{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.11.11","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":35332,"databundleVersionId":3723648,"sourceType":"competition"}],"dockerImageVersionId":31012,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"🎯 What Are We Predicting in This Competition?\nYou are predicting the probability that a customer will default on their credit card payments in the future.\n\n✅ Specifically:\nFor each customer_ID in the test set, you must predict a number between 0 and 1.\n\nThis number represents the likelihood that the customer will default — i.e., fail to pay the due balance within 120 days of their last statement.\n\n","metadata":{}},{"cell_type":"code","source":"import pandas as pd \nimport numpy as np \n\ndf_train = pd.read_csv(\"/kaggle/input/amex-default-prediction/train_data.csv\")\ndf_t_lablel = pd.read_csv(\"/kaggle/input/amex-default-prediction/train_data.csv\") \n\ndf_train.head()\ndf_t-label.head()","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2025-04-24T16:22:59.545667Z","iopub.execute_input":"2025-04-24T16:22:59.545983Z","execution_failed":"2025-04-24T16:29:35.224Z"}},"outputs":[],"execution_count":null}]}