{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":67356,"databundleVersionId":8006601,"sourceType":"competition"},{"sourceId":8048149,"sourceType":"datasetVersion","datasetId":4745893}],"dockerImageVersionId":30673,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# **FOREWORD**","metadata":{}},{"cell_type":"markdown","source":"This kernel is used to submit the results to the leaderboard. Please find the training kernel [here](https://www.kaggle.com/code/ravi20076/belka2024-baseline-training)<br>\nOne may directly submit to the leaderboard also, this is only for check and illustration purposes. <br>\n**One may use parquet/ csv/ even compressed files for submission, .csv is not compulsory**\n","metadata":{}},{"cell_type":"code","source":"%%time \n\nimport polars as pl;\nimport polars.selectors as cs;\n\nsub_fl = pl.scan_parquet(f\"/kaggle/input/belka2024ancillary/Submission_E1V1.parquet\");\nprint(sub_fl.columns)\n\nsub_fl.collect().write_parquet(f\"submission.parquet\");","metadata":{"execution":{"iopub.status.busy":"2024-04-06T19:51:48.519677Z","iopub.execute_input":"2024-04-06T19:51:48.520510Z","iopub.status.idle":"2024-04-06T19:51:49.107645Z","shell.execute_reply.started":"2024-04-06T19:51:48.520469Z","shell.execute_reply":"2024-04-06T19:51:49.106350Z"},"trusted":true},"execution_count":null,"outputs":[]}]}