{"id":2517,"date":"2023-07-21T22:38:17","date_gmt":"2023-07-21T22:38:17","guid":{"rendered":"https:\/\/statorials.org\/cn\/python%e4%b8%ad%e7%9a%84%e6%95%b0%e6%8d%ae%e5%88%86%e7%bb%84\/"},"modified":"2023-07-21T22:38:17","modified_gmt":"2023-07-21T22:38:17","slug":"python%e4%b8%ad%e7%9a%84%e6%95%b0%e6%8d%ae%e5%88%86%e7%bb%84","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/python%e4%b8%ad%e7%9a%84%e6%95%b0%e6%8d%ae%e5%88%86%e7%bb%84\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u8fdb\u884c\u6570\u636e\u5206\u7ec4\uff1a\u793a\u4f8b"},"content":{"rendered":"

<\/p>\n

\n

\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u57fa\u672c\u8bed\u6cd5\u5bf9 pandas DataFrame \u6267\u884c\u6570\u636e\u5206\u7ec4\uff1a<\/span><\/p>\n

 import<\/span> pandas as<\/span> pd\n\n#perform binning with 3 bins<\/span>\ndf[' new_bin<\/span> '] = pd. qcut<\/span> (df[' variable_name<\/span> '], q= 3<\/span> )\n<\/strong><\/pre>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u901a\u8fc7\u4ee5\u4e0b pandas DataFrame \u4f7f\u7528\u6b64\u8bed\u6cd5\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' points<\/span> ': [4, 4, 7, 8, 12, 13, 15, 18, 22, 23, 23, 25],\n                   ' assists<\/span> ': [2, 5, 4, 7, 7, 8, 5, 4, 5, 11, 13, 8],\n                   ' rebounds<\/span> ': [7, 7, 4, 6, 3, 8, 9, 9, 12, 11, 8, 9]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n    points assists rebounds\n0 4 2 7\n1 4 5 7\n2 7 4 4\n3 8 7 6\n4 12 7 3\n5 13 8 8\n6 15 5 9\n7 18 4 9\n8 22 5 12\n9 23 11 11\n10 23 13 8\n11 25 8 9\n<\/span><\/span><\/strong><\/pre>\n
\u793a\u4f8b1\uff1a\u6267\u884c\u4e3b\u6570\u636e\u5206\u7ec4<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528\u5177\u6709\u7279\u5b9a\u65ad\u70b9\u6807\u8bb0\u7684qcut()<\/a>\u51fd\u6570\u5bf9\u70b9<\/strong>\u53d8\u91cf\u6267\u884c\u6570\u636e\u5206\u7ec4\uff1a<\/span><\/p>\n
 #perform data binning on variable points<\/em>\n<\/span>df[' points_bin<\/span> '] = pd. qcut<\/span> (df[' points<\/span> '], q= 3<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n    points assists rebounds points_bin\n0 4 2 7 (3,999, 10,667]\n1 4 5 7 (3,999, 10,667]\n2 7 4 4 (3,999, 10,667]\n3 8 7 6 (3,999, 10,667]\n4 12 7 3 (10,667, 19,333]\n5 13 8 8 (10,667, 19,333]\n6 15 5 9 (10,667, 19,333]\n7 18 4 9 (10,667, 19,333]\n8 22 5 12 (19.333, 25.0]\n9 23 11 11 (19.333, 25.0]\n10 23 13 8 (19.333, 25.0]\n11 25 8 9 (19.333, 25.0]\n<\/span><\/span><\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u6570\u636e\u6846\u4e2d\u7684\u6bcf\u4e00\u884c\u5df2\u6839\u636e\u70b9\u5217\u7684\u503c\u653e\u5165\u4e09\u4e2a\u7ec4\u4e4b\u4e00\u3002<\/span><\/p>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528value_counts()<\/strong>\u51fd\u6570\u6765\u67e5\u627e\u6bcf\u4e2a bin \u4e2d\u653e\u7f6e\u4e86\u591a\u5c11\u884c\uff1a<\/span><\/p>\n
 #count frequency of each bin\n<\/span>df[' points_bin<\/span> ']. value_counts<\/span> ()\n\n(3,999, 10,667] 4\n(10.667, 19.333] 4\n(19.333, 25.0] 4\nName: points_bin, dtype: int64\n<\/span><\/span><\/strong><\/pre>\n
\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u6bcf\u4e2a bin \u5305\u542b 4 \u4e2a\u89c2\u6d4b\u503c\u3002<\/span><\/p>\n
\u793a\u4f8b 2\uff1a\u4f7f\u7528\u7279\u5b9a\u5206\u4f4d\u6570\u6267\u884c\u6570\u636e\u805a\u7c7b<\/strong><\/span><\/h3>\n
\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528\u7279\u5b9a\u5206\u4f4d\u6570\u6267\u884c\u6570\u636e\u805a\u7c7b\uff1a<\/span><\/p>\n
 #perform data binning on variable points<\/em> with specific quantiles\n<\/span>df[' points_bin<\/span> '] = pd. qcut<\/span> (df[' points<\/span> '], q=[0, .2, .4, .6, .8, 1])\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n    points assists rebounds points_bin\n0 4 2 7 (3.999, 7.2]\n1 4 5 7 (3.999, 7.2]\n2 7 4 4 (3.999, 7.2]\n3 8 7 6 (7.2, 12.4]\n4 12 7 3 (7.2, 12.4]\n5 13 8 8 (12.4, 16.8]\n6 15 5 9 (12.4, 16.8]\n7 18 4 9 (16.8, 22.8]\n8 22 5 12 (16.8, 22.8]\n9 23 11 11 (22.8, 25.0]\n10 23 13 8 (22.8, 25.0]\n11 25 8 9 (22.8, 25.0]\n<\/span><\/span><\/strong><\/pre>\n
\u793a\u4f8b 3\uff1a<\/strong><\/span>\u4f7f\u7528\u6807\u7b7e\u8fdb\u884c\u6570\u636e\u5206\u7ec4<\/strong><\/span><\/h3>\n
\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528\u7279\u5b9a\u7684\u5206\u4f4d\u6570\u548c\u6807\u7b7e\u6765\u6267\u884c\u6570\u636e\u5206\u7ec4\uff1a<\/span><\/p>\n
 #perform data binning on points<\/em> variable with specific quantiles and labels\n<\/span>df[' points_bin<\/span> '] = pd. qcut<\/span> (df[' points<\/span> '],\n                           q=[0, .2, .4, .6, .8, 1],\n                           labels=[' A<\/span> ',' B<\/span> ',' C<\/span> ',' D<\/span> ',' E<\/span> '])\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n    points assists rebounds points_bin\n0 4 2 7 A\n1 4 5 7 A\n2 7 4 4 A\n3 8 7 6 B\n4 12 7 3 B\n5 13 8 8 C\n6 15 5 9 C\n7 18 4 9 D\n8 22 5 12 D\n9 23 11 11 E\n10 23 13 8 E\n11 25 8 9 E\n<\/span><\/span><\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u6bcf\u884c\u90fd\u6839\u636e\u70b9<\/strong>\u5217\u503c\u5206\u914d\u4e86\u4e00\u4e2a\u5bb9\u5668\uff0c\u5e76\u4e14\u5bb9\u5668\u5df2\u4f7f\u7528\u5b57\u6bcd\u8fdb\u884c\u6807\u8bb0\u3002<\/span><\/p>\n
\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u4efb\u52a1\uff1a<\/span><\/p>\n
 Pandas\uff1a\u5982\u4f55\u4f7f\u7528 value_counts() \u51fd\u6570<\/a>
Pandas\uff1a\u5982\u4f55\u521b\u5efa\u5305\u542b\u591a\u4e2a\u503c\u7684\u6570\u636e\u900f\u89c6\u8868<\/a>
Pandas\uff1a\u5982\u4f55\u8ba1\u7b97\u5217\u4e2d\u7279\u5b9a\u503c\u7684\u51fa\u73b0\u6b21\u6570<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u57fa\u672c\u8bed\u6cd5\u5bf9 pandas DataFrame \u6267\u884c\u6570\u636e\u5206\u7ec4\uff1a import pandas as  […]<\/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-2517","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u6570\u636e\u805a\u7c7b\uff08\u5e26\u6709\u793a\u4f8b\uff09 - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u51e0\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u6570\u636e\u5206\u7ec4\u3002\" \/>\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\/cn\/python\u4e2d\u7684\u6570\u636e\u5206\u7ec4\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u6570\u636e\u805a\u7c7b\uff08\u5e26\u6709\u793a\u4f8b\uff09 - 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