\u673a\u5668\u5b66\u4e60<\/a>\u6280\u672f\u3001\u53ef\u89c6\u5316\u7ed3\u679c<\/strong>\u662f\u5173\u952e\u6b65\u9aa4\u3002\u5176\u4e2d\uff0c\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u5c24\u4e3a\u91cd\u8981\uff0c\u56e0\u4e3a\u5b83\u76f4\u63a5\u5f71\u54cd\u540e\u7eed\u5206\u6790\u7684\u6548\u7387\u548c\u6548\u679c\u3002Python\u63d0\u4f9b\u4e86\u4e00\u7cfb\u5217\u5f3a\u5927\u7684\u5e93\uff0c\u5982Pandas\u7528\u4e8e\u6570\u636e\u64cd\u4f5c\u3001NumPy\u7528\u4e8e\u6570\u503c\u8ba1\u7b97\u3001Matplotlib\u548cSeaborn\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\u3001Scikit-learn\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u7b49\u3002\u8fd9\u4e9b\u5de5\u5177\u53ef\u4ee5\u5e2e\u52a9\u5206\u6790\u5e08\u5feb\u901f\u4e0a\u624b\u5e76\u6df1\u5165\u6316\u6398\u6570\u636e\u96c6\u4e2d\u7684\u4fe1\u606f\u3002<\/p>\n<\/p>\n\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u9700\u8981\u8003\u8651\u5230\u6570\u636e\u96c6\u7684\u89c4\u6a21\u3001\u7c7b\u578b\u4ee5\u53ca\u5206\u6790\u76ee\u6807\u3002\u4f8b\u5982\uff0cPandas\u975e\u5e38\u9002\u5408\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\uff0c\u5176DataFrame\u5bf9\u8c61\u53ef\u4ee5\u8f7b\u677e\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3001\u8f6c\u6362\u548c\u805a\u5408\u3002\u5bf9\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u96c6\uff0c\u53ef\u4ee5\u4f7f\u7528Dask\u6216Vaex\u7b49\u5e93\uff0c\u5b83\u4eec\u63d0\u4f9b\u4e86\u7c7b\u4f3c\u4e8ePandas\u7684\u63a5\u53e3\uff0c\u4f46\u53ef\u4ee5\u5904\u7406\u66f4\u5927\u89c4\u6a21\u7684\u6570\u636e\u3002NumPy\u7684\u6570\u7ec4\u8ba1\u7b97\u529f\u80fd\u5728\u5904\u7406\u6570\u503c\u6570\u636e\u65f6\u975e\u5e38\u9ad8\u6548\uff0c\u800c\u53ef\u89c6\u5316\u5e93\u5982Matplotlib\u548cSeaborn\u5219\u53ef\u4ee5\u5e2e\u52a9\u76f4\u89c2\u5730\u5c55\u793a\u6570\u636e\u5173\u7cfb\u548c\u8d8b\u52bf\u3002<\/p>\n<\/p>\n
\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8Python\u5728\u6570\u636e\u5206\u6790\u4e2d\u7684\u5404\u4e2a\u73af\u8282\uff0c\u4ece\u6570\u636e\u9884\u5904\u7406\u5230\u7ed3\u679c\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
\u4e00\u3001\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177<\/h3>\n<\/p>\n
\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u662f\u6570\u636e\u5206\u6790\u7684\u7b2c\u4e00\u6b65\uff0c\u56e0\u4e3a\u4e0d\u540c\u7684\u5de5\u5177\u9002\u5408\u4e0d\u540c\u7684\u6570\u636e\u7c7b\u578b\u548c\u5206\u6790\u9700\u6c42\u3002\u5728Python\u4e2d\uff0c\u6709\u591a\u4e2a\u5e93\u53ef\u4ee5\u5e2e\u52a9\u5b8c\u6210\u6570\u636e\u5206\u6790\u4efb\u52a1\u3002<\/p>\n<\/p>\n
1. Pandas<\/h4>\n<\/p>\n
Pandas\u662fPython\u4e2d\u6700\u6d41\u884c\u7684\u6570\u636e\u5206\u6790\u5e93\u4e4b\u4e00\uff0c\u7279\u522b\u9002\u7528\u4e8e\u7ed3\u6784\u5316\u6570\u636e\u7684\u64cd\u4f5c\u3002\u5b83\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684DataFrame\u5bf9\u8c61\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3001\u8fc7\u6ee4\u3001\u53d8\u6362\u548c\u805a\u5408\u64cd\u4f5c\u3002Pandas\u8fd8\u652f\u6301\u4ece\u591a\u79cd\u683c\u5f0f\uff08\u5982CSV\u3001Excel\u3001SQL\u6570\u636e\u5e93\uff09\u8bfb\u53d6\u548c\u5199\u5165\u6570\u636e\uff0c\u56e0\u6b64\u975e\u5e38\u9002\u5408\u5904\u7406\u591a\u79cd\u6765\u6e90\u7684\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n
2. NumPy<\/h4>\n<\/p>\n
NumPy\u662fPython\u7684\u4e00\u4e2a\u57fa\u7840\u5e93\uff0c\u63d0\u4f9b\u4e86\u5bf9\u6570\u7ec4\u548c\u77e9\u9635\u7684\u652f\u6301\uff0c\u53ca\u9ad8\u6548\u7684\u6570\u503c\u8ba1\u7b97\u529f\u80fd\u3002NumPy\u7684\u6570\u7ec4\u5bf9\u8c61\u6bd4Python\u7684\u5217\u8868\u66f4\u9ad8\u6548\uff0c\u5e76\u4e14\u63d0\u4f9b\u4e86\u5927\u91cf\u7684\u6570\u5b66\u51fd\u6570\uff0c\u53ef\u4ee5\u7528\u4e8e\u6267\u884c\u590d\u6742\u7684\u6570\u503c\u8fd0\u7b97\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u6570\u636e\u9884\u5904\u7406<\/h3>\n<\/p>\n
\u6570\u636e\u9884\u5904\u7406\u662f\u5206\u6790\u6570\u636e\u96c6\u7684\u5173\u952e\u6b65\u9aa4\uff0c\u901a\u5e38\u5305\u62ec\u6570\u636e\u6e05\u6d17\u3001\u683c\u5f0f\u8f6c\u6362\u3001\u7279\u5f81\u9009\u62e9\u7b49\u3002<\/p>\n<\/p>\n
1. \u6570\u636e\u6e05\u6d17<\/h4>\n<\/p>\n
\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u6e05\u6d17\u6570\u636e\u662f\u5fc5\u4e0d\u53ef\u5c11\u7684\u4e00\u6b65\u3002\u6570\u636e\u96c6\u53ef\u80fd\u5305\u542b\u7f3a\u5931\u503c\u3001\u91cd\u590d\u6570\u636e\u6216\u5f02\u5e38\u503c\uff0c\u8fd9\u4e9b\u90fd\u4f1a\u5f71\u54cd\u5206\u6790\u7ed3\u679c\u7684\u51c6\u786e\u6027\u3002Pandas\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u5904\u7406\u8fd9\u4e9b\u95ee\u9898\uff0c\u4f8b\u5982dropna()<\/code>\u7528\u4e8e\u5220\u9664\u7f3a\u5931\u503c\uff0cfillna()<\/code>\u7528\u4e8e\u586b\u5145\u7f3a\u5931\u503c\uff0cdrop_duplicates()<\/code>\u7528\u4e8e\u5220\u9664\u91cd\u590d\u503c\u3002<\/p>\n<\/p>\n2. \u683c\u5f0f\u8f6c\u6362<\/h4>\n<\/p>\n
\u5728\u5206\u6790\u6570\u636e\u4e4b\u524d\uff0c\u786e\u4fdd\u6570\u636e\u7684\u683c\u5f0f\u6b63\u786e\u662f\u81f3\u5173\u91cd\u8981\u7684\u3002Pandas\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u8f6c\u6362\u6570\u636e\u683c\u5f0f\uff0c\u4f8b\u5982astype()<\/code>\u53ef\u4ee5\u7528\u4e8e\u6539\u53d8\u6570\u636e\u7c7b\u578b\u3002\u5bf9\u4e8e\u65e5\u671f\u548c\u65f6\u95f4\u6570\u636e\uff0c\u53ef\u4ee5\u4f7f\u7528to_datetime()<\/code>\u51fd\u6570\u5c06\u5b57\u7b26\u4e32\u8f6c\u6362\u4e3a\u65e5\u671f\u65f6\u95f4\u5bf9\u8c61\u3002<\/p>\n<\/p>\n\u4e09\u3001\u63a2\u7d22\u6027\u6570\u636e\u5206\u6790<\/h3>\n<\/p>\n
\u63a2\u7d22\u6027\u6570\u636e\u5206\u6790\uff08EDA\uff09\u662f\u7406\u89e3\u6570\u636e\u96c6\u7684\u5173\u952e\u6b65\u9aa4\uff0c\u5b83\u5e2e\u52a9\u5206\u6790\u5e08\u8bc6\u522b\u6570\u636e\u4e2d\u7684\u6a21\u5f0f\u3001\u8d8b\u52bf\u548c\u5f02\u5e38\u3002<\/p>\n<\/p>\n
1. \u63cf\u8ff0\u6027\u7edf\u8ba1<\/h4>\n<\/p>\n
\u63cf\u8ff0\u6027\u7edf\u8ba1\u63d0\u4f9b\u4e86\u5173\u4e8e\u6570\u636e\u96c6\u4e2d\u5404\u4e2a\u53d8\u91cf\u7684\u57fa\u672c\u4fe1\u606f\uff0c\u4f8b\u5982\u5747\u503c\u3001\u4e2d\u4f4d\u6570\u3001\u6807\u51c6\u5dee\u7b49\u3002Pandas\u7684describe()<\/code>\u51fd\u6570\u53ef\u4ee5\u5feb\u901f\u751f\u6210\u63cf\u8ff0\u6027\u7edf\u8ba1\u4fe1\u606f\uff0c\u5e2e\u52a9\u5206\u6790\u5e08\u5feb\u901f\u4e86\u89e3\u6570\u636e\u7684\u5206\u5e03\u60c5\u51b5\u3002<\/p>\n<\/p>\n2. \u6570\u636e\u53ef\u89c6\u5316<\/h4>\n<\/p>\n
\u6570\u636e\u53ef\u89c6\u5316\u662f\u63a2\u7d22\u6027\u6570\u636e\u5206\u6790\u7684\u91cd\u8981\u7ec4\u6210\u90e8\u5206\u3002\u4f7f\u7528Matplotlib\u548cSeaborn\u7b49\u53ef\u89c6\u5316\u5e93\uff0c\u53ef\u4ee5\u521b\u5efa\u5404\u79cd\u56fe\u8868\uff0c\u5982\u67f1\u72b6\u56fe\u3001\u6298\u7ebf\u56fe\u3001\u6563\u70b9\u56fe\u7b49\u3002\u8fd9\u4e9b\u56fe\u8868\u53ef\u4ee5\u5e2e\u52a9\u76f4\u89c2\u5730\u5c55\u793a\u6570\u636e\u4e2d\u7684\u5173\u7cfb\u548c\u8d8b\u52bf\u3002<\/p>\n<\/p>\n
\u56db\u3001\u5e94\u7528\u7edf\u8ba1\u548c\u673a\u5668\u5b66\u4e60\u6280\u672f<\/h3>\n<\/p>\n
\u5728\u6570\u636e\u5206\u6790\u7684\u8fc7\u7a0b\u4e2d\uff0c\u5e94\u7528\u7edf\u8ba1\u548c\u673a\u5668\u5b66\u4e60\u6280\u672f\u53ef\u4ee5\u5e2e\u52a9\u4ece\u6570\u636e\u4e2d\u6316\u6398\u51fa\u6709\u4ef7\u503c\u7684\u6d1e\u5bdf\u3002<\/p>\n<\/p>\n
1. \u7edf\u8ba1\u5206\u6790<\/h4>\n<\/p>\n
\u7edf\u8ba1\u5206\u6790\u7528\u4e8e\u9a8c\u8bc1\u6570\u636e\u4e2d\u7684\u5047\u8bbe\u548c\u5173\u7cfb\u3002Python\u4e2d\u7684SciPy\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7edf\u8ba1\u51fd\u6570\uff0c\u53ef\u4ee5\u7528\u4e8e\u6267\u884c\u5404\u79cd\u7edf\u8ba1\u68c0\u9a8c\uff0c\u5982t\u68c0\u9a8c\u3001\u5361\u65b9\u68c0\u9a8c\u7b49\u3002\u6b64\u5916\uff0cStatsmodels\u5e93\u63d0\u4f9b\u4e86\u66f4\u591a\u9ad8\u7ea7\u7684\u7edf\u8ba1\u6a21\u578b\u548c\u68c0\u9a8c\u529f\u80fd\u3002<\/p>\n<\/p>\n
2. \u673a\u5668\u5b66\u4e60<\/h4>\n<\/p>\n
\u673a\u5668\u5b66\u4e60\u53ef\u4ee5\u7528\u4e8e\u6784\u5efa\u9884\u6d4b\u6a21\u578b\uff0c\u4ece\u6570\u636e\u4e2d\u5b66\u4e60\u6a21\u5f0f\u5e76\u8fdb\u884c\u9884\u6d4b\u3002Scikit-learn\u662fPython\u4e2d\u6700\u6d41\u884c\u7684\u673a\u5668\u5b66\u4e60\u5e93\u4e4b\u4e00\uff0c\u63d0\u4f9b\u4e86\u5404\u79cd\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u5982\u56de\u5f52\u3001\u5206\u7c7b\u3001\u805a\u7c7b\u7b49\u3002\u4f7f\u7528Scikit-learn\uff0c\u5206\u6790\u5e08\u53ef\u4ee5\u8f7b\u677e\u5730\u6784\u5efa\u548c\u8bc4\u4f30\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002<\/p>\n<\/p>\n
\u4e94\u3001\u7ed3\u679c\u53ef\u89c6\u5316<\/h3>\n<\/p>\n
\u5c06\u5206\u6790\u7ed3\u679c\u53ef\u89c6\u5316\u662f\u6c9f\u901a\u6570\u636e\u6d1e\u5bdf\u7684\u91cd\u8981\u65b9\u5f0f\u3002Python\u63d0\u4f9b\u4e86\u591a\u79cd\u53ef\u89c6\u5316\u5de5\u5177\uff0c\u53ef\u4ee5\u5e2e\u52a9\u751f\u6210\u4e13\u4e1a\u7684\u56fe\u8868\u548c\u62a5\u544a\u3002<\/p>\n<\/p>\n
1. Matplotlib<\/h4>\n<\/p>\n
Matplotlib\u662fPython\u4e2d\u6700\u57fa\u7840\u7684\u7ed8\u56fe\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u53ef\u4ee5\u7528\u4e8e\u521b\u5efa\u5404\u79cd\u57fa\u672c\u56fe\u8868\u3002\u5206\u6790\u5e08\u53ef\u4ee5\u901a\u8fc7Matplotlib\u751f\u6210\u6563\u70b9\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6298\u7ebf\u56fe\u7b49\uff0c\u5e2e\u52a9\u76f4\u89c2\u5730\u5c55\u793a\u5206\u6790\u7ed3\u679c\u3002<\/p>\n<\/p>\n
2. Seaborn<\/h4>\n<\/p>\n
Seaborn\u662f\u57fa\u4e8eMatplotlib\u7684\u9ad8\u7ea7\u53ef\u89c6\u5316\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u4e3a\u7b80\u6d01\u548c\u7f8e\u89c2\u7684\u56fe\u8868\u98ce\u683c\u3002Seaborn\u4f7f\u5f97\u751f\u6210\u590d\u6742\u7684\u7edf\u8ba1\u56fe\u8868\u53d8\u5f97\u66f4\u52a0\u5bb9\u6613\uff0c\u5982\u70ed\u56fe\u3001\u5206\u5e03\u56fe\u548c\u56de\u5f52\u56fe\u7b49\u3002\u4f7f\u7528Seaborn\uff0c\u5206\u6790\u5e08\u53ef\u4ee5\u5feb\u901f\u751f\u6210\u5177\u6709\u7edf\u8ba1\u610f\u4e49\u7684\u56fe\u8868\uff0c\u4fbf\u4e8e\u89e3\u91ca\u548c\u5c55\u793a\u6570\u636e\u5206\u6790\u7ed3\u679c\u3002<\/p>\n<\/p>\n
\u516d\u3001\u603b\u7ed3\u4e0e\u5c55\u671b<\/h3>\n<\/p>\n
\u901a\u8fc7\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u3001\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406\u3001\u6267\u884c\u63a2\u7d22\u6027\u6570\u636e\u5206\u6790\u3001\u5e94\u7528\u7edf\u8ba1\u548c\u673a\u5668\u5b66\u4e60\u6280\u672f\u4ee5\u53ca\u7ed3\u679c\u53ef\u89c6\u5316\uff0cPython\u4e3a\u6570\u636e\u5206\u6790\u63d0\u4f9b\u4e86\u5168\u9762\u7684\u652f\u6301\u3002\u968f\u7740\u6570\u636e\u79d1\u5b66\u7684\u53d1\u5c55\uff0cPython\u7684\u6570\u636e\u5206\u6790\u5de5\u5177\u548c\u6280\u672f\u4e5f\u5728\u4e0d\u65ad\u8fdb\u6b65\uff0c\u672a\u6765\u5c06\u6709\u66f4\u591a\u7684\u529f\u80fd\u548c\u4f18\u5316\u53ef\u4f9b\u4f7f\u7528\u3002<\/p>\n<\/p>\n
1. \u6301\u7eed\u5b66\u4e60\u4e0e\u5b9e\u8df5<\/h4>\n<\/p>\n
\u6570\u636e\u5206\u6790\u662f\u4e00\u95e8\u9700\u8981\u4e0d\u65ad\u5b66\u4e60\u548c\u5b9e\u8df5\u7684\u5b66\u79d1\u3002\u968f\u7740\u65b0\u6280\u672f\u548c\u65b0\u5de5\u5177\u7684\u51fa\u73b0\uff0c\u5206\u6790\u5e08\u9700\u8981\u4e0d\u65ad\u66f4\u65b0\u81ea\u5df1\u7684\u77e5\u8bc6\u4f53\u7cfb\u3002\u901a\u8fc7\u53c2\u4e0e\u6570\u636e\u79d1\u5b66\u793e\u533a\u3001\u53c2\u52a0\u5728\u7ebf\u8bfe\u7a0b\u548c\u5b9e\u9645\u9879\u76ee\uff0c\u5206\u6790\u5e08\u53ef\u4ee5\u63d0\u5347\u81ea\u5df1\u7684\u6280\u80fd\u6c34\u5e73\u3002<\/p>\n<\/p>\n
2. \u62d3\u5c55\u5e94\u7528\u9886\u57df<\/h4>\n<\/p>\n
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