{"metadata":{"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"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":84493,"databundleVersionId":9871156,"sourceType":"competition"},{"sourceId":10245336,"sourceType":"datasetVersion","datasetId":6336300},{"sourceId":203900450,"sourceType":"kernelVersion"}],"dockerImageVersionId":30787,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":false},"papermill":{"default_parameters":{},"duration":7.594014,"end_time":"2024-10-10T11:58:36.355301","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2024-10-10T11:58:28.761287","version":"2.6.0"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nimport polars as pl\nimport numpy as np\nimport os\nfrom tqdm.auto import tqdm\nfrom matplotlib import pyplot as plt\nimport pickle\n\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n%matplotlib inline\n\nfrom sklearn.metrics import r2_score\nfrom lightgbm import LGBMRegressor\nimport lightgbm as lgb\nfrom xgboost import XGBRegressor\nfrom catboost import CatBoostRegressor\nfrom sklearn.ensemble import VotingRegressor\n\nimport warnings\nwarnings.filterwarnings('ignore')\npd.options.display.max_columns = None\n\nimport kaggle_evaluation.jane_street_inference_server","metadata":{"execution":{"iopub.status.busy":"2024-12-29T13:07:32.290104Z","iopub.execute_input":"2024-12-29T13:07:32.290657Z","iopub.status.idle":"2024-12-29T13:07:38.102128Z","shell.execute_reply.started":"2024-12-29T13:07:32.290604Z","shell.execute_reply":"2024-12-29T13:07:38.100782Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"class CONFIG:\n    seed = 42\n    target_col = \"responder_6\"\n    feature_cols = [\"symbol_id\", \"time_id\"] \\\n        + [f\"feature_{idx:02d}\" for idx in range(79)] \\\n        + [f\"responder_{idx}_lag_1\" for idx in range(9)]\n    categorical_cols = []","metadata":{"execution":{"iopub.status.busy":"2024-12-29T13:08:00.186831Z","iopub.execute_input":"2024-12-29T13:08:00.187575Z","iopub.status.idle":"2024-12-29T13:08:00.194316Z","shell.execute_reply.started":"2024-12-29T13:08:00.187530Z","shell.execute_reply":"2024-12-29T13:08:00.193069Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train = pl.scan_parquet(\"/kaggle/input/20241219-data/training.parquet\").collect().to_pandas()\ntrain.shape, valid.shape","metadata":{"execution":{"iopub.status.busy":"2024-12-29T13:09:42.329280Z","iopub.execute_input":"2024-12-29T13:09:42.330764Z","iopub.status.idle":"2024-12-29T13:09:50.643672Z","shell.execute_reply.started":"2024-12-29T13:09:42.330698Z","shell.execute_reply":"2024-12-29T13:09:50.642527Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train","metadata":{"trusted":true,"execution":{"execution_failed":"2024-12-29T13:04:13.525Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"sta_df = train[['feature_08','responder_6']]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:09:56.205072Z","iopub.execute_input":"2024-12-29T13:09:56.205475Z","iopub.status.idle":"2024-12-29T13:09:56.242918Z","shell.execute_reply.started":"2024-12-29T13:09:56.205441Z","shell.execute_reply":"2024-12-29T13:09:56.241765Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"sta_df","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:10:00.437457Z","iopub.execute_input":"2024-12-29T13:10:00.437917Z","iopub.status.idle":"2024-12-29T13:10:00.459735Z","shell.execute_reply.started":"2024-12-29T13:10:00.437876Z","shell.execute_reply":"2024-12-29T13:10:00.458297Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# **直接对两者进行分析**","metadata":{}},{"cell_type":"markdown","source":"单变量分布图（直方图 + 密度图)","metadata":{}},{"cell_type":"code","source":"# 绘制feature_08分布\nsns.histplot(sta_df['feature_08'], kde=True, bins=50, color='blue')\nplt.title(\"Distribution of feature_08\")\nplt.show()\n\n# 绘制responder_6分布\nsns.histplot(sta_df['responder_6'], kde=True, bins=50, color='orange')\nplt.title(\"Distribution of responder_6\")\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:25:47.682593Z","iopub.execute_input":"2024-12-29T13:25:47.683110Z","iopub.status.idle":"2024-12-29T13:26:48.858452Z","shell.execute_reply.started":"2024-12-29T13:25:47.683065Z","shell.execute_reply":"2024-12-29T13:26:48.857028Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**两者均是分布于-2到2的范围之间，未发现偏态的情况**","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize=(8, 6))\nsns.scatterplot(x=sta_df['feature_08'], y=sta_df['responder_6'])\nplt.title('Scatter Plot of feature_08 vs responder_6')\nplt.xlabel('feature_08')\nplt.ylabel('responder_6')\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T12:36:08.769872Z","iopub.execute_input":"2024-12-29T12:36:08.770293Z","iopub.status.idle":"2024-12-29T12:36:22.456537Z","shell.execute_reply.started":"2024-12-29T12:36:08.770257Z","shell.execute_reply":"2024-12-29T12:36:22.455361Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**从这张图来看，目前并没有明显的线性趋势，数据点看起来比较随机地分布在中心点周围。这可能意味着 “feature_08” 和 “responder_6” 之间没有明显的线性相关性。**\n","metadata":{}},{"cell_type":"markdown","source":"**计算皮尔逊系数**","metadata":{}},{"cell_type":"code","source":"correlation = sta_df[['feature_08', 'responder_6']].corr()\nprint(\"Correlation matrix:\")\nprint(correlation)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T12:40:45.654417Z","iopub.execute_input":"2024-12-29T12:40:45.654812Z","iopub.status.idle":"2024-12-29T12:40:45.840482Z","shell.execute_reply.started":"2024-12-29T12:40:45.654781Z","shell.execute_reply":"2024-12-29T12:40:45.839335Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**feature_08 和 responder_6 的相关性是 0.011034，接近于 0。\n这表明 feature_08 和 responder_6 几乎没有线性相关性，即一个变量的变化无法通过另一个变量的线性变化来解释。**","metadata":{}},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"spearman_corr = sta_df[['feature_08', 'responder_6']].corr(method='spearman')\nkendall_corr = sta_df[['feature_08', 'responder_6']].corr(method='kendall')\nprint(\"Spearman Correlation:\")\nprint(spearman_corr)\nprint(\"Kendall Correlation:\")\nprint(kendall_corr)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T12:44:14.604874Z","iopub.execute_input":"2024-12-29T12:44:14.605268Z","iopub.status.idle":"2024-12-29T12:44:26.667226Z","shell.execute_reply.started":"2024-12-29T12:44:14.605237Z","shell.execute_reply":"2024-12-29T12:44:26.666153Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**相关性值接近 0**\n\n**Spearman（秩相关系数） 和 Kendall（等级相关系数） 的值都非常接近 0。\n这表明 feature_08 和 responder_6 之间几乎没有任何单调关系（即一个变量的升高或降低无法系统地对应另一个变量的升高或降低）。\n与 Pearson 结果一致**\n\n**Pearson 相关性结果接近 0，说明两者没有显著的线性关系。\nSpearman 和 Kendall 的结果进一步验证了两者之间没有显著的非线性单调关系。**","metadata":{},"attachments":{"6971fa5f-7240-49b0-97dc-c03d5645ecfa.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"**分布趋势分析（分段均值图）**","metadata":{}},{"cell_type":"code","source":"bins = pd.cut(sta_df['feature_08'], bins=10)\ngrouped = sta_df.groupby(bins)['responder_6'].mean().reset_index()\n\n# 绘制均值趋势\nsns.lineplot(x=grouped.index, y=grouped['responder_6'])\nplt.title(\"Mean of responder_6 across Binned feature_08\")\nplt.xlabel(\"Binned feature_08\")\nplt.ylabel(\"Mean of responder_6\")\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:36:54.148264Z","iopub.execute_input":"2024-12-29T13:36:54.148774Z","iopub.status.idle":"2024-12-29T13:36:54.632724Z","shell.execute_reply.started":"2024-12-29T13:36:54.148733Z","shell.execute_reply":"2024-12-29T13:36:54.631117Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**总体趋势**\n随着 “Binned feature_08” 的值从 0 增加到 8，“Mean of responder_6” 总体上呈现出上升的趋势。\n特别是在 “Binned feature_08” 接近 8 时，“Mean of responder_6” 的值急剧上升，达到接近 0.35 的峰值。\n\n**局部波动**\n在上升的过程中，“Mean of responder_6” 的值并非单调递增，而是有一些小的波动。例如，在 “Binned feature_08” 为 2 到 4 之间，“Mean of responder_6” 的值有小幅上升和下降。","metadata":{}},{"cell_type":"markdown","source":"**箱形图**","metadata":{}},{"cell_type":"code","source":"sta_df['Duration_Binned1'] = pd.cut(sta_df['feature_08'], bins=10)  # 将数据分箱\nsns.boxplot(x='Duration_Binned1', y='responder_6', data=sta_df)\nplt.xticks(rotation=45)\nplt.title(\"Boxplot of responder_6 by Binned feature_08\")\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:43:17.118593Z","iopub.execute_input":"2024-12-29T13:43:17.118930Z","iopub.status.idle":"2024-12-29T13:43:19.095183Z","shell.execute_reply.started":"2024-12-29T13:43:17.118896Z","shell.execute_reply":"2024-12-29T13:43:19.093972Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**不同的 “Binned feature_08” 类别对 “responder_6” 的值有显著影响，表现为不同的中位数、四分位数范围和异常值情况。\n这些差异表明在数据分析或建模过程中，“Binned feature_08” 可能是一个重要的变量，需要进一步研究其与 “responder_6” 之间的关系。**","metadata":{}},{"cell_type":"markdown","source":"# **尝试构建新特征**","metadata":{"execution":{"iopub.status.busy":"2024-12-29T12:47:12.922060Z","iopub.execute_input":"2024-12-29T12:47:12.922471Z","iopub.status.idle":"2024-12-29T12:47:12.954276Z","shell.execute_reply.started":"2024-12-29T12:47:12.922441Z","shell.execute_reply":"2024-12-29T12:47:12.952839Z"}}},{"cell_type":"markdown","source":"**乘**    \n在 x = 0 附近，y 值的分布较为集中，表明当 “interaction” 为 0 时，“responder_6” 的值较为稳定。\n当 “interaction” 的值偏离 0 时，“responder_6” 的值开始出现较大的波动，显示出两者之间可能存在某种非线性关系。","metadata":{}},{"cell_type":"code","source":"sta_df['interaction'] = sta_df['feature_08'] * sta_df['responder_6']\nsns.histplot(sta_df['interaction'], kde=True)\nplt.title('Distribution of Interaction Feature')\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:27:08.086539Z","iopub.execute_input":"2024-12-29T13:27:08.087069Z","iopub.status.idle":"2024-12-29T13:28:05.990105Z","shell.execute_reply.started":"2024-12-29T13:27:08.086991Z","shell.execute_reply":"2024-12-29T13:28:05.988734Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plt.figure(figsize=(8, 6))\nsns.scatterplot(x=sta_df['interaction'], y=sta_df['responder_6'])\nplt.title('Scatter Plot of interaction vs responder_6')\nplt.xlabel('interaction')\nplt.ylabel('responder_6')\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:28:05.992062Z","iopub.execute_input":"2024-12-29T13:28:05.992435Z","iopub.status.idle":"2024-12-29T13:28:19.443652Z","shell.execute_reply.started":"2024-12-29T13:28:05.992398Z","shell.execute_reply":"2024-12-29T13:28:19.442321Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"spearman_corr = sta_df[['interaction', 'responder_6']].corr(method='spearman')\nkendall_corr = sta_df[['interaction', 'responder_6']].corr(method='kendall')\nprint(\"Spearman Correlation:\")\nprint(spearman_corr)\nprint(\"Kendall Correlation:\")\nprint(kendall_corr)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:28:19.445135Z","iopub.execute_input":"2024-12-29T13:28:19.445495Z","iopub.status.idle":"2024-12-29T13:28:33.055846Z","shell.execute_reply.started":"2024-12-29T13:28:19.445460Z","shell.execute_reply":"2024-12-29T13:28:33.054460Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**没有线性相关性**","metadata":{}},{"cell_type":"code","source":"bins = pd.cut(sta_df['interaction'], bins=10)\ngrouped = sta_df.groupby(bins)['responder_6'].mean().reset_index()\n\n# 绘制均值趋势\nsns.lineplot(x=grouped.index, y=grouped['responder_6'])\nplt.title(\"Mean of responder_6 across Binned interaction\")\nplt.xlabel(\"Binned interaction\")\nplt.ylabel(\"Mean of responder_6\")\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:38:39.922290Z","iopub.execute_input":"2024-12-29T13:38:39.923604Z","iopub.status.idle":"2024-12-29T13:38:40.473452Z","shell.execute_reply.started":"2024-12-29T13:38:39.923535Z","shell.execute_reply":"2024-12-29T13:38:40.472209Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**总体趋势**\n随着 “Binned interaction” 的值从 0 增加到 8，“Mean of responder_6” 总体上呈现出上升的趋势。\n特别是在 “Binned interaction” 接近 8 时，“Mean of responder_6” 的值急剧上升，达到接近 5 的峰值。\n\n**局部波动**\n在上升的过程中，“Mean of responder_6” 的值并非单调递增，而是有一些小的波动。例如，在 “Binned interaction” 为 2 到 4 之间，“Mean of responder_6” 的值有小幅上升和下降","metadata":{}},{"cell_type":"markdown","source":"**箱形图**","metadata":{}},{"cell_type":"code","source":"sta_df['Duration_Binned2'] = pd.cut(sta_df['interaction'], bins=10)  # 将数据分箱\nsns.boxplot(x='Duration_Binned2', y='responder_6', data=sta_df)\nplt.xticks(rotation=45)\nplt.title(\"Boxplot of responder_6 by Binned interaction\")\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:46:47.065756Z","iopub.execute_input":"2024-12-29T13:46:47.066300Z","iopub.status.idle":"2024-12-29T13:46:48.962933Z","shell.execute_reply.started":"2024-12-29T13:46:47.066258Z","shell.execute_reply":"2024-12-29T13:46:48.961701Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**1. 数据分布特征**\n中位数（Median）\n不同颜色的箱线图代表不同的 “Binned interaction” 类别，其对应的中位数（箱体中间的线）位置各不相同。这表明不同类别的 “responder_6” 中位数存在差异。\n例如，橙色箱线图的中位数明显高于蓝色箱线图的中位数。\n四分位数\n箱体的上下边缘分别代表上四分位数（Q3）和下四分位数（Q1）。不同类别的箱体长度和位置各异，反映了数据的离散程度不同。\n例如，绿色箱线图的箱体较长，说明该类别中的数据变异性较大；而粉色箱线图的箱体较短，表明其数据变异性较小。\n\n**2. 异常值**\n图中用单独的点表示异常值。多个类别中都存在异常值，且异常值的分布范围较广。\n例如，橙色箱线图和绿色箱线图都有较多的异常值，这些异常值可能对数据分析和建模产生重要影响。\n\n**3. 总体趋势**\n从左到右观察箱线图，可以发现 “responder_6” 的值在不同类别之间存在较大波动。\n某些类别（如橙色和绿色）的数据分布较为分散，而其他类别（如粉色）的数据分布较为集中。\n\n**总结**\n不同的 “Binned interaction” 类别对 “responder_6” 的数据分布有显著影响，表现为中位数、四分位数范围和异常值的差异。\n在进行数据分析或建模时，需要考虑这些差异，特别是异常值可能对结果产生的影响。\n","metadata":{}},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**除**-----没跑出来","metadata":{}},{"cell_type":"code","source":"sta_df['feature_ratio'] = sta_df['feature_08'] / (sta_df['responder_6'] + 1e-9) \nsns.histplot(sta_df['feature_ratio'], kde=True)\nplt.title('Distribution of feature_ratio Feature')\nplt.show()","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plt.figure(figsize=(8, 6))\nsns.scatterplot(x=sta_df['feature_ratio'], y=sta_df['responder_6'])\nplt.title('Scatter Plot of feature_ratio vs responder_6')\nplt.xlabel('feature_ratio')\nplt.ylabel('responder_6')\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2024-12-29T13:21:21.974488Z","iopub.status.idle":"2024-12-29T13:21:21.974868Z","shell.execute_reply.started":"2024-12-29T13:21:21.974693Z","shell.execute_reply":"2024-12-29T13:21:21.974711Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# **结论**\n# feature_08和interaction与responder_6虽然没有明显的线性关系，但两者对responder_6也具有一定的影响。具有研究价值，构建模型时可以考虑加入特征\n","metadata":{}},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}