{"id":942727,"date":"2024-12-26T22:15:35","date_gmt":"2024-12-26T14:15:35","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/942727.html"},"modified":"2024-12-26T22:15:36","modified_gmt":"2024-12-26T14:15:36","slug":"python-%e5%a6%82%e4%bd%95%e5%af%bc%e5%85%a5numpy","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/942727.html","title":{"rendered":"python \u5982\u4f55\u5bfc\u5165numpy"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25080420\/0e5368fc-f60f-455b-a371-70ab543105a6.webp\" alt=\"python \u5982\u4f55\u5bfc\u5165numpy\" \/><\/p>\n<p><p> <strong>\u8981\u5728Python\u4e2d\u5bfc\u5165NumPy\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528import\u8bed\u53e5\u3002\u5bfc\u5165NumPy\u7684\u57fa\u672c\u65b9\u5f0f\u662f\u901a\u8fc7\u4f7f\u7528import numpy as np\uff0c\u8fd9\u6837\u53ef\u4ee5\u7b80\u5316\u5bf9NumPy\u529f\u80fd\u7684\u8c03\u7528\u3001\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u548c\u53ef\u7ef4\u62a4\u6027\u3002<\/strong> <\/p>\n<\/p>\n<p><p>\u4f7f\u7528import numpy as np\u7684\u4f18\u52bf\u5728\u4e8e\uff0c\u5b83\u4e0d\u4ec5\u4f7f\u4ee3\u7801\u66f4\u7b80\u6d01\uff0c\u800c\u4e14\u6210\u4e3a\u4e86\u4e00\u4e2a\u975e\u6b63\u5f0f\u7ea6\u5b9a\uff0c\u4f7f\u5f97\u5176\u4ed6\u5f00\u53d1\u8005\u5728\u9605\u8bfb\u4ee3\u7801\u65f6\uff0c\u80fd\u591f\u7acb\u523b\u8bc6\u522b\u51fanp\u4ee3\u8868NumPy\u5e93\u3002NumPy\u662fPython\u4e2d\u4e00\u4e2a\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u57fa\u7840\u5e93\uff0c\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\u3001\u5404\u79cd\u5bfc\u5165\/\u5bfc\u51fa\u529f\u80fd\u3001\u7ebf\u6027\u4ee3\u6570\u3001\u5085\u91cc\u53f6\u53d8\u6362\u548c\u968f\u673a\u6570\u751f\u6210\u7b49\u529f\u80fd\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u63a2\u8ba8\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528NumPy\u4ee5\u53ca\u5b83\u7684\u4e00\u4e9b\u5173\u952e\u529f\u80fd\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001NUMPY\u7684\u5b89\u88c5\u548c\u57fa\u672c\u5bfc\u5165<\/p>\n<\/p>\n<p><p>\u5728\u5f00\u59cb\u4f7f\u7528NumPy\u4e4b\u524d\uff0c\u5fc5\u987b\u786e\u4fdd\u5b83\u5df2\u88ab\u6b63\u786e\u5b89\u88c5\u3002\u5982\u679c\u4f60\u4f7f\u7528\u7684\u662fAnaconda\u6216\u7c7b\u4f3c\u7684Python\u53d1\u884c\u7248\uff0cNumPy\u901a\u5e38\u5df2\u7ecf\u9884\u88c5\u3002\u5426\u5219\uff0c\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u6765\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u4fbf\u53ef\u4ee5\u5728\u4f60\u7684Python\u811a\u672c\u6216\u4ea4\u4e92\u5f0f\u73af\u5883\uff08\u5982Jupyter Notebook\u6216IPython\uff09\u4e2d\u5bfc\u5165NumPy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4f7f\u7528as np\u662f\u4e3a\u4e86\u7b80\u5316\u4ee3\u7801\u4e2d\u7684\u8c03\u7528\u3002NumPy\u5e93\u4e2d\u7684\u51fd\u6570\u548c\u5bf9\u8c61\u90fd\u53ef\u4ee5\u901a\u8fc7np\u524d\u7f00\u6765\u8c03\u7528\uff0c\u6bd4\u5982\uff1anp.array()\u3001np.arange()\u7b49\u3002<\/p>\n<\/p>\n<p><p>\u4e8c\u3001NUMPY\u7684\u6838\u5fc3\u5bf9\u8c61\uff1aNDARRAY<\/p>\n<\/p>\n<p><p>NumPy\u7684\u6838\u5fc3\u662f\u5176\u63d0\u4f9b\u7684\u591a\u7ef4\u6570\u7ec4\u5bf9\u8c61\uff0c\u79f0\u4e3andarray\u3002ndarray\u662f\u4e00\u4e2a\u5feb\u901f\u800c\u7075\u6d3b\u7684\u5bb9\u5668\uff0c\u53ef\u4ee5\u5b58\u50a8\u5927\u578b\u6570\u636e\u96c6\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u521b\u5efandarray<\/strong><\/li>\n<\/ol>\n<p><p>\u6700\u5e38\u89c1\u7684\u521b\u5efandarray\u7684\u65b9\u6cd5\u662f\u4f7f\u7528np.array()\u51fd\u6570\u3002\u53ef\u4ee5\u4ecePython\u7684\u5217\u8868\u6216\u5143\u7ec4\u521b\u5efa\u6570\u7ec4\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<h2><strong>\u4ece\u5217\u8868\u521b\u5efa\u4e00\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>array1d = np.array([1, 2, 3, 4, 5])<\/p>\n<h2><strong>\u4ece\u5d4c\u5957\u5217\u8868\u521b\u5efa\u4e8c\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>array2d = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<p>print(array1d)<\/p>\n<p>print(array2d)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u6570\u7ec4\u5c5e\u6027<\/strong><\/li>\n<\/ol>\n<p><p>ndarray\u6709\u8bb8\u591a\u5c5e\u6027\u53ef\u4ee5\u8ba9\u4f60\u4e86\u89e3\u6570\u7ec4\u7684\u7ed3\u6784\u548c\u5185\u5bb9\uff1a<\/p>\n<\/p>\n<ul>\n<li><code>ndarray.ndim<\/code>: \u6570\u7ec4\u7684\u7ef4\u6570<\/li>\n<li><code>ndarray.shape<\/code>: \u6570\u7ec4\u7684\u5f62\u72b6<\/li>\n<li><code>ndarray.size<\/code>: \u6570\u7ec4\u4e2d\u5143\u7d20\u7684\u603b\u6570<\/li>\n<li><code>ndarray.dtype<\/code>: \u6570\u7ec4\u4e2d\u5143\u7d20\u7684\u6570\u636e\u7c7b\u578b<\/li>\n<\/ul>\n<p><pre><code class=\"language-python\">print(&quot;Dimensions:&quot;, array2d.ndim)<\/p>\n<p>print(&quot;Shape:&quot;, array2d.shape)<\/p>\n<p>print(&quot;Size:&quot;, array2d.size)<\/p>\n<p>print(&quot;Data type:&quot;, array2d.dtype)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e09\u3001NUMPY\u7684\u57fa\u672c\u64cd\u4f5c<\/p>\n<\/p>\n<p><p>NumPy\u63d0\u4f9b\u4e86\u8bb8\u591a\u65b9\u4fbf\u7684\u64cd\u4f5c\uff0c\u5e2e\u52a9\u4f60\u9ad8\u6548\u5730\u5904\u7406\u6570\u636e\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u6570\u7ec4\u7684\u7b97\u672f\u8fd0\u7b97<\/strong><\/li>\n<\/ol>\n<p><p>NumPy\u5141\u8bb8\u5728\u6570\u7ec4\u4e4b\u95f4\u8fdb\u884c\u5143\u7d20\u7ea7\u7684\u7b97\u672f\u8fd0\u7b97\uff0c\u8fd9\u4f7f\u5f97\u6570\u636e\u5904\u7406\u53d8\u5f97\u7b80\u5355\u800c\u9ad8\u6548\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">array1 = np.array([1, 2, 3])<\/p>\n<p>array2 = np.array([4, 5, 6])<\/p>\n<h2><strong>\u52a0\u6cd5<\/strong><\/h2>\n<p>print(array1 + array2)<\/p>\n<h2><strong>\u4e58\u6cd5<\/strong><\/h2>\n<p>print(array1 * array2)<\/p>\n<h2><strong>\u5e42\u8fd0\u7b97<\/strong><\/h2>\n<p>print(array1  2)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u6570\u7ec4\u7684\u7d22\u5f15\u548c\u5207\u7247<\/strong><\/li>\n<\/ol>\n<p><p>NumPy\u7684ndarray\u5bf9\u8c61\u652f\u6301\u4e30\u5bcc\u7684\u7d22\u5f15\u548c\u5207\u7247\u64cd\u4f5c\uff0c\u8fd9\u4f7f\u5f97\u8bbf\u95ee\u548c\u4fee\u6539\u6570\u7ec4\u7684\u7279\u5b9a\u90e8\u5206\u53d8\u5f97\u7b80\u5355\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">array = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])<\/p>\n<h2><strong>\u83b7\u53d6\u5143\u7d20<\/strong><\/h2>\n<p>print(array[0, 1])  # \u8f93\u51fa2<\/p>\n<h2><strong>\u5207\u7247<\/strong><\/h2>\n<p>print(array[0:2, 1:3])  # \u8f93\u51fa[[2, 3], [5, 6]]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u56db\u3001NUMPY\u7684\u9ad8\u7ea7\u529f\u80fd<\/p>\n<\/p>\n<ol>\n<li><strong>\u5e7f\u64ad<\/strong><\/li>\n<\/ol>\n<p><p>\u5e7f\u64ad\u662fNumPy\u7684\u4e00\u9879\u5f3a\u5927\u529f\u80fd\uff0c\u5b83\u5141\u8bb8\u4e0d\u540c\u5f62\u72b6\u7684\u6570\u7ec4\u5728\u7b97\u672f\u8fd0\u7b97\u4e2d\u8fdb\u884c\u81ea\u52a8\u6269\u5c55\u4ee5\u4fbf\u517c\u5bb9\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">array = np.array([1, 2, 3])<\/p>\n<p>scalar = 2<\/p>\n<h2><strong>\u5e7f\u64ad\u673a\u5236<\/strong><\/h2>\n<p>result = array + scalar  # \u8f93\u51fa [3, 4, 5]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u7ebf\u6027\u4ee3\u6570<\/strong><\/li>\n<\/ol>\n<p><p>NumPy\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ebf\u6027\u4ee3\u6570\u529f\u80fd\uff0c\u5982\u77e9\u9635\u4e58\u6cd5\u3001\u77e9\u9635\u5206\u89e3\u548c\u6c42\u9006\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">matrix1 = np.array([[1, 2], [3, 4]])<\/p>\n<p>matrix2 = np.array([[5, 6], [7, 8]])<\/p>\n<h2><strong>\u77e9\u9635\u4e58\u6cd5<\/strong><\/h2>\n<p>product = np.dot(matrix1, matrix2)<\/p>\n<h2><strong>\u9006\u77e9\u9635<\/strong><\/h2>\n<p>inverse = np.linalg.inv(matrix1)<\/p>\n<p>print(&quot;Product:\\n&quot;, product)<\/p>\n<p>print(&quot;Inverse:\\n&quot;, inverse)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li><strong>\u968f\u673a\u6570\u751f\u6210<\/strong><\/li>\n<\/ol>\n<p><p>NumPy\u7684random\u6a21\u5757\u63d0\u4f9b\u4e86\u591a\u79cd\u968f\u673a\u6570\u751f\u6210\u529f\u80fd\uff0c\u9002\u7528\u4e8e\u968f\u673a\u91c7\u6837\u548c\u6a21\u62df\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u5747\u5300\u5206\u5e03\u7684\u968f\u673a\u6570<\/p>\n<p>random_numbers = np.random.rand(3, 3)<\/p>\n<h2><strong>\u751f\u6210\u6b63\u6001\u5206\u5e03\u7684\u968f\u673a\u6570<\/strong><\/h2>\n<p>normal_numbers = np.random.randn(3, 3)<\/p>\n<p>print(&quot;Uniform random numbers:\\n&quot;, random_numbers)<\/p>\n<p>print(&quot;Normal random numbers:\\n&quot;, normal_numbers)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e94\u3001NUMPY\u7684\u5e94\u7528\u573a\u666f<\/p>\n<\/p>\n<p><p>NumPy\u5728\u79d1\u5b66\u8ba1\u7b97\u3001\u6570\u636e\u5206\u6790\u3001<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u7b49\u9886\u57df\u90fd\u6709\u5e7f\u6cdb\u5e94\u7528\u3002\u5b83\u662f\u8bb8\u591a\u9ad8\u7ea7\u5e93\uff08\u5982Pandas\u3001SciPy\u3001TensorFlow\u7b49\uff09\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u6570\u636e\u5206\u6790<\/strong><\/li>\n<\/ol>\n<p><p>NumPy\u9ad8\u6548\u7684\u6570\u7ec4\u64cd\u4f5c\u4f7f\u5f97\u5b83\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\u975e\u5e38\u6709\u7528\uff0c\u7279\u522b\u662f\u5728\u6570\u636e\u6e05\u6d17\u548c\u9884\u5904\u7406\u9636\u6bb5\u3002<\/p>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u673a\u5668\u5b66\u4e60<\/strong><\/li>\n<\/ol>\n<p><p>\u8bb8\u591a\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u4f9d\u8d56\u4e8e\u77e9\u9635\u8fd0\u7b97\uff0cNumPy\u63d0\u4f9b\u7684\u7ebf\u6027\u4ee3\u6570\u529f\u80fd\u548c\u5feb\u901f\u7684\u77e9\u9635\u8fd0\u7b97\u4f7f\u5f97\u5b83\u6210\u4e3a\u5b9e\u73b0\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u7406\u60f3\u5de5\u5177\u3002<\/p>\n<\/p>\n<ol start=\"3\">\n<li><strong>\u56fe\u50cf\u5904\u7406<\/strong><\/li>\n<\/ol>\n<p><p>\u56fe\u50cf\u53ef\u4ee5\u770b\u4f5c\u662f\u4e00\u4e2a\u4e8c\u7ef4\u6216\u4e09\u7ef4\u6570\u7ec4\uff0cNumPy\u5f3a\u5927\u7684\u6570\u7ec4\u5904\u7406\u80fd\u529b\u4f7f\u5f97\u5b83\u5728\u56fe\u50cf\u5904\u7406\u9886\u57df\u540c\u6837\u9002\u7528\u3002<\/p>\n<\/p>\n<p><p>\u603b\u7ed3\u6765\u8bf4\uff0cNumPy\u662fPython\u4e2d\u4e00\u4e2a\u5f3a\u5927\u800c\u7075\u6d3b\u7684\u5de5\u5177\uff0c\u9002\u7528\u4e8e\u5404\u79cd\u79d1\u5b66\u8ba1\u7b97\u4efb\u52a1\u3002\u901a\u8fc7\u4e86\u89e3\u5176\u57fa\u672c\u529f\u80fd\u548c\u9ad8\u7ea7\u7279\u6027\uff0c\u4f60\u53ef\u4ee5\u66f4\u9ad8\u6548\u5730\u8fdb\u884c\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5b89\u88c5NumPy\u5e93\uff1f<\/strong><br \/>\u8981\u5728Python\u4e2d\u4f7f\u7528NumPy\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u5b83\u5df2\u88ab\u5b89\u88c5\u3002\u53ef\u4ee5\u4f7f\u7528pip\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\u3002\u5728\u547d\u4ee4\u884c\u4e2d\u8f93\u5165<code>pip install numpy<\/code>\uff0c\u7136\u540e\u6309\u4e0b\u56de\u8f66\u952e\u3002\u5982\u679c\u60a8\u4f7f\u7528\u7684\u662fAnaconda\uff0c\u53ef\u4ee5\u4f7f\u7528<code>conda install numpy<\/code>\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\u3002\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u5c31\u53ef\u4ee5\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165NumPy\u3002<\/p>\n<p><strong>\u5728\u5bfc\u5165NumPy\u540e\uff0c\u5982\u4f55\u4f7f\u7528\u5b83\u7684\u4e3b\u8981\u529f\u80fd\uff1f<\/strong><br \/>\u5bfc\u5165NumPy\u540e\uff0c\u53ef\u4ee5\u5229\u7528\u5176\u5f3a\u5927\u7684\u6570\u7ec4\u64cd\u4f5c\u529f\u80fd\u3002\u901a\u8fc7<code>import numpy as np<\/code>\u8bed\u53e5\u5bfc\u5165NumPy\u540e\uff0c\u53ef\u4ee5\u521b\u5efa\u6570\u7ec4\u3001\u8fdb\u884c\u6570\u5b66\u8fd0\u7b97\u3001\u751f\u6210\u968f\u673a\u6570\u4ee5\u53ca\u5904\u7406\u591a\u7ef4\u6570\u636e\u3002\u4f8b\u5982\uff0c\u4f7f\u7528<code>np.array()<\/code>\u53ef\u4ee5\u521b\u5efa\u6570\u7ec4\uff0c<code>np.mean()<\/code>\u53ef\u4ee5\u8ba1\u7b97\u5e73\u5747\u503c\u7b49\u3002<\/p>\n<p><strong>NumPy\u4e0e\u5176\u4ed6Python\u5e93\u7684\u517c\u5bb9\u6027\u5982\u4f55\uff1f<\/strong><br \/>NumPy\u4e0e\u8bb8\u591a\u5176\u4ed6Python\u5e93\u5177\u6709\u826f\u597d\u7684\u517c\u5bb9\u6027\u3002\u5b83\u662f\u8bb8\u591a\u6570\u636e\u79d1\u5b66\u548c\u673a\u5668\u5b66\u4e60\u5e93\uff08\u5982Pandas\u3001Matplotlib\u548cTensorFlow\uff09\u7684\u57fa\u7840\u3002\u4f7f\u7528NumPy\u6570\u7ec4\u4f5c\u4e3a\u6570\u636e\u7ed3\u6784\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u4e0e\u8fd9\u4e9b\u5e93\u8fdb\u884c\u4ea4\u4e92\uff0c\u63d0\u5347\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u7684\u6548\u7387\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u8981\u5728Python\u4e2d\u5bfc\u5165NumPy\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528import\u8bed\u53e5\u3002\u5bfc\u5165NumPy\u7684\u57fa\u672c\u65b9\u5f0f\u662f\u901a\u8fc7\u4f7f\u7528import 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