{"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":"94eeab1a-63f5-5fcd-baee-e480aab3aba9","task_key":"default--test--921","task_revision_id":"1","upstream_id":"921","short_description":"I have a data which include dates in sorted order.","config":"default","split":"test","body":"{\"library\":\"Sklearn\",\"prompt\":\"Problem:\\n\\nI have a data which include dates in sorted order.\\n\\nI would like to split the given data to train and test set. However, I must to split the data in a way that the test have to be newer than the train set.\\n\\nPlease look at the given example:\\n\\nLet's assume that we have data by dates:\\n\\n1, 2, 3, ..., n.\\n\\nThe numbers from 1 to n represents the days.\\n\\nI would like to split it to 20% from the data to be train set and 80% of the data to be test set.\\n\\nGood results:\\n\\n1) train set = 1, 2, 3, ..., 20\\n\\n   test set = 21, ..., 100\\n\\n\\n2) train set = 101, 102, ... 120\\n\\n    test set = 121, ... 200\\nMy code:\\n\\ntrain_size = 0.2\\ntrain_dataframe, test_dataframe = cross_validation.train_test_split(features_dataframe, train_size=train_size)\\n\\ntrain_dataframe = train_dataframe.sort([\\\"date\\\"])\\ntest_dataframe = test_dataframe.sort([\\\"date\\\"])\\nDoes not work for me!\\n\\nAny suggestions?\\n\\nA:\\n\\n<code>\\nimport numpy as np\\nimport pandas as pd\\nfrom sklearn.model_selection import train_test_split\\nfeatures_dataframe = load_data()\\n</code>\\ntrain_dataframe, test_dataframe = ... # put solution in these variables\\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":[]}