{"published":"2018-07-04 15:46:32","width":"100%","author_url":"https://blog.hatena.ne.jp/kidnohr/","blog_url":"https://kidnohr.hatenadiary.com/","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fkidnohr.hatenadiary.com%2Fentry%2F2018%2F07%2F04%2F154632\" title=\"python\u306escipy\u3067sparse\u306a\u884c\u5217\u306e\u5909\u63db - \u65e5\u306b\u65e5\u306b\u5206\u304b\u3089\u3093\u3053\u3068\u304c\u5897\u3048\u3066\u3044\u304f\u2026\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","description":"sparse\u306a\u884c\u5217\u306b\u3064\u3044\u3066\u306e\u5b9f\u88c5 import numpy as np from scipy.sparse import coo_matrix ) a = np.arange(30).reshape(10,3) print(a) [[ 0 1 2] [ 3 4 5] [ 6 7 8] [ 9 10 11] [12 13 14] [15 16 17] [18 19 20] [21 22 23] [24 25 26] [27 28 29]] b, c, d = zip(*a) print(b, c, d) (0, 3, 6, 9, 12, 15, 18, 21, 24, 27) (1, 4, 7,\u2026","provider_name":"Hatena Blog","title":"python\u306escipy\u3067sparse\u306a\u884c\u5217\u306e\u5909\u63db","version":"1.0","provider_url":"https://hatena.blog","image_url":null,"categories":["Python3"],"height":"190","url":"https://kidnohr.hatenadiary.com/entry/2018/07/04/154632","type":"rich","blog_title":"\u65e5\u306b\u65e5\u306b\u5206\u304b\u3089\u3093\u3053\u3068\u304c\u5897\u3048\u3066\u3044\u304f\u2026","author_name":"kidnohr"}