Problems with logistic regression in Titanic dataset

Question

I'm an aspiring data scientist. I stumbled across the titanic dataset. I tried to use logistic regression for the problem. However, I got stuck.

Since I have two different datasets, I didn't use the train-test-split function

In the code below I can show you where I got stuck after getting my datasets (train and test) ready to undergo logistic regression:

lr = LogisticRegression(C=100, random_state=42, solver="liblinear", 
max_iter=1000)
lr.fit(X_train, y_train)



mms = MinMaxScaler()
X_train = mms.fit_transform(X_train)
X_test = mms.transform(X_test)

I want to make a prediction of the people who survived during the titanic sinking.

I trained the model using the train dataset and I want to use this model to make a prediction on the test dataset

I don't have information about the survival outcome in the test dataset

X_train and X_test are the datasets with all the information about the passengers

y_train is the NumPy array with the survival outcome of the passengers in the X_train dataset