{"id":1215,"date":"2023-07-27T06:29:39","date_gmt":"2023-07-27T06:29:39","guid":{"rendered":"https:\/\/statorials.org\/th\/%e0%b8%95%e0%b8%b2%e0%b8%a3%e0%b8%b2%e0%b8%87-matplotlib\/"},"modified":"2023-07-27T06:29:39","modified_gmt":"2023-07-27T06:29:39","slug":"%e0%b8%95%e0%b8%b2%e0%b8%a3%e0%b8%b2%e0%b8%87-matplotlib","status":"publish","type":"post","link":"https:\/\/statorials.org\/th\/%e0%b8%95%e0%b8%b2%e0%b8%a3%e0%b8%b2%e0%b8%87-matplotlib\/","title":{"rendered":"\u0e27\u0e34\u0e18\u0e35\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07\u0e14\u0e49\u0e27\u0e22 matplotlib"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0e04\u0e38\u0e13\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e27\u0e34\u0e18\u0e35\u0e43\u0e14\u0e27\u0e34\u0e18\u0e35\u0e2b\u0e19\u0e36\u0e48\u0e07\u0e08\u0e32\u0e01\u0e2a\u0e2d\u0e07\u0e27\u0e34\u0e18\u0e35\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07\u0e43\u0e19 Python \u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49 Matplotlib:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u0e27\u0e34\u0e18\u0e35\u0e17\u0e35\u0e48 1: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07\u0e08\u0e32\u0e01 pandas DataFrame<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create pandas DataFrame\n<\/span>df = pd.DataFrame(np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">randn<\/span> (20, 2), columns=[' <span style=\"color: #008000;\">First<\/span> ', ' <span style=\"color: #008000;\">Second<\/span> '])\n\n<span style=\"color: #008080;\">#create table\n<\/span>table = ax. <span style=\"color: #3366ff;\">table<\/span> (cellText=df. <span style=\"color: #3366ff;\">values<\/span> , colLabels=df. <span style=\"color: #3366ff;\">columns<\/span> , loc=' <span style=\"color: #008000;\">center<\/span> ')\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u0e27\u0e34\u0e18\u0e35\u0e17\u0e35\u0e48 2: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e2d\u0e32\u0e23\u0e4c\u0e40\u0e23\u0e22\u0e4c\u0e08\u0e32\u0e01\u0e04\u0e48\u0e32\u0e17\u0e35\u0e48\u0e01\u0e33\u0e2b\u0e19\u0e14\u0e40\u0e2d\u0e07<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create values for table\n<\/span>table_data=[\n    [\"Player 1\", 30],\n    [\"Player 2\", 20],\n    [\"Player 3\", 33],\n    [\"Player 4\", 25],\n    [\"Player 5\", 12]\n]\n\n<span style=\"color: #008080;\">#create table\n<\/span>table = ax. <span style=\"color: #3366ff;\">table<\/span> (cellText=table_data, loc=' <span style=\"color: #008000;\">center<\/span> ')<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0e1a\u0e17\u0e0a\u0e48\u0e27\u0e22\u0e2a\u0e2d\u0e19\u0e19\u0e35\u0e49\u0e43\u0e2b\u0e49\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e27\u0e34\u0e18\u0e35\u0e01\u0e32\u0e23\u0e40\u0e2b\u0e25\u0e48\u0e32\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: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07\u0e08\u0e32\u0e01 Pandas DataFrame<\/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\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07\u0e43\u0e19 Matplotlib \u0e17\u0e35\u0e48\u0e21\u0e35\u0e04\u0e48\u0e32\u0e02\u0e2d\u0e07 pandas DataFrame:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n<span style=\"color: #008000;\">import<\/span> matplotlib.pyplot <span style=\"color: #008000;\">as<\/span> plt\n\n<span style=\"color: #008080;\">#make this example reproducible\n<\/span>n.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (0)\n\n<span style=\"color: #008080;\">#define figure and axes\n<\/span>fig, ax = plt. <span style=\"color: #3366ff;\">subplots<\/span> ()\n\n<span style=\"color: #008080;\">#hide the axes\n<\/span>fig.patch. <span style=\"color: #3366ff;\">set_visible<\/span> (False)\nax.axis(' <span style=\"color: #008000;\">off<\/span> ')\nax.axis(' <span style=\"color: #008000;\">tight<\/span> ')\n\n<span style=\"color: #008080;\">#createdata\n<\/span>df = pd.DataFrame(np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">randn<\/span> (20, 2), columns=[' <span style=\"color: #008000;\">First<\/span> ', ' <span style=\"color: #008000;\">Second<\/span> '])\n\n<span style=\"color: #008080;\">#create table\n<\/span>table = ax. <span style=\"color: #3366ff;\">table<\/span> (cellText=df.values, colLabels=df.columns, loc=' <span style=\"color: #008000;\">center<\/span> ')\n\n<span style=\"color: #008080;\">#display table\n<\/span>fig. <span style=\"color: #3366ff;\">tight_layout<\/span> ()\nplt. <span style=\"color: #3366ff;\">show<\/span> ()<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-12030 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/tableau-1.png\" alt=\"\u0e15\u0e32\u0e23\u0e32\u0e07 Matplotlib\" width=\"393\" height=\"301\" srcset=\"\" sizes=\"auto, \"><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e17\u0e35\u0e48 2: \u0e2a\u0e23\u0e49\u0e32\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07\u0e08\u0e32\u0e01\u0e04\u0e48\u0e32\u0e17\u0e35\u0e48\u0e01\u0e33\u0e2b\u0e19\u0e14\u0e40\u0e2d\u0e07<\/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\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07\u0e43\u0e19 Matplotlib \u0e17\u0e35\u0e48\u0e21\u0e35\u0e04\u0e48\u0e32\u0e17\u0e35\u0e48\u0e01\u0e33\u0e2b\u0e19\u0e14\u0e40\u0e2d\u0e07:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n<span style=\"color: #008000;\">import<\/span> matplotlib.pyplot <span style=\"color: #008000;\">as<\/span> plt \n\n<span style=\"color: #008080;\">#define figure and axes\n<\/span>fig, ax = plt. <span style=\"color: #3366ff;\">subplots<\/span> ()\n\n<span style=\"color: #008080;\">#create values for table\n<span style=\"color: #000000;\">table_data=[\n    [\"Player 1\", 30],\n    [\"Player 2\", 20],\n    [\"Player 3\", 33],\n    [\"Player 4\", 25],\n    [\"Player 5\", 12]\n]\n\n<span style=\"color: #008080;\">#create table\n<\/span>table = ax. <span style=\"color: #3366ff;\">table<\/span> (cellText=table_data, loc=' <span style=\"color: #008000;\">center<\/span> ')\n\n<span style=\"color: #008080;\">#modify table\n<\/span>table. <span style=\"color: #3366ff;\">set_fontsize<\/span> (14)\ntable. <span style=\"color: #3366ff;\">scale<\/span> (1.4)\nax. <span style=\"color: #3366ff;\">axis<\/span> (' <span style=\"color: #008000;\">off<\/span> ')\n\n<span style=\"color: #008080;\">#displaytable\n<\/span>plt. <span style=\"color: #3366ff;\">show<\/span> ()<\/span><\/span><\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-12031 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/tableau-2.png\" alt=\"\u0e15\u0e32\u0e23\u0e32\u0e07 matplotlib \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e04\u0e48\u0e32\u0e17\u0e35\u0e48\u0e01\u0e33\u0e2b\u0e19\u0e14\u0e40\u0e2d\u0e07\" width=\"340\" height=\"248\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\u0e42\u0e1b\u0e23\u0e14\u0e17\u0e23\u0e32\u0e1a\u0e27\u0e48\u0e32 <strong>table.scale(width, length)<\/strong> \u0e08\u0e30\u0e1b\u0e23\u0e31\u0e1a\u0e40\u0e1b\u0e25\u0e35\u0e48\u0e22\u0e19\u0e04\u0e27\u0e32\u0e21\u0e01\u0e27\u0e49\u0e32\u0e07\u0e41\u0e25\u0e30\u0e04\u0e27\u0e32\u0e21\u0e22\u0e32\u0e27\u0e02\u0e2d\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07 \u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e40\u0e0a\u0e48\u0e19 \u0e40\u0e23\u0e32\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e17\u0e33\u0e43\u0e2b\u0e49\u0e15\u0e32\u0e23\u0e32\u0e07\u0e22\u0e32\u0e27\u0e02\u0e36\u0e49\u0e19\u0e42\u0e14\u0e22\u0e01\u0e32\u0e23\u0e40\u0e1b\u0e25\u0e35\u0e48\u0e22\u0e19\u0e04\u0e27\u0e32\u0e21\u0e22\u0e32\u0e27:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\">table. <span style=\"color: #3366ff;\">scale<\/span> (1.10)\n<\/span><\/span><\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-12032 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/tableau-3.png\" alt=\"\u0e15\u0e32\u0e23\u0e32\u0e07\u0e43\u0e19 matplotlib\" width=\"343\" height=\"611\" srcset=\"\" sizes=\"auto, \"><\/p>\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\/matplotlib-\u0e40\u0e1e\u0e34\u0e48\u0e21\u0e02\u0e49\u0e2d\u0e04\u0e27\u0e32\u0e21\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0e27\u0e34\u0e18\u0e35\u0e40\u0e1e\u0e34\u0e48\u0e21\u0e02\u0e49\u0e2d\u0e04\u0e27\u0e32\u0e21\u0e25\u0e07\u0e43\u0e19\u0e41\u0e1b\u0e25\u0e07 Matplotlib<\/a><br \/> <a href=\"https:\/\/statorials.org\/th\/\u0e2d\u0e31\u0e15\u0e23\u0e32\u0e2a\u0e48\u0e27\u0e19\u0e20\u0e32\u0e1e-matplotlib\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0e27\u0e34\u0e18\u0e35\u0e15\u0e31\u0e49\u0e07\u0e04\u0e48\u0e32\u0e2d\u0e31\u0e15\u0e23\u0e32\u0e2a\u0e48\u0e27\u0e19\u0e20\u0e32\u0e1e\u0e43\u0e19 Matplotlib<\/a><br \/> <a href=\"https:\/\/statorials.org\/th\/\u0e02\u0e19\u0e32\u0e14\u0e15\u0e31\u0e27\u0e2d\u0e31\u0e01\u0e29\u0e23\u0e15\u0e33\u0e19\u0e32\u0e19\u0e02\u0e2d\u0e07-matplotlib\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u0e27\u0e34\u0e18\u0e35\u0e40\u0e1b\u0e25\u0e35\u0e48\u0e22\u0e19\u0e02\u0e19\u0e32\u0e14\u0e15\u0e31\u0e27\u0e2d\u0e31\u0e01\u0e29\u0e23\u0e04\u0e33\u0e2d\u0e18\u0e34\u0e1a\u0e32\u0e22\u0e41\u0e1c\u0e19\u0e20\u0e39\u0e21\u0e34\u0e43\u0e19 Matplotlib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0e04\u0e38\u0e13\u0e2a\u0e32\u0e21\u0e32\u0e23\u0e16\u0e43\u0e0a\u0e49\u0e27\u0e34\u0e18\u0e35\u0e43\u0e14\u0e27\u0e34\u0e18\u0e35\u0e2b\u0e19\u0e36\u0e48\u0e07\u0e08\u0e32\u0e01\u0e2a\u0e2d\u0e07\u0e27\u0e34\u0e18\u0e35\u0e15\u0e48\u0e2d\u0e44\u0e1b\u0e19\u0e35\u0e49\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e2a\u0e23\u0e49\u0e32\u0e07 [&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-1215","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\u0e2a\u0e23\u0e49\u0e32\u0e07\u0e15\u0e32\u0e23\u0e32\u0e07\u0e14\u0e49\u0e27\u0e22 Matplotlib - Statology<\/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\u0e15\u0e32\u0e23\u0e32\u0e07\u0e42\u0e14\u0e22\u0e43\u0e0a\u0e49 Matplotlib \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e15\u0e31\u0e27\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e15\u0e48\u0e32\u0e07\u0e46\" 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