\u5b66\u4e60\u66f2\u7ebf\u76f8\u5bf9\u8f83\u9661\uff0c\u5bf9\u4e8e\u65b0\u624b\u53ef\u80fd\u9700\u8981\u4e00\u4e9b\u65f6\u95f4\u9002\u5e94\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\u4e8c\u3001\u914d\u7f6e\u73af\u5883<\/h3>\n<\/p>\n
\u5728\u9009\u62e9\u597d\u5de5\u5177\u4e4b\u540e\uff0c\u4e0b\u4e00\u6b65\u5c31\u662f\u914d\u7f6ePython\u4ea4\u4e92\u73af\u5883\u3002\u8fd9\u4e00\u6b65\u9aa4\u5305\u62ec\u5b89\u88c5Python\u3001\u8bbe\u7f6e\u8def\u5f84\u3001\u521b\u5efa\u865a\u62df\u73af\u5883\u7b49\u3002<\/p>\n<\/p>\n
1. \u5b89\u88c5Python<\/h4>\n<\/p>\n
\u9996\u5148\uff0c\u9700\u8981\u5728\u7cfb\u7edf\u4e0a\u5b89\u88c5Python\u3002\u53ef\u4ee5\u4ecePython\u5b98\u65b9\u7f51\u7ad9\u4e0b\u8f7d\u9002\u5408\u81ea\u5df1\u64cd\u4f5c\u7cfb\u7edf\u7684\u5b89\u88c5\u5305\u3002\u5b89\u88c5\u8fc7\u7a0b\u4e2d\uff0c\u786e\u4fdd\u52fe\u9009\u201cAdd Python to PATH\u201d\u9009\u9879\uff0c\u4ee5\u4fbf\u5728\u547d\u4ee4\u884c\u4e2d\u76f4\u63a5\u4f7f\u7528Python\u547d\u4ee4\u3002<\/p>\n<\/p>\n
2. \u8bbe\u7f6e\u8def\u5f84<\/h4>\n<\/p>\n
\u5728Windows\u7cfb\u7edf\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u201c\u7cfb\u7edf\u5c5e\u6027\u201d->\u201c\u73af\u5883\u53d8\u91cf\u201d\u6765\u8bbe\u7f6ePython\u7684\u8def\u5f84\u3002\u5728Linux\u548cmacOS\u7cfb\u7edf\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u7f16\u8f91.bashrc<\/code>\u6216.zshrc<\/code>\u6587\u4ef6\uff0c\u5c06Python\u8def\u5f84\u6dfb\u52a0\u5230PATH<\/code>\u53d8\u91cf\u4e2d\u3002<\/p>\n<\/p>\n3. \u521b\u5efa\u865a\u62df\u73af\u5883<\/h4>\n<\/p>\n
\u4f7f\u7528\u865a\u62df\u73af\u5883\u53ef\u4ee5\u9694\u79bb\u4e0d\u540c\u9879\u76ee\u7684\u4f9d\u8d56\uff0c\u907f\u514d\u7248\u672c\u51b2\u7a81\u3002\u53ef\u4ee5\u4f7f\u7528venv<\/code>\u6a21\u5757\u6765\u521b\u5efa\u865a\u62df\u73af\u5883\uff1a<\/p>\n<\/p>\npython -m venv myenv<\/p>\n<\/code><\/pre>\n<\/p>\n
\u6fc0\u6d3b\u865a\u62df\u73af\u5883\uff1a<\/p>\n<\/p>\n
\n- \n
\u5728Windows\u7cfb\u7edf\u4e2d\uff1a<\/p>\n<\/p>\n
myenv\\Scripts\\activate<\/p>\n<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
\u5728Linux\u548cmacOS\u7cfb\u7edf\u4e2d\uff1a<\/p>\n<\/p>\n
source myenv\/bin\/activate<\/p>\n<\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n
\u4e09\u3001\u5b89\u88c5\u5fc5\u8981\u7684\u5e93<\/h3>\n<\/p>\n
\u5728\u914d\u7f6e\u597d\u73af\u5883\u540e\uff0c\u9700\u8981\u5b89\u88c5\u5fc5\u8981\u7684Python\u5e93\uff0c\u4ee5\u4fbf\u5728\u4ea4\u4e92\u73af\u5883\u4e2d\u6267\u884c\u5404\u79cd\u4efb\u52a1\u3002\u5e38\u7528\u7684\u5e93\u5305\u62ec\u4f46\u4e0d\u9650\u4e8eNumPy\u3001Pandas\u3001Matplotlib\u3001Scikit-learn\u7b49\u3002<\/p>\n<\/p>\n
1. NumPy<\/h4>\n<\/p>\n
NumPy\u662fPython\u4e2d\u7528\u4e8e\u79d1\u5b66\u8ba1\u7b97\u7684\u57fa\u7840\u5e93\uff0c\u63d0\u4f9b\u4e86\u652f\u6301\u591a\u7ef4\u6570\u7ec4\u548c\u77e9\u9635\u8fd0\u7b97\u7684\u9ad8\u6548\u63a5\u53e3\u3002<\/p>\n<\/p>\n
\n- \n
\u5b89\u88c5NumPy\uff1a<\/p>\n<\/p>\n
pip install numpy<\/p>\n<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
\u4f7f\u7528NumPy\u53ef\u4ee5\u65b9\u4fbf\u5730\u8fdb\u884c\u6570\u503c\u8ba1\u7b97\u548c\u7ebf\u6027\u4ee3\u6570\u64cd\u4f5c\uff0c\u662f\u6570\u636e\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n<\/li>\n<\/ul>\n
2. Pandas<\/h4>\n<\/p>\n
Pandas\u662f\u7528\u4e8e\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u7684\u9ad8\u7ea7\u5e93\uff0c\u652f\u6301\u6570\u636e\u6e05\u6d17\u3001\u53d8\u6362\u3001\u5408\u5e76\u3001\u5206\u7ec4\u7b49\u591a\u79cd\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
\n- \n
\u5b89\u88c5Pandas\uff1a<\/p>\n<\/p>\n
pip install pandas<\/p>\n<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
Pandas\u63d0\u4f9b\u4e86DataFrame\u548cSeries\u6570\u636e\u7ed3\u6784\uff0c\u53ef\u4ee5\u9ad8\u6548\u5730\u5904\u7406\u7ed3\u6784\u5316\u6570\u636e\uff0c\u5e7f\u6cdb\u7528\u4e8e\u6570\u636e\u5206\u6790\u548c\u9884\u5904\u7406\u3002<\/p>\n<\/p>\n<\/li>\n<\/ul>\n
3. Matplotlib<\/h4>\n<\/p>\n
Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u80fd\u591f\u521b\u5efa\u9759\u6001\u3001\u52a8\u6001\u548c\u4ea4\u4e92\u5f0f\u56fe\u8868\u3002<\/p>\n<\/p>\n
\n- \n
\u5b89\u88c5Matplotlib\uff1a<\/p>\n<\/p>\n
pip install matplotlib<\/p>\n<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
Matplotlib\u652f\u6301\u591a\u79cd\u56fe\u8868\u7c7b\u578b\uff0c\u5305\u62ec\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u3001\u997c\u56fe\u7b49\uff0c\u662f\u6570\u636e\u53ef\u89c6\u5316\u7684\u5229\u5668\u3002<\/p>\n<\/p>\n<\/li>\n<\/ul>\n
4. Scikit-learn<\/h4>\n<\/p>\n
Scikit-learn\u662fPython\u4e2d\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u7684\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7b97\u6cd5\u548c\u5de5\u5177\uff0c\u7528\u4e8e\u5206\u7c7b\u3001\u56de\u5f52\u3001\u805a\u7c7b\u3001\u964d\u7ef4\u7b49\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\n- \n
\u5b89\u88c5Scikit-learn\uff1a<\/p>\n<\/p>\n
pip install scikit-learn<\/p>\n<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
Scikit-learn\u7684\u63a5\u53e3\u7b80\u6d01\u7edf\u4e00\uff0c\u6613\u4e8e\u5b66\u4e60\u548c\u4f7f\u7528\uff0c\u9002\u5408\u4e8e\u5404\u7c7b\u673a\u5668\u5b66\u4e60\u4efb\u52a1\u3002<\/p>\n<\/p>\n<\/li>\n<\/ul>\n
\u56db\u3001\u719f\u6089\u57fa\u672c\u547d\u4ee4\u548c\u64cd\u4f5c<\/h3>\n<\/p>\n
\u5728\u63a8\u51faPython\u4ea4\u4e92\u73af\u5883\u65f6\uff0c\u719f\u6089\u57fa\u672c\u547d\u4ee4\u548c\u64cd\u4f5c\u53ef\u4ee5\u5e2e\u52a9\u7528\u6237\u66f4\u597d\u5730\u5229\u7528\u73af\u5883\u8fdb\u884c\u5404\u79cd\u4efb\u52a1\u3002<\/p>\n<\/p>\n
1. \u57fa\u672c\u547d\u4ee4<\/h4>\n<\/p>\n
\u5728Python\u4ea4\u4e92\u73af\u5883\u4e2d\uff0c\u5e38\u7528\u7684\u547d\u4ee4\u5305\u62ec\u53d8\u91cf\u8d4b\u503c\u3001\u51fd\u6570\u5b9a\u4e49\u3001\u6761\u4ef6\u5224\u65ad\u3001\u5faa\u73af\u7b49\u3002\u638c\u63e1\u8fd9\u4e9b\u57fa\u672c\u547d\u4ee4\u662f\u7f16\u5199Python\u4ee3\u7801\u7684\u57fa\u7840\u3002<\/p>\n<\/p>\n
\n- \n
\u53d8\u91cf\u8d4b\u503c\uff1a<\/p>\n<\/p>\n
a = 10<\/p>\nb = 20<\/p>\n
<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
\u51fd\u6570\u5b9a\u4e49\uff1a<\/p>\n<\/p>\n
def add(x, y):<\/p>\n return x + y<\/p>\n
<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
\u6761\u4ef6\u5224\u65ad\uff1a<\/p>\n<\/p>\n
if a > b:<\/p>\n print("a is greater than b")<\/p>\n
else:<\/p>\n
print("a is not greater than b")<\/p>\n
<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
\u5faa\u73af\uff1a<\/p>\n<\/p>\n
for i in range(5):<\/p>\n print(i)<\/p>\n
<\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n
2. \u6570\u636e\u64cd\u4f5c<\/h4>\n<\/p>\n
\u5728Python\u4ea4\u4e92\u73af\u5883\u4e2d\uff0c\u6570\u636e\u64cd\u4f5c\u662f\u5e38\u89c1\u7684\u4efb\u52a1\u4e4b\u4e00\u3002\u5e38\u7528\u7684\u6570\u636e\u64cd\u4f5c\u5305\u62ec\u6570\u7ec4\u64cd\u4f5c\u3001\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u53d8\u6362\u7b49\u3002<\/p>\n<\/p>\n
\n- \n
\u6570\u7ec4\u64cd\u4f5c\uff1a<\/p>\n<\/p>\n
\u4f7f\u7528NumPy\u8fdb\u884c\u6570\u7ec4\u64cd\u4f5c\uff0c\u4f8b\u5982\u521b\u5efa\u6570\u7ec4\u3001\u6570\u7ec4\u8fd0\u7b97\u3001\u6570\u7ec4\u5207\u7247\u7b49\u3002<\/p>\n<\/p>\n
import numpy as np<\/p>\narr = np.array([1, 2, 3, 4, 5])<\/p>\n
print(arr + 10)<\/p>\n
<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
\u6570\u636e\u6e05\u6d17\uff1a<\/p>\n<\/p>\n
\u4f7f\u7528Pandas\u8fdb\u884c\u6570\u636e\u6e05\u6d17\uff0c\u4f8b\u5982\u7f3a\u5931\u503c\u5904\u7406\u3001\u6570\u636e\u7c7b\u578b\u8f6c\u6362\u7b49\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\ndf = pd.DataFrame({'A': [1, 2, None], 'B': [4, None, 6]})<\/p>\n
df.fillna(0, inplace=True)<\/p>\n
print(df)<\/p>\n
<\/code><\/pre>\n<\/p>\n<\/li>\n
- \n
\u6570\u636e\u53d8\u6362\uff1a<\/p>\n<\/p>\n
\u4f7f\u7528Pandas\u8fdb\u884c\u6570\u636e\u53d8\u6362\uff0c\u4f8b\u5982\u6570\u636e\u805a\u5408\u3001\u6570\u636e\u900f\u89c6\u7b49\u3002<\/p>\n<\/p>\n
df = pd.DataFrame({'A': ['foo', 'bar', 'foo', 'bar'],<\/p>\n 'B': ['one', 'one', 'two', 'two'],<\/p>\n
'C': [1, 2, 3, 4]})<\/p>\n
result = df.pivot_table(index='A', columns='B', values='C', aggfunc='sum')<\/p>\n
print(result)<\/p>\n
<\/code><\/pre>\n<\/p>\n<\/li>\n<\/ul>\n
\u901a\u8fc7\u4e0a\u8ff0\u6b65\u9aa4\uff0c\u7528\u6237\u53ef\u4ee5\u6210\u529f\u63a8\u51faPython\u4ea4\u4e92\u73af\u5883\uff0c\u5e76\u5f00\u59cb\u8fdb\u884c\u6570\u636e\u5206\u6790\u3001\u53ef\u89c6\u5316\u548c\u673a\u5668\u5b66\u4e60\u7b49\u4efb\u52a1\u3002\u719f\u6089\u5de5\u5177\u3001\u914d\u7f6e\u73af\u5883\u3001\u5b89\u88c5\u5e93\u548c\u638c\u63e1\u57fa\u672c\u547d\u4ee4\u64cd\u4f5c\u662f\u786e\u4fddPython\u4ea4\u4e92\u73af\u5883\u987a\u5229\u8fd0\u884c\u7684\u5173\u952e\u3002\u9009\u62e9\u5408\u9002\u7684\u5de5\u5177\u3001\u5408\u7406\u914d\u7f6e\u73af\u5883\u3001\u79d1\u5b66\u4f7f\u7528\u5e93\u548c\u719f\u7ec3\u64cd\u4f5c\u547d\u4ee4\uff0c\u80fd\u591f\u663e\u8457\u63d0\u9ad8\u5de5\u4f5c\u6548\u7387\u548c\u9879\u76ee\u8d28\u91cf\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n \u5982\u4f55\u5728\u4e0d\u540c\u64cd\u4f5c\u7cfb\u7edf\u4e0a\u542f\u52a8Python\u4ea4\u4e92\u73af\u5883\uff1f<\/strong>
\u5728Windows\u7cfb\u7edf\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u547d\u4ee4\u63d0\u793a\u7b26\u8f93\u5165python<\/code>\u6216python3<\/code>\u6765\u542f\u52a8\u4ea4\u4e92\u73af\u5883\u3002\u5982\u679c\u4f60\u5b89\u88c5\u4e86Anaconda\uff0c\u53ef\u4ee5\u901a\u8fc7Anaconda Prompt\u8fdb\u5165Python\u4ea4\u4e92\u73af\u5883\u3002\u5728Mac\u548cLinux\u7cfb\u7edf\u4e2d\uff0c\u6253\u5f00\u7ec8\u7aef\u5e76\u8f93\u5165python<\/code>\u6216python3<\/code>\u540c\u6837\u53ef\u4ee5\u542f\u52a8\u4ea4\u4e92\u73af\u5883\u3002\u786e\u4fdd\u5df2\u7ecf\u6b63\u786e\u5b89\u88c5Python\uff0c\u5e76\u5c06\u5176\u6dfb\u52a0\u5230\u7cfb\u7edf\u7684PATH\u53d8\u91cf\u4e2d\u3002<\/p>\n\u5728Python\u4ea4\u4e92\u73af\u5883\u4e2d\u53ef\u4ee5\u6267\u884c\u54ea\u4e9b\u64cd\u4f5c\uff1f<\/strong>
Python\u4ea4\u4e92\u73af\u5883\u5141\u8bb8\u7528\u6237\u5b9e\u65f6\u8f93\u5165Python\u4ee3\u7801\u5e76\u7acb\u5373\u67e5\u770b\u7ed3\u679c\u3002\u7528\u6237\u53ef\u4ee5\u6267\u884c\u7b80\u5355\u7684\u6570\u5b66\u8fd0\u7b97\u3001\u5b9a\u4e49\u53d8\u91cf\u3001\u7f16\u5199\u51fd\u6570\u4ee5\u53ca\u6d4b\u8bd5\u4ee3\u7801\u7247\u6bb5\u3002\u8fd9\u79cd\u5373\u65f6\u53cd\u9988\u673a\u5236\u975e\u5e38\u9002\u5408\u5b66\u4e60\u548c\u8c03\u8bd5\u4ee3\u7801\uff0c\u5e2e\u52a9\u7528\u6237\u5feb\u901f\u7406\u89e3Python\u7684\u8bed\u6cd5\u548c\u529f\u80fd\u3002<\/p>\n\u5982\u4f55\u5728Python\u4ea4\u4e92\u73af\u5883\u4e2d\u5b89\u88c5\u548c\u4f7f\u7528\u7b2c\u4e09\u65b9\u5e93\uff1f<\/strong>
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