{"library":"miceforest","title":"miceforest","description":"Fast multiple imputation using Random Forests and LightGBM, implementing Multiple Imputation by Chained Equations (MICE). Current version: 6.0.5, release cadence: irregular major versions with breaking changes.","language":"python","status":"active","last_verified":"Sat May 09","install":{"commands":["pip install miceforest"],"cli":null},"imports":["from miceforest import ImputationKernel","from miceforest import ImputedData"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import miceforest as mf\nfrom sklearn.datasets import load_iris\nimport pandas as pd\nimport numpy as np\niris = load_iris()\ndf = pd.DataFrame(iris.data, columns=iris.feature_names)\ndf.iloc[:20, 0] = np.nan\nkernel = mf.ImputationKernel(dataset=df, datasets=1, save_all_iterations=True, random_state=1)\nkernel.mice(1)\ncompleted = kernel.complete_data()\nprint(completed.isnull().sum())","lang":"python","description":"Basic imputation using the main class.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}