{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":98450,"databundleVersionId":11749951,"sourceType":"competition"}],"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Load train and test CSVs\ntrain_df = pd.read_csv(\"/kaggle/input/beyond-visible-spectrum-ai-for-agriculture-2025/train.csv\")\ntest_df = pd.read_csv(\"/kaggle/input/beyond-visible-spectrum-ai-for-agriculture-2025/test.csv\")","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Compute the mean of the target column\nmean_target = train_df['label'].mean()\n\n# Create a prediction column with the mean value for all test samples\ntest_df['TARGET'] = mean_target\n\n# Prepare submission with renamed ID column\nsubmission = test_df[['id', 'TARGET']].rename(columns={'id': 'ID'})\nsubmission.to_csv('submission.csv', index=False)\n\nprint(\"submission.csv created successfully!\")","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}