{"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":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n","metadata":{"id":"NekT4kQ8jrsi","outputId":"10884834-989b-4c9c-b3e2-b35d50a5f9d4","execution":{"iopub.status.busy":"2022-07-06T17:47:00.871232Z","iopub.execute_input":"2022-07-06T17:47:00.871971Z","iopub.status.idle":"2022-07-06T17:47:02.057755Z","shell.execute_reply.started":"2022-07-06T17:47:00.871845Z","shell.execute_reply":"2022-07-06T17:47:02.056783Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df = pd.read_csv(\"/kaggle/input/titanic/train.csv\")\ntest_df = pd.read_csv(\"/kaggle/input/titanic/test.csv\")\n\ntrain_df.shape","metadata":{"execution":{"iopub.status.busy":"2022-07-06T17:47:05.005983Z","iopub.execute_input":"2022-07-06T17:47:05.006341Z","iopub.status.idle":"2022-07-06T17:47:05.039323Z","shell.execute_reply.started":"2022-07-06T17:47:05.006312Z","shell.execute_reply":"2022-07-06T17:47:05.037982Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_df.shape","metadata":{"id":"RqB6hhDikJNv","outputId":"12fe9fce-3fb0-437b-a8bb-57ec75a31004","execution":{"iopub.status.busy":"2022-07-06T17:47:15.321972Z","iopub.execute_input":"2022-07-06T17:47:15.322390Z","iopub.status.idle":"2022-07-06T17:47:15.329933Z","shell.execute_reply.started":"2022-07-06T17:47:15.322355Z","shell.execute_reply":"2022-07-06T17:47:15.328876Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Exploratory Data Analysis","metadata":{"id":"iJpIirjNsrCM"}},{"cell_type":"code","source":"train_df.info()","metadata":{"id":"kddG357MkMy7","outputId":"a774ad12-b977-4322-8a8d-c1d895879e4c","execution":{"iopub.status.busy":"2022-07-06T17:47:18.706119Z","iopub.execute_input":"2022-07-06T17:47:18.706492Z","iopub.status.idle":"2022-07-06T17:47:18.739364Z","shell.execute_reply.started":"2022-07-06T17:47:18.706462Z","shell.execute_reply":"2022-07-06T17:47:18.738185Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Columns Age, Cabin and Embarked have some missing values:","metadata":{"id":"JFPn-w_Ikn0M"}},{"cell_type":"code","source":"sns.boxplot(\n    x = \"Age\",\n    data = train_df\n)","metadata":{"id":"eFHrILXIkmiF","outputId":"e6d05b8d-f5ae-4c98-f4fd-9eed94460331","execution":{"iopub.status.busy":"2022-07-06T17:47:26.172152Z","iopub.execute_input":"2022-07-06T17:47:26.172562Z","iopub.status.idle":"2022-07-06T17:47:26.370400Z","shell.execute_reply.started":"2022-07-06T17:47:26.172527Z","shell.execute_reply":"2022-07-06T17:47:26.369686Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"We have some outliers in the Age column, therefore we will use the median to fill in missing values","metadata":{"id":"cph8fd7YlCD2"}},{"cell_type":"code","source":"train_df[\"Cabin\"][:10].value_counts()","metadata":{"id":"AUGCV_IxlVDV","outputId":"705ee13c-f9c5-4ca7-80e4-6ac5bfbbea63","execution":{"iopub.status.busy":"2022-07-06T17:47:36.216255Z","iopub.execute_input":"2022-07-06T17:47:36.216695Z","iopub.status.idle":"2022-07-06T17:47:36.226207Z","shell.execute_reply.started":"2022-07-06T17:47:36.216647Z","shell.execute_reply":"2022-07-06T17:47:36.225267Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_df.isnull().sum()","metadata":{"id":"Cz-8MqLD36kA","outputId":"29648e2c-709a-412a-ea61-f597ac0e5aaf","execution":{"iopub.status.busy":"2022-07-06T17:47:40.886318Z","iopub.execute_input":"2022-07-06T17:47:40.886717Z","iopub.status.idle":"2022-07-06T17:47:40.895735Z","shell.execute_reply.started":"2022-07-06T17:47:40.886686Z","shell.execute_reply":"2022-07-06T17:47:40.895034Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df1 = train_df.drop(columns=[\"PassengerId\", \"Cabin\", \"Name\"], axis=1)","metadata":{"id":"lrdpALcfm0Ti","execution":{"iopub.status.busy":"2022-07-06T17:47:59.161354Z","iopub.execute_input":"2022-07-06T17:47:59.161780Z","iopub.status.idle":"2022-07-06T17:47:59.168992Z","shell.execute_reply.started":"2022-07-06T17:47:59.161748Z","shell.execute_reply":"2022-07-06T17:47:59.168246Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_df1 = test_df.drop(columns=[\"PassengerId\", \"Cabin\", \"Name\"], axis=1)","metadata":{"id":"ssz-Iqp15hfz","execution":{"iopub.status.busy":"2022-07-06T17:48:02.251099Z","iopub.execute_input":"2022-07-06T17:48:02.252121Z","iopub.status.idle":"2022-07-06T17:48:02.257332Z","shell.execute_reply.started":"2022-07-06T17:48:02.252071Z","shell.execute_reply":"2022-07-06T17:48:02.256625Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sns.countplot(\n    x = \"Embarked\",\n    hue = \"Survived\",\n    data = train_df1\n)","metadata":{"id":"4tx81852qKW-","outputId":"03fe92aa-cc7f-4b32-b5dc-bf0cce37370d","execution":{"iopub.status.busy":"2022-07-06T17:48:22.293633Z","iopub.execute_input":"2022-07-06T17:48:22.294010Z","iopub.status.idle":"2022-07-06T17:48:22.499497Z","shell.execute_reply.started":"2022-07-06T17:48:22.293980Z","shell.execute_reply":"2022-07-06T17:48:22.498805Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df1.info()","metadata":{"id":"_58iRZrPqpGv","outputId":"ee152907-4400-45e8-fef0-33085fb5db68","execution":{"iopub.status.busy":"2022-07-06T17:48:30.351143Z","iopub.execute_input":"2022-07-06T17:48:30.351543Z","iopub.status.idle":"2022-07-06T17:48:30.366458Z","shell.execute_reply.started":"2022-07-06T17:48:30.351513Z","shell.execute_reply":"2022-07-06T17:48:30.365518Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_df1.info()","metadata":{"id":"r7MC7wrc5qA6","outputId":"6d55ea02-a478-4c96-e4fe-4d5b00b8b471","execution":{"iopub.status.busy":"2022-07-06T17:48:42.166487Z","iopub.execute_input":"2022-07-06T17:48:42.166931Z","iopub.status.idle":"2022-07-06T17:48:42.181203Z","shell.execute_reply.started":"2022-07-06T17:48:42.166901Z","shell.execute_reply":"2022-07-06T17:48:42.180165Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df1[\"Survived\"].value_counts()","metadata":{"id":"WhJHC3WLrFeX","outputId":"b439da9a-a37b-4882-f377-f5711e036208","execution":{"iopub.status.busy":"2022-07-06T17:48:53.457328Z","iopub.execute_input":"2022-07-06T17:48:53.458176Z","iopub.status.idle":"2022-07-06T17:48:53.466333Z","shell.execute_reply.started":"2022-07-06T17:48:53.458112Z","shell.execute_reply":"2022-07-06T17:48:53.465290Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df1[\"Ticket\"].value_counts()","metadata":{"id":"sB9K6nGQsI9s","outputId":"c82fed99-c9dc-4050-9a86-4db28b980c8f","execution":{"iopub.status.busy":"2022-07-06T17:49:18.151764Z","iopub.execute_input":"2022-07-06T17:49:18.152162Z","iopub.status.idle":"2022-07-06T17:49:18.162599Z","shell.execute_reply.started":"2022-07-06T17:49:18.152131Z","shell.execute_reply":"2022-07-06T17:49:18.161617Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_df1.drop(columns=[\"Ticket\"], axis=1, inplace=True)","metadata":{"id":"CELbaNcfsUa2","execution":{"iopub.status.busy":"2022-07-06T17:49:26.315766Z","iopub.execute_input":"2022-07-06T17:49:26.316155Z","iopub.status.idle":"2022-07-06T17:49:26.322466Z","shell.execute_reply.started":"2022-07-06T17:49:26.316125Z","shell.execute_reply":"2022-07-06T17:49:26.321673Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_df1.drop(columns=[\"Ticket\"], axis=1, inplace=True)","metadata":{"id":"Az7RPYQ-503E","execution":{"iopub.status.busy":"2022-07-06T17:49:31.765972Z","iopub.execute_input":"2022-07-06T17:49:31.766713Z","iopub.status.idle":"2022-07-06T17:49:31.899728Z","shell.execute_reply.started":"2022-07-06T17:49:31.766675Z","shell.execute_reply":"2022-07-06T17:49:31.898230Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_df1.info()","metadata":{"execution":{"iopub.status.busy":"2022-07-06T17:50:14.601309Z","iopub.execute_input":"2022-07-06T17:50:14.603562Z","iopub.status.idle":"2022-07-06T17:50:14.616489Z","shell.execute_reply.started":"2022-07-06T17:50:14.603516Z","shell.execute_reply":"2022-07-06T17:50:14.615523Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sns.histplot(\n    x = \"SibSp\",\n    data = train_df1\n)","metadata":{"id":"Oe63S9RSszEB","outputId":"50fee695-0e2f-4a9d-8ed2-775f0057c548","execution":{"iopub.status.busy":"2022-07-06T17:50:32.646030Z","iopub.execute_input":"2022-07-06T17:50:32.646808Z","iopub.status.idle":"2022-07-06T17:50:32.920874Z","shell.execute_reply.started":"2022-07-06T17:50:32.646765Z","shell.execute_reply":"2022-07-06T17:50:32.920117Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sns.histplot(\n    x = \"Parch\",\n    data = train_df1\n)","metadata":{"id":"eL1usDzKsy6p","outputId":"4011a2b3-6fec-47f3-9713-d310c77fe917","execution":{"iopub.status.busy":"2022-07-06T17:50:39.521659Z","iopub.execute_input":"2022-07-06T17:50:39.522139Z","iopub.status.idle":"2022-07-06T17:50:39.742903Z","shell.execute_reply.started":"2022-07-06T17:50:39.522100Z","shell.execute_reply":"2022-07-06T17:50:39.741700Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"sns.boxplot(\n    x = \"Fare\",\n    data = train_df1\n)","metadata":{"id":"0yV3AfCwsykQ","outputId":"c8586e6c-7be5-481c-8e98-debe834a9baa","execution":{"iopub.status.busy":"2022-07-06T17:50:47.357798Z","iopub.execute_input":"2022-07-06T17:50:47.358632Z","iopub.status.idle":"2022-07-06T17:50:47.513946Z","shell.execute_reply.started":"2022-07-06T17:50:47.358588Z","shell.execute_reply":"2022-07-06T17:50:47.512615Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Splitting dataset into features and target","metadata":{"id":"qyko-cRHrAYP"}},{"cell_type":"code","source":"X = train_df1.drop(columns=[\"Survived\"], axis=1)\nX.shape","metadata":{"id":"mz0VyHdFqryD","outputId":"e8ba2297-43a4-4acb-b3e9-609b2c10b532","execution":{"iopub.status.busy":"2022-07-06T17:50:55.966875Z","iopub.execute_input":"2022-07-06T17:50:55.967367Z","iopub.status.idle":"2022-07-06T17:50:55.977747Z","shell.execute_reply.started":"2022-07-06T17:50:55.967333Z","shell.execute_reply":"2022-07-06T17:50:55.975616Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y = train_df1.Survived\ny.shape","metadata":{"id":"jKIhOv9yrZ8Q","outputId":"377cce8d-59d1-44fd-b111-e32bbed41bc9","execution":{"iopub.status.busy":"2022-07-06T17:51:00.760709Z","iopub.execute_input":"2022-07-06T17:51:00.761450Z","iopub.status.idle":"2022-07-06T17:51:00.768075Z","shell.execute_reply.started":"2022-07-06T17:51:00.761389Z","shell.execute_reply":"2022-07-06T17:51:00.767191Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Feature Preprocessing\nWe are going to one hot encode categorical values.\nFare has some outliers, so we will use a Robust Scaler to suppress their effect","metadata":{"id":"fNe9CtEnrmOf"}},{"cell_type":"markdown","source":"## Dummy Encoding of categorical features:\n\n\n*   Sex\n*   Embarked\n\n","metadata":{"id":"O4rNefb6rrC0"}},{"cell_type":"code","source":"cat_list = [\"Sex\", \"Embarked\"]\n\nX_encoded = pd.get_dummies(columns=cat_list, data=X, drop_first=True)\nX_encoded.head()","metadata":{"id":"xWvNILk0rfSA","outputId":"8663f57b-d4ec-415a-dcc6-790ccad27ee0","execution":{"iopub.status.busy":"2022-07-06T17:51:33.096041Z","iopub.execute_input":"2022-07-06T17:51:33.096411Z","iopub.status.idle":"2022-07-06T17:51:33.118986Z","shell.execute_reply.started":"2022-07-06T17:51:33.096381Z","shell.execute_reply":"2022-07-06T17:51:33.118132Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_encoded = pd.get_dummies(columns=cat_list, data=test_df1, drop_first=True)","metadata":{"id":"0K00aHY86AEM","execution":{"iopub.status.busy":"2022-07-06T17:51:47.988113Z","iopub.execute_input":"2022-07-06T17:51:47.988509Z","iopub.status.idle":"2022-07-06T17:51:48.232945Z","shell.execute_reply.started":"2022-07-06T17:51:47.988472Z","shell.execute_reply":"2022-07-06T17:51:48.231876Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from sklearn.preprocessing import RobustScaler\n\nrob_scaler = RobustScaler()\nX_scaled = rob_scaler.fit_transform(X_encoded)\n","metadata":{"id":"H5dPgq3YuWBB","outputId":"e9f0eef0-a271-43c2-eac5-1d127404e3fe","execution":{"iopub.status.busy":"2022-07-06T17:51:56.935564Z","iopub.execute_input":"2022-07-06T17:51:56.936628Z","iopub.status.idle":"2022-07-06T17:51:57.012250Z","shell.execute_reply.started":"2022-07-06T17:51:56.936581Z","shell.execute_reply":"2022-07-06T17:51:57.011447Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_scaled = rob_scaler.fit_transform(test_encoded)","metadata":{"id":"tGb837Xv6KW6","execution":{"iopub.status.busy":"2022-07-06T17:52:09.256159Z","iopub.execute_input":"2022-07-06T17:52:09.257156Z","iopub.status.idle":"2022-07-06T17:52:09.268893Z","shell.execute_reply.started":"2022-07-06T17:52:09.257085Z","shell.execute_reply":"2022-07-06T17:52:09.267758Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Imputing missing values using KNN Imputer","metadata":{}},{"cell_type":"code","source":"from sklearn.impute import KNNImputer\nimputer = KNNImputer(n_neighbors=5)\nX_imputed = imputer.fit_transform(X_scaled)","metadata":{"execution":{"iopub.status.busy":"2022-07-06T17:55:59.185904Z","iopub.execute_input":"2022-07-06T17:55:59.186278Z","iopub.status.idle":"2022-07-06T17:55:59.209482Z","shell.execute_reply.started":"2022-07-06T17:55:59.186248Z","shell.execute_reply":"2022-07-06T17:55:59.208373Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_imputed = imputer.fit_transform(test_scaled)","metadata":{"execution":{"iopub.status.busy":"2022-07-06T17:56:16.845501Z","iopub.execute_input":"2022-07-06T17:56:16.846275Z","iopub.status.idle":"2022-07-06T17:56:16.860281Z","shell.execute_reply.started":"2022-07-06T17:56:16.846238Z","shell.execute_reply":"2022-07-06T17:56:16.858840Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"y = y.to_numpy()","metadata":{"id":"e0LLWoU5w60C","execution":{"iopub.status.busy":"2022-07-06T17:56:20.600705Z","iopub.execute_input":"2022-07-06T17:56:20.601092Z","iopub.status.idle":"2022-07-06T17:56:20.605706Z","shell.execute_reply.started":"2022-07-06T17:56:20.601061Z","shell.execute_reply":"2022-07-06T17:56:20.604611Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"# Model Training","metadata":{"id":"4NWUxNVAvUbr"}},{"cell_type":"code","source":"from sklearn.model_selection import train_test_split, KFold\nfrom sklearn.metrics import accuracy_score\nimport xgboost as xgb\n\nX_train, X_test, y_train, y_test = train_test_split(X_imputed, y)\n\nkf = KFold(n_splits=10)\n\nacc_list = []\n\nxgb_clf = xgb.XGBClassifier()\n\n#training using KFold cross validation\nfor train_idx, test_idx in kf.split(X_train):\n  xgb_clf.fit(X_train[train_idx], y_train[train_idx])\n\n  #predict\n  y_preds = xgb_clf.predict(X_train[test_idx])\n\n  #evaluate\n  acc = accuracy_score(y_train[test_idx], y_preds)\n  acc_list.append(acc)\n\nprint(acc_list)\n","metadata":{"id":"TLrkO0nRvFdH","outputId":"5ed8c4c9-dae6-43b1-9303-e6269fa5abad","execution":{"iopub.status.busy":"2022-07-06T17:56:50.976130Z","iopub.execute_input":"2022-07-06T17:56:50.976521Z","iopub.status.idle":"2022-07-06T17:56:55.708296Z","shell.execute_reply.started":"2022-07-06T17:56:50.976485Z","shell.execute_reply":"2022-07-06T17:56:55.705965Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"#Hyperparameter tuning\nWe will use GridSearchCV to find the best hyperparameters for the model","metadata":{"id":"ZyL5MNb30dTM"}},{"cell_type":"code","source":"from sklearn.model_selection import GridSearchCV\n\nparams = [{\n    \"max_depth\" : [3, 5, 7],\n    \"learning_rate\" : [0.01, 0.05, 0.1],\n    \"n_estimators\" : [100, 300, 500]\n}]\n\ngs_xgb = GridSearchCV(\n    estimator = xgb_clf,\n    param_grid = params,\n    cv = 3,\n    verbose = 2,\n    scoring = \"accuracy\"\n)\n\ngs_xgb.fit(X_train, y_train)","metadata":{"id":"iI_ZhOKY0gkn","outputId":"042c9f8b-1233-4e45-d0d2-02ba03b4036b","execution":{"iopub.status.busy":"2022-07-06T17:57:07.286256Z","iopub.execute_input":"2022-07-06T17:57:07.286646Z","iopub.status.idle":"2022-07-06T17:58:46.151264Z","shell.execute_reply.started":"2022-07-06T17:57:07.286611Z","shell.execute_reply":"2022-07-06T17:58:46.150325Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"gs_xgb.best_params_","metadata":{"id":"l05pWFn72xzD","outputId":"60e5b445-56bd-4e60-f325-63f543a709b6","execution":{"iopub.status.busy":"2022-07-06T17:59:32.425577Z","iopub.execute_input":"2022-07-06T17:59:32.426000Z","iopub.status.idle":"2022-07-06T17:59:32.431983Z","shell.execute_reply.started":"2022-07-06T17:59:32.425965Z","shell.execute_reply":"2022-07-06T17:59:32.431130Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"gs_xgb.best_score_","metadata":{"id":"-fJev_642-cB","outputId":"f0fbfe94-1dfb-43e9-9f4b-7cc151f493dd","execution":{"iopub.status.busy":"2022-07-06T17:59:37.405987Z","iopub.execute_input":"2022-07-06T17:59:37.406401Z","iopub.status.idle":"2022-07-06T17:59:37.412543Z","shell.execute_reply.started":"2022-07-06T17:59:37.406367Z","shell.execute_reply":"2022-07-06T17:59:37.411644Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"best_xgb = gs_xgb.best_estimator_","metadata":{"id":"ljgnyhoi3Pbo","execution":{"iopub.status.busy":"2022-07-06T17:59:57.532024Z","iopub.execute_input":"2022-07-06T17:59:57.532456Z","iopub.status.idle":"2022-07-06T17:59:57.536751Z","shell.execute_reply.started":"2022-07-06T17:59:57.532409Z","shell.execute_reply":"2022-07-06T17:59:57.536005Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"test_preds = best_xgb.predict(test_imputed)","metadata":{"id":"r8siVJLc3b9B","execution":{"iopub.status.busy":"2022-07-06T18:00:09.076587Z","iopub.execute_input":"2022-07-06T18:00:09.076968Z","iopub.status.idle":"2022-07-06T18:00:09.089204Z","shell.execute_reply.started":"2022-07-06T18:00:09.076939Z","shell.execute_reply":"2022-07-06T18:00:09.088448Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Save predictions in format used for competition scoring\noutput = pd.DataFrame({'PassengerId': test_df.PassengerId,\n                       'Survived': test_preds.reshape(1,-1).flatten().tolist()})\noutput.to_csv('submission.csv', index=False)","metadata":{"id":"7kHvGoL86b7y","execution":{"iopub.status.busy":"2022-07-06T18:00:17.206984Z","iopub.execute_input":"2022-07-06T18:00:17.207415Z","iopub.status.idle":"2022-07-06T18:00:17.217256Z","shell.execute_reply.started":"2022-07-06T18:00:17.207378Z","shell.execute_reply":"2022-07-06T18:00:17.216538Z"},"trusted":true},"execution_count":null,"outputs":[]}]}