{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"!pip install --quiet tables","metadata":{"execution":{"iopub.status.busy":"2022-08-16T16:28:41.336051Z","iopub.execute_input":"2022-08-16T16:28:41.336567Z","iopub.status.idle":"2022-08-16T16:28:56.948550Z","shell.execute_reply.started":"2022-08-16T16:28:41.336451Z","shell.execute_reply":"2022-08-16T16:28:56.947243Z"},"trusted":true},"execution_count":null,"outputs":[]},{"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)\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        \npd.options.display.max_columns = 228942 \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":"2022-08-16T16:29:00.247757Z","iopub.execute_input":"2022-08-16T16:29:00.248177Z","iopub.status.idle":"2022-08-16T16:29:00.259697Z","shell.execute_reply.started":"2022-08-16T16:29:00.248139Z","shell.execute_reply":"2022-08-16T16:29:00.258289Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_cite_targets = pd.read_hdf('/kaggle/input/open-problems-multimodal/train_cite_targets.h5')\ntrain_cite_targets.shape","metadata":{"execution":{"iopub.status.busy":"2022-08-16T16:29:04.593316Z","iopub.execute_input":"2022-08-16T16:29:04.594374Z","iopub.status.idle":"2022-08-16T16:29:05.352229Z","shell.execute_reply.started":"2022-08-16T16:29:04.594323Z","shell.execute_reply":"2022-08-16T16:29:05.350923Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_cite_targets.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-16T16:29:09.745932Z","iopub.execute_input":"2022-08-16T16:29:09.747257Z","iopub.status.idle":"2022-08-16T16:29:09.871389Z","shell.execute_reply.started":"2022-08-16T16:29:09.747203Z","shell.execute_reply":"2022-08-16T16:29:09.869847Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nimport plotly.express as px","metadata":{"execution":{"iopub.status.busy":"2022-08-16T16:32:53.420059Z","iopub.execute_input":"2022-08-16T16:32:53.420798Z","iopub.status.idle":"2022-08-16T16:32:53.426409Z","shell.execute_reply.started":"2022-08-16T16:32:53.420748Z","shell.execute_reply":"2022-08-16T16:32:53.425193Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"features =['CD86', 'CD274','CD270']\nfig = px.scatter_matrix(train_cite_targets,dimensions= features )\nfig.show()\n","metadata":{"execution":{"iopub.status.busy":"2022-08-16T16:35:03.720771Z","iopub.execute_input":"2022-08-16T16:35:03.721530Z","iopub.status.idle":"2022-08-16T16:35:03.831486Z","shell.execute_reply.started":"2022-08-16T16:35:03.721482Z","shell.execute_reply":"2022-08-16T16:35:03.829140Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_cite_inputs = pd.read_hdf('/kaggle/input/open-problems-multimodal/train_cite_inputs.h5',start=0, stop = 1000)\ntrain_cite_inputs.shape","metadata":{"execution":{"iopub.status.busy":"2022-08-16T16:27:50.552684Z","iopub.execute_input":"2022-08-16T16:27:50.554005Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_multi_targets = pd.read_hdf('/kaggle/input/open-problems-multimodal/train_multi_targets.h5',start=0, stop = 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pd.read_hdf('/kaggle/input/open-problems-multimodal/train_multi_inputs.h5',start=0, stop = 1000)","metadata":{"execution":{"iopub.status.busy":"2022-08-16T15:44:07.236115Z","iopub.execute_input":"2022-08-16T15:44:07.236841Z","iopub.status.idle":"2022-08-16T15:44:11.263755Z","shell.execute_reply.started":"2022-08-16T15:44:07.236771Z","shell.execute_reply":"2022-08-16T15:44:11.262525Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_cite_targets.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-16T15:44:11.265365Z","iopub.execute_input":"2022-08-16T15:44:11.265722Z","iopub.status.idle":"2022-08-16T15:44:11.401724Z","shell.execute_reply.started":"2022-08-16T15:44:11.265692Z","shell.execute_reply":"2022-08-16T15:44:11.400360Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_cite_inputs.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-16T15:44:11.406788Z","iopub.execute_input":"2022-08-16T15:44:11.407335Z","iopub.status.idle":"2022-08-16T15:44:31.115965Z","shell.execute_reply.started":"2022-08-16T15:44:11.407283Z","shell.execute_reply":"2022-08-16T15:44:31.114926Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_multi_targets.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-16T15:44:31.117180Z","iopub.execute_input":"2022-08-16T15:44:31.117976Z","iopub.status.idle":"2022-08-16T15:44:52.303576Z","shell.execute_reply.started":"2022-08-16T15:44:31.117942Z","shell.execute_reply":"2022-08-16T15:44:52.301963Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_multi_inputs.head()","metadata":{"execution":{"iopub.status.busy":"2022-08-16T15:44:52.305692Z","iopub.execute_input":"2022-08-16T15:44:52.306596Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"'''\n/kaggle/input/open-problems-multimodal/test_multi_inputs.h5\n/kaggle/input/open-problems-multimodal/test_cite_inputs.h5\n'''","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"'''\n/kaggle/input/open-problems-multimodal/train_cite_inputs.h5\n/kaggle/input/open-problems-multimodal/train_multi_targets.h5\n/kaggle/input/open-problems-multimodal/train_multi_inputs.h5\n/kaggle/input/open-problems-multimodal/train_cite_targets.h5\n'''","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"metadata= 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