{"id":3727,"date":"2023-07-15T21:54:45","date_gmt":"2023-07-15T21:54:45","guid":{"rendered":"https:\/\/statorials.org\/th\/pandas-%e0%b8%aa%e0%b8%a3%e0%b9%89%e0%b8%b2%e0%b8%87%e0%b8%84%e0%b8%ad%e0%b8%a5%e0%b8%b1%e0%b8%a1%e0%b8%99%e0%b9%8c%e0%b9%83%e0%b8%ab%e0%b8%a1%e0%b9%88%e0%b8%95%e0%b8%b2%e0%b8%a1%e0%b9%80%e0%b8%87\/"},"modified":"2023-07-15T21:54:45","modified_gmt":"2023-07-15T21:54:45","slug":"pandas-%e0%b8%aa%e0%b8%a3%e0%b9%89%e0%b8%b2%e0%b8%87%e0%b8%84%e0%b8%ad%e0%b8%a5%e0%b8%b1%e0%b8%a1%e0%b8%99%e0%b9%8c%e0%b9%83%e0%b8%ab%e0%b8%a1%e0%b9%88%e0%b8%95%e0%b8%b2%e0%b8%a1%e0%b9%80%e0%b8%87","status":"publish","type":"post","link":"https:\/\/statorials.org\/th\/pandas-%e0%b8%aa%e0%b8%a3%e0%b9%89%e0%b8%b2%e0%b8%87%e0%b8%84%e0%b8%ad%e0%b8%a5%e0%b8%b1%e0%b8%a1%e0%b8%99%e0%b9%8c%e0%b9%83%e0%b8%ab%e0%b8%a1%e0%b9%88%e0%b8%95%e0%b8%b2%e0%b8%a1%e0%b9%80%e0%b8%87\/","title":{"rendered":"Pandas: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 if else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02"},"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\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e43\u0e19 DataFrame \u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 if else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define conditions\n<\/span>conditions = [\n    (df[' <span style=\"color: #ff0000;\">column1<\/span> '] == ' <span style=\"color: #ff0000;\">A<\/span> ') &amp; (df[' <span style=\"color: #ff0000;\">column2<\/span> '] &lt; <span style=\"color: #008000;\">20<\/span> ),\n    (df[' <span style=\"color: #ff0000;\">column1<\/span> '] == ' <span style=\"color: #ff0000;\">A<\/span> ') &amp; (df[' <span style=\"color: #ff0000;\">column2<\/span> '] &gt;= <span style=\"color: #008000;\">20<\/span> ),\n    (df[' <span style=\"color: #ff0000;\">column1<\/span> '] == ' <span style=\"color: #ff0000;\">B<\/span> ') &amp; (df[' <span style=\"color: #ff0000;\">column2<\/span> '] &lt; <span style=\"color: #008000;\">20<\/span> ),\n    (df[' <span style=\"color: #ff0000;\">column1<\/span> '] == ' <span style=\"color: #ff0000;\">B<\/span> ') &amp; (df[' <span style=\"color: #ff0000;\">column2<\/span> '] &gt;= <span style=\"color: #008000;\">20<\/span> )\n]\n\n<span style=\"color: #008080;\">#define results\n<\/span>results = [' <span style=\"color: #ff0000;\">result1<\/span> ', ' <span style=\"color: #ff0000;\">result2<\/span> ', ' <span style=\"color: #ff0000;\">result3<\/span> ', ' <span style=\"color: #ff0000;\">result4<\/span> ']\n\n<span style=\"color: #008080;\">#create new column based on conditions in column1 and column2\n<\/span>df[' <span style=\"color: #ff0000;\">new_column<\/span> '] = np. <span style=\"color: #3366ff;\">select<\/span> (conditions, results)\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e19\u0e35\u0e49\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e0a\u0e37\u0e48\u0e2d <strong>new_column<\/strong> \u0e0b\u0e36\u0e48\u0e07\u0e04\u0e48\u0e32\u0e08\u0e30\u0e02\u0e36\u0e49\u0e19\u0e2d\u0e22\u0e39\u0e48\u0e01\u0e31\u0e1a\u0e04\u0e48\u0e32\u0e02\u0e2d\u0e07 <strong>column1<\/strong> \u0e41\u0e25\u0e30 <strong>column2<\/strong> \u0e43\u0e19 DataFrame<\/span><\/p>\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\u0e44\u0e27\u0e22\u0e32\u0e01\u0e23\u0e13\u0e4c\u0e19\u0e35\u0e49\u0e43\u0e19\u0e17\u0e32\u0e07\u0e1b\u0e0f\u0e34\u0e1a\u0e31\u0e15\u0e34<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 If Else \u0e2b\u0e25\u0e32\u0e22\u0e23\u0e32\u0e22\u0e01\u0e32\u0e23\u0e43\u0e19 Pandas<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u0e2a\u0e21\u0e21\u0e15\u0e34\u0e27\u0e48\u0e32\u0e40\u0e23\u0e32\u0e21\u0e35 DataFrame \u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e0b\u0e36\u0e48\u0e07\u0e21\u0e35\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e40\u0e01\u0e35\u0e48\u0e22\u0e27\u0e01\u0e31\u0e1a\u0e1c\u0e39\u0e49\u0e40\u0e25\u0e48\u0e19\u0e1a\u0e32\u0e2a\u0e40\u0e01\u0e15\u0e1a\u0e2d\u0e25\u0e15\u0e48\u0e32\u0e07\u0e46:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [15, 18, 22, 24, 12, 17, 20, 28]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points\n0 to 15\n1 to 18\n2 to 22\n3 to 24\n4 B 12\n5 B 17\n6 B 20\n7 B 28\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\u0e15\u0e2d\u0e19\u0e19\u0e35\u0e49 \u0e2a\u0e21\u0e21\u0e15\u0e34\u0e27\u0e48\u0e32\u0e40\u0e23\u0e32\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e17\u0e35\u0e48\u0e40\u0e23\u0e35\u0e22\u0e01\u0e27\u0e48\u0e32 <strong>\u0e04\u0e25\u0e32\u0e2a<\/strong> \u0e0b\u0e36\u0e48\u0e07\u0e08\u0e30\u0e41\u0e22\u0e01\u0e1b\u0e23\u0e30\u0e40\u0e20\u0e17\u0e1c\u0e39\u0e49\u0e40\u0e25\u0e48\u0e19\u0e41\u0e15\u0e48\u0e25\u0e30\u0e04\u0e19\u0e43\u0e2b\u0e49\u0e40\u0e1b\u0e47\u0e19\u0e2b\u0e19\u0e36\u0e48\u0e07\u0e43\u0e19\u0e2a\u0e35\u0e48\u0e01\u0e25\u0e38\u0e48\u0e21\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49:<\/span><\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>Bad_A<\/strong> \u0e16\u0e49\u0e32\u0e17\u0e35\u0e21\u0e40\u0e1b\u0e47\u0e19 A \u0e41\u0e25\u0e30\u0e04\u0e30\u0e41\u0e19\u0e19 &lt; 20<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>Good_A<\/strong> \u0e16\u0e49\u0e32\u0e17\u0e35\u0e21\u0e40\u0e1b\u0e47\u0e19 A \u0e41\u0e25\u0e30\u0e04\u0e30\u0e41\u0e19\u0e19 \u2265 20<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>Bad_B<\/strong> \u0e16\u0e49\u0e32\u0e17\u0e35\u0e21\u0e40\u0e1b\u0e47\u0e19 B \u0e41\u0e25\u0e30\u0e04\u0e30\u0e41\u0e19\u0e19 &lt; 20<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>Good_B<\/strong> \u0e16\u0e49\u0e32\u0e17\u0e35\u0e21\u0e40\u0e1b\u0e47\u0e19 B \u0e41\u0e25\u0e30\u0e04\u0e30\u0e41\u0e19\u0e19 \u2265 20<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0e40\u0e23\u0e32\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e44\u0e27\u0e22\u0e32\u0e01\u0e23\u0e13\u0e4c\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e17\u0e33\u0e2a\u0e34\u0e48\u0e07\u0e19\u0e35\u0e49:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np<\/span>\n\n#define conditions\n<\/span>conditions = [\n    (df[' <span style=\"color: #ff0000;\">team<\/span> '] == ' <span style=\"color: #ff0000;\">A<\/span> ') &amp; (df[' <span style=\"color: #ff0000;\">points<\/span> '] &lt; <span style=\"color: #008000;\">20<\/span> ),\n    (df[' <span style=\"color: #ff0000;\">team<\/span> '] == ' <span style=\"color: #ff0000;\">A<\/span> ') &amp; (df[' <span style=\"color: #ff0000;\">points<\/span> '] &gt;= <span style=\"color: #008000;\">20<\/span> ),\n    (df[' <span style=\"color: #ff0000;\">team<\/span> '] == ' <span style=\"color: #ff0000;\">B<\/span> ') &amp; (df[' <span style=\"color: #ff0000;\">points<\/span> '] &lt; <span style=\"color: #008000;\">20<\/span> ),\n    (df[' <span style=\"color: #ff0000;\">team<\/span> '] == ' <span style=\"color: #ff0000;\">B<\/span> ') &amp; (df[' <span style=\"color: #ff0000;\">points<\/span> '] &gt;= <span style=\"color: #008000;\">20<\/span> )\n]\n\n<span style=\"color: #008080;\">#define results\n<\/span>results = [' <span style=\"color: #ff0000;\">Bad_A<\/span> ', ' <span style=\"color: #ff0000;\">Good_A<\/span> ', ' <span style=\"color: #ff0000;\">Bad_B<\/span> ', ' <span style=\"color: #ff0000;\">Good_B<\/span> ']\n\n<span style=\"color: #008080;\">#create new column based on conditions in column1 and column2\n<\/span>df[' <span style=\"color: #ff0000;\">class<\/span> '] = np. <span style=\"color: #3366ff;\">select<\/span> (conditions, results)\n\n<span style=\"color: #008080;\">#view updated DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points class\n0 A 15 Bad_A\n1 A 18 Bad_A\n2 A 22 Good_A\n3 A 24 Good_A\n4 B 12 Bad_B\n5 B 17 Bad_B\n6 B 20 Good_B\n7 B 28 Good_B<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e17\u0e35\u0e48\u0e40\u0e23\u0e35\u0e22\u0e01\u0e27\u0e48\u0e32 <strong>\u0e04\u0e25\u0e32\u0e2a<\/strong> \u0e08\u0e30\u0e41\u0e2a\u0e14\u0e07\u0e2d\u0e31\u0e19\u0e14\u0e31\u0e1a\u0e02\u0e2d\u0e07\u0e1c\u0e39\u0e49\u0e40\u0e25\u0e48\u0e19\u0e41\u0e15\u0e48\u0e25\u0e30\u0e04\u0e19\u0e15\u0e32\u0e21\u0e04\u0e48\u0e32\u0e43\u0e19\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c <strong>\u0e17\u0e35\u0e21<\/strong> \u0e41\u0e25\u0e30 <strong>\u0e04\u0e30\u0e41\u0e19\u0e19<\/strong><\/span><\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u0e2b\u0e21\u0e32\u0e22\u0e40\u0e2b\u0e15\u0e38<\/strong> : \u0e04\u0e38\u0e13\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e14\u0e39\u0e40\u0e2d\u0e01\u0e2a\u0e32\u0e23\u0e09\u0e1a\u0e31\u0e1a\u0e40\u0e15\u0e47\u0e21\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e1f\u0e31\u0e07\u0e01\u0e4c\u0e0a\u0e31\u0e19 NumPy <strong>select()<\/strong> <a href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.select.html\" target=\"_blank\" rel=\"noopener\">\u0e44\u0e14\u0e49\u0e17\u0e35\u0e48\u0e19\u0e35\u0e48<\/a><\/span><\/p>\n<h2> <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><\/h2>\n<p> <span style=\"color: #000000;\">\u0e1a\u0e17\u0e0a\u0e48\u0e27\u0e22\u0e2a\u0e2d\u0e19\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e08\u0e30\u0e2d\u0e18\u0e34\u0e1a\u0e32\u0e22\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e17\u0e33\u0e07\u0e32\u0e19\u0e17\u0e31\u0e48\u0e27\u0e44\u0e1b\u0e2d\u0e37\u0e48\u0e19\u0e46 \u0e43\u0e19\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/th\/\u0e19\u0e38\u0e48\u0e19\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e1a\u0e39\u0e25\u0e35\u0e19\u0e15\u0e32\u0e21\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u0e27\u0e34\u0e18\u0e35\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e1a\u0e39\u0e25\u0e35\u0e19\u0e15\u0e32\u0e21\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02<\/a><br \/> <a href=\"https:\/\/statorials.org\/th\/\u0e19\u0e38\u0e48\u0e19\u0e19\u0e31\u0e1a\u0e04\u0e48\u0e32\u0e43\u0e19\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e42\u0e14\u0e22\u0e21\u0e35\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u0e27\u0e34\u0e18\u0e35\u0e19\u0e31\u0e1a\u0e04\u0e48\u0e32\u0e43\u0e19\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e17\u0e35\u0e48\u0e21\u0e35\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02<\/a><br \/> <a href=\"https:\/\/statorials.org\/th\/\u0e41\u0e1e\u0e19\u0e14\u0e49\u0e32-groupby-\u0e19\u0e31\u0e1a\u0e41\u0e1a\u0e1a\u0e21\u0e35\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u0e27\u0e34\u0e18\u0e35\u0e43\u0e0a\u0e49 Groupby \u0e41\u0e25\u0e30\u0e19\u0e31\u0e1a\u0e41\u0e1a\u0e1a\u0e21\u0e35\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02<\/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\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e43\u0e19 Dat [&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-3727","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>Pandas: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 If Else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 - \u0e2a\u0e16\u0e34\u0e15\u0e34<\/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\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e43\u0e19 DataFrame \u0e02\u0e2d\u0e07 pandas \u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 if else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 \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\/pandas-\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e15\u0e32\u0e21\u0e40\u0e07\/\" \/>\n<meta property=\"og:locale\" content=\"th_TH\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 If Else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 - \u0e2a\u0e16\u0e34\u0e15\u0e34\" \/>\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\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e43\u0e19 DataFrame \u0e02\u0e2d\u0e07 pandas \u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 if else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 \u0e23\u0e27\u0e21\u0e16\u0e36\u0e07\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e14\u0e49\u0e27\u0e22\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/th\/pandas-\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e15\u0e32\u0e21\u0e40\u0e07\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-15T21:54:45+00:00\" \/>\n<meta name=\"author\" content=\"\u0e14\u0e23.\u0e40\u0e1a\u0e19\u0e08\u0e32\u0e21\u0e34\u0e19 \u0e41\u0e2d\u0e19\u0e40\u0e14\u0e2d\u0e23\u0e4c\u0e2a\u0e31\u0e19\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u0e14\u0e23.\u0e40\u0e1a\u0e19\u0e08\u0e32\u0e21\u0e34\u0e19 \u0e41\u0e2d\u0e19\u0e40\u0e14\u0e2d\u0e23\u0e4c\u0e2a\u0e31\u0e19\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 \u0e19\u0e32\u0e17\u0e35\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/th\/pandas-%e0%b8%aa%e0%b8%a3%e0%b9%89%e0%b8%b2%e0%b8%87%e0%b8%84%e0%b8%ad%e0%b8%a5%e0%b8%b1%e0%b8%a1%e0%b8%99%e0%b9%8c%e0%b9%83%e0%b8%ab%e0%b8%a1%e0%b9%88%e0%b8%95%e0%b8%b2%e0%b8%a1%e0%b9%80%e0%b8%87\/\",\"url\":\"https:\/\/statorials.org\/th\/pandas-%e0%b8%aa%e0%b8%a3%e0%b9%89%e0%b8%b2%e0%b8%87%e0%b8%84%e0%b8%ad%e0%b8%a5%e0%b8%b1%e0%b8%a1%e0%b8%99%e0%b9%8c%e0%b9%83%e0%b8%ab%e0%b8%a1%e0%b9%88%e0%b8%95%e0%b8%b2%e0%b8%a1%e0%b9%80%e0%b8%87\/\",\"name\":\"Pandas: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 If Else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 - \u0e2a\u0e16\u0e34\u0e15\u0e34\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/th\/#website\"},\"datePublished\":\"2023-07-15T21:54:45+00:00\",\"dateModified\":\"2023-07-15T21:54:45+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/th\/#\/schema\/person\/7c9bb3d0f799d0f1b17883495e1de332\"},\"description\":\"\u0e1a\u0e17\u0e0a\u0e48\u0e27\u0e22\u0e2a\u0e2d\u0e19\u0e19\u0e35\u0e49\u0e08\u0e30\u0e2d\u0e18\u0e34\u0e1a\u0e32\u0e22\u0e27\u0e34\u0e18\u0e35\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e43\u0e19 DataFrame \u0e02\u0e2d\u0e07 pandas \u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 if else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 \u0e23\u0e27\u0e21\u0e16\u0e36\u0e07\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e14\u0e49\u0e27\u0e22\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/th\/pandas-%e0%b8%aa%e0%b8%a3%e0%b9%89%e0%b8%b2%e0%b8%87%e0%b8%84%e0%b8%ad%e0%b8%a5%e0%b8%b1%e0%b8%a1%e0%b8%99%e0%b9%8c%e0%b9%83%e0%b8%ab%e0%b8%a1%e0%b9%88%e0%b8%95%e0%b8%b2%e0%b8%a1%e0%b9%80%e0%b8%87\/#breadcrumb\"},\"inLanguage\":\"th\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/th\/pandas-%e0%b8%aa%e0%b8%a3%e0%b9%89%e0%b8%b2%e0%b8%87%e0%b8%84%e0%b8%ad%e0%b8%a5%e0%b8%b1%e0%b8%a1%e0%b8%99%e0%b9%8c%e0%b9%83%e0%b8%ab%e0%b8%a1%e0%b9%88%e0%b8%95%e0%b8%b2%e0%b8%a1%e0%b9%80%e0%b8%87\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/th\/pandas-%e0%b8%aa%e0%b8%a3%e0%b9%89%e0%b8%b2%e0%b8%87%e0%b8%84%e0%b8%ad%e0%b8%a5%e0%b8%b1%e0%b8%a1%e0%b8%99%e0%b9%8c%e0%b9%83%e0%b8%ab%e0%b8%a1%e0%b9%88%e0%b8%95%e0%b8%b2%e0%b8%a1%e0%b9%80%e0%b8%87\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u0e1a\u0e49\u0e32\u0e19\",\"item\":\"https:\/\/statorials.org\/th\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Pandas: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e04\u0e2d\u0e25\u0e31\u0e21\u0e19\u0e4c\u0e43\u0e2b\u0e21\u0e48\u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02 if else \u0e2b\u0e25\u0e32\u0e22\u0e40\u0e07\u0e37\u0e48\u0e2d\u0e19\u0e44\u0e02\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/th\/#website\",\"url\":\"https:\/\/statorials.org\/th\/\",\"name\":\"Statorials\",\"description\":\"\u0e04\u0e33\u0e41\u0e19\u0e30\u0e19\u0e33\u0e02\u0e2d\u0e07\u0e04\u0e38\u0e13\u0e40\u0e01\u0e35\u0e48\u0e22\u0e27\u0e01\u0e31\u0e1a\u0e04\u0e27\u0e32\u0e21\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e17\u0e32\u0e07\u0e2a\u0e16\u0e34\u0e15\u0e34!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/th\/?s={search_term_string}\"},\"query-input\":\"required 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\u0e28\u0e32\u0e2a\u0e15\u0e23\u0e32\u0e08\u0e32\u0e23\u0e22\u0e4c\u0e2a\u0e16\u0e34\u0e15\u0e34\u0e40\u0e01\u0e29\u0e35\u0e22\u0e13\u0e2d\u0e32\u0e22\u0e38\u0e41\u0e25\u0e49\u0e27 \u0e41\u0e25\u0e30\u0e1c\u0e31\u0e19\u0e15\u0e31\u0e27\u0e21\u0e32\u0e40\u0e1b\u0e47\u0e19\u0e04\u0e23\u0e39\u0e2a\u0e2d\u0e19\u0e2a\u0e16\u0e34\u0e15\u0e34\u0e42\u0e14\u0e22\u0e40\u0e09\u0e1e\u0e32\u0e30 \u0e14\u0e49\u0e27\u0e22\u0e1b\u0e23\u0e30\u0e2a\u0e1a\u0e01\u0e32\u0e23\u0e13\u0e4c\u0e41\u0e25\u0e30\u0e04\u0e27\u0e32\u0e21\u0e40\u0e0a\u0e35\u0e48\u0e22\u0e27\u0e0a\u0e32\u0e0d\u0e17\u0e35\u0e48\u0e01\u0e27\u0e49\u0e32\u0e07\u0e02\u0e27\u0e32\u0e07\u0e43\u0e19\u0e2a\u0e32\u0e02\u0e32\u0e2a\u0e16\u0e34\u0e15\u0e34 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