# load needed packages (the dataset comes from Kaggle's "Titanic" competition)
library(tidyverse)
library(rpart)
library(rpart.plot)

# import the data
train <- read_csv("train.csv")
test <- read_csv("test.csv")

# create a decision tree
model <- rpart(Survived ~ Pclass + Sex, data = train, method = "class", cp = -1)

# make the predictions using the test data
predictions <- as.numeric(predict(model, test, type = "class")) - 1

# create a submission data frame
submission <- as.data.frame(cbind(PassengerId = test$PassengerId, Survived = predictions))

# write your submission as a file
write_csv(submission, "submit.csv")