dataset.

df1 = pd.concat([X_test.reset_index(drop='Tru‌​e'),y_pred.reset_index(drop='Tru‌​e')],axis=1)

I want to join the x_test+y_pred so that i can compare the predicted result one by one. By doing above concat, does each row of y_test and y_pred align in the same order as in x_test?
I am developing a model to classify the behavior of people so that necessary actions can be taken for each individual.