{"id":3534,"date":"2023-07-16T23:18:53","date_gmt":"2023-07-16T23:18:53","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af-2-%e3%81%a4%e3%81%ae%e6%97%a5%e4%bb%98%e9%96%93%e3%81%ae%e8%a1%8c%e3%82%92%e9%81%b8%e6%8a%9e%e3%81%97%e3%81%be%e3%81%99\/"},"modified":"2023-07-16T23:18:53","modified_gmt":"2023-07-16T23:18:53","slug":"%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af-2-%e3%81%a4%e3%81%ae%e6%97%a5%e4%bb%98%e9%96%93%e3%81%ae%e8%a1%8c%e3%82%92%e9%81%b8%e6%8a%9e%e3%81%97%e3%81%be%e3%81%99","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99%e3%81%af-2-%e3%81%a4%e3%81%ae%e6%97%a5%e4%bb%98%e9%96%93%e3%81%ae%e8%a1%8c%e3%82%92%e9%81%b8%e6%8a%9e%e3%81%97%e3%81%be%e3%81%99\/","title":{"rendered":"\u30d1\u30f3\u30c0: 2 \u3064\u306e\u65e5\u4ed8\u9593\u306e\u884c\u3092\u9078\u629e\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"

<\/p>\n

\n

\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u5185\u306e 2 \u3064\u306e\u7279\u5b9a\u306e\u65e5\u4ed8\u306e\u9593\u306e\u884c\u3092\u9078\u629e\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n

 df[df. date<\/span> . between<\/span> (' 2022-01-02<\/span> ', ' 2022-01-06<\/span> ')]\n<\/strong><\/pre>\n
\u3053\u306e\u7279\u5b9a\u306e\u4f8b\u3067\u306f\u300101\/02\/2022 \u304b\u3089 01\/06\/2022 \u307e\u3067\u306e DataFrame \u5185\u306e\u3059\u3079\u3066\u306e\u884c\u3092\u9078\u629e\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
\u4f8b: Pandas \u3067 2 \u3064\u306e\u65e5\u4ed8\u9593\u306e\u884c\u3092\u9078\u629e\u3059\u308b<\/strong><\/span><\/h2>\n
\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\n<\/span>df = pd. DataFrame<\/span> ({' date<\/span> ': pd. date_range<\/span> (start=' 1\/1\/2022<\/span> ', periods= 8<\/span> ),\n                   ' sales<\/span> ': [18, 20, 15, 14, 10, 9, 8, 12],\n                   ' returns<\/span> ': [5, 7, 7, 9, 12, 3, 2, 4]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n        date sales returns\n0 2022-01-01 18 5\n1 2022-01-02 20 7\n2 2022-01-03 15 7\n3 2022-01-04 14 9\n4 2022-01-05 10 12\n5 2022-01-06 9 3\n6 2022-01-07 8 2\n7 2022-01-08 12 4<\/span>\n<\/span><\/strong><\/pre>\n
\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u65e5\u4ed8 01\/02\/2022 \u304b\u3089 01\/06\/2022 \u307e\u3067\u306e\u884c\u306e\u307f\u3092\u9078\u629e\u3067\u304d\u307e\u3059\u3002<\/span><\/span><\/p>\n
 #select all rows where date is between 2022-01-02 and 2022-01-06\n<\/span>df[df. date<\/span> . between<\/span> (' 2022-01-02<\/span> ', ' 2022-01-06<\/span> ')]\n\n              date sales returns\n1 2022-01-02 20 7\n2 2022-01-03 15 7\n3 2022-01-04 14 9\n4 2022-01-05 10 12\n5 2022-01-06 9 3<\/span><\/span><\/strong><\/pre>\n
\u65e5\u4ed8 2022-01-02 \u3068 2022-01-06 \u306e\u9593\u306e\u884c\u306e\u307f\u304c\u9078\u629e\u3055\u308c\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n
\u5fc5\u8981\u306b\u5fdc\u3058\u3066\u3001 between()<\/strong>\u95a2\u6570\u306e\u5916\u5074\u3067\u958b\u59cb\u65e5\u3068\u7d42\u4e86\u65e5\u3092\u8a2d\u5b9a\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
 #define start and end dates<\/span>\nstart_date = ' 2022-01-02<\/span> '\nend_date = ' 2022-01-06<\/span> '\n\n#select all rows where date is between start and end\n<\/span>df[df. date<\/span> . between<\/span> (start_date, end_date)]\n\n\n              date sales returns\n1 2022-01-02 20 7\n2 2022-01-03 15 7\n3 2022-01-04 14 9\n4 2022-01-05 10 12\n5 2022-01-06 9 3\n<\/span><\/span><\/strong><\/pre>\n
\u3053\u308c\u3067\u3082\u540c\u3058\u7d50\u679c\u304c\u5f97\u3089\u308c\u307e\u3059\u3002<\/span><\/p>\n
\u65e5\u4ed8\u5217\u304c\u8a8d\u8b58\u53ef\u80fd\u306a\u65e5\u6642\u5f62\u5f0f\u3067\u306a\u3044\u5834\u5408\u306f\u3001\u6700\u521d\u306b\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3057\u3066\u65e5\u6642\u5f62\u5f0f\u306b\u5909\u63db\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u5834\u5408\u304c\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n
 df[' date<\/span> '] = pd. to_datetime<\/span> (df[' date<\/span> ']) \n<\/span><\/span><\/strong><\/pre>\n
\u305d\u308c\u304c\u5b8c\u4e86\u3057\u305f\u3089\u3001 between()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u7279\u5b9a\u306e\u65e5\u4ed8\u9593\u306e\u884c\u3092\u9078\u629e\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n
\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h2>\n
\u6b21\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001\u30d1\u30f3\u30c0\u3067\u4ed6\u306e\u4e00\u822c\u7684\u306a\u64cd\u4f5c\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n
 Pandas \u3067\u65e5\u4ed8\u7bc4\u56f2\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/a>
Pandas\u3067\u65e5\u4ed8\u304b\u3089\u6708\u3092\u62bd\u51fa\u3059\u308b\u65b9\u6cd5<\/a>
Pandas\u3067\u30bf\u30a4\u30e0\u30b9\u30bf\u30f3\u30d7\u3092\u65e5\u4ed8\/\u6642\u523b\u306b\u5909\u63db\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u5185\u306e 2 \u3064\u306e\u7279\u5b9a\u306e\u65e5\u4ed8\u306e\u9593\u306e\u884c\u3092\u9078\u629e\u3067\u304d\u307e\u3059\u3002 df[df. date . between (‘ 2022-01-02 ‘, ‘ 2022-01-06 ‘)] \u3053\u306e […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-3534","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"\n\u30d1\u30f3\u30c0: 2 \u3064\u306e\u65e5\u4ed8\u9593\u306e\u884c\u3092\u9078\u629e\u3059\u308b\u65b9\u6cd5 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas DataFrame \u306e 2 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