{"metadata":{"kaggle":{"accelerator":"none","dataSources":[{"sourceId":84493,"databundleVersionId":9871156,"sourceType":"competition"}],"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false},"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.10.14"},"papermill":{"default_parameters":{},"duration":55.506705,"end_time":"2024-10-18T02:48:27.579024","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2024-10-18T02:47:32.072319","version":"2.6.0"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Jane Street Data View","metadata":{"papermill":{"duration":0.003047,"end_time":"2024-10-18T02:47:34.758750","exception":false,"start_time":"2024-10-18T02:47:34.755703","status":"completed"},"tags":[]}},{"cell_type":"code","source":"import os\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns","metadata":{"execution":{"iopub.execute_input":"2024-10-18T02:47:34.765291Z","iopub.status.busy":"2024-10-18T02:47:34.764991Z","iopub.status.idle":"2024-10-18T02:47:36.882308Z","shell.execute_reply":"2024-10-18T02:47:36.881519Z"},"papermill":{"duration":2.12321,"end_time":"2024-10-18T02:47:36.884606","exception":false,"start_time":"2024-10-18T02:47:34.761396","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train = pd.read_parquet('/kaggle/input/jane-street-real-time-market-data-forecasting/train.parquet/partition_id=0/part-0.parquet')\ntest = pd.read_parquet('/kaggle/input/jane-street-real-time-market-data-forecasting/test.parquet/date_id=0/part-0.parquet')","metadata":{"execution":{"iopub.execute_input":"2024-10-18T02:47:36.891189Z","iopub.status.busy":"2024-10-18T02:47:36.890790Z","iopub.status.idle":"2024-10-18T02:47:41.589586Z","shell.execute_reply":"2024-10-18T02:47:41.588614Z"},"papermill":{"duration":4.704539,"end_time":"2024-10-18T02:47:41.591883","exception":false,"start_time":"2024-10-18T02:47:36.887344","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"print(len(train))\nprint(len(test))\n\ncols=train.columns.tolist()\nprint(cols)\n\nprint(train['date_id'].nunique())\nprint(train['time_id'].nunique())\nprint(train['symbol_id'].nunique())\n\n","metadata":{"execution":{"iopub.execute_input":"2024-10-18T02:47:41.598631Z","iopub.status.busy":"2024-10-18T02:47:41.598280Z","iopub.status.idle":"2024-10-18T02:47:41.643256Z","shell.execute_reply":"2024-10-18T02:47:41.642242Z"},"papermill":{"duration":0.050456,"end_time":"2024-10-18T02:47:41.645240","exception":false,"start_time":"2024-10-18T02:47:41.594784","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# time_id == 0","metadata":{}},{"cell_type":"code","source":"df=train[train['time_id']==0]\ndisplay(df)","metadata":{"execution":{"iopub.execute_input":"2024-10-18T02:47:41.651606Z","iopub.status.busy":"2024-10-18T02:47:41.651293Z","iopub.status.idle":"2024-10-18T02:47:41.682519Z","shell.execute_reply":"2024-10-18T02:47:41.681659Z"},"papermill":{"duration":0.036794,"end_time":"2024-10-18T02:47:41.684664","exception":false,"start_time":"2024-10-18T02:47:41.647870","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"for col in cols[3:]:\n    plt.figure(figsize=(12, 6)) \n    for symbol in df['symbol_id'].unique():\n        subset = df[df['symbol_id'] == symbol]\n        plt.plot(subset['date_id'], subset[col], label=symbol)\n\n    plt.xlabel('Date')\n    plt.ylabel(f'{col} Value')\n    plt.title(f'Symbol-wise {col}')\n    plt.legend(title='Symbol ID', bbox_to_anchor=(1.05, 1), loc='upper left')\n\n    plt.xticks(rotation=45)\n    plt.tight_layout()\n    plt.show()","metadata":{"execution":{"iopub.execute_input":"2024-10-18T02:47:41.692097Z","iopub.status.busy":"2024-10-18T02:47:41.691819Z","iopub.status.idle":"2024-10-18T02:48:26.188075Z","shell.execute_reply":"2024-10-18T02:48:26.187025Z"},"papermill":{"duration":44.507994,"end_time":"2024-10-18T02:48:26.195813","exception":false,"start_time":"2024-10-18T02:47:41.687819","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# date_id == 0","metadata":{}},{"cell_type":"code","source":"df2=train[train['date_id']==0]\ndisplay(df2)","metadata":{"papermill":{"duration":0.29087,"end_time":"2024-10-18T02:48:26.790968","exception":false,"start_time":"2024-10-18T02:48:26.500098","status":"completed"},"tags":[]},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"for col in cols[3:]:\n    plt.figure(figsize=(12, 6)) \n    for symbol in df2['symbol_id'].unique():\n        subset = df2[df2['symbol_id'] == symbol]\n        plt.plot(subset['time_id'], subset[col], label=symbol)\n\n    plt.xlabel('Time')\n    plt.ylabel(f'{col} Value')\n    plt.title(f'Symbol-wise {col}')\n    plt.legend(title='Symbol ID', bbox_to_anchor=(1.05, 1), loc='upper left')\n\n    plt.xticks(rotation=45)\n    plt.tight_layout()\n    plt.show()","metadata":{},"execution_count":null,"outputs":[]}]}