{"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":81000,"databundleVersionId":8812083,"sourceType":"competition"}],"dockerImageVersionId":30732,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport seaborn as sns # plotting\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2024-06-11T08:55:42.756877Z","iopub.execute_input":"2024-06-11T08:55:42.757317Z","iopub.status.idle":"2024-06-11T08:55:45.136400Z","shell.execute_reply.started":"2024-06-11T08:55:42.757280Z","shell.execute_reply":"2024-06-11T08:55:45.134679Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"def load_data(crop: str, mode: str=\"train\"):\n    # note that years represent an offset from model spinup;\n    # soil co2 dataset has real year;\n    # 0-30 are days before sowing, 31-238 are days after sowing\n    tasmax = pd.read_parquet(f\"/kaggle/input/the-future-crop-challenge/tasmax_{crop}_{mode}.parquet\")\n    tasmin = pd.read_parquet(f\"/kaggle/input/the-future-crop-challenge/tasmin_{crop}_{mode}.parquet\")\n    pr = pd.read_parquet(f\"/kaggle/input/the-future-crop-challenge/pr_{crop}_{mode}.parquet\")\n    rsds = pd.read_parquet(f\"/kaggle/input/the-future-crop-challenge/rsds_{crop}_{mode}.parquet\")\n    soil_co2 = pd.read_parquet(f\"/kaggle/input/the-future-crop-challenge/soil_co2_{crop}_{mode}.parquet\")\n    target = pd.read_parquet(f\"/kaggle/input/the-future-crop-challenge/{mode}_solutions_{crop}.parquet\") if mode == \"train\" else None\n    return {\n        'tasmax': tasmax,\n        'tasmin': tasmin,\n        'pr': pr,\n        'rsds': rsds,\n        'soil_co2': soil_co2,\n        'target': target,\n    }","metadata":{"execution":{"iopub.status.busy":"2024-06-11T08:55:45.139708Z","iopub.execute_input":"2024-06-11T08:55:45.140477Z","iopub.status.idle":"2024-06-11T08:55:45.151266Z","shell.execute_reply.started":"2024-06-11T08:55:45.140422Z","shell.execute_reply":"2024-06-11T08:55:45.149652Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"maize_train = load_data(\"maize\", \"train\")\nmaize_train.keys()","metadata":{"execution":{"iopub.status.busy":"2024-06-11T08:55:45.153143Z","iopub.execute_input":"2024-06-11T08:55:45.153619Z","iopub.status.idle":"2024-06-11T08:55:51.395964Z","shell.execute_reply.started":"2024-06-11T08:55:45.153565Z","shell.execute_reply":"2024-06-11T08:55:51.394637Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"maize_train['tasmax']","metadata":{"execution":{"iopub.status.busy":"2024-06-11T08:55:51.398495Z","iopub.execute_input":"2024-06-11T08:55:51.398886Z","iopub.status.idle":"2024-06-11T08:55:51.576839Z","shell.execute_reply.started":"2024-06-11T08:55:51.398853Z","shell.execute_reply":"2024-06-11T08:55:51.575325Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"plt = sns.lineplot(maize_train['tasmax'], x='year', y='30')\nplt.set_title(\"Maize, tasmax, day 30\")\nplt","metadata":{"execution":{"iopub.status.busy":"2024-06-11T08:55:51.578490Z","iopub.execute_input":"2024-06-11T08:55:51.578965Z","iopub.status.idle":"2024-06-11T08:55:55.949106Z","shell.execute_reply.started":"2024-06-11T08:55:51.578916Z","shell.execute_reply":"2024-06-11T08:55:55.947830Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}