{"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":"2b19dba0-c9c3-58a0-9d88-28593d01b188","task_key":"default--test--486","task_revision_id":"1","upstream_id":"486","short_description":"Right now, I have my data in a 2D numpy array `a`. If I was to use MinMaxScaler…","config":"default","split":"test","body":"{\"library\":\"Numpy\",\"prompt\":\"Problem:\\n\\nRight now, I have my data in a 2D numpy array `a`. If I was to use MinMaxScaler fit_transform on the array, it will normalize it column by column, whereas I wish to normalize the entire np array all together. Is there anyway to do that?\\nA:\\n<code>\\nimport numpy as np\\nfrom sklearn.preprocessing import MinMaxScaler\\na = np.array([[-1, 2], [-0.5, 6]])\\n</code>\\nresult = ... # 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":[]}