{"id":1604,"date":"2023-07-25T16:44:55","date_gmt":"2023-07-25T16:44:55","guid":{"rendered":"https:\/\/statorials.org\/th\/%e0%b9%80%e0%b8%a7%e0%b8%a5%e0%b8%b2%e0%b8%a7%e0%b8%b1%e0%b8%99%e0%b8%97%e0%b8%b5%e0%b9%88%e0%b8%9b%e0%b8%a3%e0%b8%b0%e0%b8%97%e0%b8%b1%e0%b8%9a%e0%b8%82%e0%b8%ad%e0%b8%87%e0%b9%81%e0%b8%9e%e0%b8%99\/"},"modified":"2023-07-25T16:44:55","modified_gmt":"2023-07-25T16:44:55","slug":"%e0%b9%80%e0%b8%a7%e0%b8%a5%e0%b8%b2%e0%b8%a7%e0%b8%b1%e0%b8%99%e0%b8%97%e0%b8%b5%e0%b9%88%e0%b8%9b%e0%b8%a3%e0%b8%b0%e0%b8%97%e0%b8%b1%e0%b8%9a%e0%b8%82%e0%b8%ad%e0%b8%87%e0%b9%81%e0%b8%9e%e0%b8%99","status":"publish","type":"post","link":"https:\/\/statorials.org\/th\/%e0%b9%80%e0%b8%a7%e0%b8%a5%e0%b8%b2%e0%b8%a7%e0%b8%b1%e0%b8%99%e0%b8%97%e0%b8%b5%e0%b9%88%e0%b8%9b%e0%b8%a3%e0%b8%b0%e0%b8%97%e0%b8%b1%e0%b8%9a%e0%b8%82%e0%b8%ad%e0%b8%87%e0%b9%81%e0%b8%9e%e0%b8%99\/","title":{"rendered":"\u0e27\u0e34\u0e18\u0e35\u0e41\u0e1b\u0e25\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\/\u0e40\u0e27\u0e25\u0e32\u0e43\u0e19 pandas"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0e04\u0e38\u0e13\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e44\u0e27\u0e22\u0e32\u0e01\u0e23\u0e13\u0e4c\u0e1e\u0e37\u0e49\u0e19\u0e10\u0e32\u0e19\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e41\u0e1b\u0e25\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32\u0e43\u0e19 DataFrame \u0e02\u0e2d\u0e07\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>timestamp. <span style=\"color: #3366ff;\">to_pydatetime<\/span> ()\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e41\u0e2a\u0e14\u0e07\u0e27\u0e34\u0e18\u0e35\u0e43\u0e0a\u0e49\u0e1f\u0e31\u0e07\u0e01\u0e4c\u0e0a\u0e31\u0e19\u0e19\u0e35\u0e49\u0e43\u0e19\u0e17\u0e32\u0e07\u0e1b\u0e0f\u0e34\u0e1a\u0e31\u0e15\u0e34<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e17\u0e35\u0e48 1: \u0e41\u0e1b\u0e25\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e14\u0e35\u0e22\u0e27\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\/\u0e40\u0e27\u0e25\u0e32<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0e23\u0e2b\u0e31\u0e2a\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e41\u0e2a\u0e14\u0e07\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e41\u0e1b\u0e25\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e14\u0e35\u0e22\u0e27\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define timestamp<\/span>\nstamp = pd. <span style=\"color: #3366ff;\">Timestamp<\/span> (' <span style=\"color: #ff0000;\">2021-01-01 00:00:00<\/span> ')\n\n<span style=\"color: #008080;\">#convert timestamp to datetime\n<\/span>stamp. <span style=\"color: #3366ff;\">to_pydatetime<\/span> ()\n\ndatetime.datetime(2021, 1, 1, 0, 0)<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e17\u0e35\u0e48 2: \u0e41\u0e1b\u0e25\u0e07\u0e2d\u0e32\u0e23\u0e4c\u0e40\u0e23\u0e22\u0e4c\u0e02\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0e23\u0e2b\u0e31\u0e2a\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e41\u0e2a\u0e14\u0e07\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e41\u0e1b\u0e25\u0e07\u0e2d\u0e32\u0e23\u0e4c\u0e40\u0e23\u0e22\u0e4c\u0e02\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define array of timestamps<\/span>\nstamps = pd. <span style=\"color: #3366ff;\">date_range<\/span> (start=' <span style=\"color: #ff0000;\">2020-01-01 12:00:00<\/span> ', periods= <span style=\"color: #008000;\">6<\/span> , freq=' <span style=\"color: #ff0000;\">H<\/span> ')\n\n<span style=\"color: #008080;\">#view array of timestamps\n<\/span>stamps\n\nDatetimeIndex(['2020-01-01 12:00:00', '2020-01-01 13:00:00',\n               '2020-01-01 14:00:00', '2020-01-01 15:00:00',\n               '2020-01-01 16:00:00', '2020-01-01 17:00:00'],\n              dtype='datetime64[ns]', freq='H')\n\n<span style=\"color: #008080;\">#convert timestamps to datetimes<\/span>\nstamps. <span style=\"color: #3366ff;\">to_pydatetime<\/span> ()\n\narray([datetime.datetime(2020, 1, 1, 12, 0),\n       datetime.datetime(2020, 1, 1, 13, 0),\n       datetime.datetime(2020, 1, 1, 14, 0),\n       datetime.datetime(2020, 1, 1, 15, 0),\n       datetime.datetime(2020, 1, 1, 16, 0),\n       datetime.datetime(2020, 1, 1, 17, 0)], dtype=object)<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e17\u0e35\u0e48 3: \u0e41\u0e1b\u0e25\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c Pandas \u0e02\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19 Datetime<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0e23\u0e2b\u0e31\u0e2a\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e41\u0e2a\u0e14\u0e07\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e41\u0e1b\u0e25\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\u0e02\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32:<\/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;\">stamps<\/span> ': pd. <span style=\"color: #3366ff;\">date_range<\/span> (start=' <span style=\"color: #ff0000;\">2020-01-01 12:00:00<\/span> ',\n                             periods= <span style=\"color: #008000;\">6<\/span> ,\n                             freq=' <span style=\"color: #ff0000;\">H<\/span> '),\n                   ' <span style=\"color: #ff0000;\">sales<\/span> ': [11, 14, 25, 31, 34, 35]})\n\n<span style=\"color: #008080;\">#convert column of timestamps to datetimes<\/span>\ndf. <span style=\"color: #3366ff;\">stamps<\/span> = df. <span style=\"color: #3366ff;\">stamps<\/span> . <span style=\"color: #3366ff;\">apply<\/span> (lambda x: <span style=\"color: #3366ff;\">x.date<\/span> ())\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tdirty stamps\n0 2020-01-01 11\n1 2020-01-01 14\n2 2020-01-01 25\n3 2020-01-01 31\n4 2020-01-01 34\n5 2020-01-01 35\n<\/strong><\/span><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u0e41\u0e2b\u0e25\u0e48\u0e07\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e40\u0e1e\u0e34\u0e48\u0e21\u0e40\u0e15\u0e34\u0e21<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/th\/\u0e41\u0e1b\u0e25\u0e07-datetime-\u0e40\u0e1b\u0e47\u0e19-date-pandas\/\" target=\"_blank\" rel=\"noopener\">\u0e27\u0e34\u0e18\u0e35\u0e41\u0e1b\u0e25\u0e07 DateTime \u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e43\u0e19 Pandas<\/a><br \/> <a href=\"https:\/\/statorials.org\/th\/\u0e41\u0e1b\u0e25\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32\u0e02\u0e2d\u0e07\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\/\" target=\"_blank\" rel=\"noopener\">\u0e27\u0e34\u0e18\u0e35\u0e41\u0e1b\u0e25\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e40\u0e1b\u0e47\u0e19 DateTime \u0e43\u0e19 Pandas<\/a><br \/> <a href=\"https:\/\/statorials.org\/th\/\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\u0e40\u0e23\u0e35\u0e22\u0e07\u0e15\u0e32\u0e21\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\/\" target=\"_blank\" rel=\"noopener\">\u0e27\u0e34\u0e18\u0e35\u0e08\u0e31\u0e14\u0e40\u0e23\u0e35\u0e22\u0e07 Pandas DataFrame \u0e15\u0e32\u0e21\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0e04\u0e38\u0e13\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e44\u0e27\u0e22\u0e32\u0e01\u0e23\u0e13\u0e4c\u0e1e\u0e37\u0e49\u0e19\u0e10\u0e32\u0e19\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e41\u0e1b\u0e25\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27 [&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":[],"class_list":["post-1604","post","type-post","status-publish","format-standard","hentry","category-3"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u0e27\u0e34\u0e18\u0e35\u0e41\u0e1b\u0e25\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\/\u0e40\u0e27\u0e25\u0e32\u0e43\u0e19 Pandas - Statorials<\/title>\n<meta name=\"description\" content=\"\u0e1a\u0e17\u0e0a\u0e48\u0e27\u0e22\u0e2a\u0e2d\u0e19\u0e19\u0e35\u0e49\u0e08\u0e30\u0e2d\u0e18\u0e34\u0e1a\u0e32\u0e22\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e41\u0e1b\u0e25\u0e07\u0e04\u0e48\u0e32\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e04\u0e48\u0e32\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32\u0e43\u0e19 Pandas DataFrame \u0e23\u0e27\u0e21\u0e16\u0e36\u0e07\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e14\u0e49\u0e27\u0e22\" \/>\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\/th\/\u0e40\u0e27\u0e25\u0e32\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e02\u0e2d\u0e07\u0e41\u0e1e\u0e19\/\" \/>\n<meta property=\"og:locale\" content=\"th_TH\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u0e27\u0e34\u0e18\u0e35\u0e41\u0e1b\u0e25\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\/\u0e40\u0e27\u0e25\u0e32\u0e43\u0e19 Pandas - Statorials\" \/>\n<meta property=\"og:description\" content=\"\u0e1a\u0e17\u0e0a\u0e48\u0e27\u0e22\u0e2a\u0e2d\u0e19\u0e19\u0e35\u0e49\u0e08\u0e30\u0e2d\u0e18\u0e34\u0e1a\u0e32\u0e22\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e41\u0e1b\u0e25\u0e07\u0e04\u0e48\u0e32\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e17\u0e31\u0e1a\u0e40\u0e27\u0e25\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e04\u0e48\u0e32\u0e27\u0e31\u0e19\u0e17\u0e35\u0e48\u0e41\u0e25\u0e30\u0e40\u0e27\u0e25\u0e32\u0e43\u0e19 Pandas DataFrame \u0e23\u0e27\u0e21\u0e16\u0e36\u0e07\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e14\u0e49\u0e27\u0e22\" \/>\n<meta property=\"og:url\" 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