{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":53666,"databundleVersionId":6589269,"sourceType":"competition"},{"sourceId":7167266,"sourceType":"datasetVersion","datasetId":4106702}],"dockerImageVersionId":30558,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nimport matplotlib.pyplot as plt","metadata":{"execution":{"iopub.status.busy":"2023-12-10T11:42:18.205551Z","iopub.execute_input":"2023-12-10T11:42:18.206107Z","iopub.status.idle":"2023-12-10T11:42:18.211763Z","shell.execute_reply.started":"2023-12-10T11:42:18.206067Z","shell.execute_reply":"2023-12-10T11:42:18.210376Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_series = pd.read_parquet(\"/kaggle/input/child-mind-institute-detect-sleep-states/train_series.parquet\")\ntrain_events = pd.read_csv(\"/kaggle/input/child-mind-institute-detect-sleep-states/train_events.csv\")\nsubmit_events = pd.read_csv(\"/kaggle/input/fold-dataseries/submission.csv\")\nseries_ids = submit_events['series_id'].unique()","metadata":{"execution":{"iopub.status.busy":"2023-12-10T11:42:18.213760Z","iopub.execute_input":"2023-12-10T11:42:18.214076Z","iopub.status.idle":"2023-12-10T11:43:23.834827Z","shell.execute_reply.started":"2023-12-10T11:42:18.214047Z","shell.execute_reply":"2023-12-10T11:43:23.833586Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"for series_id in series_ids[:20]:\n    _train_series = train_series[train_series['series_id']==series_id]\n    _train_events = train_events[train_events['series_id']==series_id]\n    _submit_events = submit_events[submit_events['series_id']==series_id]\n\n    nan_index = _train_events.isnull().any(axis=1)\n    _train_events_nonan = _train_events[~nan_index]\n    _submit_events_nonan = _submit_events#[~nan_index]\n\n    _train_series.index = _train_series['step']\n    _train_events_nonan.index = _train_events_nonan['step']\n    _submit_events_nonan.index = _submit_events_nonan['step']\n\n    print('\\n'+'='*100)\n    print(series_id)\n\n    fig, ax = plt.subplots(figsize=(20, 3))\n    _train_series['anglez'].plot(ax=ax)\n    for _time, _event in zip(_train_events_nonan.index, _train_events_nonan['event']):\n        ax.axvline(x=_time, color='red' if _event=='onset' else 'green')\n    print(\"# Train Events(anglez)\")\n    plt.show()\n    \n    fig, ax = plt.subplots(figsize=(20, 3))\n    _train_series['anglez'].plot(ax=ax)\n    for _time, _event in zip(_submit_events_nonan.index, _submit_events_nonan['event']):\n        ax.axvline(x=_time, color='red' if _event=='onset' else 'green')\n    print(\"# Submit Events(anglez)\")\n    plt.show()\n    \n\n    fig, ax = plt.subplots(figsize=(20, 3))\n    _train_series['enmo'].plot(ax=ax)\n    for _time, _event in zip(_train_events_nonan.index, _train_events_nonan['event']):\n        ax.axvline(x=_time, color='red' if _event=='onset' else 'green')\n    print(\"# Train Events(enmo)\")\n    plt.show();\n    \n    fig, ax = plt.subplots(figsize=(20, 3))\n    _train_series['enmo'].plot(ax=ax)\n    for _time, _event in zip(_submit_events_nonan.index, _submit_events_nonan['event']):\n        ax.axvline(x=_time, color='red' if _event=='onset' else 'green')\n    print(\"# Submit Events(enmo)\")\n    plt.show();\n    \n    #pd.set_option('display.max_rows', None)\n    \n    print(\"# Train Events\")\n    print(_train_events)\n    print(\"# Submit Events\")\n    print(_submit_events)\n    print('\\n'+'='*100)","metadata":{"execution":{"iopub.status.busy":"2023-12-10T11:45:17.086012Z","iopub.execute_input":"2023-12-10T11:45:17.086459Z","iopub.status.idle":"2023-12-10T11:46:32.182609Z","shell.execute_reply.started":"2023-12-10T11:45:17.086425Z","shell.execute_reply":"2023-12-10T11:46:32.180598Z"},"trusted":true},"execution_count":null,"outputs":[]}]}