{"id":2238,"date":"2023-07-23T03:16:00","date_gmt":"2023-07-23T03:16:00","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e6%b5%b7%e6%b4%8b%e6%ac%a1%e8%a6%81%e6%83%85%e8%8a%82\/"},"modified":"2023-07-23T03:16:00","modified_gmt":"2023-07-23T03:16:00","slug":"%e6%b5%b7%e6%b4%8b%e6%ac%a1%e8%a6%81%e6%83%85%e8%8a%82","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e6%b5%b7%e6%b4%8b%e6%ac%a1%e8%a6%81%e6%83%85%e8%8a%82\/","title":{"rendered":"\u5982\u4f55\u5728 seaborn \u4e2d\u521b\u5efa\u5b50\u56fe\uff08\u9644\u793a\u4f8b\uff09"},"content":{"rendered":"

<\/p>\n

\n

\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u57fa\u672c\u8bed\u6cd5\u5728 Python \u7684Seaborn<\/a>\u6570\u636e\u53ef\u89c6\u5316\u5e93\u4e2d\u521b\u5efa\u5b50\u56fe\uff1a<\/span><\/p>\n

 #define dimensions of subplots (rows, columns)\n<\/span>fig, axes = plt. subplots<\/span> (2, 2)\n\n#create chart in each subplot\n<\/span>sns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' points<\/span> ', ax=axes[0,0])\nsns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' assists<\/span> ', ax=axes[0,1])\n\n...\n<\/strong><\/span><\/pre>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u6b64\u8bed\u6cd5\u3002<\/span><\/p>\n
\u793a\u4f8b\uff1a\u5728 Seaborn \u4e2d\u521b\u5efa\u5b50\u56fe<\/strong><\/span><\/h3>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b pandas DataFrame\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'],\n                   ' points<\/span> ': [19, 12, 15, 14, 19, 23, 25, 29],\n                   ' assists<\/span> ': [13, 15, 11, 8, 6, 8, 11, 14],\n                   ' rebounds<\/span> ': [11, 7, 8, 12, 13, 7, 6, 8],\n                   ' blocks<\/span> ': [1, 2, 2, 3, 5, 4, 3, 3]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  team points assists rebounds blocks\n0 A 19 13 11 1\n1 A 12 15 7 2\n2 A 15 11 8 2\n3 A 14 8 12 3\n4 B 19 6 13 5\n5 B 23 8 7 4\n6 B 25 11 6 3\n7 B 29 14 8 3<\/span><\/span><\/strong><\/pre>\n
\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u5982\u4f55\u5b9a\u4e49\u5177\u6709\u4e24\u884c\u548c\u4e24\u5217\u7684\u7ed8\u56fe\u533a\u57df\uff0c\u5e76\u5728\u6bcf\u4e2a\u5b50\u56fe\u4e2d\u4e3a DataFrame \u4e2d\u7684\u56db\u4e2a\u6570\u503c\u53d8\u91cf\u4e2d\u7684\u6bcf\u4e00\u4e2a\u521b\u5efa\u4e00\u4e2a\u7bb1\u7ebf\u56fe\uff1a<\/span> <\/p>\n
 import<\/span> matplotlib.<\/b><\/span> pyplot<\/span> <\/b>as<\/span> plt\n<\/b><\/span>import<\/span> seaborn<\/b><\/span> as<\/span> sns\n\n#set seaborn plotting aesthetics as default<\/span>\n<\/b><\/span>sns.<\/b><\/span> set<\/span> ()\n\n#define plotting region (2 rows, 2 columns)\n<\/span>fig, axes = plt.<\/b><\/span> subplots<\/span> (2, 2)\n\n<\/b><\/span>#create boxplot in each subplot\n<\/span>sns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' points<\/span> ', ax=axes[0,0])\nsns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' assists<\/span> ', ax=axes[0,1])\nsns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' rebounds<\/span> ', ax=axes[1,0])\nsns. boxplot<\/span> (data=df, x=' team<\/span> ', y=' blocks<\/span> ', ax=axes[1,1])\n<\/b><\/span><\/pre>\n
\"Python<\/p>\n
\u5728\u6b64\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u521b\u5efa\u4e86\u4e00\u4e2a\u5305\u542b\u4e24\u884c\u548c\u4e24\u5217\u7684\u7ed8\u56fe\u533a\u57df\uff0c\u5e76\u7528\u7bb1\u7ebf\u56fe\u586b\u5145\u4e86\u6bcf\u4e2a\u5b50\u56fe\u3002<\/span><\/p>\n
\u4f46\u662f\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u7c7b\u4f3c\u7684\u8bed\u6cd5\u6765\u521b\u5efa\u5177\u6709\u4e0d\u540c\u7ef4\u5ea6\u7684\u7ed8\u56fe\u533a\u57df\uff0c\u5e76\u4f7f\u7528\u4e0d\u540c\u7684\u56fe\u5f62\u586b\u5145\u5b50\u56fe\u3002<\/span><\/p>\n
\u4f8b\u5982\uff0c\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u5982\u4f55\u521b\u5efa\u4e00\u884c\u4e24\u5217\u7684\u7ed8\u56fe\u533a\u57df\uff0c\u5e76\u7528\u5c0f\u63d0\u7434\u56fe\u586b\u5145\u6bcf\u4e2a\u56fe\uff1a<\/span> <\/p>\n
 import<\/span> matplotlib.<\/b><\/span> pyplot<\/span> <\/b>as<\/span> plt\n<\/b><\/span>import<\/span> seaborn<\/b><\/span> as<\/span> sns\n\n#set seaborn plotting<\/span><\/b><\/span> aesthetics<\/b><\/span><\/span> as default\n<\/span>sns.<\/b><\/span> set<\/span> ()\n\n#define plotting region (1 row, 2 columns)\n<\/span>fig, axes = plt.<\/b><\/span> subplots<\/span> (1, 2)\n\n<\/b><\/span>#create boxplot in each subplot\n<\/span>sns. violinplot<\/span> (data=df, x=' team<\/span> ', y=' points<\/span> ', ax=axes[0])\nsns. violinplot<\/span> (data=df, x=' team<\/span> ', y=' assists<\/span> ', ax=axes[1])\n<\/b><\/span><\/pre>\n
\"\"<\/p>\n
\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728seaborn\u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u529f\u80fd\uff1a<\/span><\/p>\n
\u5982\u4f55\u4e3a Seaborn \u7ed8\u56fe\u6dfb\u52a0\u6807\u9898<\/a>
\u5982\u4f55\u5c06 Seaborn \u56fe\u4fdd\u5b58\u5230\u6587\u4ef6
\u5982\u4f55\u66f4\u6539 Seaborn \u4e2d\u56fe\u4f8b\u7684\u4f4d\u7f6e<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u57fa\u672c\u8bed\u6cd5\u5728 Python \u7684Seaborn\u6570\u636e\u53ef\u89c6\u5316\u5e93\u4e2d\u521b\u5efa\u5b50\u56fe\uff1a #define dimens […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-2238","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u5728 Seaborn \u4e2d\u521b\u5efa\u5b50\u56fe\uff08\u9644\u793a\u4f8b\uff09 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u51e0\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 Seaborn \u4e2d\u521b\u5efa\u5b50\u56fe\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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