{"id":3750,"date":"2023-07-15T18:09:49","date_gmt":"2023-07-15T18:09:49","guid":{"rendered":"https:\/\/statorials.org\/ja\/5%e5%88%86%e9%96%93%e9%9a%94%e3%81%ae%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae%e7%be%a4%e3%82%8c\/"},"modified":"2023-07-15T18:09:49","modified_gmt":"2023-07-15T18:09:49","slug":"5%e5%88%86%e9%96%93%e9%9a%94%e3%81%ae%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae%e7%be%a4%e3%82%8c","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/5%e5%88%86%e9%96%93%e9%9a%94%e3%81%ae%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%ae%e7%be%a4%e3%82%8c\/","title":{"rendered":"\u30d1\u30f3\u30c0\u30675\u5206\u9593\u9694\u3067\u30b0\u30eb\u30fc\u30d7\u5316\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"

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\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u3067\u884c\u3092 5 \u5206\u9593\u9694\u306b\u30b0\u30eb\u30fc\u30d7\u5316\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

 df. resample<\/span> (' 5min<\/span> '). sum<\/span> ()\n<\/strong><\/pre>\n
\u3053\u306e\u7279\u5b9a\u306e\u6570\u5f0f\u306f\u3001DataFrame \u306e\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u306b\u65e5\u6642\u5024\u304c\u542b\u307e\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u524d\u63d0\u3068\u3057\u3066\u3001DataFrame \u5185\u306e\u5404\u5217\u306e\u5408\u8a08\u3092 5 \u5206\u9593\u9694\u306b\u30b0\u30eb\u30fc\u30d7\u5316\u3057\u3066\u8a08\u7b97\u3057\u307e\u3059\u3002<\/span><\/p>\n
\u6b21\u306e\u4f8b\u306f\u3001\u3053\u306e\u69cb\u6587\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n
\u95a2\u9023:<\/strong> pandas \u306e resample() \u306e\u6982\u8981<\/a><\/span><\/p>\n
\u4f8b: pandas \u3067 5 \u5206\u9593\u9694\u3067\u30b0\u30eb\u30fc\u30d7\u5316\u3059\u308b\u65b9\u6cd5<\/strong><\/span><\/h2>\n
\u3055\u307e\u3056\u307e\u306a\u65e5\u4ed8\u3068\u6642\u523b\u306b\u304a\u3051\u308b\u4f01\u696d\u306e\u58f2\u4e0a\u3092\u793a\u3059\u6b21\u306e\u30d1\u30f3\u30c0 \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/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
\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u30015 \u5206\u9593\u9694\u3067\u30b0\u30eb\u30fc\u30d7\u5316\u3055\u308c\u305f\u58f2\u4e0a\u306e\u5408\u8a08\u3092\u8a08\u7b97\u3067\u304d\u307e\u3059\u3002<\/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
\u7d50\u679c\u3092\u89e3\u91c8\u3059\u308b\u65b9\u6cd5\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n
\u95a2\u9023:<\/strong> Pandas \u3067\u65e5\u4ed8\u7bc4\u56f2\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/a><\/span><\/p>\n