{"id":963646,"date":"2024-12-27T04:20:20","date_gmt":"2024-12-26T20:20:20","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/963646.html"},"modified":"2024-12-27T04:20:23","modified_gmt":"2024-12-26T20:20:23","slug":"%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8python%e8%a1%a8%e7%a4%ba%e7%9f%a9%e9%98%b5","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/963646.html","title":{"rendered":"\u5982\u4f55\u4f7f\u7528python\u8868\u793a\u77e9\u9635"},"content":{"rendered":"

\"\u5982\u4f55\u4f7f\u7528python\u8868\u793a\u77e9\u9635\"<\/p>\n

\u5728Python\u4e2d\uff0c\u8868\u793a\u77e9\u9635\u53ef\u4ee5\u4f7f\u7528\u591a\u79cd\u65b9\u5f0f\uff0c\u5e38\u7528\u7684\u65b9\u6cd5\u5305\u62ec\u5217\u8868\u5217\u8868\u3001NumPy\u5e93\u548cPandas\u5e93\u3002\u5176\u4e2d\uff0cNumPy\u5e93\u56e0\u5176\u9ad8\u6548\u7684\u6570\u7ec4\u5904\u7406\u80fd\u529b\u800c\u88ab\u5e7f\u6cdb\u4f7f\u7528\u3002\u672c\u6587\u5c06\u91cd\u70b9\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528NumPy\u5e93\u8868\u793a\u77e9\u9635\uff0c\u5e76\u8be6\u7ec6\u63cf\u8ff0\u5176\u4f18\u52bf\u3002<\/strong><\/p>\n<\/p>\n

Python\u662f\u4e00\u95e8\u529f\u80fd\u5f3a\u5927\u7684\u7f16\u7a0b\u8bed\u8a00\uff0c\u5c24\u5176\u5728\u6570\u636e\u5904\u7406\u548c\u79d1\u5b66\u8ba1\u7b97\u9886\u57df\u8868\u73b0\u7a81\u51fa\u3002\u77e9\u9635\u662f\u8fd9\u4e9b\u9886\u57df\u4e2d\u7684\u4e00\u4e2a\u57fa\u672c\u6570\u636e\u7ed3\u6784\uff0c\u56e0\u6b64\u7406\u89e3\u5982\u4f55\u5728Python\u4e2d\u8868\u793a\u77e9\u9635\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u4f7f\u7528\u5217\u8868\u5217\u8868\u53ef\u4ee5\u5feb\u901f\u521b\u5efa\u5c0f\u89c4\u6a21\u77e9\u9635\uff0c\u800cNumPy\u5e93\u5219\u63d0\u4f9b\u4e86\u9ad8\u6548\u5904\u7406\u5927\u578b\u77e9\u9635\u7684\u80fd\u529b\u3002\u6b64\u5916\uff0cPandas\u5e93\u5728\u5904\u7406\u6570\u636e\u6846\u65f6\u4e5f\u53ef\u4ee5\u88ab\u770b\u4f5c\u662f\u4e00\u79cd\u77e9\u9635\u8868\u793a\u65b9\u5f0f\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u6df1\u5165\u63a2\u8ba8\u8fd9\u4e9b\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5217\u8868\u5217\u8868\u8868\u793a\u6cd5<\/h3>\n<\/p>\n

\u5217\u8868\u5217\u8868\u662f\u4e00\u79cd\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u6cd5\u6765\u8868\u793a\u77e9\u9635\u3002\u901a\u8fc7\u5c06\u5217\u8868\u5d4c\u5957\u5728\u5217\u8868\u4e2d\uff0c\u53ef\u4ee5\u8868\u793a\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u9635\u3002<\/p>\n<\/p>\n

1. \u521b\u5efa\u77e9\u9635<\/h4>\n<\/p>\n

\u4f7f\u7528\u5217\u8868\u5217\u8868\u8868\u793a\u77e9\u9635\u7684\u6700\u76f4\u63a5\u65b9\u5f0f\u662f\u521b\u5efa\u4e00\u4e2a\u5305\u542b\u591a\u4e2a\u5217\u8868\u7684\u5217\u8868\uff0c\u6bcf\u4e2a\u5185\u5c42\u5217\u8868\u4ee3\u8868\u77e9\u9635\u7684\u4e00\u884c\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\uff1a<\/p>\n<\/p>\n

matrix = [<\/p>\n
    [1, 2, 3],<\/p>\n
    [4, 5, 6],<\/p>\n
    [7, 8, 9]<\/p>\n
]<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u8bbf\u95ee\u548c\u4fee\u6539\u5143\u7d20<\/h4>\n<\/p>\n
\u53ef\u4ee5\u901a\u8fc7\u7d22\u5f15\u8bbf\u95ee\u548c\u4fee\u6539\u5217\u8868\u5217\u8868\u4e2d\u7684\u5143\u7d20\u3002\u4f8b\u5982\uff0c\u8981\u8bbf\u95ee\u7b2c\u4e8c\u884c\u7b2c\u4e09\u5217\u7684\u5143\u7d20\uff1a<\/p>\n<\/p>\n
element = matrix[1][2]  # \u8f93\u51fa\u4e3a6<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8981\u4fee\u6539\u8fd9\u4e2a\u5143\u7d20\u7684\u503c\uff1a<\/p>\n<\/p>\n
matrix[1][2] = 10<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u4f18\u7f3a\u70b9\u5206\u6790<\/h4>\n<\/p>\n
\u5217\u8868\u5217\u8868\u8868\u793a\u6cd5\u7b80\u5355\u6613\u61c2\uff0c\u9002\u7528\u4e8e\u5c0f\u89c4\u6a21\u77e9\u9635\u7684\u64cd\u4f5c\u3002\u7136\u800c\uff0c\u5f53\u9762\u5bf9\u5927\u578b\u77e9\u9635\u65f6\uff0c\u8fd9\u79cd\u65b9\u6cd5\u7684\u6548\u7387\u4e0d\u53caNumPy\u3002\u6b64\u5916\uff0c\u5217\u8868\u5217\u8868\u7f3a\u4e4f\u4e00\u4e9b\u9ad8\u7ea7\u7684\u77e9\u9635\u8fd0\u7b97\u529f\u80fd\u3002<\/p>\n<\/p>\n
\u4e8c\u3001NumPy\u5e93\u8868\u793a\u6cd5<\/h3>\n<\/p>\n
NumPy\u662fPython\u4e2d\u79d1\u5b66\u8ba1\u7b97\u7684\u6838\u5fc3\u5e93\uff0c\u63d0\u4f9b\u4e86\u9ad8\u6548\u7684\u6570\u7ec4\u5904\u7406\u529f\u80fd\u3002NumPy\u6570\u7ec4\uff08ndarray\uff09\u662f\u8868\u793a\u77e9\u9635\u7684\u7406\u60f3\u9009\u62e9\uff0c\u56e0\u4e3a\u5b83\u4eec\u5728\u6027\u80fd\u548c\u529f\u80fd\u4e0a\u90fd\u4f18\u4e8e\u5217\u8868\u5217\u8868\u3002<\/p>\n<\/p>\n
1. \u521b\u5efa\u77e9\u9635<\/h4>\n<\/p>\n
\u8981\u4f7f\u7528NumPy\u8868\u793a\u77e9\u9635\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5NumPy\u5e93\u5e76\u5bfc\u5165\uff1a<\/p>\n<\/p>\n
pip install numpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5bfc\u5165NumPy\u5e93\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528numpy.array<\/code>\u51fd\u6570\u521b\u5efa\u77e9\u9635\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
matrix = np.array([<\/p>\n
    [1, 2, 3],<\/p>\n
    [4, 5, 6],<\/p>\n
    [7, 8, 9]<\/p>\n
])<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u8bbf\u95ee\u548c\u4fee\u6539\u5143\u7d20<\/h4>\n<\/p>\n
NumPy\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\u53ef\u4ee5\u901a\u8fc7\u7d22\u5f15\u8bbf\u95ee\u548c\u4fee\u6539\uff0c\u65b9\u6cd5\u7c7b\u4f3c\u4e8e\u5217\u8868\u5217\u8868\uff1a<\/p>\n<\/p>\n
element = matrix[1, 2]  # \u8f93\u51fa\u4e3a6<\/p>\n
matrix[1, 2] = 10<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u77e9\u9635\u8fd0\u7b97<\/h4>\n<\/p>\n
NumPy\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u77e9\u9635\u8fd0\u7b97\u529f\u80fd\uff0c\u5982\u77e9\u9635\u52a0\u6cd5\u3001\u4e58\u6cd5\u3001\u8f6c\u7f6e\u7b49\uff1a<\/p>\n<\/p>\n
# \u77e9\u9635\u52a0\u6cd5<\/p>\n
matrix2 = np.array([<\/p>\n
    [9, 8, 7],<\/p>\n
    [6, 5, 4],<\/p>\n
    [3, 2, 1]<\/p>\n
])<\/p>\n
result = matrix + matrix2<\/p>\n
\u77e9\u9635\u4e58\u6cd5<\/strong><\/h2>\n
result = np.dot(matrix, matrix2)<\/p>\n
\u77e9\u9635\u8f6c\u7f6e<\/strong><\/h2>\n
transpose = np.transpose(matrix)<\/p>\n
<\/code><\/pre>\n<\/p>\n
4. \u4f18\u7f3a\u70b9\u5206\u6790<\/h4>\n<\/p>\n
NumPy\u662f\u5904\u7406\u5927\u578b\u77e9\u9635\u7684\u9996\u9009\u5de5\u5177\uff0c\u5176\u9ad8\u6548\u6027\u548c\u4e30\u5bcc\u7684\u529f\u80fd\u4f7f\u5176\u5728\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60<\/a>\u9886\u57df\u5c24\u4e3a\u91cd\u8981\u3002\u7136\u800c\uff0c\u521d\u5b66\u8005\u53ef\u80fd\u9700\u8981\u82b1\u8d39\u4e00\u4e9b\u65f6\u95f4\u6765\u5b66\u4e60\u5176API\u548c\u7528\u6cd5\u3002<\/p>\n<\/p>\n
\u4e09\u3001Pandas\u5e93\u8868\u793a\u6cd5<\/h3>\n<\/p>\n
Pandas\u5e93\u63d0\u4f9b\u4e86\u6570\u636e\u6846\uff08DataFrame\uff09\u7ed3\u6784\uff0c\u53ef\u4ee5\u5c06\u5176\u770b\u4f5c\u662f\u4e00\u79cd\u77e9\u9635\u8868\u793a\u65b9\u5f0f\u3002\u867d\u7136Pandas\u4e3b\u8981\u7528\u4e8e\u6570\u636e\u5206\u6790\uff0c\u4f46\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\u4e5f\u53ef\u4ee5\u7528\u6765\u8868\u793a\u548c\u64cd\u4f5c\u77e9\u9635\u3002<\/p>\n<\/p>\n
1. \u521b\u5efa\u77e9\u9635<\/h4>\n<\/p>\n
\u8981\u4f7f\u7528Pandas\u8868\u793a\u77e9\u9635\uff0c\u9996\u5148\u9700\u8981\u5b89\u88c5Pandas\u5e93\u5e76\u5bfc\u5165\uff1a<\/p>\n<\/p>\n
pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5bfc\u5165Pandas\u5e93\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528pandas.DataFrame<\/code>\u521b\u5efa\u77e9\u9635\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
matrix = pd.DataFrame([<\/p>\n
    [1, 2, 3],<\/p>\n
    [4, 5, 6],<\/p>\n
    [7, 8, 9]<\/p>\n
])<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u8bbf\u95ee\u548c\u4fee\u6539\u5143\u7d20<\/h4>\n<\/p>\n
\u5728Pandas\u6570\u636e\u6846\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7iloc<\/code>\u65b9\u6cd5\u8bbf\u95ee\u548c\u4fee\u6539\u5143\u7d20\uff1a<\/p>\n<\/p>\n
element = matrix.iloc[1, 2]  # \u8f93\u51fa\u4e3a6<\/p>\n
matrix.iloc[1, 2] = 10<\/p>\n
<\/code><\/pre>\n<\/p>\n
3. \u4f18\u7f3a\u70b9\u5206\u6790<\/h4>\n<\/p>\n
Pandas\u6570\u636e\u6846\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u80fd\u529b\uff0c\u9002\u5408\u5904\u7406\u5e26\u6709\u6807\u7b7e\u7684\u6570\u636e\u96c6\u3002\u7136\u800c\uff0c\u5bf9\u4e8e\u7eaf\u77e9\u9635\u8fd0\u7b97\uff0cPandas\u7684\u6548\u7387\u4e0d\u5982NumPy\u3002<\/p>\n<\/p>\n
\u56db\u3001\u7ed3\u8bba<\/h3>\n<\/p>\n
\u7efc\u4e0a\u6240\u8ff0\uff0c\u5728Python\u4e2d\u8868\u793a\u77e9\u9635\u7684\u65b9\u6cd5\u591a\u79cd\u591a\u6837<\/strong>\uff0c\u9009\u62e9\u5408\u9002\u7684\u65b9\u6cd5\u53d6\u51b3\u4e8e\u5177\u4f53\u9700\u6c42\u3002\u5bf9\u4e8e\u7b80\u5355\u7684\u4efb\u52a1\uff0c\u5217\u8868\u5217\u8868\u662f\u4e00\u4e2a\u5feb\u901f\u7684\u9009\u62e9\uff1b\u5bf9\u4e8e\u5927\u578b\u77e9\u9635\u548c\u590d\u6742\u8fd0\u7b97\uff0cNumPy\u65e0\u7591\u662f\u6700\u4f73\u9009\u62e9\uff1b\u800c\u5728\u9700\u8981\u5904\u7406\u5e26\u6709\u6807\u7b7e\u7684\u6570\u636e\u96c6\u65f6\uff0cPandas\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5de5\u5177\u3002\u7406\u89e3\u8fd9\u4e9b\u65b9\u6cd5\u7684\u4f18\u7f3a\u70b9\uff0c\u6709\u52a9\u4e8e\u6839\u636e\u5177\u4f53\u60c5\u51b5\u9009\u62e9\u6700\u4f73\u7684\u77e9\u9635\u8868\u793a\u65b9\u5f0f\uff0c\u4ece\u800c\u63d0\u9ad8\u4ee3\u7801\u7684\u6548\u7387\u548c\u53ef\u8bfb\u6027\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Python\u4e2d\u521b\u5efa\u4e00\u4e2a\u77e9\u9635\uff1f<\/strong>
\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5217\u8868\u5d4c\u5957\u7684\u65b9\u5f0f\u521b\u5efa\u77e9\u9635\u3002\u4f8b\u5982\uff0c\u4f7f\u7528\u4e24\u4e2a\u5217\u8868\u7684\u5217\u8868\u6765\u8868\u793a\u4e00\u4e2a\u4e8c\u7ef4\u77e9\u9635\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff1a  <\/p>\n
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\n<\/code><\/pre>\n
\u6b64\u5916\uff0c\u4f7f\u7528NumPy\u5e93\u53ef\u4ee5\u66f4\u65b9\u4fbf\u5730\u521b\u5efa\u548c\u64cd\u4f5c\u77e9\u9635\u3002\u53ea\u9700\u5b89\u88c5NumPy\u540e\uff0c\u4f7f\u7528numpy.array()<\/code>\u51fd\u6570\u5373\u53ef\uff1a  <\/p>\n
import numpy as np\nmatrix = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\n<\/code><\/pre>\n
\u5728Python\u4e2d\uff0c\u5982\u4f55\u5bf9\u77e9\u9635\u8fdb\u884c\u57fa\u672c\u7684\u64cd\u4f5c\uff1f<\/strong>
\u5bf9\u4e8e\u4f7f\u7528\u5217\u8868\u8868\u793a\u7684\u77e9\u9635\uff0c\u53ef\u4ee5\u76f4\u63a5\u901a\u8fc7\u7d22\u5f15\u8bbf\u95ee\u5143\u7d20\uff0c\u8fdb\u884c\u52a0\u6cd5\u3001\u51cf\u6cd5\u7b49\u64cd\u4f5c\u3002\u4f46\u8fd9\u79cd\u65b9\u5f0f\u76f8\u5bf9\u7e41\u7410\u3002\u4f7f\u7528NumPy\u5e93\u53ef\u4ee5\u66f4\u8f7b\u677e\u5730\u8fdb\u884c\u77e9\u9635\u7684\u52a0\u6cd5\u3001\u4e58\u6cd5\u7b49\u64cd\u4f5c\u3002\u4f8b\u5982\uff0c\u4e24\u4e2a\u77e9\u9635\u76f8\u52a0\u53ef\u4ee5\u76f4\u63a5\u4f7f\u7528+<\/code>\u8fd0\u7b97\u7b26\uff1a  <\/p>\n
import numpy as np\nmatrix1 = np.array([[1, 2, 3], [4, 5, 6]])\nmatrix2 = np.array([[7, 8, 9], [10, 11, 12]])\nresult = matrix1 + matrix2\n<\/code><\/pre>\n
NumPy\u8fd8\u63d0\u4f9b\u4e86\u5927\u91cf\u7684\u51fd\u6570\uff0c\u5982np.dot()<\/code>\u7528\u4e8e\u77e9\u9635\u4e58\u6cd5\uff0cnp.transpose()<\/code>\u7528\u4e8e\u8f6c\u7f6e\u77e9\u9635\u7b49\u3002<\/p>\n
\u5728Python\u4e2d\u5982\u4f55\u8bfb\u53d6\u548c\u4fdd\u5b58\u77e9\u9635\u6570\u636e\uff1f<\/strong>
\u53ef\u4ee5\u4f7f\u7528NumPy\u7684np.loadtxt()<\/code>\u548cnp.savetxt()<\/code>\u51fd\u6570\u6765\u8bfb\u53d6\u548c\u4fdd\u5b58\u77e9\u9635\u6570\u636e\u3002\u8fd9\u4e9b\u51fd\u6570\u652f\u6301\u591a\u79cd\u683c\u5f0f\uff0c\u65b9\u4fbf\u4e0e\u6587\u4ef6\u8fdb\u884c\u4ea4\u4e92\u3002\u4f8b\u5982\uff0c\u4fdd\u5b58\u77e9\u9635\u5230\u6587\u672c\u6587\u4ef6\uff1a  <\/p>\n
np.savetxt('matrix.txt', matrix)\n<\/code><\/pre>\n
\u8bfb\u53d6\u6587\u672c\u6587\u4ef6\u4e2d\u7684\u77e9\u9635\u6570\u636e\uff1a  <\/p>\n
loaded_matrix = np.loadtxt('matrix.txt')\n<\/code><\/pre>\n
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