{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"ds-1000","formal_name":"DS-1000","introduction":"DS-1000 builds 1,000 data-science problems from real StackOverflow questions across seven libraries including NumPy, Pandas and Matplotlib. The problems are perturbed so that recalling the original answer does not solve them.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://ds1000-code-gen.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"4269f2f6-0241-593d-8a90-4c0c2c8b404e","task_key":"default--test--861","task_revision_id":"1","upstream_id":"861","short_description":"I performed feature selection using ExtraTreesClassifier and SelectFromModel in…","config":"default","split":"test","body":"{\"library\":\"Sklearn\",\"prompt\":\"Problem:\\n\\nI performed feature selection using ExtraTreesClassifier and SelectFromModel in data set that loaded as DataFrame, however i want to save these selected feature as a list(python type list) while maintaining columns name as well. So is there away to get selected columns names from SelectFromModel method? note that output is numpy array return important features whole columns not columns header. Please help me with the code below.\\n\\nimport pandas as pd\\nfrom sklearn.ensemble import ExtraTreesClassifier\\nfrom sklearn.feature_selection import SelectFromModel\\nimport numpy as np\\n\\n\\ndf = pd.read_csv('los_10_one_encoder.csv')\\ny = df['LOS'] # target\\nX= df.drop('LOS',axis=1) # drop LOS column\\nclf = ExtraTreesClassifier(random_state=42)\\nclf = clf.fit(X, y)\\nprint(clf.feature_importances_)\\n\\nmodel = SelectFromModel(clf, prefit=True)\\nX_new = model.transform(X)\\n\\n\\nA:\\n\\n<code>\\nimport pandas as pd\\nfrom sklearn.ensemble import ExtraTreesClassifier\\nfrom sklearn.feature_selection import SelectFromModel\\nimport numpy as np\\n\\nX, y = load_data()\\nclf = ExtraTreesClassifier(random_state=42)\\nclf = clf.fit(X, y)\\n</code>\\ncolumn_names = ... # put solution in this variable\\nBEGIN SOLUTION\\n<code>\\n\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://ds1000-code-gen.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}