{"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","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"},"papermill":{"default_parameters":{},"duration":42.399313,"end_time":"2022-09-13T14:09:35.443305","environment_variables":{},"exception":null,"input_path":"__notebook__.ipynb","output_path":"__notebook__.ipynb","parameters":{},"start_time":"2022-09-13T14:08:53.043992","version":"2.3.4"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":102335,"databundleVersionId":12518947,"isSourceIdPinned":false,"sourceType":"competition"}],"dockerImageVersionId":30626,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Behavior Data HistPlot","metadata":{"papermill":{"duration":0.004852,"end_time":"2022-09-13T14:09:03.598005","exception":false,"start_time":"2022-09-13T14:09:03.593153","status":"completed"},"tags":[]}},{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport os\nimport random\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom tqdm import tqdm\nimport plotly.express as px\nimport plotly.graph_objects as go\nfrom plotly.subplots import make_subplots","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","papermill":{"duration":2.47983,"end_time":"2022-09-13T14:09:06.081763","exception":false,"start_time":"2022-09-13T14:09:03.601933","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2024-12-17T14:16:22.940542Z","iopub.execute_input":"2024-12-17T14:16:22.940981Z","iopub.status.idle":"2024-12-17T14:16:22.947142Z","shell.execute_reply.started":"2024-12-17T14:16:22.940952Z","shell.execute_reply":"2024-12-17T14:16:22.945972Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train=pd.read_csv('/kaggle/input/cmi-detect-behavior-with-sensor-data/train.csv')\ndisplay(train[0:3].T)","metadata":{"papermill":{"duration":0.170345,"end_time":"2022-09-13T14:09:06.256061","exception":false,"start_time":"2022-09-13T14:09:06.085716","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2024-12-17T14:16:22.949586Z","iopub.execute_input":"2024-12-17T14:16:22.950056Z","iopub.status.idle":"2024-12-17T14:16:23.268177Z","shell.execute_reply.started":"2024-12-17T14:16:22.950013Z","shell.execute_reply":"2024-12-17T14:16:23.266944Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"print(len(train))\nM=list(range(len(train)))\nrandom.shuffle(M)\ntrain=train.iloc[M[0:4000]]\ntrain=train.reset_index(drop=True)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"cols=train.columns.tolist()\nprint(cols)\nprint(len(cols))\ncols=cols[0:60]","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"fig, ax = plt.subplots(30,2,figsize=(12,90))\nplt.subplots_adjust(hspace=3)\n\nfor i in tqdm(range(len(cols))):\n    r=i//2\n    c=i%2\n    sns.histplot(train[cols[i]], label='train '+cols[i], ax=ax[r,c], color='C1',bins=40, alpha=0.5)\n\n    ax[r,c].legend()\n    ax[r,c].grid()\n    ax[r,c].tick_params(axis='x', labelrotation=80)\n\nplt.show()","metadata":{"papermill":{"duration":0.016812,"end_time":"2022-09-13T14:09:34.604792","exception":false,"start_time":"2022-09-13T14:09:34.58798","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2024-12-17T14:17:05.569507Z","iopub.execute_input":"2024-12-17T14:17:05.570067Z","iopub.status.idle":"2024-12-17T14:17:17.798164Z","shell.execute_reply.started":"2024-12-17T14:17:05.570027Z","shell.execute_reply":"2024-12-17T14:17:17.796879Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train2=pd.read_csv('/kaggle/input/cmi-detect-behavior-with-sensor-data/train_demographics.csv')\ndisplay(train2[0:3].T)","metadata":{"papermill":{"duration":0.016405,"end_time":"2022-09-13T14:09:06.315603","exception":false,"start_time":"2022-09-13T14:09:06.299198","status":"completed"},"tags":[],"execution":{"iopub.status.busy":"2024-12-17T14:16:23.29013Z","iopub.execute_input":"2024-12-17T14:16:23.290406Z","iopub.status.idle":"2024-12-17T14:16:23.302922Z","shell.execute_reply.started":"2024-12-17T14:16:23.290382Z","shell.execute_reply":"2024-12-17T14:16:23.30174Z"},"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"print(len(train2))\nM2=list(range(len(train2)))\nrandom.shuffle(M2)\ntrain2=train2.iloc[M2[0:4000]]\ntrain2=train2.reset_index(drop=True)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"cols2=train2.columns.tolist()\nprint(cols2)\nprint(len(cols2))\n","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"fig, ax = plt.subplots(4,2,figsize=(12,12))\nplt.subplots_adjust(hspace=3)\n\nfor i in tqdm(range(len(cols2))):\n    r=i//2\n    c=i%2\n    sns.histplot(train2[cols2[i]], label='train '+cols2[i], ax=ax[r,c], color='C1',bins=40, alpha=0.5)\n\n    ax[r,c].legend()\n    ax[r,c].grid()\n    ax[r,c].tick_params(axis='x', labelrotation=80)\n\nplt.show()","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}