{"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":"267f102e-541e-5003-8015-205ce4624291","task_key":"default--test--746","task_revision_id":"1","upstream_id":"746","short_description":"I have a sparse 988x1 vector (stored in col, a column in a csr_matrix) created…","config":"default","split":"test","body":"{\"library\":\"Scipy\",\"prompt\":\"Problem:\\nI have a sparse 988x1 vector (stored in col, a column in a csr_matrix) created through scipy.sparse. Is there a way to gets its max and min value without having to convert the sparse matrix to a dense one?\\nnumpy.max seems to only work for dense vectors.\\n\\nA:\\n<code>\\nimport numpy as np\\nfrom scipy.sparse import csr_matrix\\n\\nnp.random.seed(10)\\narr = np.random.randint(4,size=(988,988))\\nsA = csr_matrix(arr)\\ncol = sA.getcol(0)\\n</code>\\nMax, Min = ... # 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":[]}