{"id":2027,"date":"2023-07-24T00:50:04","date_gmt":"2023-07-24T00:50:04","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e7%86%8a%e7%8c%ab%e7%9b%b4%e6%96%b9%e5%9b%be\/"},"modified":"2023-07-24T00:50:04","modified_gmt":"2023-07-24T00:50:04","slug":"%e7%86%8a%e7%8c%ab%e7%9b%b4%e6%96%b9%e5%9b%be","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e7%86%8a%e7%8c%ab%e7%9b%b4%e6%96%b9%e5%9b%be\/","title":{"rendered":"\u5982\u4f55\u4ece pandas dataframe \u521b\u5efa\u76f4\u65b9\u56fe"},"content":{"rendered":"

<\/p>\n

\n

\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u57fa\u672c\u8bed\u6cd5\u4ece pandas DataFrame \u521b\u5efa\u76f4\u65b9\u56fe\uff1a<\/span><\/p>\n

 df. hist<\/span> (column=' col_name<\/span> ')\n<\/strong><\/pre>\n
\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u6b64\u8bed\u6cd5\u3002<\/span><\/p>\n
\u793a\u4f8b 1\uff1a\u7ed8\u5236\u5355\u4e2a\u76f4\u65b9\u56fe<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u4e3a pandas DataFrame \u4e2d\u7684\u7279\u5b9a\u5217\u521b\u5efa\u5355\u4e2a\u76f4\u65b9\u56fe\uff1a<\/span> <\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf = pd. DataFrame<\/span> ({' points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29, 29, 31, 31, 33],\n                   ' assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4, 7, 7, 8, 9],\n                   ' rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12, 10, 7, 7, 9]})\n\n#view first five rows of DataFrame\n<\/span>df. head<\/span> ()\n\n\tpoints assists rebounds\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n\n<\/span>#create histogram for 'points' column<\/span>\ndf. hist<\/span> (column=' points<\/span> ')\n<\/strong><\/pre>\n
\"\"<\/p>\n
\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528\u7279\u5b9a\u7684\u989c\u8272\u3001\u6837\u5f0f\u3001\u6807\u7b7e\u548c\u7bb1\u6570\u81ea\u5b9a\u4e49\u76f4\u65b9\u56fe\uff1a<\/span> <\/p>\n
 #create custom histogram for 'points' column<\/span>\ndf. hist<\/span> (column=' points<\/span> ', bins= 5<\/span> , grid= False<\/span> , rwidth= .9<\/span> , color=' purple<\/span> ')\n<\/strong><\/pre>\n
\"\u718a\u732b\u76f4\u65b9\u56fe\"<\/p>\n
 x \u8f74\u663e\u793a\u6bcf\u4e2a\u73a9\u5bb6\u5f97\u5206\uff0cy \u8f74\u663e\u793a\u6709\u591a\u5c11\u73a9\u5bb6\u5f97\u5206\u7684\u9891\u7387\u3002<\/span><\/p>\n
\u793a\u4f8b 2\uff1a\u7ed8\u5236\u591a\u4e2a\u76f4\u65b9\u56fe<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u4e86\u5982\u4f55\u4ece pandas DataFrame \u7ed8\u5236\u591a\u4e2a\u76f4\u65b9\u56fe\uff1a<\/span> <\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' team<\/span> ':['A', 'A', 'A', 'A', 'A', 'A',\n                           'B', 'B', 'B', 'B', 'B', 'B'],\n                   ' points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29, 29, 31, 31, 33]})\n\n#view first five rows\n<\/span>df. head<\/span> ()\n\n        team points\n0 to 25\n1 to 12\n2 to 15\n3 to 14\n4 to 19\n\n#create histogram for each team\n<\/span>df. hist<\/span> (column=' points<\/span> ', by=' team<\/span> ', bins= 3<\/span> , grid= False<\/span> , rwidth= .9<\/span> ,\n        color=' purple<\/span> ', sharex= True<\/span> )\n<\/strong><\/pre>\n
\"pandas<\/p>\n
\u8bf7\u6ce8\u610f\uff0c sharex<\/strong>\u53c2\u6570\u6307\u5b9a\u4e24\u4e2a\u76f4\u65b9\u56fe\u5fc5\u987b\u5171\u4eab\u76f8\u540c\u7684 x \u8f74\u3002<\/span><\/p>\n
\u8fd9\u4f7f\u5f97\u6bd4\u8f83\u4e24\u4e2a\u76f4\u65b9\u56fe\u4e4b\u95f4\u7684\u503c\u7684\u5206\u5e03\u53d8\u5f97\u66f4\u52a0\u5bb9\u6613\u3002<\/span><\/p>\n
\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n
\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 Python \u4e2d\u521b\u5efa\u5176\u4ed6\u5e38\u89c1\u7ed8\u56fe\uff1a<\/span><\/p>\n
\u5982\u4f55\u5728 Matplotlib \u4e2d\u7ed8\u5236\u591a\u6761\u7ebf<\/a>
\u5982\u4f55\u4ece Pandas DataFrame \u521b\u5efa\u7bb1\u7ebf\u56fe<\/a>
\u5982\u4f55\u5728\u6761\u5f62\u56fe\u4e0a\u7ed8\u5236\u591a\u4e2a Pandas \u5217<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u57fa\u672c\u8bed\u6cd5\u4ece pandas DataFrame \u521b\u5efa\u76f4\u65b9\u56fe\uff1a df. hist (column=’ […]<\/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-2027","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u4ece Pandas DataFrame \u521b\u5efa\u76f4\u65b9\u56fe - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u51e0\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u4ece pandas DataFrame \u521b\u5efa\u76f4\u65b9\u56fe\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\/\u718a\u732b\u76f4\u65b9\u56fe\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u5982\u4f55\u4ece Pandas DataFrame \u521b\u5efa\u76f4\u65b9\u56fe - 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