{"id":3754,"date":"2023-07-15T18:09:49","date_gmt":"2023-07-15T18:09:49","guid":{"rendered":"https:\/\/statorials.org\/tr\/5-dakikalik-araliklarla-panda-grubu\/"},"modified":"2023-07-15T18:09:49","modified_gmt":"2023-07-15T18:09:49","slug":"5-dakikalik-araliklarla-panda-grubu","status":"publish","type":"post","link":"https:\/\/statorials.org\/tr\/5-dakikalik-araliklarla-panda-grubu\/","title":{"rendered":"Pandalarda 5 dakikal\u0131k aral\u0131klarla nas\u0131l gruplan\u0131r"},"content":{"rendered":"

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Bir pandas DataFrame’de sat\u0131rlar\u0131 5 dakikal\u0131k aral\u0131klarla gruplamak i\u00e7in a\u015fa\u011f\u0131daki temel s\u00f6zdizimini kullanabilirsiniz:<\/span><\/p>\n

 df. resample<\/span> (' 5min<\/span> '). sum<\/span> ()\n<\/strong><\/pre>\n
 Bu \u00f6zel form\u00fcl, DataFrame’inizin dizininin tarihsaat de\u011ferleri i\u00e7erdi\u011fini varsayar ve DataFrame’deki her s\u00fctunun toplam\u0131n\u0131 5 dakikal\u0131k aral\u0131klarla grupland\u0131r\u0131lm\u0131\u015f olarak hesaplar.<\/span><\/p>\n
 A\u015fa\u011f\u0131daki \u00f6rnek, bu s\u00f6zdiziminin pratikte nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n
 \u0130lgili:<\/strong> Pandalarda resample()’a giri\u015f<\/a><\/span><\/p>\n
 \u00d6rnek: Pandalarda 5 dakikal\u0131k aral\u0131klarla nas\u0131l grupland\u0131r\u0131l\u0131r<\/strong><\/span><\/h2>\n
 Diyelim ki bir \u015firketin farkl\u0131 tarih ve saatlerde yapt\u0131\u011f\u0131 sat\u0131\u015flar\u0131 g\u00f6steren a\u015fa\u011f\u0131daki panda DataFrame’imiz var:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' date<\/span> ': pd.date_range<\/span> (start=' 1\/1\/2020<\/span> ', freq=' min<\/span> ', periods= 12<\/span> ),\n                   ' sales<\/span> ': [6, 8, 9, 11, 13, 8, 8, 15, 22, 9, 8, 4],\n                   ' returns<\/span> ': [0, 3, 2, 2, 1, 3, 2, 4, 1, 5, 3, 2]})\n\n#set 'date' column as index\n<\/span>df = df. set_index<\/span> (' date<\/span> ')\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n                     sales returns\ndate                               \n2020-01-01 00:00:00 6 0\n2020-01-01 00:01:00 8 3\n2020-01-01 00:02:00 9 2\n2020-01-01 00:03:00 11 2\n2020-01-01 00:04:00 13 1\n2020-01-01 00:05:00 8 3\n2020-01-01 00:06:00 8 2\n2020-01-01 00:07:00 15 4\n2020-01-01 00:08:00 22 1\n2020-01-01 00:09:00 9 5\n2020-01-01 00:10:00 8 3\n2020-01-01 00:11:00 4 2\n<\/strong><\/span><\/pre>\n
 5 dakikal\u0131k aral\u0131klarla grupland\u0131r\u0131lm\u0131\u015f sat\u0131\u015flar\u0131n toplam\u0131n\u0131 hesaplamak i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/span><\/p>\n
 #calculate sum of sales and returns grouped by 5-minute intervals\ndf. resample<\/span> (' 5min<\/span> '). sum<\/span> ()\n\n                     sales returns\ndate\t\t\n2020-01-01 00:00:00 47 8\n2020-01-01 00:05:00 62 15\n2020-01-01 00:10:00 12 5<\/span><\/span><\/strong><\/pre>\n
 Sonucun nas\u0131l yorumlanaca\u011f\u0131 a\u015fa\u011f\u0131da a\u00e7\u0131klanm\u0131\u015ft\u0131r:<\/span><\/p>\n
 \u0130lgili:<\/strong> Pandalarda Tarih Aral\u0131\u011f\u0131 Nas\u0131l Olu\u015fturulur<\/a><\/span><\/p>\n