\u521b\u5efa\u6570\u7ec4<\/strong><\/li>\n<\/ol>\nNumPy\u7684\u6838\u5fc3\u662fndarray\u5bf9\u8c61\uff0c\u7528\u4e8e\u5b58\u50a8\u591a\u7ef4\u6570\u7ec4\u3002\u53ef\u4ee5\u901a\u8fc7numpy.array()<\/code>\u51fd\u6570\u521b\u5efa\u6570\u7ec4\uff1a<\/p>\n<\/p>\nimport numpy as np<\/p>\n\u521b\u5efa\u4e00\u7ef4\u6570\u7ec4<\/strong><\/h2>\narr1 = np.array([1, 2, 3, 4, 5])<\/p>\n
print(arr1)<\/p>\n
\u521b\u5efa\u4e8c\u7ef4\u6570\u7ec4<\/strong><\/h2>\narr2 = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n
print(arr2)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\n- \u6570\u7ec4\u8fd0\u7b97<\/strong><\/li>\n<\/ol>\n
NumPy\u652f\u6301\u591a\u79cd\u6570\u7ec4\u8fd0\u7b97\uff0c\u5305\u62ec\u52a0\u51cf\u4e58\u9664\u3001\u6307\u6570\u3001\u5bf9\u6570\u7b49\uff1a<\/p>\n<\/p>\n
# \u6570\u7ec4\u52a0\u6cd5<\/p>\narr3 = arr1 + 10<\/p>\n
print(arr3)<\/p>\n
\u6570\u7ec4\u4e58\u6cd5<\/strong><\/h2>\narr4 = arr2 * 2<\/p>\n
print(arr4)<\/p>\n
\u6570\u7ec4\u6c42\u548c<\/strong><\/h2>\nsum_arr1 = np.sum(arr1)<\/p>\n
print(sum_arr1)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\n- \u6570\u7ec4\u5f62\u72b6\u548c\u91cd\u5851<\/strong><\/li>\n<\/ol>\n
\u53ef\u4ee5\u4f7f\u7528shape<\/code>\u5c5e\u6027\u67e5\u770b\u6570\u7ec4\u7684\u5f62\u72b6\uff0c\u5e76\u4f7f\u7528reshape()<\/code>\u51fd\u6570\u91cd\u5851\u6570\u7ec4\uff1a<\/p>\n<\/p>\n# \u67e5\u770b\u6570\u7ec4\u5f62\u72b6<\/p>\nprint(arr2.shape)<\/p>\n
\u91cd\u5851\u6570\u7ec4<\/strong><\/h2>\narr5 = np.reshape(arr2, (3, 2))<\/p>\n
print(arr5)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\n- \u6570\u7ec4\u7d22\u5f15\u548c\u5207\u7247<\/strong><\/li>\n<\/ol>\n
NumPy\u652f\u6301\u7075\u6d3b\u7684\u6570\u7ec4\u7d22\u5f15\u548c\u5207\u7247\u64cd\u4f5c\uff1a<\/p>\n<\/p>\n
# \u4e00\u7ef4\u6570\u7ec4\u7d22\u5f15<\/p>\nprint(arr1[0])<\/p>\n
\u4e8c\u7ef4\u6570\u7ec4\u7d22\u5f15<\/strong><\/h2>\nprint(arr2[1, 2])<\/p>\n
\u6570\u7ec4\u5207\u7247<\/strong><\/h2>\nprint(arr1[1:4])<\/p>\n
<\/code><\/pre>\n<\/p>\n
\n- \u7ebf\u6027\u4ee3\u6570<\/strong><\/li>\n<\/ol>\n
NumPy\u63d0\u4f9b\u4e86\u591a\u79cd\u7ebf\u6027\u4ee3\u6570\u51fd\u6570\uff0c\u5982\u77e9\u9635\u4e58\u6cd5\u3001\u7279\u5f81\u503c\u8ba1\u7b97\u7b49\uff1a<\/p>\n<\/p>\n
# \u77e9\u9635\u4e58\u6cd5<\/p>\narr6 = np.dot(arr2, arr5)<\/p>\n
print(arr6)<\/p>\n
\u8ba1\u7b97\u7279\u5f81\u503c<\/strong><\/h2>\neigvals, eigvecs = np.linalg.eig(arr2)<\/p>\n
print(eigvals)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\n- \u968f\u673a\u6570\u751f\u6210<\/strong><\/li>\n<\/ol>\n
NumPy\u7684random<\/code>\u6a21\u5757\u63d0\u4f9b\u4e86\u968f\u673a\u6570\u751f\u6210\u529f\u80fd\uff1a<\/p>\n<\/p>\n# \u751f\u6210\u968f\u673a\u6570\u7ec4<\/p>\nrandom_arr = np.random.rand(3, 3)<\/p>\n
print(random_arr)<\/p>\n
\u751f\u6210\u670d\u4ece\u6b63\u6001\u5206\u5e03\u7684\u968f\u673a\u6570<\/strong><\/h2>\nnormal_arr = np.random.randn(3, 3)<\/p>\n
print(normal_arr)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001NUMPY\u4f7f\u7528\u4e2d\u7684\u6ce8\u610f\u4e8b\u9879<\/p>\n<\/p>\n
\u5728\u4f7f\u7528NumPy\u65f6\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u4e00\u4e9b\u5e38\u89c1\u95ee\u9898\u548c\u6ce8\u610f\u4e8b\u9879\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u9700\u8981\u6ce8\u610f\u7684\u4e8b\u9879\uff1a<\/p>\n<\/p>\n
\n- \u6570\u636e\u7c7b\u578b<\/strong><\/li>\n<\/ol>\n
NumPy\u6570\u7ec4\u652f\u6301\u591a\u79cd\u6570\u636e\u7c7b\u578b\uff0c\u5982\u6574\u6570\u3001\u6d6e\u70b9\u6570\u3001\u5e03\u5c14\u503c\u7b49\u3002\u5728\u521b\u5efa\u6570\u7ec4\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7dtype<\/code>\u53c2\u6570\u6307\u5b9a\u6570\u636e\u7c7b\u578b\uff1a<\/p>\n<\/p>\narr7 = np.array([1, 2, 3], dtype=np.float32)<\/p>\nprint(arr7)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\n- \u5185\u5b58\u5e03\u5c40<\/strong><\/li>\n<\/ol>\n
NumPy\u6570\u7ec4\u5728\u5185\u5b58\u4e2d\u7684\u5e03\u5c40\u53ef\u80fd\u4f1a\u5f71\u54cd\u6027\u80fd\u3002\u53ef\u4ee5\u901a\u8fc7order<\/code>\u53c2\u6570\u6307\u5b9a\u6570\u7ec4\u7684\u5185\u5b58\u5e03\u5c40\uff1a<\/p>\n<\/p>\narr8 = np.array([[1, 2], [3, 4]], order='F')<\/p>\nprint(arr8)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\n- \u5e7f\u64ad\u673a\u5236<\/strong><\/li>\n<\/ol>\n
NumPy\u652f\u6301\u5e7f\u64ad\u673a\u5236\uff0c\u5141\u8bb8\u5bf9\u5f62\u72b6\u4e0d\u5339\u914d\u7684\u6570\u7ec4\u8fdb\u884c\u8fd0\u7b97\uff1a<\/p>\n<\/p>\n
# \u5e7f\u64ad\u673a\u5236<\/p>\narr9 = np.array([1, 2, 3])<\/p>\n
arr10 = arr9 + arr2<\/p>\n
print(arr10)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\n- \u6027\u80fd\u4f18\u5316<\/strong><\/li>\n<\/ol>\n
\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u7684\u5411\u91cf\u5316\u64cd\u4f5c\u6765\u63d0\u9ad8\u6027\u80fd\uff0c\u907f\u514d\u4f7f\u7528Python\u5faa\u73af\uff1a<\/p>\n<\/p>\n
# \u5411\u91cf\u5316\u64cd\u4f5c<\/p>\narr11 = np.array([i for i in range(1000000)])<\/p>\n
arr12 = arr11 * 2 # \u6bd4\u4f7f\u7528\u5faa\u73af\u66f4\u5feb<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u5185\u5bb9\uff0c\u60a8\u5e94\u8be5\u5bf9\u5982\u4f55\u5728Python\u4e2d\u5b89\u88c5\u548c\u4f7f\u7528NumPy\u5e93\u6709\u4e86\u66f4\u6df1\u5165\u7684\u4e86\u89e3\u3002NumPy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u5de5\u5177\uff0c\u638c\u63e1\u5b83\u53ef\u4ee5\u4e3a\u60a8\u7684\u79d1\u5b66\u8ba1\u7b97\u548c\u6570\u636e\u5206\u6790\u5de5\u4f5c\u63d0\u4f9b\u6781\u5927\u7684\u4fbf\u5229\u3002\u5e0c\u671b\u672c\u6587\u80fd\u5e2e\u52a9\u60a8\u66f4\u597d\u5730\u7406\u89e3\u548c\u5e94\u7528NumPy\u5e93\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n \u5982\u4f55\u786e\u5b9a\u6211\u7684Python\u7248\u672c\u4ee5\u5b89\u88c5NumPy\u5e93\uff1f<\/strong>
\u53ef\u4ee5\u901a\u8fc7\u5728\u547d\u4ee4\u884c\u6216\u7ec8\u7aef\u4e2d\u8f93\u5165python --version<\/code>\u6216python3 --version<\/code>\u6765\u67e5\u770b\u5f53\u524d\u5b89\u88c5\u7684Python\u7248\u672c\u3002\u786e\u4fdd\u4f60\u7684Python\u7248\u672c\u4e3a3.6\u53ca\u4ee5\u4e0a\uff0c\u8fd9\u6837\u53ef\u4ee5\u786e\u4fddNumPy\u5e93\u7684\u517c\u5bb9\u6027\u3002<\/p>\n\u9664\u4e86pip\uff0c\u8fd8\u6709\u5176\u4ed6\u65b9\u6cd5\u53ef\u4ee5\u5b89\u88c5NumPy\u5417\uff1f<\/strong>
\u662f\u7684\uff0c\u9664\u4e86\u4f7f\u7528pip\uff0c\u7528\u6237\u8fd8\u53ef\u4ee5\u901a\u8fc7Anaconda\u7b49\u5305\u7ba1\u7406\u5de5\u5177\u6765\u5b89\u88c5NumPy\u3002Anaconda\u63d0\u4f9b\u4e86\u4e00\u4e2a\u96c6\u6210\u7684\u73af\u5883\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u7ba1\u7406Python\u5e93\u548c\u4f9d\u8d56\u9879\u3002\u4f7f\u7528Anaconda\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7conda install numpy<\/code>\u547d\u4ee4\u8f7b\u677e\u5b89\u88c5NumPy\u3002<\/p>\n\u5982\u679c\u5b89\u88c5\u8fc7\u7a0b\u4e2d\u9047\u5230\u9519\u8bef\uff0c\u8be5\u5982\u4f55\u89e3\u51b3\uff1f<\/strong>
\u5728\u5b89\u88c5NumPy\u65f6\uff0c\u5982\u679c\u9047\u5230\u9519\u8bef\uff0c\u5efa\u8bae\u68c0\u67e5\u7f51\u7edc\u8fde\u63a5\u548cpip\u7248\u672c\u3002\u53ef\u4ee5\u901a\u8fc7pip install --upgrade pip<\/code>\u547d\u4ee4\u6765\u66f4\u65b0pip\u3002\u6b64\u5916\uff0c\u786e\u4fdd\u6240\u6709\u4f9d\u8d56\u5e93\u90fd\u5df2\u6b63\u786e\u5b89\u88c5\uff0c\u5fc5\u8981\u65f6\u53ef\u4ee5\u5c1d\u8bd5\u4f7f\u7528\u865a\u62df\u73af\u5883\u6765\u9694\u79bb\u548c\u89e3\u51b3\u4f9d\u8d56\u95ee\u9898\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u8981\u5728Python\u4e2d\u5b89\u88c5NumPy\u5e93\uff0c\u901a\u5e38\u9700\u8981\u4f7f\u7528Python\u7684\u5305\u7ba1\u7406\u5de5\u5177pip\u3002\u5b89\u88c5NumPy\u5e93\u7684\u6b65\u9aa4\u4e3b\u8981\u5305\u62ec […]","protected":false},"author":3,"featured_media":987822,"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\/987814"}],"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=987814"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/987814\/revisions"}],"predecessor-version":[{"id":987825,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/987814\/revisions\/987825"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/987822"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=987814"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=987814"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=987814"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
![\"python\u5982\u4f55\u5b89\u88c5numpy\u5e93\"](\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25063740\/83b1631e-b924-48ec-9f30-6d371e01c81d.webp\")
<\/p>\n