Participating in a Kaggle contest using Titanic dataset

import pandas as pd

df_train=pd.read_csv("train.csv")

df_train.drop(["Name","Cabin"],axis=1,inplace=True)
df_train.set_index("PassengerId",inplace=True)
df_train["Age"].fillna(df_train["Age"].mean(),inplace=True)

X_train=pd.get_dummies(df_train.loc[:,["Pclass", "Age", "SibSp", "Parch", "Fare"]])
y_train=df_train.loc[:,"Survived"]

from sklearn.preprocessing import StandardScaler
sc=StandardScaler()
X_train = sc.fit_transform(X_train)
X_train = pd.DataFrame(X_train)
X_train.columns = ["Pclass", "Age", "SibSp", "Parch", "Fare"]

from sklearn.tree import DecisionTreeClassifier
clf = DecisionTreeClassifier()


#from sklearn.ensemble import RandomForestClassifier
#clf=RandomForestClassifier()

#from sklearn.svm import SVC
#clf=SVC()

#from sklearn.neighbors import KNeighborsClassifier
#clf=KNeighborsClassifier()

clf.fit(X_train,y_train)


X_test=pd.read_csv("test.csv")

X_test.drop(["Name","Cabin"],axis=1,inplace=True)
X_test.set_index("PassengerId",inplace=True)
X_test["Age"].fillna(X_test["Age"].mean(),inplace=True)
X_test["Fare"].fillna(X_test["Fare"].mean(),inplace=True)
X_test=pd.get_dummies(X_test.loc[:,["Pclass", "Age", "SibSp", "Parch", "Fare"]])


sc=StandardScaler()
X_test_norm = sc.fit_transform(X_test)


y_test = clf.predict(X_test_norm)
y_test = pd.DataFrame(y_test, X_test.index)
y_test.columns = ["Survived"]

y_test.to_csv("output.csv")