{"id":2350,"date":"2023-07-22T16:05:32","date_gmt":"2023-07-22T16:05:32","guid":{"rendered":"https:\/\/statorials.org\/cn\/python-%e5%b8%95%e7%b4%af%e6%89%98%e5%9b%be\/"},"modified":"2023-07-22T16:05:32","modified_gmt":"2023-07-22T16:05:32","slug":"python-%e5%b8%95%e7%b4%af%e6%89%98%e5%9b%be","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/python-%e5%b8%95%e7%b4%af%e6%89%98%e5%9b%be\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u521b\u5efa\u5e15\u7d2f\u6258\u56fe\uff08\u5206\u6b65\uff09"},"content":{"rendered":"

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\u5e15\u7d2f\u6258\u56fe<\/strong>\u662f\u4e00\u79cd\u663e\u793a\u7c7b\u522b\u7684\u6709\u5e8f\u9891\u7387\u4ee5\u53ca\u7c7b\u522b\u7684\u7d2f\u79ef\u9891\u7387\u7684\u56fe\u8868\u3002<\/span> <\/p>\n

\"Python<\/p>\n

\u672c\u6559\u7a0b\u63d0\u4f9b\u4e86\u4f7f\u7528 Python \u521b\u5efa Pareto \u56fe\u7684\u5206\u6b65\u793a\u4f8b\u3002<\/span><\/p>\n

\u7b2c 1 \u6b65\uff1a\u521b\u5efa\u6570\u636e<\/strong><\/span><\/h3>\n

\u5047\u8bbe\u6211\u4eec\u8fdb\u884c\u4e00\u9879\u8c03\u67e5\uff0c\u8981\u6c42 350 \u540d\u4e0d\u540c\u7684\u4eba\u5728\u54c1\u724c A\u3001B\u3001C\u3001D \u548c E \u4e4b\u95f4\u627e\u51fa\u4ed6\u4eec\u6700\u559c\u6b22\u7684\u8c37\u7269\u54c1\u724c\u3002<\/span><\/p>\n

\u6211\u4eec\u53ef\u4ee5\u521b\u5efa\u4ee5\u4e0b pandas DataFrame \u6765\u4fdd\u5b58\u8c03\u67e5\u7ed3\u679c\uff1a<\/span><\/p>\n

 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' count<\/span> ': [97, 140, 58, 6, 17, 32]})\ndf. index<\/span> = ['B', 'A', 'C', 'F', 'E', 'D']\n\n#sort DataFrame by count descending\n<\/span>df = df. sort_values<\/span> (by=' count<\/span> ', ascending= False<\/span> )\n\n#add column to display cumulative percentage\n<\/span>df[' cumperc<\/span> '] = df[' count<\/span> ']. cumsum<\/span> ()\/df[' count<\/span> ']. sum<\/span> ()*100\n\n#view DataFrame\n<\/span>df\n\n\tcount cumperc\nAt 140 40.000000\nB 97 67.714286\nC 58 84.285714\nD 32 93.428571\nE 17 98.285714\nF 6 100.000000<\/strong><\/pre>\n
\u7b2c 2 \u6b65\uff1a\u521b\u5efa\u5e15\u7d2f\u6258\u56fe<\/strong><\/span><\/h3>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u6765\u521b\u5efa Pareto \u56fe\uff1a<\/span><\/span> <\/p>\n
 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\nfrom<\/span> matplotlib. ticker<\/span> import<\/span> PercentFormatter\n\n#define aesthetics for plot\n<\/span>color1 = ' steelblue<\/span> '\ncolor2 = ' red<\/span> '\nline_size = 4\n\n#create basic bar plot\n<\/span>fig, ax = plt. subplots<\/span> ()\nax. bar<\/span> (df. index<\/span> , df[' count<\/span> '], color=color1)\n\n#add cumulative percentage line to plot\n<\/span>ax2 = ax. twinx<\/span> ()\nax2. plot<\/span> ( df.index<\/span> , df[' cumperc<\/span> '], color=color2, marker=\" D<\/span> \", ms=line_size)\nax2. yaxis<\/span> . set_major_formatter<\/span> (PercentFormatter())\n\n#specify axis colors\n<\/span>ax. tick_params<\/span> (axis=' y<\/span> ', colors=color1)\nax2. tick_params<\/span> (axis=' y<\/span> ', colors=color2)<\/span>\n\n#display Pareto chart\nplt. show<\/span> ()\n<\/span><\/span><\/strong><\/pre>\n
\"Python<\/p>\n
 X \u8f74\u663e\u793a\u4e0d\u540c\u54c1\u724c\u7684\u9891\u7387\u4ece\u6700\u9ad8\u5230\u6700\u4f4e\u7684\u987a\u5e8f\u3002<\/span><\/p>\n
\u5de6y\u8f74\u663e\u793a\u6bcf\u4e2a\u54c1\u724c\u7684\u9891\u7387\uff0c\u53f3y\u8f74\u663e\u793a\u54c1\u724c\u7684\u7d2f\u79ef\u9891\u7387\u3002<\/span><\/p>\n
\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff1a<\/span><\/p>\n