{"id":2185,"date":"2023-07-23T08:38:06","date_gmt":"2023-07-23T08:38:06","guid":{"rendered":"https:\/\/statorials.org\/cn\/pandas-%e9%80%89%e6%8b%a9%e5%a4%9a%e5%88%97\/"},"modified":"2023-07-23T08:38:06","modified_gmt":"2023-07-23T08:38:06","slug":"pandas-%e9%80%89%e6%8b%a9%e5%a4%9a%e5%88%97","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/pandas-%e9%80%89%e6%8b%a9%e5%a4%9a%e5%88%97\/","title":{"rendered":"\u5982\u4f55\u5728 pandas \u4e2d\u9009\u62e9\u591a\u5217\uff08\u5e26\u6709\u793a\u4f8b\uff09"},"content":{"rendered":"

<\/p>\n

\n

\u60a8\u53ef\u4ee5\u4f7f\u7528\u4e09\u79cd\u57fa\u672c\u65b9\u6cd5\u4ece pandas DataFrame \u4e2d\u9009\u62e9\u591a\u4e2a\u5217\uff1a<\/span><\/p>\n

\u65b9\u6cd5\u4e00\uff1a\u6309\u7d22\u5f15\u9009\u62e9\u5217<\/strong><\/span><\/p>\n

 df_new = df. iloc<\/span> [:,[0,1,3]]<\/strong><\/pre>\n
\u65b9\u6cd52\uff1a\u9009\u62e9\u7d22\u5f15\u8303\u56f4\u5185\u7684\u5217<\/strong><\/span><\/p>\n
 df_new = df. iloc<\/span> [:, 0:3]<\/strong><\/pre>\n
\u65b9\u6cd5 3\uff1a\u6309\u540d\u79f0\u9009\u62e9\u5217<\/strong><\/span><\/p>\n
 df_new = df[[' col1<\/span> ', ' col2<\/span> ']]\n<\/strong><\/pre>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5c06\u6bcf\u79cd\u65b9\u6cd5\u4e0e\u4ee5\u4e0b pandas DataFrame \u4e00\u8d77\u4f7f\u7528\uff1a<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\n<\/span>df = pd. DataFrame<\/span> ({' points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12],\n                   ' blocks<\/span> ': [4, 7, 7, 6, 5, 8, 9, 10]})\n\n#view DataFrame\n<\/span>df\n\n\tpoints assists rebounds blocks\n0 25 5 11 4\n1 12 7 8 7\n2 15 7 10 7\n3 14 9 6 6\n4 19 12 6 5\n5 23 9 5 8\n6 25 9 9 9\n7 29 4 12 10\n<\/strong><\/span><\/pre>\n
\u65b9\u6cd5\u4e00\uff1a\u6309\u7d22\u5f15\u9009\u62e9\u5217<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u5982\u4f55\u9009\u62e9\u7d22\u5f15\u4f4d\u7f6e 0\u30011 \u548c 3 \u5904\u7684\u5217\uff1a<\/span><\/p>\n
 #select columns in index positions 0, 1, and 3\n<\/span>df_new = df. iloc<\/span> [:,[0,1,3]]\n\n#view new DataFrame\n<\/span>df_new\n\n        points assists blocks\n0 25 5 4\n1 12 7 7\n2 15 7 7\n3 14 9 6\n4 19 12 5\n5 23 9 8\n6 25 9 9\n7 29 4 10\n<\/span><\/span><\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u7d22\u5f15\u4f4d\u7f6e 0\u30011 \u548c 3 \u5904\u7684\u5217\u5df2\u88ab\u9009\u4e2d\u3002<\/span><\/p>\n
\u6ce8\u610f<\/strong>\uff1apandas DataFrame \u7684\u7b2c\u4e00\u5217\u4f4d\u4e8e\u4f4d\u7f6e 0\u3002<\/span><\/p>\n
\u65b9\u6cd52\uff1a\u9009\u62e9\u7d22\u5f15\u8303\u56f4\u5185\u7684\u5217<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u5982\u4f55\u9009\u62e9\u7d22\u5f15\u8303\u56f4 0 \u5230 3 \u4e2d\u7684\u5217\uff1a<\/span><\/p>\n
 #select columns in index range 0 to 3\n<\/span>df_new = df. iloc<\/span> [:, 0:3]\n\n#view new DataFrame\n<\/span>df_new\n\n        points assists rebounds\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n5 23 9 5\n6 25 9 9\n7 29 4 12\n<\/span><\/span><\/strong><\/pre>\n
\u8bf7\u6ce8\u610f\uff0c\u4f4d\u4e8e\u8303\u56f4 (3) \u6700\u540e\u4e00\u4e2a\u503c\u4e2d\u7684\u5217\u5c06\u4e0d\u4f1a\u5305\u542b\u5728\u8f93\u51fa\u4e2d\u3002<\/span><\/p>\n
\u65b9\u6cd5 3\uff1a\u6309\u540d\u79f0\u9009\u62e9\u5217<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u4e86\u5982\u4f55\u6309\u540d\u79f0\u9009\u62e9\u5217\uff1a<\/span><\/p>\n
 #select columns called 'points' and 'blocks'\n<\/span>df_new = df[[' points<\/span> ', ' blocks<\/span> ']]\n\n#view new DataFrame\n<\/span>df_new\n\n        point blocks\n0 25 4\n1 12 7\n2 15 7\n3 14 6\n4 19 5\n5 23 8\n6 25 9\n7 29 10\n<\/span><\/span><\/strong><\/pre>\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\u64cd\u4f5c\uff1a<\/span><\/p>\n
\u5982\u4f55\u5217\u51fa Pandas \u4e2d\u7684\u6240\u6709\u5217\u540d\u79f0<\/a>
\u5982\u4f55\u5220\u9664 Pandas \u4e2d\u7684\u5217<\/a>
\u5982\u4f55\u5728 Pandas \u4e2d\u5c06\u7d22\u5f15\u8f6c\u6362\u4e3a\u5217<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u53ef\u4ee5\u4f7f\u7528\u4e09\u79cd\u57fa\u672c\u65b9\u6cd5\u4ece pandas DataFrame \u4e2d\u9009\u62e9\u591a\u4e2a\u5217\uff1a \u65b9\u6cd5\u4e00\uff1a\u6309\u7d22\u5f15\u9009\u62e9\u5217 df_new […]<\/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-2185","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u5728 Pandas \u4e2d\u9009\u62e9\u591a\u5217\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\u4ece pandas DataFrame \u4e2d\u9009\u62e9\u591a\u4e2a\u5217\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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