{"id":1076137,"date":"2025-01-08T11:50:44","date_gmt":"2025-01-08T03:50:44","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1076137.html"},"modified":"2025-01-08T11:50:46","modified_gmt":"2025-01-08T03:50:46","slug":"python%e4%b8%ad%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8%e4%ba%8c%e7%bb%b4%e6%95%b0%e7%bb%84-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1076137.html","title":{"rendered":"python\u4e2d\u5982\u4f55\u4f7f\u7528\u4e8c\u7ef4\u6570\u7ec4"},"content":{"rendered":"

\"python\u4e2d\u5982\u4f55\u4f7f\u7528\u4e8c\u7ef4\u6570\u7ec4\"<\/p>\n

Python\u4e2d\u4f7f\u7528\u4e8c\u7ef4\u6570\u7ec4\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5e38\u89c1\u7684\u5305\u62ec\u4f7f\u7528\u5d4c\u5957\u5217\u8868\u3001NumPy\u5e93\u3001Pandas\u5e93\u3002<\/strong> \u5728Python\u4e2d\uff0c\u4e8c\u7ef4\u6570\u7ec4\u53ef\u4ee5\u7528\u4e8e\u8868\u793a\u77e9\u9635\u3001\u8868\u683c\u7b49\u6570\u636e\u7ed3\u6784\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u5e76\u901a\u8fc7\u793a\u4f8b\u4ee3\u7801\u5c55\u793a\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528\u4e8c\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u5d4c\u5957\u5217\u8868<\/h3>\n<\/p>\n

\u5d4c\u5957\u5217\u8868\u662fPython\u4e2d\u6700\u57fa\u672c\u7684\u4e8c\u7ef4\u6570\u7ec4\u8868\u793a\u65b9\u6cd5\u3002\u6bcf\u4e2a\u5143\u7d20\u90fd\u662f\u4e00\u4e2a\u5217\u8868\uff0c\u8fd9\u4e9b\u5217\u8868\u53c8\u7ec4\u6210\u4e86\u4e00\u4e2a\u5927\u7684\u5217\u8868\u3002<\/p>\n<\/p>\n

\u521b\u5efa\u5d4c\u5957\u5217\u8868<\/h4>\n<\/p>\n

\u4f60\u53ef\u4ee5\u76f4\u63a5\u521b\u5efa\u4e00\u4e2a\u5d4c\u5957\u5217\u8868\u6765\u8868\u793a\u4e8c\u7ef4\u6570\u7ec4\uff1a<\/p>\n<\/p>\n

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
\u8bbf\u95ee\u5d4c\u5957\u5217\u8868\u5143\u7d20<\/h4>\n<\/p>\n
\u901a\u8fc7\u7d22\u5f15\u6765\u8bbf\u95ee\u5d4c\u5957\u5217\u8868\u4e2d\u7684\u5143\u7d20\uff1a<\/p>\n<\/p>\n
print(array[0][0])  # \u8f93\u51fa1<\/p>\n
print(array[1][2])  # \u8f93\u51fa6<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u904d\u5386\u5d4c\u5957\u5217\u8868<\/h4>\n<\/p>\n
\u4f60\u53ef\u4ee5\u4f7f\u7528\u5d4c\u5957\u7684for<\/code>\u5faa\u73af\u6765\u904d\u5386\u6574\u4e2a\u4e8c\u7ef4\u6570\u7ec4\uff1a<\/p>\n<\/p>\n
for row in array:<\/p>\n
    for element in row:<\/p>\n
        print(element, end=" ")<\/p>\n
    print()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528NumPy\u5e93<\/h3>\n<\/p>\n
NumPy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u63d0\u4f9b\u4e86\u5bf9\u591a\u7ef4\u6570\u7ec4\u7684\u652f\u6301\u3002NumPy\u6570\u7ec4\u6bd4\u5d4c\u5957\u5217\u8868\u66f4\u9ad8\u6548\uff0c\u5e76\u4e14\u63d0\u4f9b\u4e86\u5927\u91cf\u7684\u6570\u7ec4\u64cd\u4f5c\u51fd\u6570\u3002<\/p>\n<\/p>\n
\u5b89\u88c5NumPy<\/h4>\n<\/p>\n
\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5NumPy\uff0c\u53ef\u4ee5\u4f7f\u7528pip\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install numpy<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u521b\u5efaNumPy\u6570\u7ec4<\/h4>\n<\/p>\n
\u4f60\u53ef\u4ee5\u4f7f\u7528numpy.array<\/code>\u51fd\u6570\u5c06\u5d4c\u5957\u5217\u8868\u8f6c\u6362\u4e3aNumPy\u6570\u7ec4\uff1a<\/p>\n<\/p>\n
import numpy as np<\/p>\n
array = 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
\u8bbf\u95eeNumPy\u6570\u7ec4\u5143\u7d20<\/h4>\n<\/p>\n
\u8bbf\u95eeNumPy\u6570\u7ec4\u7684\u5143\u7d20\u65b9\u5f0f\u4e0e\u5d4c\u5957\u5217\u8868\u76f8\u540c\uff1a<\/p>\n<\/p>\n
print(array[0][0])  # \u8f93\u51fa1<\/p>\n
print(array[1, 2])  # \u8f93\u51fa6<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u904d\u5386NumPy\u6570\u7ec4<\/h4>\n<\/p>\n
\u4f60\u53ef\u4ee5\u4f7f\u7528nditer<\/code>\u51fd\u6570\u9ad8\u6548\u904d\u5386NumPy\u6570\u7ec4\uff1a<\/p>\n<\/p>\n
for element in np.nditer(array):<\/p>\n
    print(element, end=" ")<\/p>\n
<\/code><\/pre>\n<\/p>\n
NumPy\u6570\u7ec4\u7684\u66f4\u591a\u64cd\u4f5c<\/h4>\n<\/p>\n
NumPy\u63d0\u4f9b\u4e86\u8bb8\u591a\u6570\u7ec4\u64cd\u4f5c\u51fd\u6570\uff0c\u4f8b\u5982\u77e9\u9635\u76f8\u4e58\u3001\u8f6c\u7f6e\u7b49\uff1a<\/p>\n<\/p>\n
# \u77e9\u9635\u8f6c\u7f6e<\/p>\n
transposed = np.transpose(array)<\/p>\n
print(transposed)<\/p>\n
\u77e9\u9635\u76f8\u4e58<\/strong><\/h2>\n
array2 = np.array([<\/p>\n
    [1, 2],<\/p>\n
    [3, 4],<\/p>\n
    [5, 6]<\/p>\n
])<\/p>\n
result = np.dot(array, array2)<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528Pandas\u5e93<\/h3>\n<\/p>\n
Pandas\u662f\u4e00\u4e2a\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u7684\u5f3a\u5927\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86DataFrame\u6570\u636e\u7ed3\u6784\uff0c\u53ef\u4ee5\u770b\u4f5c\u662f\u5e26\u6807\u7b7e\u7684\u4e8c\u7ef4\u6570\u7ec4\u3002<\/p>\n<\/p>\n
\u5b89\u88c5Pandas<\/h4>\n<\/p>\n
\u5982\u679c\u4f60\u8fd8\u6ca1\u6709\u5b89\u88c5Pandas\uff0c\u53ef\u4ee5\u4f7f\u7528pip\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
pip install pandas<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u521b\u5efaDataFrame<\/h4>\n<\/p>\n
\u4f60\u53ef\u4ee5\u4f7f\u7528Pandas\u7684DataFrame<\/code>\u51fd\u6570\u521b\u5efa\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
data = {<\/p>\n
    'A': [1, 2, 3],<\/p>\n
    'B': [4, 5, 6],<\/p>\n
    'C': [7, 8, 9]<\/p>\n
}<\/p>\n
df = pd.DataFrame(data)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8bbf\u95eeDataFrame\u5143\u7d20<\/h4>\n<\/p>\n
\u4f60\u53ef\u4ee5\u4f7f\u7528\u5217\u540d\u548c\u884c\u7d22\u5f15\u6765\u8bbf\u95eeDataFrame\u4e2d\u7684\u5143\u7d20\uff1a<\/p>\n<\/p>\n
print(df['A'][0])  # \u8f93\u51fa1<\/p>\n
print(df['B'][1])  # \u8f93\u51fa5<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u904d\u5386DataFrame<\/h4>\n<\/p>\n
\u4f60\u53ef\u4ee5\u4f7f\u7528iterrows<\/code>\u65b9\u6cd5\u904d\u5386DataFrame\uff1a<\/p>\n<\/p>\n
for index, row in df.iterrows():<\/p>\n
    print(row['A'], row['B'], row['C'])<\/p>\n
<\/code><\/pre>\n<\/p>\n
DataFrame\u7684\u66f4\u591a\u64cd\u4f5c<\/h4>\n<\/p>\n
Pandas\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u636e\u64cd\u4f5c\u529f\u80fd\uff0c\u4f8b\u5982\u7b5b\u9009\u3001\u6392\u5e8f\u3001\u7edf\u8ba1\u7b49\uff1a<\/p>\n<\/p>\n
# \u7b5b\u9009\u6570\u636e<\/p>\n
filtered = df[df['A'] > 1]<\/p>\n
print(filtered)<\/p>\n
\u6392\u5e8f\u6570\u636e<\/strong><\/h2>\n
sorted_df = df.sort_values(by='B')<\/p>\n
print(sorted_df)<\/p>\n
\u7edf\u8ba1\u6570\u636e<\/strong><\/h2>\n
mean_values = df.mean()<\/p>\n
print(mean_values)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4e8c\u7ef4\u6570\u7ec4\u7684\u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n
\u4e8c\u7ef4\u6570\u7ec4\u5728\u6570\u636e\u5904\u7406\u548c\u79d1\u5b66\u8ba1\u7b97\u4e2d\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\uff0c\u5305\u62ec\uff1a<\/p>\n<\/p>\n
    \n
  1. \u77e9\u9635\u8fd0\u7b97\uff1a<\/strong> \u5728\u6570\u5b66\u548c\u7269\u7406\u4e2d\uff0c\u77e9\u9635\u8fd0\u7b97\u662f\u975e\u5e38\u91cd\u8981\u7684\u57fa\u7840\u8fd0\u7b97\u3002<\/li>\n
  2. \u56fe\u50cf\u5904\u7406\uff1a<\/strong> \u56fe\u50cf\u53ef\u4ee5\u770b\u4f5c\u662f\u4e00\u4e2a\u4e8c\u7ef4\u6570\u7ec4\uff0c\u6bcf\u4e2a\u50cf\u7d20\u70b9\u7684\u989c\u8272\u503c\u5bf9\u5e94\u4e8c\u7ef4\u6570\u7ec4\u4e2d\u7684\u4e00\u4e2a\u5143\u7d20\u3002<\/li>\n
  3. \u6570\u636e\u5206\u6790\uff1a<\/strong> \u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u8868\u683c\u6570\u636e\u901a\u5e38\u8868\u793a\u4e3a\u4e8c\u7ef4\u6570\u7ec4\uff0c\u4fbf\u4e8e\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u3002<\/li>\n<\/ol>\n
    \u901a\u8fc7\u5b66\u4e60\u548c\u638c\u63e1\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528\u4e8c\u7ef4\u6570\u7ec4\uff0c\u4f60\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u5904\u7406\u548c\u5206\u6790\u6570\u636e\uff0c\u5e76\u5728\u5404\u79cd\u5e94\u7528\u573a\u666f\u4e2d\u53d1\u6325\u5176\u5f3a\u5927\u7684\u529f\u80fd\u3002<\/p>\n<\/p>\n
    \u603b\u7ed3<\/h3>\n<\/p>\n
    \u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u8be6\u7ec6\u4ecb\u7ecd\u4e86Python\u4e2d\u4f7f\u7528\u4e8c\u7ef4\u6570\u7ec4\u7684\u51e0\u79cd\u65b9\u6cd5\uff0c\u5305\u62ec\u4f7f\u7528\u5d4c\u5957\u5217\u8868\u3001NumPy\u5e93\u548cPandas\u5e93\u3002\u6bcf\u79cd\u65b9\u6cd5\u90fd\u6709\u5176\u72ec\u7279\u7684\u4f18\u52bf\u548c\u9002\u7528\u573a\u666f\u3002\u5d4c\u5957\u5217\u8868\u9002\u7528\u4e8e\u7b80\u5355\u7684\u4e8c\u7ef4\u6570\u7ec4\u64cd\u4f5c\uff0c\u800cNumPy\u548cPandas\u63d0\u4f9b\u4e86\u66f4\u9ad8\u6548\u548c\u4e30\u5bcc\u7684\u6570\u7ec4\u64cd\u4f5c\u529f\u80fd\uff0c\u9002\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u548c\u6570\u636e\u5206\u6790\u3002\u901a\u8fc7\u638c\u63e1\u8fd9\u4e9b\u65b9\u6cd5\uff0c\u4f60\u53ef\u4ee5\u5728\u4e0d\u540c\u7684\u5e94\u7528\u573a\u666f\u4e2d\u7075\u6d3b\u4f7f\u7528\u4e8c\u7ef4\u6570\u7ec4\uff0c\u63d0\u5347\u6570\u636e\u5904\u7406\u7684\u6548\u7387\u548c\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u5728Python\u4e2d\u521b\u5efa\u4e8c\u7ef4\u6570\u7ec4\uff1f<\/strong>
    \u5728Python\u4e2d\uff0c\u4e8c\u7ef4\u6570\u7ec4\u53ef\u4ee5\u901a\u8fc7\u5d4c\u5957\u5217\u8868\u5b9e\u73b0\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u521b\u5efa\u4e00\u4e2a3×3\u7684\u4e8c\u7ef4\u6570\u7ec4\uff1a  <\/p>\n
    array_2d = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\n<\/code><\/pre>\n
    \u8fd9\u79cd\u65b9\u5f0f\u975e\u5e38\u7075\u6d3b\uff0c\u60a8\u53ef\u4ee5\u6839\u636e\u9700\u8981\u8c03\u6574\u6570\u7ec4\u7684\u5927\u5c0f\u548c\u5185\u5bb9\u3002<\/p>\n
    \u5982\u4f55\u8bbf\u95ee\u548c\u4fee\u6539\u4e8c\u7ef4\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\uff1f<\/strong>
    \u8bbf\u95ee\u4e8c\u7ef4\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\u4f7f\u7528\u7d22\u5f15\u8868\u793a\u6cd5\u3002\u6bd4\u5982\uff0c\u8981\u8bbf\u95ee\u7b2c2\u884c\u7b2c3\u5217\u7684\u5143\u7d20\uff0c\u53ef\u4ee5\u4f7f\u7528array_2d[1][2]<\/code>\uff0c\u7ed3\u679c\u4e3a6\u3002\u5982\u679c\u9700\u8981\u4fee\u6539\u67d0\u4e2a\u5143\u7d20\uff0c\u6bd4\u5982\u5c06\u7b2c1\u884c\u7b2c2\u5217\u7684\u5143\u7d20\u6539\u4e3a10\uff0c\u53ef\u4ee5\u7528array_2d[0][1] = 10<\/code>\uff0c\u8fd9\u5c06\u628a\u6570\u7ec4\u53d8\u4e3a[[1, 10, 3], [4, 5, 6], [7, 8, 9]]<\/code>\u3002<\/p>\n
    \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528NumPy\u5e93\u5904\u7406\u4e8c\u7ef4\u6570\u7ec4\uff1f<\/strong>
    NumPy\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u7ec4\u5904\u7406\u529f\u80fd\u3002\u9996\u5148\uff0c\u9700\u8981\u5b89\u88c5NumPy\uff1a  <\/p>\n
    pip install numpy\n<\/code><\/pre>\n
    \u7136\u540e\uff0c\u53ef\u4ee5\u7528NumPy\u521b\u5efa\u548c\u64cd\u4f5c\u4e8c\u7ef4\u6570\u7ec4\u3002\u4f8b\u5982\uff0c\u4ee5\u4e0b\u4ee3\u7801\u521b\u5efa\u4e00\u4e2a3×3\u7684NumPy\u6570\u7ec4\u5e76\u8fdb\u884c\u4e00\u4e9b\u57fa\u672c\u64cd\u4f5c\uff1a  <\/p>\n
    import numpy as np\narray_2d_np = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\nprint(array_2d_np[1, 2])  # \u8bbf\u95ee\u5143\u7d20\narray_2d_np[0, 1] = 10     # \u4fee\u6539\u5143\u7d20\n<\/code><\/pre>\n
    \u4f7f\u7528NumPy\u53ef\u4ee5\u66f4\u65b9\u4fbf\u5730\u8fdb\u884c\u77e9\u9635\u8fd0\u7b97\u548c\u9ad8\u7ea7\u529f\u80fd\uff0c\u9002\u5408\u9700\u8981\u8fdb\u884c\u5927\u91cf\u6570\u5b66\u8fd0\u7b97\u7684\u5e94\u7528\u573a\u666f\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u4e2d\u4f7f\u7528\u4e8c\u7ef4\u6570\u7ec4\u7684\u65b9\u6cd5\u6709\u591a\u79cd\uff0c\u5e38\u89c1\u7684\u5305\u62ec\u4f7f\u7528\u5d4c\u5957\u5217\u8868\u3001NumPy\u5e93\u3001Pandas\u5e93\u3002 \u5728Python […]","protected":false},"author":3,"featured_media":1076144,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1076137"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1076137"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1076137\/revisions"}],"predecessor-version":[{"id":1076146,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1076137\/revisions\/1076146"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1076144"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1076137"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1076137"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1076137"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}