{"id":998679,"date":"2024-12-27T09:35:07","date_gmt":"2024-12-27T01:35:07","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/998679.html"},"modified":"2024-12-27T09:35:09","modified_gmt":"2024-12-27T01:35:09","slug":"stata%e5%a6%82%e4%bd%95%e8%bf%90%e8%a1%8cpython%e4%bb%a3%e7%a0%81","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/998679.html","title":{"rendered":"stata\u5982\u4f55\u8fd0\u884cpython\u4ee3\u7801"},"content":{"rendered":"

\"stata\u5982\u4f55\u8fd0\u884cpython\u4ee3\u7801\"<\/p>\n

\u5728Stata\u4e2d\u8fd0\u884cPython\u4ee3\u7801\u7684\u65b9\u6cd5\u6709\u51e0\u79cd\uff0c\u5305\u62ec\u4f7f\u7528Stata\u7684\u5185\u7f6ePython\u96c6\u6210\u3001\u901a\u8fc7\u5916\u90e8\u811a\u672c\u8c03\u7528Python\u3001\u4ee5\u53ca\u5728Stata\u73af\u5883\u4e2d\u5d4c\u5165Python\u4ee3\u7801<\/strong>\u3002\u5176\u4e2d\uff0c\u6700\u76f4\u63a5\u7684\u65b9\u6cd5\u662f\u5229\u7528Stata 16\u53ca\u66f4\u9ad8\u7248\u672c\u63d0\u4f9b\u7684Python\u96c6\u6210\u529f\u80fd\u3002\u8fd9\u79cd\u96c6\u6210\u5141\u8bb8\u7528\u6237\u76f4\u63a5\u5728Stata\u4e2d\u7f16\u5199\u548c\u6267\u884cPython\u4ee3\u7801\uff0c\u4ece\u800c\u5145\u5206\u5229\u7528Python\u7684\u5f3a\u5927\u529f\u80fd\u548c\u5e7f\u6cdb\u7684\u5e93\u652f\u6301\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u8fd9\u4e9b\u65b9\u6cd5\u3002<\/p>\n<\/p>\n

\u4e00\u3001STATA\u5185\u7f6ePYTHON\u96c6\u6210<\/h3>\n<\/p>\n

1. \u914d\u7f6ePython\u73af\u5883<\/h4>\n<\/p>\n

\u5728\u4f7f\u7528Stata\u8fd0\u884cPython\u4ee3\u7801\u4e4b\u524d\uff0c\u786e\u4fddPython\u5df2\u7ecf\u5b89\u88c5\u5728\u7cfb\u7edf\u4e2d\u3002Stata\u901a\u5e38\u4f1a\u81ea\u52a8\u68c0\u6d4b\u7cfb\u7edf\u4e2d\u7684Python\u5b89\u88c5\uff0c\u4f46\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6epython set exec<\/code>\u547d\u4ee4\u6765\u6307\u5b9aPython\u7684\u53ef\u6267\u884c\u6587\u4ef6\u8def\u5f84\u3002\u5982\u679c\u9700\u8981\u4f7f\u7528\u7279\u5b9a\u7684Python\u7248\u672c\u6216\u865a\u62df\u73af\u5883\uff0c\u8fd9\u4e2a\u8bbe\u7f6e\u5c24\u4e3a\u91cd\u8981\u3002<\/p>\n<\/p>\n

python set exec "C:\\Path\\To\\python.exe", permanently<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u4f7f\u7528Python\u5757<\/h4>\n<\/p>\n
Stata\u5141\u8bb8\u7528\u6237\u5728.do\u6587\u4ef6\u6216\u76f4\u63a5\u5728\u547d\u4ee4\u7a97\u53e3\u4e2d\u4f7f\u7528Python\u5757\u3002\u5f00\u59cb\u548c\u7ed3\u675fPython\u4ee3\u7801\u5757\u7684\u6807\u8bb0\u662fpython<\/code>\u548cend<\/code>\u3002\u5728\u8fd9\u4e2a\u5757\u4e2d\uff0c\u7528\u6237\u53ef\u4ee5\u7f16\u5199\u4efb\u610fPython\u4ee3\u7801\u3002<\/p>\n<\/p>\n
python<\/p>\n
import sys<\/p>\n
print(sys.version)<\/p>\n
end<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u7528\u6237\u53ef\u4ee5\u8f7b\u677e\u8c03\u7528Python\u5e93\u8fdb\u884c\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u3001\u673a\u5668\u5b66\u4e60<\/a>\u6216\u8005\u7f51\u7edc\u722c\u866b\u7b49\u4efb\u52a1\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u901a\u8fc7DO\u6587\u4ef6\u8c03\u7528PYTHON\u811a\u672c<\/h3>\n<\/p>\n
1. \u76f4\u63a5\u8c03\u7528Python\u811a\u672c<\/h4>\n<\/p>\n
\u5728Stata\u4e2d\uff0c\u7528\u6237\u53ef\u4ee5\u76f4\u63a5\u8c03\u7528\u5916\u90e8Python\u811a\u672c\u3002\u8fd9\u79cd\u65b9\u5f0f\u9002\u7528\u4e8e\u5f53Python\u4ee3\u7801\u8f83\u957f\u6216\u9700\u8981\u91cd\u590d\u4f7f\u7528\u65f6\u3002\u4f7f\u7528Stata\u7684!<\/code>\u64cd\u4f5c\u7b26\u53ef\u4ee5\u5728\u547d\u4ee4\u884c\u4e2d\u6267\u884cPython\u811a\u672c\u3002<\/p>\n<\/p>\n
!python C:\\Path\\To\\script.py<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u8fd9\u79cd\u65b9\u6cd5\u7684\u4f18\u52bf\u5728\u4e8e\u7528\u6237\u53ef\u4ee5\u5c06\u590d\u6742\u7684Python\u7a0b\u5e8f\u6a21\u5757\u5316\uff0c\u5e76\u4e14\u4e0d\u9700\u8981\u5728Stata\u4e2d\u76f4\u63a5\u7f16\u5199\u5197\u957f\u7684\u4ee3\u7801\u3002<\/p>\n<\/p>\n
2. \u4e0eStata\u6570\u636e\u4ea4\u4e92<\/h4>\n<\/p>\n
\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u5c06\u6570\u636e\u5bfc\u51fa\u4e3aCSV\u6216\u5176\u4ed6\u683c\u5f0f\uff0c\u8ba9Python\u811a\u672c\u8bfb\u53d6\u548c\u5904\u7406\u8fd9\u4e9b\u6570\u636e\uff0c\u7136\u540e\u518d\u5c06\u7ed3\u679c\u8fd4\u56de\u7ed9Stata\u3002\u8fd9\u79cd\u4ea4\u4e92\u65b9\u5f0f\u867d\u7136\u95f4\u63a5\uff0c\u4f46\u975e\u5e38\u7075\u6d3b\u3002\u4f8b\u5982\uff0c\u7528\u6237\u53ef\u4ee5\u4f7f\u7528Stata\u5bfc\u51fa\u6570\u636e\uff0cPython\u8fdb\u884c\u590d\u6742\u5206\u6790\uff0c\u7136\u540e\u518d\u5c06\u7ed3\u679c\u5bfc\u5165Stata\u8fdb\u884c\u8fdb\u4e00\u6b65\u5904\u7406\u3002<\/p>\n<\/p>\n
export delimited using "data.csv", replace<\/p>\n
!python C:\\Path\\To\\process_data.py<\/p>\n
import delimited "processed_data.csv", clear<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001STATA\u4e0ePYTHON\u7684\u53cc\u5411\u901a\u4fe1<\/h3>\n<\/p>\n
1. \u4f7f\u7528PyStata\u6a21\u5757<\/h4>\n<\/p>\n
Stata\u7684PyStata\u6a21\u5757\u5141\u8bb8\u53cc\u5411\u901a\u4fe1\uff0c\u8fd9\u610f\u5473\u7740\u7528\u6237\u53ef\u4ee5\u5728Python\u4e2d\u8fd0\u884cStata\u547d\u4ee4\uff0c\u6216\u8005\u5728Stata\u4e2d\u8c03\u7528Python\u51fd\u6570\u3002\u8fd9\u79cd\u53cc\u5411\u901a\u4fe1\u6781\u5927\u5730\u589e\u5f3a\u4e86Stata\u548cPython\u7684\u96c6\u6210\u80fd\u529b\u3002<\/p>\n<\/p>\n
\u5728Python\u4e2d\u8fd0\u884cStata\u547d\u4ee4\u53ef\u4ee5\u4f7f\u7528stata.run()<\/code>\u51fd\u6570\u3002\u53cd\u4e4b\uff0c\u53ef\u4ee5\u5728Stata\u4e2d\u8c03\u7528Python\u51fd\u6570\u5e76\u83b7\u53d6\u8fd4\u56de\u503c\u3002\u8fd9\u79cd\u65b9\u5f0f\u9002\u5408\u9700\u8981\u9891\u7e41\u4ea4\u4e92\u548c\u6570\u636e\u4f20\u9012\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n
import stata_setup<\/p>\n
stata_setup.config("C:\/Program Files\/Stata17", "mp")<\/p>\n
import stata<\/p>\n
stata.run('sysuse auto.dta')<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u5229\u7528pandas\u4e0eStata\u4ea4\u4e92<\/h4>\n<\/p>\n
Python\u7684pandas\u5e93\u53ef\u4ee5\u4e0eStata\u6570\u636e\u96c6\u65e0\u7f1d\u4ea4\u4e92\u3002\u7528\u6237\u53ef\u4ee5\u5c06Stata\u6570\u636e\u96c6\u5bfc\u5165\u4e3apandas DataFrame\uff0c\u8fdb\u884c\u5904\u7406\u540e\u518d\u8f93\u51fa\u4e3aStata\u683c\u5f0f\u3002\u8fd9\u79cd\u65b9\u5f0f\u5229\u7528\u4e86pandas\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u80fd\u529b\uff0c\u4f7f\u5f97\u6570\u636e\u64cd\u4f5c\u66f4\u52a0\u9ad8\u6548\u3002<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
from stata import StataTools<\/p>\n
df = pd.read_stata("data.dta")<\/p>\n
\u6570\u636e\u5904\u7406<\/strong><\/h2>\n
df.to_stata("processed_data.dta")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001PYTHON\u4ee3\u7801\u5d4c\u5165STATA<\/h3>\n<\/p>\n
1. \u4f7f\u7528python:<\/code>\u547d\u4ee4<\/h4>\n<\/p>\n
\u5728Stata\u547d\u4ee4\u884c\u4e2d\u76f4\u63a5\u5d4c\u5165Python\u4ee3\u7801\uff0c\u53ef\u4ee5\u4f7f\u7528python:<\/code>\u547d\u4ee4\u3002\u8fd9\u79cd\u65b9\u5f0f\u9002\u5408\u5c0f\u578b\u4ee3\u7801\u7247\u6bb5\u6216\u9700\u8981\u5373\u65f6\u7ed3\u679c\u7684\u573a\u666f\u3002<\/p>\n<\/p>\n
python: import numpy as np; print(np.random.rand(5))<\/p>\n
<\/code><\/pre>\n<\/p>\n
2. \u5d4c\u5165\u590d\u6742\u4ee3\u7801\u5757<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u66f4\u590d\u6742\u7684\u4ee3\u7801\uff0c\u7528\u6237\u53ef\u4ee5\u4f7f\u7528python<\/code>\u548cend<\/code>\u6807\u8bb0\u5d4c\u5165Python\u4ee3\u7801\u5757\u3002\u8fd9\u79cd\u65b9\u5f0f\u5141\u8bb8\u7528\u6237\u7f16\u5199\u591a\u884c\u4ee3\u7801\uff0c\u5e76\u4f7f\u7528Python\u7684\u590d\u6742\u529f\u80fd\u3002<\/p>\n<\/p>\n
python<\/p>\n
import pandas as pd<\/p>\n
data = pd.DataFrame({'x': range(10), 'y': range(10, 20)})<\/p>\n
data['z'] = data['x'] + data['y']<\/p>\n
print(data)<\/p>\n
end<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001PYTHON\u4e0eSTATA\u7684\u6570\u636e\u7c7b\u578b\u8f6c\u6362<\/h3>\n<\/p>\n
1. \u6570\u636e\u7c7b\u578b\u6620\u5c04<\/h4>\n<\/p>\n
\u5728Stata\u548cPython\u4e4b\u95f4\u4f20\u9012\u6570\u636e\u65f6\uff0c\u7406\u89e3\u6570\u636e\u7c7b\u578b\u7684\u6620\u5c04\u5173\u7cfb\u975e\u5e38\u91cd\u8981\u3002Stata\u7684\u6570\u636e\u7c7b\u578b\u5982\u6574\u6570\u3001\u6d6e\u70b9\u6570\u3001\u5b57\u7b26\u4e32\u7b49\u5728Python\u4e2d\u6709\u5bf9\u5e94\u7684\u7c7b\u578b\u3002\u7528\u6237\u9700\u8981\u786e\u4fdd\u6570\u636e\u7c7b\u578b\u7684\u6b63\u786e\u8f6c\u6362\uff0c\u4ee5\u9632\u6b62\u6570\u636e\u4e22\u5931\u6216\u9519\u8bef\u3002<\/p>\n<\/p>\n
2. \u4f7f\u7528PyDataStata\u8fdb\u884c\u8f6c\u6362<\/h4>\n<\/p>\n
PyDataStata\u662f\u4e00\u4e2aPython\u5e93\uff0c\u4e13\u95e8\u7528\u4e8eStata\u548cPython\u4e4b\u95f4\u7684\u6570\u636e\u7c7b\u578b\u8f6c\u6362\u3002\u5b83\u53ef\u4ee5\u5e2e\u52a9\u7528\u6237\u81ea\u52a8\u5904\u7406\u6570\u636e\u7c7b\u578b\u5dee\u5f02\uff0c\u4f7f\u5f97\u6570\u636e\u4f20\u9012\u66f4\u52a0\u5e73\u6ed1\u3002<\/p>\n<\/p>\n
import pydata_stata<\/p>\n
data = pydata_stata.read_stata("data.dta")<\/p>\n
\u6570\u636e\u5904\u7406<\/strong><\/h2>\n
pydata_stata.write_stata(data, "output.dta")<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001STATA\u4e2dPYTHON\u7684\u5e94\u7528\u573a\u666f<\/h3>\n<\/p>\n
1. \u6570\u636e\u5206\u6790\u4e0e\u53ef\u89c6\u5316<\/h4>\n<\/p>\n
Python\u62e5\u6709\u4e30\u5bcc\u7684\u6570\u636e\u5206\u6790\u548c\u53ef\u89c6\u5316\u5e93\uff0c\u5982pandas\u3001numpy\u3001matplotlib\u7b49\u3002\u7528\u6237\u53ef\u4ee5\u5728Stata\u4e2d\u8c03\u7528\u8fd9\u4e9b\u5e93\uff0c\u5b9e\u73b0\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u548c\u9ad8\u8d28\u91cf\u7684\u56fe\u8868\u751f\u6210\u3002<\/p>\n<\/p>\n
2. \u673a\u5668\u5b66\u4e60\u4e0e\u9884\u6d4b<\/h4>\n<\/p>\n
Python\u7684scikit-learn\u3001TensorFlow\u7b49\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u673a\u5668\u5b66\u4e60\u529f\u80fd\u3002\u7528\u6237\u53ef\u4ee5\u5728Stata\u4e2d\u5229\u7528\u8fd9\u4e9b\u5e93\u8fdb\u884c\u9884\u6d4b\u5206\u6790\uff0c\u8fdb\u4e00\u6b65\u63d0\u5347\u6570\u636e\u5206\u6790\u7684\u6df1\u5ea6\u3002<\/p>\n<\/p>\n
3. \u7f51\u7edc\u722c\u866b\u4e0e\u6570\u636e\u83b7\u53d6<\/h4>\n<\/p>\n
\u5bf9\u4e8e\u9700\u8981\u4ece\u7f51\u7edc\u83b7\u53d6\u6570\u636e\u7684\u4efb\u52a1\uff0cPython\u7684requests\u3001BeautifulSoup\u7b49\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u652f\u6301\u3002\u7528\u6237\u53ef\u4ee5\u5728Stata\u4e2d\u5d4c\u5165Python\u4ee3\u7801\uff0c\u5b9e\u73b0\u81ea\u52a8\u5316\u7684\u6570\u636e\u83b7\u53d6\u548c\u5904\u7406\u3002<\/p>\n<\/p>\n
\u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0c\u7528\u6237\u53ef\u4ee5\u5728Stata\u4e2d\u5145\u5206\u5229\u7528Python\u7684\u5f3a\u5927\u529f\u80fd\uff0c\u5b9e\u73b0\u4ece\u6570\u636e\u5904\u7406\u3001\u5206\u6790\u5230\u53ef\u89c6\u5316\u7684\u4e00\u4f53\u5316\u89e3\u51b3\u65b9\u6848\u3002\u65e0\u8bba\u662f\u8fdb\u884c\u590d\u6742\u7684\u6570\u636e\u5206\u6790\uff0c\u8fd8\u662f\u5b9e\u73b0\u9ad8\u6548\u7684\u5de5\u4f5c\u6d41\uff0c\u8fd9\u79cdPython\u4e0eStata\u7684\u96c6\u6210\u90fd\u53ef\u4ee5\u4e3a\u7528\u6237\u5e26\u6765\u6781\u5927\u7684\u4fbf\u5229\u548c\u7075\u6d3b\u6027\u3002<\/p>\n<\/p>\n
\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
 \u5982\u4f55\u5728Stata\u4e2d\u96c6\u6210Python\u4ee3\u7801\uff1f<\/strong>
\u5728Stata\u4e2d\u96c6\u6210Python\u4ee3\u7801\u7684\u6b65\u9aa4\u76f8\u5bf9\u7b80\u5355\u3002\u9996\u5148\uff0c\u786e\u4fdd\u4f60\u7684Stata\u7248\u672c\u652f\u6301Python\u96c6\u6210\uff08Stata 16\u53ca\u4ee5\u4e0a\u7248\u672c\uff09\u3002\u63a5\u7740\uff0c\u53ef\u4ee5\u901a\u8fc7\u547d\u4ee4python<\/code>\u6765\u542f\u52a8Python\u73af\u5883\uff0c\u5728\u8fd9\u4e2a\u73af\u5883\u4e2d\u53ef\u4ee5\u8fd0\u884cPython\u4ee3\u7801\u3002\u4f60\u8fd8\u9700\u8981\u5728Stata\u4e2d\u8bbe\u7f6ePython\u7684\u8def\u5f84\uff0c\u4ee5\u786e\u4fddStata\u80fd\u591f\u627e\u5230Python\u89e3\u91ca\u5668\u3002<\/p>\n
\u5728Stata\u4e2d\u8fd0\u884cPython\u4ee3\u7801\u65f6\u9700\u8981\u6ce8\u610f\u54ea\u4e9b\u4e8b\u9879\uff1f<\/strong>
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