{"part":"task","text":"# Datasets\nPass a dataset's id as the `dataset` argument.\n{\n \"id\": \"invest_email_rnd_test\",\n \"rows\": 6000,\n \"description\": \"Data file invest_email_rnd_test.csv of this question; the question's data description is the description of dataset 'invest_email_rnd_train'.\",\n \"columns\": {\n  \"id\": \"int64\",\n  \"age\": \"float64\",\n  \"income\": \"float64\",\n  \"insurance\": \"float64\",\n  \"invested\": \"float64\",\n  \"em1\": \"int64\",\n  \"em2\": \"int64\",\n  \"em3\": \"int64\",\n  \"converted\": \"int64\"\n }\n}\n{\n \"id\": \"invest_email_rnd_train\",\n \"rows\": 9000,\n \"description\": \"To evaluate the effectiveness of email marketing on customer investment decisions, the dataset invest_email_rnd_train.csv is used for training, and invest_email_rnd_train.csv is used for testing. They contain customer data including id, age, income, insurance, invested amount, binary indicators for whether they received three different emails (em1, em2, em3), and a binary outcome variable indicating whether the customer converted (invested vs. didn't invest) after receiving an email. The goal is to personalize email marketing by sending email-1 only to customers predicted to have the highest increase in the probability of conversion.\",\n \"columns\": {\n  \"id\": \"int64\",\n  \"age\": \"float64\",\n  \"income\": \"float64\",\n  \"insurance\": \"float64\",\n  \"invested\": \"float64\",\n  \"em1\": \"int64\",\n  \"em2\": \"int64\",\n  \"em3\": \"int64\",\n  \"converted\": \"int64\"\n }\n}"}