{"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":"0aa40513-c9b0-540c-9ad9-726e5445dfe6","task_key":"default--test--792","task_revision_id":"1","upstream_id":"792","short_description":"I have problems using scipy.sparse.csr_matrix:","config":"default","split":"test","body":"{\"library\":\"Scipy\",\"prompt\":\"Problem:\\nI have problems using scipy.sparse.csr_matrix:\\nfor instance:\\na = csr_matrix([[1,2,3],[4,5,6]])\\nb = csr_matrix([[7,8,9],[10,11,12]])\\nhow to merge them into\\n[[1,2,3],[4,5,6],[7,8,9],[10,11,12]]\\nI know a way is to transfer them into numpy array first:\\ncsr_matrix(numpy.vstack((a.toarray(),b.toarray())))\\nbut it won't work when the matrix is huge and sparse, because the memory would run out.\\nso are there any way to merge them together in csr_matrix?\\nany answers are appreciated!\\nA:\\n<code>\\nfrom scipy import sparse\\nsa = sparse.random(10, 10, density = 0.01, format = 'csr')\\nsb = sparse.random(10, 10, density = 0.01, format = 'csr')\\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":[]}