{"id":3389,"date":"2021-07-23T12:12:09","date_gmt":"2021-07-23T12:12:09","guid":{"rendered":"https:\/\/www.bearloga.space\/?page_id=3389"},"modified":"2021-07-23T12:12:09","modified_gmt":"2021-07-23T12:12:09","slug":"piton-pandy-agregaczii","status":"publish","type":"page","link":"https:\/\/www.bearloga.space\/uk\/piton-pandy-agregaczii\/","title":{"rendered":"\u041f\u0438\u0442\u043e\u043d \u041f\u0430\u043d\u0434\u044b \u2014 \u0410\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u0438"},"content":{"rendered":"\n<pre class=\"wp-block-code\"><code>\r\u041f\u043e\u0441\u043b\u0435 \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u044f \u043e\u0431\u044a\u0435\u043a\u0442\u043e\u0432 \u043f\u0440\u043e\u043a\u0440\u0443\u0442\u043a\u0438, \u0440\u0430\u0437\u0432\u0435\u0440\u0442\u044b\u0432\u0430\u043d\u0438\u044f \u0438 ewm \u0434\u043e\u0441\u0442\u0443\u043f\u043d\u044b \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043c\u0435\u0442\u043e\u0434\u043e\u0432 \u0434\u043b\u044f \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0434\u0430\u043d\u043d\u044b\u0445.\r\n\r\n\u041f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435 \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u0439 \u0432 DataFrame\r\n\u0414\u0430\u0432\u0430\u0439\u0442\u0435 \u0441\u043e\u0437\u0434\u0430\u0434\u0438\u043c DataFrame \u0438 \u043f\u0440\u0438\u043c\u0435\u043d\u0438\u043c \u043a \u043d\u0435\u043c\u0443 \u0430\u0433\u0440\u0435\u0433\u0430\u0442\u044b.\r\n\r\n Live Demo\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ndf = pd.DataFrame(np.random.randn(10, 4),\r\n   index = pd.date_range('1\/1\/2000', periods=10),\r\n   columns = &#91;'A', 'B', 'C', 'D'])\r\n\r\nprint df\r\nr = df.rolling(window=3,min_periods=1)\r\nprint r\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                    A           B           C           D\r\n2000-01-01   1.088512   -0.650942   -2.547450   -0.566858\r\n2000-01-02   0.790670   -0.387854   -0.668132    0.267283\r\n2000-01-03  -0.575523   -0.965025    0.060427   -2.179780\r\n2000-01-04   1.669653    1.211759   -0.254695    1.429166\r\n2000-01-05   0.100568   -0.236184    0.491646   -0.466081\r\n2000-01-06   0.155172    0.992975   -1.205134    0.320958\r\n2000-01-07   0.309468   -0.724053   -1.412446    0.627919\r\n2000-01-08   0.099489   -1.028040    0.163206   -1.274331\r\n2000-01-09   1.639500   -0.068443    0.714008   -0.565969\r\n2000-01-10   0.326761    1.479841    0.664282   -1.361169\r\n\r\nRolling &#91;window=3,min_periods=1,center=False,axis=0]                \r\n\u041c\u044b \u043c\u043e\u0436\u0435\u043c \u0430\u0433\u0440\u0435\u0433\u0438\u0440\u043e\u0432\u0430\u0442\u044c, \u043f\u0435\u0440\u0435\u0434\u0430\u0432\u0430\u044f \u0444\u0443\u043d\u043a\u0446\u0438\u044e \u0432\u0441\u0435\u043c\u0443 DataFrame \u0438\u043b\u0438 \u0432\u044b\u0431\u0438\u0440\u0430\u044f \u0441\u0442\u043e\u043b\u0431\u0435\u0446 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u043e\u0433\u043e \u043c\u0435\u0442\u043e\u0434\u0430 get item .\r\n\r\n\u041f\u0440\u0438\u043c\u0435\u043d\u0438\u0442\u044c \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u044e \u043d\u0430 \u0432\u0435\u0441\u044c \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u043d\u044b\u0445\r\n Live Demo\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ndf = pd.DataFrame(np.random.randn(10, 4),\r\n   index = pd.date_range('1\/1\/2000', periods=10),\r\n   columns = &#91;'A', 'B', 'C', 'D'])\r\nprint df\r\nr = df.rolling(window=3,min_periods=1)\r\nprint r.aggregate(np.sum)\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\n\u0410\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0435 \u0442\u0435\u0441\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043d\u0430 Java\r\n                    A           B           C           D\r\n2000-01-01   1.088512   -0.650942   -2.547450   -0.566858\r\n2000-01-02   1.879182   -1.038796   -3.215581   -0.299575\r\n2000-01-03   1.303660   -2.003821   -3.155154   -2.479355\r\n2000-01-04   1.884801   -0.141119   -0.862400   -0.483331\r\n2000-01-05   1.194699    0.010551    0.297378   -1.216695\r\n2000-01-06   1.925393    1.968551   -0.968183    1.284044\r\n2000-01-07   0.565208    0.032738   -2.125934    0.482797\r\n2000-01-08   0.564129   -0.759118   -2.454374   -0.325454\r\n2000-01-09   2.048458   -1.820537   -0.535232   -1.212381\r\n2000-01-10   2.065750    0.383357    1.541496   -3.201469\r\n\r\n                    A           B           C           D\r\n2000-01-01   1.088512   -0.650942   -2.547450   -0.566858\r\n2000-01-02   1.879182   -1.038796   -3.215581   -0.299575\r\n2000-01-03   1.303660   -2.003821   -3.155154   -2.479355\r\n2000-01-04   1.884801   -0.141119   -0.862400   -0.483331\r\n2000-01-05   1.194699    0.010551    0.297378   -1.216695\r\n2000-01-06   1.925393    1.968551   -0.968183    1.284044\r\n2000-01-07   0.565208    0.032738   -2.125934    0.482797\r\n2000-01-08   0.564129   -0.759118   -2.454374   -0.325454\r\n2000-01-09   2.048458   -1.820537   -0.535232   -1.212381\r\n2000-01-10   2.065750    0.383357    1.541496   -3.201469\r\n\u041f\u0440\u0438\u043c\u0435\u043d\u0438\u0442\u044c \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u044e \u043a \u043e\u0434\u043d\u043e\u043c\u0443 \u0441\u0442\u043e\u043b\u0431\u0446\u0443 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u043e\u043d\u043d\u043e\u0433\u043e \u043a\u0430\u0434\u0440\u0430\r\n Live Demo\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ndf = pd.DataFrame(np.random.randn(10, 4),\r\n   index = pd.date_range('1\/1\/2000', periods=10),\r\n   columns = &#91;'A', 'B', 'C', 'D'])\r\nprint df\r\nr = df.rolling(window=3,min_periods=1)\r\nprint r&#91;'A'].aggregate(np.sum)\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                 A           B           C           D\r\n2000-01-01   1.088512   -0.650942   -2.547450   -0.566858\r\n2000-01-02   1.879182   -1.038796   -3.215581   -0.299575\r\n2000-01-03   1.303660   -2.003821   -3.155154   -2.479355\r\n2000-01-04   1.884801   -0.141119   -0.862400   -0.483331\r\n2000-01-05   1.194699    0.010551    0.297378   -1.216695\r\n2000-01-06   1.925393    1.968551   -0.968183    1.284044\r\n2000-01-07   0.565208    0.032738   -2.125934    0.482797\r\n2000-01-08   0.564129   -0.759118   -2.454374   -0.325454\r\n2000-01-09   2.048458   -1.820537   -0.535232   -1.212381\r\n2000-01-10   2.065750    0.383357    1.541496   -3.201469\r\n2000-01-01   1.088512\r\n2000-01-02   1.879182\r\n2000-01-03   1.303660\r\n2000-01-04   1.884801\r\n2000-01-05   1.194699\r\n2000-01-06   1.925393\r\n2000-01-07   0.565208\r\n2000-01-08   0.564129\r\n2000-01-09   2.048458\r\n2000-01-10   2.065750\r\nFreq: D, Name: A, dtype: float64\r\n\u041f\u0440\u0438\u043c\u0435\u043d\u0438\u0442\u044c \u0430\u0433\u0440\u0435\u0433\u0430\u0446\u0438\u044e \u043a \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c \u0432 DataFrame\r\n Live Demo\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ndf = pd.DataFrame(np.random.randn(10, 4),\r\n   index = pd.date_range('1\/1\/2000', periods=10),\r\n   columns = &#91;'A', 'B', 'C', 'D'])\r\nprint df\r\nr = df.rolling(window=3,min_periods=1)\r\nprint r&#91;&#91;'A','B']].aggregate(np.sum)\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                 A           B           C           D\r\n2000-01-01   1.088512   -0.650942   -2.547450   -0.566858\r\n2000-01-02   1.879182   -1.038796   -3.215581   -0.299575\r\n2000-01-03   1.303660   -2.003821   -3.155154   -2.479355\r\n2000-01-04   1.884801   -0.141119   -0.862400   -0.483331\r\n2000-01-05   1.194699    0.010551    0.297378   -1.216695\r\n2000-01-06   1.925393    1.968551   -0.968183    1.284044\r\n2000-01-07   0.565208    0.032738   -2.125934    0.482797\r\n2000-01-08   0.564129   -0.759118   -2.454374   -0.325454\r\n2000-01-09   2.048458   -1.820537   -0.535232   -1.212381\r\n2000-01-10   2.065750    0.383357    1.541496   -3.201469\r\n                    A           B\r\n2000-01-01   1.088512   -0.650942\r\n2000-01-02   1.879182   -1.038796\r\n2000-01-03   1.303660   -2.003821\r\n2000-01-04   1.884801   -0.141119\r\n2000-01-05   1.194699    0.010551\r\n2000-01-06   1.925393    1.968551\r\n2000-01-07   0.565208    0.032738\r\n2000-01-08   0.564129   -0.759118\r\n2000-01-09   2.048458   -1.820537\r\n2000-01-10   2.065750    0.383357\r\n\u041f\u0440\u0438\u043c\u0435\u043d\u0438\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043a \u043e\u0434\u043d\u043e\u043c\u0443 \u0441\u0442\u043e\u043b\u0431\u0446\u0443 DataFrame\r\n Live Demo\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ndf = pd.DataFrame(np.random.randn(10, 4),\r\n   index = pd.date_range('1\/1\/2000', periods=10),\r\n   columns = &#91;'A', 'B', 'C', 'D'])\r\nprint df\r\nr = df.rolling(window=3,min_periods=1)\r\nprint r&#91;'A'].aggregate(&#91;np.sum,np.mean])\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                 A           B           C           D\r\n2000-01-01   1.088512   -0.650942   -2.547450   -0.566858\r\n2000-01-02   1.879182   -1.038796   -3.215581   -0.299575\r\n2000-01-03   1.303660   -2.003821   -3.155154   -2.479355\r\n2000-01-04   1.884801   -0.141119   -0.862400   -0.483331\r\n2000-01-05   1.194699    0.010551    0.297378   -1.216695\r\n2000-01-06   1.925393    1.968551   -0.968183    1.284044\r\n2000-01-07   0.565208    0.032738   -2.125934    0.482797\r\n2000-01-08   0.564129   -0.759118   -2.454374   -0.325454\r\n2000-01-09   2.048458   -1.820537   -0.535232   -1.212381\r\n2000-01-10   2.065750    0.383357    1.541496   -3.201469\r\n                  sum       mean\r\n2000-01-01   1.088512   1.088512\r\n2000-01-02   1.879182   0.939591\r\n2000-01-03   1.303660   0.434553\r\n2000-01-04   1.884801   0.628267\r\n2000-01-05   1.194699   0.398233\r\n2000-01-06   1.925393   0.641798\r\n2000-01-07   0.565208   0.188403\r\n2000-01-08   0.564129   0.188043\r\n2000-01-09   2.048458   0.682819\r\n2000-01-10   2.065750   0.688583\r\n\u041f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043a \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c \u0432 DataFrame\r\n Live Demo\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\ndf = pd.DataFrame(np.random.randn(10, 4),\r\n   index = pd.date_range('1\/1\/2000', periods=10),\r\n   columns = &#91;'A', 'B', 'C', 'D'])\r\nprint df\r\nr = df.rolling(window=3,min_periods=1)\r\nprint r&#91;&#91;'A','B']].aggregate(&#91;np.sum,np.mean])\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                 A           B           C           D\r\n2000-01-01   1.088512   -0.650942   -2.547450   -0.566858\r\n2000-01-02   1.879182   -1.038796   -3.215581   -0.299575\r\n2000-01-03   1.303660   -2.003821   -3.155154   -2.479355\r\n2000-01-04   1.884801   -0.141119   -0.862400   -0.483331\r\n2000-01-05   1.194699    0.010551    0.297378   -1.216695\r\n2000-01-06   1.925393    1.968551   -0.968183    1.284044\r\n2000-01-07   0.565208    0.032738   -2.125934    0.482797\r\n2000-01-08   0.564129   -0.759118   -2.454374   -0.325454\r\n2000-01-09   2.048458   -1.820537   -0.535232   -1.212381\r\n2000-01-10   2.065750    0.383357    1.541496   -3.201469\r\n                    A                      B\r\n                  sum       mean         sum        mean\r\n2000-01-01   1.088512   1.088512   -0.650942   -0.650942\r\n2000-01-02   1.879182   0.939591   -1.038796   -0.519398\r\n2000-01-03   1.303660   0.434553   -2.003821   -0.667940\r\n2000-01-04   1.884801   0.628267   -0.141119   -0.047040\r\n2000-01-05   1.194699   0.398233    0.010551    0.003517\r\n2000-01-06   1.925393   0.641798    1.968551    0.656184\r\n2000-01-07   0.565208   0.188403    0.032738    0.010913\r\n2000-01-08   0.564129   0.188043   -0.759118   -0.253039\r\n2000-01-09   2.048458   0.682819   -1.820537   -0.606846\r\n2000-01-10   2.065750   0.688583    0.383357    0.127786\r\n\u041f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435 \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u0444\u0443\u043d\u043a\u0446\u0438\u0439 \u043a \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0430\u043c \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u043e\u043d\u043d\u043e\u0433\u043e \u043a\u0430\u0434\u0440\u0430\r\n Live Demo\r\n\r\nimport pandas as pd\r\nimport numpy as np\r\n \r\ndf = pd.DataFrame(np.random.randn(3, 4),\r\n   index = pd.date_range('1\/1\/2000', periods=3),\r\n   columns = &#91;'A', 'B', 'C', 'D'])\r\nprint df\r\nr = df.rolling(window=3,min_periods=1)\r\nprint r.aggregate({'A' : np.sum,'B' : np.mean})<\/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-3389","page","type-page","status-publish","hentry","category-python-pandas"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/pages\/3389","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/comments?post=3389"}],"version-history":[{"count":0,"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/pages\/3389\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/media?parent=3389"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/categories?post=3389"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bearloga.space\/uk\/wp-json\/wp\/v2\/tags?post=3389"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}