{"id":1164886,"date":"2025-01-15T15:13:29","date_gmt":"2025-01-15T07:13:29","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1164886.html"},"modified":"2025-01-15T15:13:32","modified_gmt":"2025-01-15T07:13:32","slug":"python%e5%a6%82%e4%bd%95%e5%ae%89%e8%a3%85%e5%ba%93%e6%96%87%e4%bb%b6numpy","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1164886.html","title":{"rendered":"python\u5982\u4f55\u5b89\u88c5\u5e93\u6587\u4ef6numpy"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25205340\/5e231c05-8c36-4733-b9c6-93416d9def18.webp\" alt=\"python\u5982\u4f55\u5b89\u88c5\u5e93\u6587\u4ef6numpy\" \/><\/p>\n<p><p> <strong>Python\u5b89\u88c5\u5e93\u6587\u4ef6numpy\u7684\u6b65\u9aa4<\/strong>\uff1a\u4f7f\u7528pip\u5de5\u5177\u5b89\u88c5\u3001\u4f7f\u7528conda\u5de5\u5177\u5b89\u88c5\u3001\u901a\u8fc7\u6e90\u7801\u5b89\u88c5\u3002<strong>\u63a8\u8350\u4f7f\u7528pip\u5de5\u5177\u5b89\u88c5<\/strong>\uff0c\u56e0\u4e3a\u5b83\u662f\u6700\u5e38\u7528\u548c\u6700\u7b80\u5355\u7684\u65b9\u6cd5\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u63cf\u8ff0\uff1a<\/p>\n<\/p>\n<p><p>\u8981\u5728Python\u4e2d\u5b89\u88c5\u5e93\u6587\u4ef6numpy\uff0c\u53ef\u4ee5\u4f7f\u7528<code>pip<\/code>\u5de5\u5177\uff0c\u8fd9\u662fPython\u7684\u5305\u7ba1\u7406\u7cfb\u7edf\u3002\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Python\u548cpip\u3002\u4f60\u53ef\u4ee5\u5728\u7ec8\u7aef\u6216\u547d\u4ee4\u63d0\u793a\u7b26\u4e2d\u8f93\u5165<code>python --version<\/code>\u548c<code>pip --version<\/code>\u6765\u68c0\u67e5\u5b83\u4eec\u662f\u5426\u5df2\u7ecf\u5b89\u88c5\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5pip\uff0c\u53ef\u4ee5\u4ecePython\u7684\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u5b89\u88c5\u3002<\/p>\n<\/p>\n<p><p>\u5b89\u88c5numpy\u7684\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n<ol>\n<li>\u6253\u5f00\u7ec8\u7aef\u6216\u547d\u4ee4\u63d0\u793a\u7b26\u3002<\/li>\n<li>\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\u6765\u5b89\u88c5numpy\uff1a\n<pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\u7b49\u5f85\u5b89\u88c5\u5b8c\u6210\u3002\u5b89\u88c5\u6210\u529f\u540e\uff0c\u4f60\u53ef\u4ee5\u5728Python\u811a\u672c\u6216\u4ea4\u4e92\u5f0fPython\u73af\u5883\u4e2d\u4f7f\u7528numpy\u3002<\/li>\n<\/ol>\n<p><h3>\u4e00\u3001\u4f7f\u7528pip\u5de5\u5177\u5b89\u88c5<\/h3>\n<\/p>\n<p><p>pip\u662fPython\u7684\u5305\u7ba1\u7406\u5de5\u5177\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u5b89\u88c5\u3001\u5347\u7ea7\u548c\u5378\u8f7dPython\u5305\u3002\u4f7f\u7528pip\u5de5\u5177\u5b89\u88c5numpy\u975e\u5e38\u7b80\u5355\uff0c\u53ea\u9700\u5728\u547d\u4ee4\u884c\u8f93\u5165\u4e00\u884c\u547d\u4ee4\u5373\u53ef\u3002<\/p>\n<\/p>\n<p><h4>1.1 \u68c0\u67e5Python\u548cpip\u5b89\u88c5\u60c5\u51b5<\/h4>\n<\/p>\n<p><p>\u5728\u5b89\u88c5numpy\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u786e\u4fdd\u4f60\u5df2\u7ecf\u5b89\u88c5\u4e86Python\u548cpip\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u68c0\u67e5\u5b83\u4eec\u662f\u5426\u5df2\u7ecf\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">python --version<\/p>\n<p>pip --version<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5982\u679cPython\u548cpip\u90fd\u5df2\u5b89\u88c5\uff0c\u4f60\u4f1a\u770b\u5230\u5b83\u4eec\u7684\u7248\u672c\u53f7\u3002\u5982\u679c\u6ca1\u6709\u5b89\u88c5\uff0c\u53ef\u4ee5\u4ecePython\u7684\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u548c\u5b89\u88c5Python\uff0cpip\u901a\u5e38\u4f1a\u968fPython\u4e00\u8d77\u5b89\u88c5\u3002<\/p>\n<\/p>\n<p><h4>1.2 \u4f7f\u7528pip\u5b89\u88c5numpy<\/h4>\n<\/p>\n<p><p>\u5728\u786e\u8ba4Python\u548cpip\u90fd\u5df2\u5b89\u88c5\u540e\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u6765\u5b89\u88c5numpy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u4e2a\u547d\u4ee4\u4f1a\u81ea\u52a8\u4e0b\u8f7d\u548c\u5b89\u88c5numpy\u53ca\u5176\u4f9d\u8d56\u9879\u3002\u5982\u679c\u4f60\u9700\u8981\u5b89\u88c5\u7279\u5b9a\u7248\u672c\u7684numpy\uff0c\u53ef\u4ee5\u5728\u547d\u4ee4\u4e2d\u6307\u5b9a\u7248\u672c\u53f7\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy==1.21.0<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>1.3 \u9a8c\u8bc1\u5b89\u88c5<\/h4>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u9a8c\u8bc1numpy\u662f\u5426\u5b89\u88c5\u6210\u529f\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy<\/p>\n<p>print(numpy.__version__)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5982\u679c\u6ca1\u6709\u62a5\u9519\u5e76\u4e14\u6210\u529f\u6253\u5370\u51fanumpy\u7684\u7248\u672c\u53f7\uff0c\u5219\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528conda\u5de5\u5177\u5b89\u88c5<\/h3>\n<\/p>\n<p><p>Conda\u662f\u4e00\u4e2a\u5f00\u6e90\u5305\u7ba1\u7406\u7cfb\u7edf\u548c\u73af\u5883\u7ba1\u7406\u7cfb\u7edf\uff0c\u9002\u7528\u4e8e\u5b89\u88c5\u548c\u7ba1\u7406Python\u53ca\u5176\u4ed6\u8bed\u8a00\u7684\u8f6f\u4ef6\u5305\u3002\u7279\u522b\u662f\u5728\u4f7f\u7528Anaconda\u6216Miniconda\u5206\u53d1\u7248\u65f6\uff0cconda\u5de5\u5177\u975e\u5e38\u6709\u7528\u3002<\/p>\n<\/p>\n<p><h4>2.1 \u5b89\u88c5Anaconda\u6216Miniconda<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u4f60\u9700\u8981\u5b89\u88c5Anaconda\u6216Miniconda\u3002Anaconda\u662f\u4e00\u4e2a\u5305\u542b\u4e86\u5927\u91cf\u79d1\u5b66\u8ba1\u7b97\u5305\u7684Python\u53d1\u884c\u7248\uff0c\u800cMiniconda\u662f\u4e00\u4e2a\u8f83\u5c0f\u7684\u3001\u53ea\u5305\u542bconda\u7684\u5b89\u88c5\u7a0b\u5e8f\u3002<\/p>\n<\/p>\n<p><p>\u53ef\u4ee5\u4eceAnaconda\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u5e76\u5b89\u88c5Anaconda\u6216Miniconda\u3002<\/p>\n<\/p>\n<p><h4>2.2 \u4f7f\u7528conda\u5b89\u88c5numpy<\/h4>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8cAnaconda\u6216Miniconda\u540e\uff0c\u4f60\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u6765\u5b89\u88c5numpy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">conda install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u4e2a\u547d\u4ee4\u4f1a\u81ea\u52a8\u4e0b\u8f7d\u548c\u5b89\u88c5numpy\u53ca\u5176\u4f9d\u8d56\u9879\u3002\u5982\u679c\u4f60\u9700\u8981\u5b89\u88c5\u7279\u5b9a\u7248\u672c\u7684numpy\uff0c\u53ef\u4ee5\u5728\u547d\u4ee4\u4e2d\u6307\u5b9a\u7248\u672c\u53f7\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">conda install numpy=1.21.0<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2.3 \u9a8c\u8bc1\u5b89\u88c5<\/h4>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u9a8c\u8bc1numpy\u662f\u5426\u5b89\u88c5\u6210\u529f\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy<\/p>\n<p>print(numpy.__version__)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5982\u679c\u6ca1\u6709\u62a5\u9519\u5e76\u4e14\u6210\u529f\u6253\u5370\u51fanumpy\u7684\u7248\u672c\u53f7\uff0c\u5219\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u901a\u8fc7\u6e90\u7801\u5b89\u88c5<\/h3>\n<\/p>\n<p><p>\u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u4f60\u53ef\u80fd\u9700\u8981\u4ece\u6e90\u7801\u5b89\u88c5numpy\uff0c\u4f8b\u5982\u9700\u8981\u4fee\u6539numpy\u7684\u6e90\u7801\u6216\u4f7f\u7528\u5c1a\u672a\u53d1\u5e03\u7684\u6700\u65b0\u7248\u672c\u3002\u4ee5\u4e0b\u662f\u4ece\u6e90\u7801\u5b89\u88c5numpy\u7684\u6b65\u9aa4\u3002<\/p>\n<\/p>\n<p><h4>3.1 \u4e0b\u8f7dnumpy\u6e90\u7801<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u4ecenumpy\u7684GitHub\u4ed3\u5e93\u6216\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u6e90\u7801\u3002\u4f60\u53ef\u4ee5\u4f7f\u7528git\u5de5\u5177\u4eceGitHub\u514b\u9686\u4ed3\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">git clone https:\/\/github.com\/numpy\/numpy.git<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3.2 \u5b89\u88c5\u6784\u5efa\u5de5\u5177<\/h4>\n<\/p>\n<p><p>\u5728\u4ece\u6e90\u7801\u6784\u5efanumpy\u4e4b\u524d\uff0c\u4f60\u9700\u8981\u5b89\u88c5\u4e00\u4e9b\u6784\u5efa\u5de5\u5177\u3002\u5bf9\u4e8e\u5927\u591a\u6570Linux\u7cfb\u7edf\uff0c\u53ef\u4ee5\u4f7f\u7528\u5305\u7ba1\u7406\u5668\u5b89\u88c5\u8fd9\u4e9b\u5de5\u5177\uff0c\u4f8b\u5982\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">sudo apt-get install build-essential python3-dev<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5bf9\u4e8eWindows\u7cfb\u7edf\uff0c\u53ef\u4ee5\u5b89\u88c5Microsoft Visual C++ Build Tools\u3002<\/p>\n<\/p>\n<p><h4>3.3 \u6784\u5efa\u548c\u5b89\u88c5numpy<\/h4>\n<\/p>\n<p><p>\u8fdb\u5165\u4e0b\u8f7d\u7684numpy\u6e90\u7801\u76ee\u5f55\uff0c\u7136\u540e\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\u6765\u6784\u5efa\u548c\u5b89\u88c5numpy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">cd numpy<\/p>\n<p>pip install .<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u8fd9\u4e2a\u547d\u4ee4\u4f1a\u81ea\u52a8\u6784\u5efa\u548c\u5b89\u88c5numpy\u3002\u5982\u679c\u4f60\u9700\u8981\u5b89\u88c5\u5f00\u53d1\u7248\u672c\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install -e .<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3.4 \u9a8c\u8bc1\u5b89\u88c5<\/h4>\n<\/p>\n<p><p>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u9a8c\u8bc1numpy\u662f\u5426\u5b89\u88c5\u6210\u529f\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy<\/p>\n<p>print(numpy.__version__)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5982\u679c\u6ca1\u6709\u62a5\u9519\u5e76\u4e14\u6210\u529f\u6253\u5370\u51fanumpy\u7684\u7248\u672c\u53f7\uff0c\u5219\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u5176\u4ed6\u5b89\u88c5\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p>\u9664\u4e86\u4ee5\u4e0a\u5e38\u89c1\u7684\u5b89\u88c5\u65b9\u6cd5\u5916\uff0c\u8fd8\u6709\u4e00\u4e9b\u5176\u4ed6\u65b9\u6cd5\u53ef\u4ee5\u5b89\u88c5numpy\uff0c\u4f8b\u5982\u4f7f\u7528\u7cfb\u7edf\u5305\u7ba1\u7406\u5668\u6216\u901a\u8fc7\u865a\u62df\u73af\u5883\u5b89\u88c5\u3002<\/p>\n<\/p>\n<p><h4>4.1 \u4f7f\u7528\u7cfb\u7edf\u5305\u7ba1\u7406\u5668<\/h4>\n<\/p>\n<p><p>\u5728\u67d0\u4e9bLinux\u53d1\u884c\u7248\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u7cfb\u7edf\u5305\u7ba1\u7406\u5668\u5b89\u88c5numpy\u3002\u4f8b\u5982\uff0c\u5728Debian\u6216Ubuntu\u7cfb\u7edf\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5numpy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">sudo apt-get install python3-numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728Fedora\u7cfb\u7edf\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5numpy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">sudo dnf install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4.2 \u5728\u865a\u62df\u73af\u5883\u4e2d\u5b89\u88c5<\/h4>\n<\/p>\n<p><p>\u4e3a\u4e86\u907f\u514d\u4f9d\u8d56\u51b2\u7a81\u548c\u7ba1\u7406\u4e0d\u540c\u7684\u9879\u76ee\u73af\u5883\uff0c\u5efa\u8bae\u5728\u865a\u62df\u73af\u5883\u4e2d\u5b89\u88c5numpy\u3002\u53ef\u4ee5\u4f7f\u7528Python\u81ea\u5e26\u7684venv\u6a21\u5757\u521b\u5efa\u865a\u62df\u73af\u5883\uff0c\u5e76\u5728\u5176\u4e2d\u5b89\u88c5numpy\u3002<\/p>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u521b\u5efa\u4e00\u4e2a\u865a\u62df\u73af\u5883\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">python -m venv myenv<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u7136\u540e\uff0c\u6fc0\u6d3b\u865a\u62df\u73af\u5883\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\"># \u5728Windows\u7cfb\u7edf\u4e2d<\/p>\n<p>myenv\\Scripts\\activate<\/p>\n<h2><strong>\u5728Linux\u6216macOS\u7cfb\u7edf\u4e2d<\/strong><\/h2>\n<p>source myenv\/bin\/activate<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u6fc0\u6d3b\u865a\u62df\u73af\u5883\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528pip\u5b89\u88c5numpy\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5728\u865a\u62df\u73af\u5883\u4e2d\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u9a8c\u8bc1numpy\u662f\u5426\u5b89\u88c5\u6210\u529f\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy<\/p>\n<p>print(numpy.__version__)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u5982\u679c\u6ca1\u6709\u62a5\u9519\u5e76\u4e14\u6210\u529f\u6253\u5370\u51fanumpy\u7684\u7248\u672c\u53f7\uff0c\u5219\u8bf4\u660e\u5b89\u88c5\u6210\u529f\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u5e38\u89c1\u95ee\u9898\u53ca\u89e3\u51b3\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p>\u5728\u5b89\u88c5numpy\u7684\u8fc7\u7a0b\u4e2d\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u4e00\u4e9b\u5e38\u89c1\u95ee\u9898\u548c\u9519\u8bef\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u95ee\u9898\u53ca\u5176\u89e3\u51b3\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><h4>5.1 pip\u547d\u4ee4\u627e\u4e0d\u5230<\/h4>\n<\/p>\n<p><p>\u5982\u679c\u5728\u8fd0\u884cpip\u547d\u4ee4\u65f6\u9047\u5230\u7c7b\u4f3c\u201cpip: command not found\u201d\u7684\u9519\u8bef\uff0c\u53ef\u80fd\u662f\u56e0\u4e3apip\u6ca1\u6709\u6b63\u786e\u5b89\u88c5\u6216\u6ca1\u6709\u6dfb\u52a0\u5230\u7cfb\u7edf\u7684\u73af\u5883\u53d8\u91cf\u4e2d\u3002\u53ef\u4ee5\u5c1d\u8bd5\u4ee5\u4e0b\u65b9\u6cd5\u89e3\u51b3\uff1a<\/p>\n<\/p>\n<ul>\n<li>\n<p>\u786e\u4fddpip\u5df2\u7ecf\u5b89\u88c5\uff0c\u5e76\u4e14\u4e0ePython\u7248\u672c\u5339\u914d\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5pip\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">python -m ensurepip --upgrade<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p>\u786e\u4fddpip\u8def\u5f84\u5df2\u7ecf\u6dfb\u52a0\u5230\u7cfb\u7edf\u7684\u73af\u5883\u53d8\u91cf\u4e2d\u3002\u53ef\u4ee5\u624b\u52a8\u5c06pip\u8def\u5f84\u6dfb\u52a0\u5230\u7cfb\u7edf\u7684PATH\u53d8\u91cf\u4e2d\u3002<\/p>\n<\/p>\n<\/li>\n<\/ul>\n<p><h4>5.2 \u6743\u9650\u95ee\u9898<\/h4>\n<\/p>\n<p><p>\u5728\u5b89\u88c5numpy\u65f6\uff0c\u5982\u679c\u9047\u5230\u6743\u9650\u95ee\u9898\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u89e3\u51b3\uff1a<\/p>\n<\/p>\n<ul>\n<li>\n<p>\u4f7f\u7528\u7ba1\u7406\u5458\u6743\u9650\u8fd0\u884cpip\u547d\u4ee4\u3002\u4f8b\u5982\uff0c\u5728Linux\u6216macOS\u7cfb\u7edf\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528sudo\u547d\u4ee4\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">sudo pip install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p>\u5728\u7528\u6237\u76ee\u5f55\u4e0b\u5b89\u88c5numpy\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install --user numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<p><h4>5.3 \u4f9d\u8d56\u95ee\u9898<\/h4>\n<\/p>\n<p><p>\u5728\u5b89\u88c5numpy\u65f6\uff0c\u5982\u679c\u9047\u5230\u4f9d\u8d56\u95ee\u9898\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u4ee5\u4e0b\u65b9\u6cd5\u89e3\u51b3\uff1a<\/p>\n<\/p>\n<ul>\n<li>\n<p>\u4f7f\u7528pip\u7684\u5347\u7ea7\u529f\u80fd\u5b89\u88c5\u4f9d\u8d56\u9879\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install --upgrade numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<li>\n<p>\u4f7f\u7528conda\u5de5\u5177\u5b89\u88c5numpy\u53ca\u5176\u4f9d\u8d56\u9879\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">conda install numpy<\/p>\n<p><\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n<p><h3>\u516d\u3001numpy\u7684\u57fa\u672c\u4f7f\u7528\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p>\u5b89\u88c5numpy\u540e\uff0c\u53ef\u4ee5\u5728Python\u811a\u672c\u6216\u4ea4\u4e92\u5f0fPython\u73af\u5883\u4e2d\u4f7f\u7528numpy\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9bnumpy\u7684\u57fa\u672c\u4f7f\u7528\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><h4>6.1 \u5bfc\u5165numpy<\/h4>\n<\/p>\n<p><p>\u5728\u4f7f\u7528numpy\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5728Python\u811a\u672c\u4e2d\u5bfc\u5165numpy\u6a21\u5757\u3002\u901a\u5e38\uff0cnumpy\u4f1a\u88ab\u5bfc\u5165\u4e3anp\uff0c\u4ee5\u7b80\u5316\u4ee3\u7801\u4e66\u5199\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import numpy as np<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>6.2 \u521b\u5efa\u6570\u7ec4<\/h4>\n<\/p>\n<p><p>numpy\u7684\u6838\u5fc3\u6570\u636e\u7ed3\u6784\u662fndarray\uff08n\u7ef4\u6570\u7ec4\uff09\uff0c\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u65b9\u5f0f\u521b\u5efa\u6570\u7ec4\uff0c\u4f8b\u5982\u4f7f\u7528\u5217\u8868\u6216\u5143\u7ec4\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u4ece\u5217\u8868\u521b\u5efa\u6570\u7ec4<\/p>\n<p>a = np.array([1, 2, 3, 4, 5])<\/p>\n<h2><strong>\u4ece\u5143\u7ec4\u521b\u5efa\u6570\u7ec4<\/strong><\/h2>\n<p>b = np.array((6, 7, 8, 9, 10))<\/p>\n<h2><strong>\u521b\u5efa\u591a\u7ef4\u6570\u7ec4<\/strong><\/h2>\n<p>c = np.array([[1, 2, 3], [4, 5, 6]])<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>6.3 \u6570\u7ec4\u64cd\u4f5c<\/h4>\n<\/p>\n<p><p>numpy\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u6570\u7ec4\u64cd\u4f5c\u65b9\u6cd5\uff0c\u4f8b\u5982\u6570\u7ec4\u5207\u7247\u3001\u5f62\u72b6\u53d8\u6362\u548c\u6570\u7ec4\u8fd0\u7b97\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6570\u7ec4\u5207\u7247<\/p>\n<p>print(a[1:4])  # \u8f93\u51fa\uff1a[2 3 4]<\/p>\n<h2><strong>\u6570\u7ec4\u5f62\u72b6\u53d8\u6362<\/strong><\/h2>\n<p>d = c.reshape(3, 2)<\/p>\n<p>print(d)  # \u8f93\u51fa\uff1a[[1 2] [3 4] [5 6]]<\/p>\n<h2><strong>\u6570\u7ec4\u8fd0\u7b97<\/strong><\/h2>\n<p>e = a + b<\/p>\n<p>print(e)  # \u8f93\u51fa\uff1a[ 7  9 11 13 15]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>6.4 \u6570\u5b66\u51fd\u6570<\/h4>\n<\/p>\n<p><p>numpy\u63d0\u4f9b\u4e86\u8bb8\u591a\u6570\u5b66\u51fd\u6570\uff0c\u4f8b\u5982\u6c42\u548c\u3001\u5e73\u5747\u503c\u548c\u6807\u51c6\u5dee\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u6c42\u548c<\/p>\n<p>print(np.sum(a))  # \u8f93\u51fa\uff1a15<\/p>\n<h2><strong>\u5e73\u5747\u503c<\/strong><\/h2>\n<p>print(np.mean(a))  # \u8f93\u51fa\uff1a3.0<\/p>\n<h2><strong>\u6807\u51c6\u5dee<\/strong><\/h2>\n<p>print(np.std(a))  # \u8f93\u51fa\uff1a1.4142135623730951<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>6.5 \u751f\u6210\u968f\u673a\u6570<\/h4>\n<\/p>\n<p><p>numpy\u8fd8\u63d0\u4f9b\u4e86\u751f\u6210\u968f\u673a\u6570\u7684\u529f\u80fd\uff0c\u4f8b\u5982\u751f\u6210\u5747\u5300\u5206\u5e03\u548c\u6b63\u6001\u5206\u5e03\u7684\u968f\u673a\u6570\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u5747\u5300\u5206\u5e03\u7684\u968f\u673a\u6570<\/p>\n<p>f = np.random.rand(5)<\/p>\n<p>print(f)  # \u8f93\u51fa\uff1a[0.5488135  0.71518937 0.60276338 0.54488318 0.4236548 ]<\/p>\n<h2><strong>\u751f\u6210\u6b63\u6001\u5206\u5e03\u7684\u968f\u673a\u6570<\/strong><\/h2>\n<p>g = np.random.randn(5)<\/p>\n<p>print(g)  # \u8f93\u51fa\uff1a[ 0.97873798  2.2408932   1.86755799 -0.97727788  0.95008842]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e03\u3001numpy\u5728\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e94\u7528<\/h3>\n<\/p>\n<p><p>numpy\u5728\u6570\u636e\u5206\u6790\u4e2d\u6709\u7740\u5e7f\u6cdb\u7684\u5e94\u7528\uff0c\u7279\u522b\u662f\u5728\u79d1\u5b66\u8ba1\u7b97\u548c\u6570\u636e\u5904\u7406\u65b9\u9762\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9bnumpy\u5728\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e38\u89c1\u5e94\u7528\u3002<\/p>\n<\/p>\n<p><h4>7.1 \u6570\u636e\u8bfb\u53d6\u4e0e\u5904\u7406<\/h4>\n<\/p>\n<p><p>numpy\u53ef\u4ee5\u65b9\u4fbf\u5730\u8bfb\u53d6\u548c\u5904\u7406\u6570\u636e\uff0c\u4f8b\u5982\u4ece\u6587\u672c\u6587\u4ef6\u4e2d\u8bfb\u53d6\u6570\u636e\u5e76\u8fdb\u884c\u5904\u7406\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u4ece\u6587\u672c\u6587\u4ef6\u4e2d\u8bfb\u53d6\u6570\u636e<\/p>\n<p>data = np.loadtxt(&#39;data.txt&#39;, delimiter=&#39;,&#39;)<\/p>\n<h2><strong>\u6570\u636e\u5904\u7406<\/strong><\/h2>\n<p>mean_data = np.mean(data, axis=0)<\/p>\n<p>std_data = np.std(data, axis=0)<\/p>\n<p>normalized_data = (data - mean_data) \/ std_data<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>7.2 \u6570\u636e\u53ef\u89c6\u5316<\/h4>\n<\/p>\n<p><p>numpy\u4e0ematplotlib\u5e93\u914d\u5408\u4f7f\u7528\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\u3002\u4f8b\u5982\uff0c\u7ed8\u5236\u6570\u636e\u7684\u6298\u7ebf\u56fe\u548c\u6563\u70b9\u56fe\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<h2><strong>\u751f\u6210\u6570\u636e<\/strong><\/h2>\n<p>x = np.linspace(0, 10, 100)<\/p>\n<p>y = np.sin(x)<\/p>\n<h2><strong>\u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n<p>plt.plot(x, y)<\/p>\n<p>plt.xlabel(&#39;x&#39;)<\/p>\n<p>plt.ylabel(&#39;sin(x)&#39;)<\/p>\n<p>plt.title(&#39;Sine Wave&#39;)<\/p>\n<p>plt.show()<\/p>\n<h2><strong>\u751f\u6210\u968f\u673a\u6570\u636e<\/strong><\/h2>\n<p>x = np.random.rand(100)<\/p>\n<p>y = np.random.rand(100)<\/p>\n<h2><strong>\u7ed8\u5236\u6563\u70b9\u56fe<\/strong><\/h2>\n<p>plt.scatter(x, y)<\/p>\n<p>plt.xlabel(&#39;x&#39;)<\/p>\n<p>plt.ylabel(&#39;y&#39;)<\/p>\n<p>plt.title(&#39;Scatter Plot&#39;)<\/p>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>7.3 \u7edf\u8ba1\u5206\u6790<\/h4>\n<\/p>\n<p><p>numpy\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7edf\u8ba1\u51fd\u6570\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u7edf\u8ba1\u5206\u6790\u3002\u4f8b\u5982\uff0c\u8ba1\u7b97\u6570\u636e\u7684\u5747\u503c\u3001\u4e2d\u4f4d\u6570\u548c\u65b9\u5dee\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n<p>data = np.random.randn(1000)<\/p>\n<h2><strong>\u7edf\u8ba1\u5206\u6790<\/strong><\/h2>\n<p>mean_data = np.mean(data)<\/p>\n<p>median_data = np.median(data)<\/p>\n<p>var_data = np.var(data)<\/p>\n<p>print(f&#39;Mean: {mean_data}, Median: {median_data}, Variance: {var_data}&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u516b\u3001numpy\u5728<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u4e2d\u7684\u5e94\u7528<\/h3>\n<\/p>\n<p><p>numpy\u5728\u673a\u5668\u5b66\u4e60\u4e2d\u4e5f\u6709\u7740\u5e7f\u6cdb\u7684\u5e94\u7528\uff0c\u7279\u522b\u662f\u5728\u6570\u636e\u9884\u5904\u7406\u548c\u7279\u5f81\u5de5\u7a0b\u65b9\u9762\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9bnumpy\u5728\u673a\u5668\u5b66\u4e60\u4e2d\u7684\u5e38\u89c1\u5e94\u7528\u3002<\/p>\n<\/p>\n<p><h4>8.1 \u6570\u636e\u9884\u5904\u7406<\/h4>\n<\/p>\n<p><p>\u5728\u673a\u5668\u5b66\u4e60\u4e2d\uff0c\u6570\u636e\u9884\u5904\u7406\u662f\u4e00\u4e2a\u91cd\u8981\u7684\u6b65\u9aa4\u3002numpy\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u636e\u9884\u5904\u7406\uff0c\u4f8b\u5982\u5f52\u4e00\u5316\u548c\u6807\u51c6\u5316\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n<p>data = np.random.rand(100, 5)<\/p>\n<h2><strong>\u5f52\u4e00\u5316<\/strong><\/h2>\n<p>min_data = np.min(data, axis=0)<\/p>\n<p>max_data = np.max(data, axis=0)<\/p>\n<p>normalized_data = (data - min_data) \/ (max_data - min_data)<\/p>\n<h2><strong>\u6807\u51c6\u5316<\/strong><\/h2>\n<p>mean_data = np.mean(data, axis=0)<\/p>\n<p>std_data = np.std(data, axis=0)<\/p>\n<p>standardized_data = (data - mean_data) \/ std_data<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>8.2 \u7279\u5f81\u5de5\u7a0b<\/h4>\n<\/p>\n<p><p>\u7279\u5f81\u5de5\u7a0b\u662f\u673a\u5668\u5b66\u4e60\u4e2d\u7684\u5173\u952e\u6b65\u9aa4\uff0cnumpy\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u7279\u5f81\u5de5\u7a0b\uff0c\u4f8b\u5982\u7279\u5f81\u9009\u62e9\u548c\u7279\u5f81\u63d0\u53d6\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u968f\u673a\u6570\u636e<\/p>\n<p>data = np.random.rand(100, 10)<\/p>\n<h2><strong>\u7279\u5f81\u9009\u62e9<\/strong><\/h2>\n<p>selected_features = data[:, [0, 2, 4, 6, 8]]<\/p>\n<h2><strong>\u7279\u5f81\u63d0\u53d6<\/strong><\/h2>\n<p>mean_features = np.mean(data, axis=1)<\/p>\n<p>std_features = np.std(data, axis=1)<\/p>\n<p>extracted_features = np.column_stack((mean_features, std_features))<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e5d\u3001numpy\u9ad8\u7ea7\u6280\u5de7<\/h3>\n<\/p>\n<p><p>numpy\u63d0\u4f9b\u4e86\u8bb8\u591a\u9ad8\u7ea7\u6280\u5de7\uff0c\u53ef\u4ee5\u63d0\u9ad8\u4ee3\u7801\u7684\u6548\u7387\u548c\u53ef\u8bfb\u6027\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684numpy\u9ad8\u7ea7\u6280\u5de7\u3002<\/p>\n<\/p>\n<p><h4>9.1 \u5e7f\u64ad\u673a\u5236<\/h4>\n<\/p>\n<p><p>numpy\u7684\u5e7f\u64ad\u673a\u5236\u5141\u8bb8\u4e0d\u540c\u5f62\u72b6\u7684\u6570\u7ec4\u8fdb\u884c\u7b97\u672f\u8fd0\u7b97\uff0c\u800c\u65e0\u9700\u663e\u5f0f\u5730\u590d\u5236\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u6570\u636e<\/p>\n<p>a = np.array([1, 2, 3])<\/p>\n<p>b = np.array([[1], [2], [3]])<\/p>\n<h2><strong>\u5e7f\u64ad\u673a\u5236<\/strong><\/h2>\n<p>result = a + b<\/p>\n<p>print(result)  # \u8f93\u51fa\uff1a[[2 3 4] [3 4 5] [4 5 6]]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>9.2 \u5411\u91cf\u5316\u64cd\u4f5c<\/h4>\n<\/p>\n<p><p>\u5411\u91cf\u5316\u64cd\u4f5c\u662f\u6307\u4f7f\u7528numpy\u7684\u6570\u7ec4\u8fd0\u7b97\u4ee3\u66ffPython\u7684\u5faa\u73af\u64cd\u4f5c\uff0c\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u4ee3\u7801\u7684\u6267\u884c\u6548\u7387\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u6570\u636e<\/p>\n<p>data = np.random.rand(1000000)<\/p>\n<h2><strong>\u4f7f\u7528\u5faa\u73af\u8ba1\u7b97<\/strong><\/h2>\n<p>result_loop = np.zeros_like(data)<\/p>\n<p>for i in range(len(data)):<\/p>\n<p>    result_loop[i] = data[i]  2<\/p>\n<h2><strong>\u4f7f\u7528\u5411\u91cf\u5316\u64cd\u4f5c<\/strong><\/h2>\n<p>result_vectorized = data  2<\/p>\n<h2><strong>\u9a8c\u8bc1\u7ed3\u679c<\/strong><\/h2>\n<p>print(np.allclose(result_loop, result_vectorized))  # \u8f93\u51fa\uff1aTrue<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>9.3 \u5185\u5b58\u4f18\u5316<\/h4>\n<\/p>\n<p><p>numpy\u63d0\u4f9b\u4e86\u4e00\u4e9b\u5185\u5b58\u4f18\u5316\u6280\u5de7\uff0c\u53ef\u4ee5\u51cf\u5c11\u5185\u5b58\u5360\u7528\u548c\u63d0\u9ad8\u8ba1\u7b97\u6548\u7387\u3002\u4f8b\u5982\uff0c\u4f7f\u7528in-place\u64cd\u4f5c\u548c\u5408\u7406\u9009\u62e9\u6570\u636e\u7c7b\u578b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u6570\u636e<\/p>\n<p>data = np.random.rand(1000000)<\/p>\n<h2><strong>\u4f7f\u7528in-place\u64cd\u4f5c<\/strong><\/h2>\n<p>data = 2<\/p>\n<h2><strong>\u5408\u7406\u9009\u62e9\u6570\u636e\u7c7b\u578b<\/strong><\/h2>\n<p>data_int = np.array(data, dtype=np.int32)<\/p>\n<p>print(data_int.nbytes)  # \u8f93\u51fa\uff1a4000000\uff08\u6bd4\u9ed8\u8ba4\u7684float64\u7c7b\u578b\u8282\u7701\u4e86\u4e00\u534a\u5185\u5b58\uff09<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u5341\u3001numpy\u5e38\u89c1\u9519\u8bef\u53ca\u8c03\u8bd5\u65b9\u6cd5<\/h3>\n<\/p>\n<p><p>\u5728\u4f7f\u7528numpy\u7684\u8fc7\u7a0b\u4e2d\uff0c\u53ef\u80fd\u4f1a\u9047\u5230\u4e00\u4e9b\u5e38\u89c1\u9519\u8bef\u548c\u8c03\u8bd5\u95ee\u9898\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u9519\u8bef\u53ca\u5176\u8c03\u8bd5\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<p><h4>10.1 \u5f62\u72b6\u4e0d\u5339\u914d\u9519\u8bef<\/h4>\n<\/p>\n<p><p>\u5f62\u72b6\u4e0d\u5339\u914d\u9519\u8bef\u901a\u5e38\u53d1\u751f\u5728\u8fdb\u884c\u6570\u7ec4\u8fd0\u7b97\u65f6\uff0c\u4e24\u4e2a\u6570\u7ec4\u7684\u5f62\u72b6\u4e0d\u517c\u5bb9\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u89e3\u51b3\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u6570\u636e<\/p>\n<p>a = np.array([1, 2, 3])<\/p>\n<p>b = np.array([4, 5])<\/p>\n<h2><strong>\u5f62\u72b6\u4e0d\u5339\u914d\u9519\u8bef<\/strong><\/h2>\n<p>try:<\/p>\n<p>    result = a + b<\/p>\n<p>except ValueError as e:<\/p>\n<p>    print(f&#39;Error: {e}&#39;)<\/p>\n<h2><strong>\u8c03\u6574\u5f62\u72b6<\/strong><\/h2>\n<p>b = np.array([4, 5, 6])<\/p>\n<p>result = a + b<\/p>\n<p>print(result)  # \u8f93\u51fa\uff1a[5 7 9]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>10.2 \u6570\u636e\u7c7b\u578b\u9519\u8bef<\/h4>\n<\/p>\n<p><p>\u6570\u636e\u7c7b\u578b\u9519\u8bef\u901a\u5e38\u53d1\u751f\u5728\u8fdb\u884c\u6570\u7ec4\u8fd0\u7b97\u65f6\uff0c\u4e24\u4e2a\u6570\u7ec4\u7684\u6570\u636e\u7c7b\u578b\u4e0d\u517c\u5bb9\u3002\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u89e3\u51b3\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u6570\u636e<\/p>\n<p>a = np.array([1, 2, 3])<\/p>\n<p>b = np.array([4.0, 5.0, 6.0])<\/p>\n<h2><strong>\u6570\u636e\u7c7b\u578b\u9519\u8bef<\/strong><\/h2>\n<p>try:<\/p>\n<p>    result = a + b<\/p>\n<p>except TypeError as e:<\/p>\n<p>    print(f&#39;Error: {e}&#39;)<\/p>\n<h2><strong>\u8f6c\u6362\u6570\u636e\u7c7b\u578b<\/strong><\/h2>\n<p>a = a.astype(float)<\/p>\n<p>result = a + b<\/p>\n<p>print(result)  # \u8f93\u51fa\uff1a[5. 7. 9.]<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>10.3 \u5185\u5b58\u4e0d\u8db3\u9519\u8bef<\/h4>\n<\/p>\n<p><p>\u5185\u5b58\u4e0d\u8db3\u9519\u8bef\u901a\u5e38\u53d1\u751f\u5728\u5904\u7406\u5927\u6570\u636e\u96c6\u65f6\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u89e3\u51b3\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210\u5927\u6570\u636e\u96c6<\/p>\n<p>try:<\/p>\n<p>    data = np.ones((100000, 100000))<\/p>\n<p>except MemoryError as e:<\/p>\n<p>    print(f&#39;Error: {e}&#39;)<\/p>\n<h2><strong>\u4f7f\u7528\u751f\u6210\u5668\u8bfb\u53d6\u6570\u636e<\/strong><\/h2>\n<p>def data_generator(file_path, chunk_size):<\/p>\n<p>    with open(file_path, &#39;r&#39;) as f:<\/p>\n<p>        while True:<\/p>\n<p>            chunk = f.read(chunk_size)<\/p>\n<p>            if not chunk:<\/p>\n<p><\/code><\/pre>\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\u5b89\u88c5numpy\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u7684\u5305\u7ba1\u7406\u5de5\u5177pip\u3002\u6253\u5f00\u547d\u4ee4\u884c\u6216\u7ec8\u7aef\uff0c\u8f93\u5165\u4ee5\u4e0b\u547d\u4ee4\uff1a<code>pip install numpy<\/code>\u3002\u786e\u4fdd\u4f60\u7684Python\u73af\u5883\u5df2\u7ecf\u914d\u7f6e\u597dpip\u5de5\u5177\u3002\u5982\u679c\u4f60\u4f7f\u7528\u7684\u662fAnaconda\uff0c\u53ef\u4ee5\u901a\u8fc7\u547d\u4ee4<code>conda install numpy<\/code>\u6765\u5b89\u88c5\u3002<\/p>\n<p><strong>\u5982\u679c\u6211\u5728\u5b89\u88c5numpy\u65f6\u9047\u5230\u9519\u8bef\uff0c\u5e94\u8be5\u5982\u4f55\u89e3\u51b3\uff1f<\/strong><br \/>\u5982\u679c\u5728\u5b89\u88c5\u8fc7\u7a0b\u4e2d\u9047\u5230\u9519\u8bef\uff0c\u9996\u5148\u68c0\u67e5\u4f60\u7684Python\u548cpip\u7248\u672c\u662f\u5426\u662f\u6700\u65b0\u7684\u3002\u53ef\u4ee5\u901a\u8fc7\u547d\u4ee4<code>python --version<\/code>\u548c<code>pip --version<\/code>\u6765\u786e\u8ba4\u3002\u82e5\u7248\u672c\u8fc7\u65e7\uff0c\u53ef\u4ee5\u5347\u7ea7pip\uff0c\u4f7f\u7528\u547d\u4ee4<code>pip install --upgrade pip<\/code>\u3002\u53e6\u5916\uff0c\u786e\u4fdd\u7f51\u7edc\u8fde\u63a5\u826f\u597d\uff0c\u6709\u65f6\u7f51\u7edc\u95ee\u9898\u4f1a\u5bfc\u81f4\u5b89\u88c5\u5931\u8d25\u3002<\/p>\n<p><strong>numpy\u5e93\u5b89\u88c5\u540e\uff0c\u5982\u4f55\u786e\u8ba4\u5b83\u662f\u5426\u6b63\u786e\u5b89\u88c5\uff1f<\/strong><br \/>\u5b89\u88c5\u5b8c\u6210\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7\u5728Python\u4ea4\u4e92\u5f0f\u547d\u4ee4\u884c\u6216\u811a\u672c\u4e2d\u8f93\u5165<code>import numpy<\/code>\u6765\u786e\u8ba4\u662f\u5426\u6b63\u786e\u5b89\u88c5\u3002\u5982\u679c\u6ca1\u6709\u51fa\u73b0\u9519\u8bef\u63d0\u793a\uff0c\u8868\u793anumpy\u5b89\u88c5\u6210\u529f\u3002\u8fd8\u53ef\u4ee5\u901a\u8fc7<code>print(numpy.__version__)<\/code>\u6765\u67e5\u770b\u5b89\u88c5\u7684numpy\u7248\u672c\uff0c\u786e\u4fdd\u5b83\u7b26\u5408\u4f60\u7684\u9700\u6c42\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u5b89\u88c5\u5e93\u6587\u4ef6numpy\u7684\u6b65\u9aa4\uff1a\u4f7f\u7528pip\u5de5\u5177\u5b89\u88c5\u3001\u4f7f\u7528conda\u5de5\u5177\u5b89\u88c5\u3001\u901a\u8fc7\u6e90\u7801\u5b89\u88c5\u3002\u63a8\u8350\u4f7f\u7528pi [&hellip;]","protected":false},"author":3,"featured_media":1164895,"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\/1164886"}],"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=1164886"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1164886\/revisions"}],"predecessor-version":[{"id":1164897,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1164886\/revisions\/1164897"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1164895"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1164886"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1164886"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1164886"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}