{"id":4292,"date":"2023-07-12T05:01:09","date_gmt":"2023-07-12T05:01:09","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e6%97%a5%e6%99%82%e5%bd%a2%e5%bc%8f%e3%81%ae%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99\/"},"modified":"2023-07-12T05:01:09","modified_gmt":"2023-07-12T05:01:09","slug":"%e6%97%a5%e6%99%82%e5%bd%a2%e5%bc%8f%e3%81%ae%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e6%97%a5%e6%99%82%e5%bd%a2%e5%bc%8f%e3%81%ae%e3%83%8f%e3%82%9a%e3%83%b3%e3%82%bf%e3%82%99\/","title":{"rendered":"Pandas.to_datetime\u3067\u5f62\u5f0f\u3092\u6307\u5b9a\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>pandas.to_datetime()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306e\u6587\u5b57\u5217\u5217\u3092 datetime \u5217\u306b\u5909\u63db\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u3001 <strong>format<\/strong>\u5f15\u6570\u3092\u4f7f\u7528\u3057\u3066\u65e5\u4ed8\u306e\u5f62\u5f0f\u3092\u6307\u5b9a\u3057\u3001\u6587\u5b57\u5217\u304b\u3089\u65e5\u6642\u3078\u306e\u5909\u63db\u6642\u306e\u30a8\u30e9\u30fc\u3092\u56de\u907f\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u306f\u6b21\u306e\u57fa\u672c\u69cb\u6587\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[' <span style=\"color: #ff0000;\">datetime<\/span> '] = pd. <span style=\"color: #3366ff;\">to_datetime<\/span> (df[' <span style=\"color: #ff0000;\">my_date_column<\/span> '], format=' <span style=\"color: #ff0000;\">%m%d%Y %H:%M:%S<\/span> '])\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\"><strong>format<\/strong>\u5f15\u6570\u306b\u6307\u5b9a\u3067\u304d\u308b\u6700\u3082\u4e00\u822c\u7684\u306a\u30c7\u30a3\u30ec\u30af\u30c6\u30a3\u30d6\u3092\u6b21\u306b\u793a\u3057\u307e\u3059\u3002<\/span><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>%m<\/strong> : \u30bc\u30ed\u3092\u542b\u3080\u6570\u5024\u3068\u3057\u3066\u306e\u6708 (01\u300102\u3001\u2026 12)<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>%d<\/strong> : \u30bc\u30ed\u3092\u542b\u3080\u6570\u5024\u3068\u3057\u3066\u306e\u65e5\u4ed8 (01\u300102\u3001\u2026 31)<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>%y<\/strong> : \u4e16\u7d00\u3092\u6570\u5b57\u306b\u3057\u305f\u5e74 (2020\u30012021\u30012022 \u306a\u3069)<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>%H<\/strong> : \u30bc\u30ed\u3067\u57cb\u3081\u3089\u308c\u305f\u6570\u5024\u3068\u3057\u3066\u306e\u6642\u9593 (24 \u6642\u9593\u5236) (00\u300101\u3001\u2026 23)<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>%I<\/strong> : \u30bc\u30ed\u304c\u57cb\u3081\u8fbc\u307e\u308c\u305f\u6570\u5024\u3068\u3057\u3066\u306e\u6642\u523b (12 \u6642\u9593\u5236) (01\u300102\u3001\u2026 12)<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>%p<\/strong> : \u5348\u524d\u307e\u305f\u306f\u5348\u5f8c\u306e\u3044\u305a\u308c\u304b<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>%M<\/strong> : \u30bc\u30ed\u3067\u88dc\u5b8c\u3055\u308c\u305f\u6570\u5024\u5f62\u5f0f\u306e\u5206 (00\u300101\u3001\u2026 59)<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>%S<\/strong> : \u30bc\u30ed\u3067\u88dc\u5b8c\u3055\u308c\u305f\u6570\u5024\u5f62\u5f0f\u306e\u79d2 (00\u300101\u3001\u2026 59)<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u30ac\u30a4\u30c9\u30e9\u30a4\u30f3\u306e\u5b8c\u5168\u306a\u30ea\u30b9\u30c8\u306b\u3064\u3044\u3066\u306f\u3001 <a href=\"https:\/\/docs.python.org\/3\/library\/datetime.html#strftime-and-strptime-behavior\" target=\"_blank\" rel=\"noopener\">\u3053\u306e\u30da\u30fc\u30b8<\/a>\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u3055\u307e\u3056\u307e\u306a\u30b7\u30ca\u30ea\u30aa\u3067<strong>to_datetime()<\/strong>\u95a2\u6570\u306e<strong>format<\/strong>\u5f15\u6570\u3092\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u4f8b: pandas.to_datetime \u306b\u5f62\u5f0f\u3092\u6307\u5b9a\u3059\u308b<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u5c0f\u58f2\u5e97\u3067\u306e\u3055\u307e\u3056\u307e\u306a\u65e5\u4ed8\u306e\u7dcf\u58f2\u4e0a\u9ad8\u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u542b\u3080\u6b21\u306e\u30d1\u30f3\u30c0 \u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<span style=\"color: #000000;\">\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">date<\/span> ': ['10012023 4:15:30', '10042023 7:16:04', '10062023 9:25:00',\n                            '10142023 15:30:50', '10152023 18:15:00'],\n                   ' <span style=\"color: #ff0000;\">sales<\/span> ': [100, 140, 235, 120, 250]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n                dirty dates\n0 10012023 4:15:30 100\n1 10042023 7:16:04 140\n2 10062023 9:25:00 235\n3 10142023 15:30:50 120\n4 10152023 18:15:00 250\n\n<span style=\"color: #008080;\">#view data type of each column in DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df.dtypes<\/span> )\n\ndate object\ndirty int64\ndtype:object\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\"><span style=\"color: #000000;\"><strong>\u65e5\u4ed8<\/strong>\u5217\u304c\u73fe\u5728\u6587\u5b57\u5217 (\u3064\u307e\u308a\u30aa\u30d6\u30b8\u30a7\u30af\u30c8) \u5217\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>pandas.to_datetime()<\/strong>\u3092\u4f7f\u7528\u3057\u3066\u3053\u306e\u5217\u3092 datetime \u306b\u5909\u63db\u3057\u3088\u3046\u3068\u3059\u308b\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#attempt to convert date column to datetime format\n<span style=\"color: #000000;\">df[' <span style=\"color: #ff0000;\">date<\/span> '] = pd. <span style=\"color: #3366ff;\">to_datetime<\/span> (df[' <span style=\"color: #ff0000;\">date<\/span> '])\n\nParserError: month must be in 1..12: 10012023 4:15:30 present at position 0<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\"><strong>pandas.to_datetime()<\/strong>\u95a2\u6570\u304c<strong>\u65e5\u4ed8<\/strong>\u5217\u306e\u73fe\u5728\u306e\u65e5\u4ed8\u3068\u6642\u523b\u306e\u5f62\u5f0f\u3092\u8a8d\u8b58\u3057\u306a\u3044\u305f\u3081\u3001\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3057\u307e\u3059\u3002<\/span><\/span><\/p>\n<p> <span style=\"color: #000000;\"><b>format<\/b>\u5f15\u6570\u3092\u4f7f\u7528\u3057\u3066\u5217\u306e\u5f62\u5f0f\u3092\u6307\u5b9a\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#convert date column to datetime format\n<\/span>df[' <span style=\"color: #ff0000;\">date<\/span> '] = pd. <span style=\"color: #3366ff;\">to_datetime<\/span> (df[' <span style=\"color: #ff0000;\">date<\/span> '], format=' <span style=\"color: #ff0000;\">%m%d%Y %H:%M:%S<\/span> ')\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n                 dirty dates\n0 2023-10-01 04:15:30 100\n1 2023-10-04 07:16:04 140\n2 2023-10-06 09:25:00 235\n3 2023-10-14 15:30:50 120\n4 2023-10-15 18:15:00 250\n\n<span style=\"color: #008080;\">#view updated type of each column\n<\/span><span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df.dtypes<\/span> )\n\ndate datetime64[ns]\ndirty int64\ndtype:object<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u65e5\u4ed8<\/strong>\u5217\u304c\u65e5\u6642\u5217\u306b\u6b63\u5e38\u306b\u5909\u63db\u3055\u308c\u3001 <strong>format<\/strong>\u5f15\u6570\u3092\u4f7f\u7528\u3057\u3066<strong>\u65e5\u4ed8<\/strong>\u5217\u306e\u6b63\u78ba\u306a\u5f62\u5f0f\u3092\u6307\u5b9a\u3057\u305f\u305f\u3081\u3001\u30a8\u30e9\u30fc\u306f\u767a\u751f\u3057\u306a\u304b\u3063\u305f\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u6ce8<\/strong>: pandas <strong>to_datetime()<\/strong>\u95a2\u6570\u306e\u5b8c\u5168\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306f<a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.to_datetime.html\" target=\"_blank\" rel=\"noopener\">\u3053\u3053\u3067<\/a>\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u8ffd\u52a0\u30ea\u30bd\u30fc\u30b9<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\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<p> <a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306e\u65e5\u4ed8\u7bc4\u56f2\/\" target=\"_blank\" rel=\"noopener\">Pandas \u3067\u65e5\u4ed8\u7bc4\u56f2\u3092\u4f5c\u6210\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306e\u30bf\u30a4\u30e0\u30b9\u30bf\u30f3\u30d5\u309a\u306e\u65e5\u4ed8\u6642\u523b\/\" target=\"_blank\" rel=\"noopener\">Pandas\u3067\u30bf\u30a4\u30e0\u30b9\u30bf\u30f3\u30d7\u3092\u65e5\u4ed8\/\u6642\u523b\u306b\u5909\u63db\u3059\u308b\u65b9\u6cd5<\/a><br \/><a href=\"https:\/\/statorials.org\/ja\/\u30cf\u309a\u30f3\u30bf\u3099\u306e\u65e5\u4ed8\u306e\u9055\u3044\/\" target=\"_blank\" rel=\"noopener\">\u30d1\u30f3\u30c0\u3067 2 \u3064\u306e\u65e5\u4ed8\u306e\u5dee\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>pandas.to_datetime()\u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001pandas DataFrame \u306e\u6587\u5b57\u5217\u5217\u3092 datetime \u5217\u306b\u5909\u63db\u3067\u304d\u307e\u3059\u3002 \u3053\u306e\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u5834\u5408\u3001 format\u5f15\u6570\u3092\u4f7f\u7528\u3057\u3066\u65e5\u4ed8\u306e\u5f62\u5f0f\u3092\u6307\u5b9a\u3057\u3001\u6587\u5b57\u5217 [&hellip;]<\/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-4292","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>pandas.to_datetime \u3067\u5f62\u5f0f\u3092\u6307\u5b9a\u3059\u308b\u65b9\u6cd5 \u2013 \u8a18\u4e8b<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas.to_datetime \u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3068\u304d\u306b\u65e5\u4ed8\u5f62\u5f0f\u3092\u6307\u5b9a\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ja\/\u65e5\u6642\u5f62\u5f0f\u306e\u30cf\u309a\u30f3\u30bf\u3099\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"pandas.to_datetime \u3067\u5f62\u5f0f\u3092\u6307\u5b9a\u3059\u308b\u65b9\u6cd5 \u2013 \u8a18\u4e8b\" \/>\n<meta property=\"og:description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001pandas.to_datetime \u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3068\u304d\u306b\u65e5\u4ed8\u5f62\u5f0f\u3092\u6307\u5b9a\u3059\u308b\u65b9\u6cd5\u3092\u3044\u304f\u3064\u304b\u306e\u4f8b\u3068\u3068\u3082\u306b\u8aac\u660e\u3057\u307e\u3059\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ja\/\u65e5\u6642\u5f62\u5f0f\u306e\u30cf\u309a\u30f3\u30bf\u3099\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-12T05:01:09+00:00\" \/>\n<meta name=\"author\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" 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