{"id":4109,"date":"2023-07-13T13:24:27","date_gmt":"2023-07-13T13:24:27","guid":{"rendered":"https:\/\/statorials.org\/cn\/pandas-%e6%8c%89%e9%93%be%e6%8e%92%e5%ba%8f\/"},"modified":"2023-07-13T13:24:27","modified_gmt":"2023-07-13T13:24:27","slug":"pandas-%e6%8c%89%e9%93%be%e6%8e%92%e5%ba%8f","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/pandas-%e6%8c%89%e9%93%be%e6%8e%92%e5%ba%8f\/","title":{"rendered":"Pandas\uff1a\u5982\u4f55\u6839\u636e\u5b57\u7b26\u4e32\u5217\u5bf9 dataframe \u8fdb\u884c\u6392\u5e8f"},"content":{"rendered":"

<\/p>\n

\n

\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u6839\u636e\u7279\u5b9a\u5b57\u7b26\u4e32\u5217\u7684\u503c\u5bf9 pandas DataFrame \u7684\u884c\u8fdb\u884c\u6392\u5e8f\uff1a<\/span><\/p>\n

\u65b9\u6cd5\u4e00\uff1a\u6309\u5b57\u7b26\u4e32\u5217\u6392\u5e8f\uff08\u5f53\u8be5\u5217\u4ec5\u5305\u542b\u5b57\u7b26\u65f6\uff09<\/strong><\/span><\/p>\n

 df = df. sort_values<\/span> (' my_string_column<\/span> ')\n<\/strong><\/pre>\n
\u65b9\u6cd5\u4e8c\uff1a\u6309\u5b57\u7b26\u4e32\u5217\u6392\u5e8f\uff08\u5f53\u5217\u5305\u542b\u5b57\u7b26\u548c<\/em>\u6570\u5b57\u65f6\uff09<\/strong><\/span><\/p>\n
 #create 'sort' column that contains digits from 'my_string_column'\n<\/span>df[' sort<\/span> '] = df[' my_string_column<\/span> ']. str<\/span> . extract<\/span> (' (\\d+)<\/span> ', expand= False<\/span> ). astype<\/span> (int)\n<\/span>\n#sort rows based on digits in 'sort' column\n<\/span>df = df. sort_values<\/span> (' sort<\/span> ')\n<\/strong><\/pre>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u6bcf\u79cd\u65b9\u6cd5\u3002<\/span><\/p>\n
\u793a\u4f8b 1\uff1a\u6309\u5b57\u7b26\u4e32\u5217\u6392\u5e8f\uff08\u5f53\u8be5\u5217\u4ec5\u5305\u542b\u5b57\u7b26\u65f6\uff09<\/strong><\/span><\/h2>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b pandas DataFrame\uff0c\u5176\u4e2d\u5305\u542b\u6709\u5173\u6742\u8d27\u5e97\u5404\u79cd\u4ea7\u54c1\u9500\u552e\u7684\u4fe1\u606f\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' product<\/span> ': ['Apples', 'Oranges', 'Bananas', 'Lettuce', 'Beans'],\n                   ' sales<\/span> ': [18, 22, 19, 14, 29]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n   product sales\n0 Apples 18\n1 Oranges 22\n2 Bananas 19\n3 Lettuce 14\n4 Beans 29<\/strong><\/pre>\n
\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u6839\u636e\u4ea7\u54c1<\/strong>\u5217\u4e2d\u7684\u5b57\u7b26\u4e32\u5bf9 DataFrame \u7684\u884c\u8fdb\u884c\u6392\u5e8f\uff1a<\/span><\/p>\n
 #sort rows from A to Z based on string in 'product' column\n<\/span>df = df. sort_values<\/span> (' product<\/span> ')\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n   product sales\n0 Apples 18\n2 Bananas 19\n4 Beans 29\n3 Lettuce 14\n1 Oranges 22<\/span><\/span><\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u73b0\u5728\u6839\u636e\u201c\u4ea7\u54c1\u201d<\/strong>\u5217\u4e2d\u7684\u5b57\u7b26\u4e32\u5bf9\u884c\u8fdb\u884c A \u5230 Z \u6392\u5e8f\u3002<\/span><\/p>\n
\u5982\u679c\u60a8\u60f3\u4ece Z \u5230 A \u6392\u5e8f\uff0c\u53ea\u9700\u6dfb\u52a0\u53c2\u6570ascending=False<\/strong> \uff1a<\/span><\/p>\n
 #sort rows from Z to A based on string in 'product' column\n<\/span>df = df. sort_values<\/span> (' product<\/span> ', ascending= False<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n   product sales\n1 Oranges 22\n3 Lettuce 14\n4 Beans 29\n2 Bananas 19\n0 Apples 18\n<\/span><\/span><\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u884c\u73b0\u5728\u6839\u636e\u201c\u4ea7\u54c1\u201d<\/strong>\u5217\u4e2d\u7684\u5b57\u7b26\u4e32\u4ece Z \u5230 A \u6392\u5e8f\u3002<\/span><\/p>\n
\u793a\u4f8b2\uff1a\u6309\u5b57\u7b26\u4e32\u5217\u6392\u5e8f\uff08\u5f53\u5217\u5305\u542b\u5b57\u7b26\u548c<\/em>\u6570\u5b57\u65f6\uff09<\/strong><\/span><\/h2>\n
\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b pandas DataFrame\uff0c\u5176\u4e2d\u5305\u542b\u6709\u5173\u6742\u8d27\u5e97\u5404\u79cd\u4ea7\u54c1\u9500\u552e\u7684\u4fe1\u606f\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' product<\/span> ': ['A3', 'A5', 'A22', 'A50', 'A2', 'A7', 'A9', 'A13'],\n                   ' sales<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28]})\n\n#view DataFrame\n<\/span>print<\/span> (df)\n\n  product sales\n0 A3 18\n1 A5 22\n2 A22 19\n3 A50 14\n4 A2 14\n5 A7 11\n6 A9 20\n7 A13 28\n<\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u4ea7\u54c1<\/strong>\u5217\u4e2d\u7684\u5b57\u7b26\u4e32\u540c\u65f6\u5305\u542b\u5b57\u7b26\u548c\u6570\u5b57\u3002<\/span><\/p>\n
\u5982\u679c\u6211\u4eec\u5c1d\u8bd5\u4f7f\u7528\u4ea7\u54c1<\/strong>\u5217\u4e2d\u7684\u503c\u5bf9 DataFrame \u7684\u884c\u8fdb\u884c\u6392\u5e8f\uff0c\u5219\u5b57\u7b26\u4e32\u5c06\u4e0d\u4f1a\u6839\u636e\u6570\u5b57\u6309\u6b63\u786e\u7684\u987a\u5e8f\u6392\u5e8f\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#sort rows based on strings in 'product' column\n<\/span>df = df. sort_values<\/span> (' product<\/span> ')\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n  product sales\n7 A13 28\n4 A2 14\n2 A22 19\n0 A3 18\n1 A5 22\n3 A50 14\n5 A7 11\n6 A9 20\n<\/strong><\/pre>\n
\u76f8\u53cd\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u4e00\u4e2a\u540d\u4e3asort<\/strong>\u7684\u65b0\u4e34\u65f6\u5217\uff0c\u5176\u4e2d\u4ec5\u5305\u542b\u4ea7\u54c1\u5217\u4e2d\u7684\u6570\u5b57\uff0c\u7136\u540e\u6309\u6392\u5e8f<\/strong>\u5217\u4e2d\u7684\u503c\u8fdb\u884c\u6392\u5e8f\uff0c\u7136\u540e\u5b8c\u5168\u5220\u9664\u8be5\u5217\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#create new 'sort' column that contains digits from 'product' column\n<\/span>df[' sort<\/span> '] = df[' product<\/span> ']. str<\/span> . extract<\/span> (' (\\d+)<\/span> ', expand= False<\/span> ). astype<\/span> (int)\n\n#sort rows based on digits in 'sort' column\n<\/span>df = df. sort_values<\/span> (' sort<\/span> ')\n\n#drop 'sort' column\n<\/span>df = df. drop<\/span> (' sort<\/span> ', axis= 1<\/span> )\n\n#view updated DataFrame\n<\/span>print<\/span> (df)\n\n  product sales\n4 A2 14\n0 A3 18\n1 A5 22\n5 A7 11\n6 A9 20\n7 A13 28\n2 A22 19\n3 A50 14<\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u884c\u73b0\u5728\u6309\u4ea7\u54c1<\/strong>\u5217\u4e2d\u7684\u5b57\u7b26\u4e32\u6392\u5e8f\uff0c\u5e76\u4e14\u6570\u5b57\u6309\u6b63\u786e\u7684\u987a\u5e8f\u6392\u5e8f\u3002<\/span><\/p>\n
\u6ce8\u610f<\/strong>\uff1a\u60a8\u53ef\u4ee5\u5728\u6b64\u5904<\/a>\u627e\u5230 pandas sort_values()<\/strong>\u51fd\u6570\u7684\u5b8c\u6574\u6587\u6863\u3002<\/span><\/p>\n
\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h2>\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\u6309\u65e5\u671f\u6392\u5e8f<\/a>
Pandas\uff1a\u5982\u4f55\u6309\u540d\u79f0\u5bf9\u5217\u8fdb\u884c\u6392\u5e8f<\/a>
Pandas\uff1a\u5982\u4f55\u6309\u7d22\u5f15\u548c\u5217\u6392\u5e8f<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u6839\u636e\u7279\u5b9a\u5b57\u7b26\u4e32\u5217\u7684\u503c\u5bf9 pandas DataFrame \u7684\u884c\u8fdb\u884c\u6392\u5e8f\uff1a \u65b9\u6cd5\u4e00\uff1a\u6309\u5b57\u7b26\u4e32\u5217 […]<\/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-4109","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\nPandas\uff1a\u5982\u4f55\u6839\u636e\u5b57\u7b26\u4e32\u5217\u5bf9 DataFrame \u8fdb\u884c\u6392\u5e8f \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u4e00\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u6839\u636e\u5b57\u7b26\u4e32\u5217\u7684\u503c\u5bf9 pandas DataFrame \u7684\u884c\u8fdb\u884c\u6392\u5e8f\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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