{"id":3409,"date":"2021-07-23T12:34:23","date_gmt":"2021-07-23T12:34:23","guid":{"rendered":"https:\/\/www.bearloga.space\/?page_id=3409"},"modified":"2021-07-23T12:34:24","modified_gmt":"2021-07-23T12:34:24","slug":"python-pandas-razrezhennye-dannye","status":"publish","type":"page","link":"https:\/\/www.bearloga.space\/en\/python-pandas-razrezhennye-dannye\/","title":{"rendered":"Python Pandas \u2014 \u0440\u0430\u0437\u0440\u0435\u0436\u0435\u043d\u043d\u044b\u0435 \u0434\u0430\u043d\u043d\u044b\u0435"},"content":{"rendered":"\n<pre class=\"wp-block-code\"><code>\r\n\u0420\u0430\u0437\u0440\u0435\u0436\u0435\u043d\u043d\u044b\u0435 \u043e\u0431\u044a\u0435\u043a\u0442\u044b \u00ab\u0441\u0436\u0438\u043c\u0430\u044e\u0442\u0441\u044f\u00bb, \u043a\u043e\u0433\u0434\u0430 \u043b\u044e\u0431\u044b\u0435 \u0434\u0430\u043d\u043d\u044b\u0435, \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0438\u0435 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u043c\u0443 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044e (NaN \/ \u043e\u0442\u0441\u0443\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435, \u0445\u043e\u0442\u044f \u043b\u044e\u0431\u043e\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043c\u043e\u0436\u0435\u0442 \u0431\u044b\u0442\u044c \u0432\u044b\u0431\u0440\u0430\u043d\u043e), \u043e\u043f\u0443\u0449\u0435\u043d\u044b. \u0421\u043f\u0435\u0446\u0438\u0430\u043b\u044c\u043d\u044b\u0439 \u043e\u0431\u044a\u0435\u043a\u0442 SparseIndex \u043e\u0442\u0441\u043b\u0435\u0436\u0438\u0432\u0430\u0435\u0442, \u0433\u0434\u0435 \u0434\u0430\u043d\u043d\u044b\u0435 \u0431\u044b\u043b\u0438 \u00ab\u043e\u0447\u0438\u0449\u0435\u043d\u044b\u00bb. \u042d\u0442\u043e \u0431\u0443\u0434\u0435\u0442 \u0438\u043c\u0435\u0442\u044c \u0433\u043e\u0440\u0430\u0437\u0434\u043e \u0431\u043e\u043b\u044c\u0448\u0435 \u0441\u043c\u044b\u0441\u043b\u0430 \u0432 \u043f\u0440\u0438\u043c\u0435\u0440\u0435. \u0412\u0441\u0435 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u044b\u0435 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u044b \u0434\u0430\u043d\u043d\u044b\u0445 Pandas \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u044e\u0442 \u043c\u0435\u0442\u043e\u0434 to_sparse \u2014\r\r\n Live Demo\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\nts = pd.Series(np.random.randn(10))\r\nts&#91;2:-2] = np.nan\r\nsts = ts.to_sparse()\r\nprint sts\r\n\u0415\u0433\u043e \u0432\u044b\u0432\u043e\u0434 \u0432\u044b\u0433\u043b\u044f\u0434\u0438\u0442 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c \u2014\r\n\r\n0   -0.810497\r\n1   -1.419954\r\n2         NaN\r\n3         NaN\r\n4         NaN\r\n5         NaN\r\n6         NaN\r\n7         NaN\r\n8    0.439240\r\n9   -1.095910\r\ndtype: float64\r\nBlockIndex\r\nBlock locations: array(&#91;0, 8], dtype=int32)\r\nBlock lengths: array(&#91;2, 2], dtype=int32)\r\n\u0420\u0430\u0437\u0440\u0435\u0436\u0435\u043d\u043d\u044b\u0435 \u043e\u0431\u044a\u0435\u043a\u0442\u044b \u0441\u0443\u0449\u0435\u0441\u0442\u0432\u0443\u044e\u0442 \u043f\u043e \u0441\u043e\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f\u043c \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u043e\u0441\u0442\u0438 \u043f\u0430\u043c\u044f\u0442\u0438.\r\n\r\n\u0414\u0430\u0432\u0430\u0439\u0442\u0435 \u0442\u0435\u043f\u0435\u0440\u044c \u043f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0447\u0442\u043e \u0443 \u0432\u0430\u0441 \u0431\u044b\u043b \u0431\u043e\u043b\u044c\u0448\u043e\u0439 DataFrame NA, \u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u0435 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434:\r\n\r\n\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ndf = pd.DataFrame(np.random.randn(10000, 4))\r\ndf.ix&#91;:9998] = np.nan\r\nsdf = df.to_sparse()\r\n\r\nprint sdf.density\r\n\u0415\u0433\u043e \u0432\u044b\u0432\u043e\u0434 \u0432\u044b\u0433\u043b\u044f\u0434\u0438\u0442 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c \u2014\r\n\r\n\r\n0.0001\r\n\u041b\u044e\u0431\u043e\u0439 \u0440\u0430\u0437\u0440\u0435\u0436\u0435\u043d\u043d\u044b\u0439 \u043e\u0431\u044a\u0435\u043a\u0442 \u043c\u043e\u0436\u043d\u043e \u043f\u0440\u0435\u043e\u0431\u0440\u0430\u0437\u043e\u0432\u0430\u0442\u044c \u043e\u0431\u0440\u0430\u0442\u043d\u043e \u0432 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u0443\u044e \u043f\u043b\u043e\u0442\u043d\u0443\u044e \u0444\u043e\u0440\u043c\u0443, \u0432\u044b\u0437\u0432\u0430\u0432 to_dense \u2014\r\n\r\n\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\nts = pd.Series(np.random.randn(10))\r\nts&#91;2:-2] = np.nan\r\nsts = ts.to_sparse()\r\nprint sts.to_dense()\r\n\u0415\u0433\u043e \u0432\u044b\u0432\u043e\u0434 \u0432\u044b\u0433\u043b\u044f\u0434\u0438\u0442 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c \u2014\r\n\r\n0   -0.810497\r\n1   -1.419954\r\n2         NaN\r\n3         NaN\r\n4         NaN\r\n5         NaN\r\n6         NaN\r\n7         NaN\r\n8    0.439240\r\n9   -1.095910\r\ndtype: float64\r\n\u0420\u0430\u0437\u0440\u0435\u0436\u0435\u043d\u043d\u044b\u0435 Dtypes\r\n\u0420\u0430\u0437\u0440\u0435\u0436\u0435\u043d\u043d\u044b\u0435 \u0434\u0430\u043d\u043d\u044b\u0435 \u0434\u043e\u043b\u0436\u043d\u044b \u0438\u043c\u0435\u0442\u044c \u0442\u043e\u0442 \u0436\u0435 \u0442\u0438\u043f d, \u0447\u0442\u043e \u0438 \u0438\u0445 \u043f\u043b\u043e\u0442\u043d\u043e\u0435 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0435. \u0412 \u043d\u0430\u0441\u0442\u043e\u044f\u0449\u0435\u0435 \u0432\u0440\u0435\u043c\u044f \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u044e\u0442\u0441\u044f float64, int64 \u0438 booldtypes . \u0412 \u0437\u0430\u0432\u0438\u0441\u0438\u043c\u043e\u0441\u0442\u0438 \u043e\u0442 \u0438\u0441\u0445\u043e\u0434\u043d\u043e\u0433\u043e dtype, \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 fill_value \u043f\u043e \u0443\u043c\u043e\u043b\u0447\u0430\u043d\u0438\u044e \u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u2014\r\n\r\nfloat64 \u2014 np.nan\r\n\r\nint64 \u2014 0\r\n\r\nbool \u2014 False\r\n\r\nfloat64 \u2014 np.nan\r\n\r\nint64 \u2014 0\r\n\r\nbool \u2014 False\r\n\r\n\u0414\u0430\u0432\u0430\u0439\u0442\u0435 \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u043c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434, \u0447\u0442\u043e\u0431\u044b \u043f\u043e\u043d\u044f\u0442\u044c \u0442\u043e \u0436\u0435 \u0441\u0430\u043c\u043e\u0435 \u2014\r\n\r\n\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ns = pd.Series(&#91;1, np.nan, np.nan])\r\nprint s\r\n\r\ns.to_sparse()\r\nprint s<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"categories":[109],"tags":[],"class_list":["post-3409","page","type-page","status-publish","hentry","category-python-pandas"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/pages\/3409","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/comments?post=3409"}],"version-history":[{"count":0,"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/pages\/3409\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/media?parent=3409"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/categories?post=3409"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bearloga.space\/en\/wp-json\/wp\/v2\/tags?post=3409"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}