{"id":3432,"date":"2023-07-17T12:20:03","date_gmt":"2023-07-17T12:20:03","guid":{"rendered":"https:\/\/statorials.org\/uk\/pandas-%d0%b2%d0%b8%d0%b1%d0%b8%d1%80%d0%b0%d1%94-%d1%81%d1%82%d0%be%d0%b2%d0%bf%d1%86%d1%96-%d0%b7%d0%b0-%d0%bd%d0%b0%d0%b7%d0%b2%d0%be%d1%8e\/"},"modified":"2023-07-17T12:20:03","modified_gmt":"2023-07-17T12:20:03","slug":"pandas-%d0%b2%d0%b8%d0%b1%d0%b8%d1%80%d0%b0%d1%94-%d1%81%d1%82%d0%be%d0%b2%d0%bf%d1%86%d1%96-%d0%b7%d0%b0-%d0%bd%d0%b0%d0%b7%d0%b2%d0%be%d1%8e","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/pandas-%d0%b2%d0%b8%d0%b1%d0%b8%d1%80%d0%b0%d1%94-%d1%81%d1%82%d0%be%d0%b2%d0%bf%d1%86%d1%96-%d0%b7%d0%b0-%d0%bd%d0%b0%d0%b7%d0%b2%d0%be%d1%8e\/","title":{"rendered":"\u042f\u043a \u0432\u0438\u0431\u0440\u0430\u0442\u0438 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e \u0432 pandas (3 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0442\u0430\u043a\u0456 \u043c\u0435\u0442\u043e\u0434\u0438, \u0449\u043e\u0431 \u0432\u0438\u0431\u0440\u0430\u0442\u0438 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0437\u0430 \u0456\u043c\u0435\u043d\u0435\u043c \u0443 pandas DataFrame:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u0421\u043f\u043e\u0441\u0456\u0431 1: \u0412\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">column1<\/span> ']\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u0421\u043f\u043e\u0441\u0456\u0431 2: \u0432\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u043a\u0456\u043b\u044c\u043a\u0430 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">loc<\/span> [:,[' <span style=\"color: #ff0000;\">column1<\/span> ',' <span style=\"color: #ff0000;\">column3<\/span> ',' <span style=\"color: #ff0000;\">column4<\/span> ']]<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u0421\u043f\u043e\u0441\u0456\u0431 3: \u0412\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0432 \u0434\u0456\u0430\u043f\u0430\u0437\u043e\u043d\u0456 \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">column2<\/span> ':' <span style=\"color: #ff0000;\">column4<\/span> ']<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u043f\u043e\u043a\u0430\u0437\u0443\u044e\u0442\u044c, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043a\u043e\u0436\u0435\u043d \u0456\u0437 \u0446\u0438\u0445 \u043c\u0435\u0442\u043e\u0434\u0456\u0432 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456 \u0437 \u0442\u0430\u043a\u0438\u043c\u0438 pandas DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">mavs<\/span> ': [10, 12, 14, 15, 19, 22, 27],\n                   ' <span style=\"color: #ff0000;\">cavs<\/span> ': [18, 22, 19, 14, 14, 11, 20],\n                   ' <span style=\"color: #ff0000;\">hornets<\/span> ': [5, 7, 7, 9, 12, 9, 14],\n                   ' <span style=\"color: #ff0000;\">spurs<\/span> ': [10, 12, 14, 13, 13, 19, 22],\n                   ' <span style=\"color: #ff0000;\">net<\/span> ': [10, 14, 25, 22, 25, 17, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n   mavs cavs hornets spurs nets\n0 10 18 5 10 10\n1 12 22 7 12 14\n2 14 19 7 14 25\n3 15 14 9 13 22\n4 19 14 12 13 25\n5 22 11 9 19 17\n6 27 20 14 22 12\n<\/strong><\/span><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 1: \u0412\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u0431\u0440\u0430\u0442\u0438 \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u00ab\u0448\u043f\u043e\u0440\u0438\u00bb \u0443 DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#select column with name 'spurs'\n<\/span>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">spurs<\/span> ']\n\n0 10\n1 12\n2 14\n3 13\n4 13\n5 19\n6 22\nName: spurs, dtype: int64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041f\u043e\u0432\u0435\u0440\u0442\u0430\u044e\u0442\u044c\u0441\u044f \u043b\u0438\u0448\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0432 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u00ab\u0448\u043f\u043e\u0440\u0438\u00bb.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 2: \u0432\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u043a\u0456\u043b\u044c\u043a\u0430 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u0431\u0440\u0430\u0442\u0438 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 cavs, spurs \u0456 net \u0443 DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#select columns with names cavs, spurs, and nets\n<\/span>df. <span style=\"color: #3366ff;\">loc<\/span> [:, [' <span style=\"color: #ff0000;\">cavs<\/span> ', ' <span style=\"color: #ff0000;\">spurs<\/span> ', ' <span style=\"color: #ff0000;\">nets<\/span> ']]\n\n        cavs spurs nets\n0 18 10 10\n1 22 12 14\n2 19 14 25\n3 14 13 22\n4 14 13 25\n5 11 19 17\n6 20 22 12<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041f\u043e\u0432\u0435\u0440\u0442\u0430\u044e\u0442\u044c\u0441\u044f \u043b\u0438\u0448\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f cavs, \u0448\u043f\u043e\u0440\u0456\u0432 \u0456 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u043c\u0435\u0440\u0435\u0436\u0456.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 3: \u0412\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0432 \u0434\u0456\u0430\u043f\u0430\u0437\u043e\u043d\u0456 \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u0431\u0440\u0430\u0442\u0438 \u0432\u0441\u0456 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u043c\u0456\u0436 \u043d\u0430\u0437\u0432\u0430\u043c\u0438 \u00abhornets\u00bb \u0456 \u00abnet\u00bb \u0443 DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#select all columns between hornets and nets\n<\/span>df. <span style=\"color: #3366ff;\">loc<\/span> [:, ' <span style=\"color: #ff0000;\">hornets<\/span> ': ' <span style=\"color: #ff0000;\">nets<\/span> ']\n\n        hornets spurs nets\n0 5 10 10\n1 7 12 14\n2 7 14 25\n3 9 13 22\n4 12 13 25\n5 9 19 17\n6 14 22 12<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041f\u043e\u0432\u0435\u0440\u0442\u0430\u044e\u0442\u044c\u0441\u044f \u0432\u0441\u0456 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u043c\u0456\u0436 \u043d\u0430\u0437\u0432\u0430\u043c\u0438 &#8220;hornets&#8221; \u0456 &#8220;net&#8221;.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0445 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0430\u0445 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0456\u043d\u0448\u0456 \u0442\u0438\u043f\u043e\u0432\u0456 \u0437\u0430\u0432\u0434\u0430\u043d\u043d\u044f \u0432 pandas:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/uk\/\u043f\u0430\u043d\u0434\u0438-\u0440\u0443\u0445\u0430\u044e\u0442\u044c\u0441\u044f-\u0432\u0456\u0434-\u0445\u0440\u0435\u0431\u0442\u0430-\u0432\u043f\u0435\u0440\u0435\u0434\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u042f\u043a \u043f\u0435\u0440\u0435\u043c\u0456\u0441\u0442\u0438\u0442\u0438 \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u043f\u0435\u0440\u0435\u0434 DataFrame<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/pandas-\u043f\u0435\u0440\u0435\u0432\u0456\u0440\u044f\u0454,-\u0447\u0438-\u043c\u0456\u0441\u0442\u0438\u0442\u044c-\u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c-\u0440\u044f\u0434\u043e\u043a\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u044f\u043a \u043f\u0435\u0440\u0435\u0432\u0456\u0440\u0438\u0442\u0438, \u0447\u0438 \u043c\u0456\u0441\u0442\u0438\u0442\u044c \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u0440\u044f\u0434\u043e\u043a<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/pandas-\u0434\u043e\u0434\u0430\u0442\u0438-\u043f\u043e\u0440\u043e\u0436\u043d\u0456\u0438-\u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u042f\u043a \u0434\u043e\u0434\u0430\u0442\u0438 \u043f\u043e\u0440\u043e\u0436\u043d\u0456\u0439 \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u0434\u043e DataFrame (3 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438)<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0442\u0430\u043a\u0456 \u043c\u0435\u0442\u043e\u0434\u0438, \u0449\u043e\u0431 \u0432\u0438\u0431\u0440\u0430\u0442\u0438 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0437\u0430 \u0456\u043c\u0435\u043d\u0435\u043c \u0443 pandas DataFrame: \u0421\u043f\u043e\u0441\u0456\u0431 1: \u0412\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e df. loc [:, &#8216; column1 &#8216;] \u0421\u043f\u043e\u0441\u0456\u0431 2: \u0432\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u043a\u0456\u043b\u044c\u043a\u0430 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e df. loc [:,[&#8216; column1 &#8216;,&#8217; column3 &#8216;,&#8217; column4 &#8216;]] \u0421\u043f\u043e\u0441\u0456\u0431 3: \u0412\u0438\u0431\u0435\u0440\u0456\u0442\u044c \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0432 \u0434\u0456\u0430\u043f\u0430\u0437\u043e\u043d\u0456 \u0437\u0430 \u043d\u0430\u0437\u0432\u043e\u044e df. loc [:, &#8216; column2 &#8216;:&#8217; [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"<!-- This site is optimized with the 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