{"id":853,"date":"2023-07-28T13:14:00","date_gmt":"2023-07-28T13:14:00","guid":{"rendered":"https:\/\/statorials.org\/cn\/python-%e9%a2%91%e7%8e%87%e8%a1%a8\/"},"modified":"2023-07-28T13:14:00","modified_gmt":"2023-07-28T13:14:00","slug":"python-%e9%a2%91%e7%8e%87%e8%a1%a8","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/python-%e9%a2%91%e7%8e%87%e8%a1%a8\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u521b\u5efa\u9891\u7387\u8868"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u9891\u7387\u8868<\/strong>\u662f\u663e\u793a\u4e0d\u540c\u7c7b\u522b\u7684\u9891\u7387\u7684\u8868\u683c\u3002\u8fd9\u79cd\u7c7b\u578b\u7684\u8868\u5bf9\u4e8e\u7406\u89e3\u6570\u636e\u96c6\u4e2d\u503c\u7684\u5206\u5e03\u7279\u522b\u6709\u7528\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 Python \u4e2d\u521b\u5efa\u9891\u7387\u8868\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4e00\u7cfb\u5217\u7684\u5355\u5411\u9891\u7387\u8868<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u8981\u67e5\u627e pandas \u7cfb\u5217\u4e2d\u5404\u4e2a\u503c\u7684\u9891\u7387\uff0c\u53ef\u4ee5\u4f7f\u7528<strong>value_counts()<\/strong>\u51fd\u6570\uff1a<\/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;\">#defineSeries<\/span>\ndata = pd.Series([1, 1, 1, 2, 3, 3, 3, 3, 4, 4, 5])\n\n<span style=\"color: #008080;\">#find frequencies of each value\n<\/span>data.value_counts()\n\n3 4\n1 3\n4 2\n5 1\n2 1\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5982\u679c\u60a8\u4e0d\u5e0c\u671b\u6570\u636e\u503c\u6309\u9891\u7387\u6392\u5e8f\uff0c\u53ef\u4ee5\u6dfb\u52a0<strong>sort=False<\/strong>\u53c2\u6570\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>data.value_counts(sort= <span style=\"color: #008000;\">False<\/span> )\n\n1 3\n2 1\n3 4\n4 2\n5 1<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u7ed3\u679c\u89e3\u91ca\u65b9\u5f0f\u5982\u4e0b\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u503c\u201c1\u201d\u5728\u8be5\u7cfb\u5217\u4e2d\u51fa\u73b0<strong>3<\/strong>\u6b21\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u503c\u201c2\u201d\u5728\u8be5\u7cfb\u5217\u4e2d\u51fa\u73b0<strong>1<\/strong>\u6b21\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u503c\u201c3\u201d\u5728\u8be5\u7cfb\u5217\u4e2d\u51fa\u73b0\u4e86<strong>4<\/strong>\u6b21\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7b49\u7b49\u3002<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>DataFrame<\/strong><\/span><span style=\"color: #000000;\"><strong>\u7684\u5355\u5411\u9891\u7387\u8868<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u8981\u67e5\u627e pandas DataFrame \u7684\u9891\u7387\uff0c\u53ef\u4ee5\u4f7f\u7528<strong>crosstab<\/strong> <strong>()<\/strong>\u51fd\u6570\uff0c\u8be5\u51fd\u6570\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u4ea4\u53c9\u8868\uff08\u7d22\u5f15\u3001\u5217\uff09<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\u5b50\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u7d22\u5f15\uff1a<\/strong>\u5206\u7ec4\u4f9d\u636e\u7684\u5217\u7684\u540d\u79f0<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>columns\uff1a<\/strong>\u9891\u7387\u5217\u7684\u540d\u79f0<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4e00\u4e2a DataFrame\uff0c\u5176\u4e2d\u5305\u542b\u73ed\u7ea7\u4e2d 10 \u540d\u4e0d\u540c\u5b66\u751f\u7684\u5e74\u7ea7\u3001\u5e74\u9f84\u548c\u6027\u522b\u4fe1\u606f\u3002\u4ee5\u4e0b\u662f\u67e5\u627e\u6bcf\u4e2a\u5b57\u6bcd\u7b49\u7ea7\u51fa\u73b0\u9891\u7387\u7684\u65b9\u6cd5\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create data<\/span>\ndf = pd.DataFrame({'Grade': ['A','A','A','B','B', 'B', 'B', 'C', 'D', 'D '],\n                   'Age': [18, 18, 18, 19, 19, 20, 18, 18, 19, 19],\n                   'Gender': ['M','M', 'F', 'F', 'F', 'M', 'M', 'F', 'M', 'F']})\n<span style=\"color: #008080;\">\n#view data<\/span>\ndf\n\n\tGrade Age Gender\n0 to 18 m\n1 to 18 m\n2 A 18 F\n3 B 19 F\n4 B 19 F\n5 B 20 M\n6 B 18 M\n7 C 18 F\n8 D 19 M\n9 D 19 F \t  \n\n<span style=\"color: #008080;\">#find frequency of each letter grade\n<\/span>pd.crosstab(index=df[' <span style=\"color: #008000;\">Grade<\/span> '], columns=' <span style=\"color: #008000;\">count<\/span> ')\n\ncol_0 count\nGrade\t\nAt 3\nB4\nC 1\nD 2<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5bf9\u6b64\u7684\u89e3\u91ca\u65b9\u6cd5\u662f\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u73ed\u4e0a\u6709<strong>3 \u540d<\/strong>\u5b66\u751f\u83b7\u5f97\u201cA\u201d\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u73ed\u4e0a\u6709<strong>4 \u540d<\/strong>\u5b66\u751f\u83b7\u5f97\u201cB\u201d\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1 \u540d<\/strong>\u5b66\u751f\u5728\u73ed\u7ea7\u4e2d\u83b7\u5f97\u201cC\u201d\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u73ed\u4e0a\u6709<strong>2 \u540d<\/strong>\u5b66\u751f\u83b7\u5f97\u201cD\u201d\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u7c7b\u4f3c\u7684\u8bed\u6cd5\u6765\u67e5\u627e\u5176\u4ed6\u5217\u7684\u9891\u7387\u8ba1\u6570\u3002\u4f8b\u5982\uff0c\u4ee5\u4e0b\u662f\u5982\u4f55\u6309\u5e74\u9f84\u67e5\u627e\u9891\u7387\u7684\u65b9\u6cd5\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>pd.crosstab(index=df[' <span style=\"color: #008000;\">Age<\/span> '], columns=' <span style=\"color: #008000;\">count<\/span> ') \n\ncol_0 count\nAge\t\n18 5\n19 4\n20 1\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5bf9\u6b64\u7684\u89e3\u91ca\u65b9\u6cd5\u662f\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>5\u540d<\/strong>\u5b66\u751f\u5747\u4e3a18\u5c81\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>4\u540d<\/strong>\u5b66\u751f\u5747\u4e3a19\u5c81\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>1\u540d<\/strong>\u5b66\u751f20\u5c81\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u60a8\u8fd8\u53ef\u4ee5\u901a\u8fc7\u9664\u4ee5\u603b\u548c\u6765\u8f7b\u677e\u5730\u5c06\u9891\u7387\u663e\u793a\u4e3a\u6570\u636e\u96c6\u7684\u6bd4\u4f8b\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define crosstab<\/span>\ntab = pd.crosstab(index=df['Age'], columns='count')\n\n<span style=\"color: #008080;\">#find proportions<\/span> \ntab\/tab.sum()\n\ncol_0 count\nAge\t\n18 0.5\n19 0.4\n20 0.1\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5bf9\u6b64\u7684\u89e3\u91ca\u65b9\u6cd5\u662f\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>50%<\/strong>\u7684\u5b66\u751f\u5e74\u9f84\u572818\u5c81\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>40%<\/strong>\u7684\u5b66\u751f\u5e74\u9f84\u572819\u5c81\u3002<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>10%<\/strong>\u7684\u5b66\u751f\u5e74\u9f84\u572820\u5c81\u3002<\/span><\/li>\n<\/ul>\n<h3> <span style=\"color: #000000;\"><strong>DataFrame \u7684\u53cc\u5411\u9891\u7387\u8868<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u60a8\u8fd8\u53ef\u4ee5\u521b\u5efa\u53cc\u5411\u9891\u7387\u8868\u6765\u663e\u793a\u6570\u636e\u96c6\u4e2d\u4e24\u4e2a\u4e0d\u540c\u53d8\u91cf\u7684\u9891\u7387\u3002\u4f8b\u5982\uff0c\u4ee5\u4e0b\u662f\u5982\u4f55\u4e3a Age \u548c Grade \u53d8\u91cf\u521b\u5efa\u53cc\u5411\u9891\u7387\u8868\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>pd.crosstab(index=df[' <span style=\"color: #008000;\">Age<\/span> '], columns=df[' <span style=\"color: #008000;\">Grade<\/span> '])\n\n\nGrade A B C D\nAge\t\t\t\t\n18 3 1 1 0\n19 0 2 0 2\n20 0 1 0 0\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5bf9\u6b64\u7684\u89e3\u91ca\u65b9\u6cd5\u662f\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u73ed\u4e0a\u6709<strong>3 \u540d<\/strong>18 \u5c81\u7684\u5b66\u751f\u83b7\u5f97\u201cA\u201d\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u73ed\u4e0a\u6709<strong>1 \u540d<\/strong>\u5b66\u751f\uff0c\u5e74\u9f84\u4e3a 18 \u5c81\uff0c\u6210\u7ee9\u4e3a\u201cB\u201d\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u73ed\u4e0a\u6709<strong>1 \u540d<\/strong>\u5b66\u751f\uff0c\u5e74\u9f84\u4e3a 18 \u5c81\uff0c\u83b7\u5f97\u201cC\u201d\u7ea7\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u73ed\u4e0a\u6709<strong>0<\/strong>\u540d 18 \u5c81\u5b66\u751f\u83b7\u5f97\u201cD\u201d\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7b49\u7b49\u3002<\/span><\/p>\n<p><em><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5<a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.crosstab.html\" target=\"_blank\" rel=\"noopener\">\u5728\u6b64\u5904<\/a>\u627e\u5230<strong>crosstab()<\/strong>\u51fd\u6570\u7684\u5b8c\u6574\u6587\u6863\u3002<\/span><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u9891\u7387\u8868\u662f\u663e\u793a\u4e0d\u540c\u7c7b\u522b\u7684\u9891\u7387\u7684\u8868\u683c\u3002\u8fd9\u79cd\u7c7b\u578b\u7684\u8868\u5bf9\u4e8e\u7406\u89e3\u6570\u636e\u96c6\u4e2d\u503c\u7684\u5206\u5e03\u7279\u522b\u6709\u7528\u3002 \u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 Pytho [&hellip;]<\/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-853","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u5728 Python 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