{"id":6256,"date":"2025-05-28T14:32:45","date_gmt":"2025-06-04T07:06:45","guid":{"rendered":"https:\/\/badgameshow.com\/steven\/?p=6256"},"modified":"2025-06-04T14:32:45","modified_gmt":"2025-06-04T07:06:45","slug":"%e4%ba%86%e8%a7%a3%e5%a6%82%e4%bd%95%e5%88%a9%e7%94%a8%e8%b6%a8%e5%8b%a2%e6%8c%87%e6%a8%99%e4%ba%a4%e6%98%93%e6%8c%87%e6%a8%99%e5%9c%a8python%e4%b8%ad%e7%9a%84%e6%87%89%e7%94%a8","status":"publish","type":"post","link":"https:\/\/badgameshow.com\/steven\/python\/%e4%ba%86%e8%a7%a3%e5%a6%82%e4%bd%95%e5%88%a9%e7%94%a8%e8%b6%a8%e5%8b%a2%e6%8c%87%e6%a8%99%e4%ba%a4%e6%98%93%e6%8c%87%e6%a8%99%e5%9c%a8python%e4%b8%ad%e7%9a%84%e6%87%89%e7%94%a8\/","title":{"rendered":"\u638c\u63e1 Python \u7a0b\u5f0f\u8a2d\u8a08\uff1a2025 \u5e74\u6700\u65b0\u8da8\u52e2\u6307\u6a19\u4ea4\u6613\u7b56\u7565\u8207\u5be6\u4f5c\u7bc4\u4f8b"},"content":{"rendered":"

<\/p>\n

\u8da8\u52e2\u6307\u6a19(Trend Indicator)\u4ea4\u6613\u6307\u6a19\u4f7f\u7528\u6642\u6a5f\u4ee5\u53caPython\u7bc4\u4f8b<\/h1>\n

\u8da8\u52e2\u6307\u6a19(Trend Indicator)\u662f\u4e00\u7a2e\u5e38\u7528\u7684\u4ea4\u6613\u6307\u6a19\uff0c\u5b83\u53ef\u4ee5\u5e6b\u52a9\u6295\u8cc7\u8005\u66f4\u597d\u5730\u5224\u65b7\u80a1\u7968\u50f9\u683c\u7684\u8d70\u52e2\uff0c\u4ee5\u53ca\u5728\u4f55\u6642\u9032\u884c\u4ea4\u6613\u3002\u8da8\u52e2\u6307\u6a19\u4e3b\u8981\u5206\u70ba\u5169\u985e\uff1a\u6280\u8853\u6307\u6a19\u548c\u57fa\u672c\u9762\u6307\u6a19\u3002\u6280\u8853\u6307\u6a19\u57fa\u65bc\u80a1\u7968\u50f9\u683c\u53ca\u4ea4\u6613\u91cf\u7684\u6578\u64da\uff0c\u800c\u57fa\u672c\u9762\u6307\u6a19\u5247\u57fa\u65bc\u516c\u53f8\u7684\u8ca1\u52d9\u6578\u64da\u3002<\/p>\n

### \u6280\u8853\u6307\u6a19\u7684\u61c9\u7528<\/p>\n

\u6280\u8853\u6307\u6a19\u80fd\u5e6b\u52a9\u6295\u8cc7\u8005\u5224\u65b7\u80a1\u7968\u7684\u8d70\u52e2\uff0c\u4e26\u63d0\u4f9b\u4ea4\u6613\u6642\u6a5f\u7684\u63d0\u793a\u3002\u5e38\u898b\u7684\u6280\u8853\u6307\u6a19\u5305\u62ec\uff1a
\n– **\u5747\u7dda (Moving Average)**
\n– **\u6307\u6578\u5e73\u6ed1\u79fb\u52d5\u5e73\u5747 (EMA)**
\n– **\u5e03\u6797\u5e36 (Bollinger Bands)**
\n– **\u91cf\u80fd\u6307\u6a19 (Volume Indicators)**<\/p>\n

### \u57fa\u672c\u9762\u6307\u6a19\u7684\u61c9\u7528<\/p>\n

\u57fa\u672c\u9762\u6307\u6a19\u5247\u662f\u57fa\u65bc\u516c\u53f8\u7684\u8ca1\u52d9\u6578\u64da\uff0c\u5e6b\u52a9\u6295\u8cc7\u8005\u8a55\u4f30\u516c\u53f8\u7684\u8ca1\u52d9\u72c0\u6cc1\u53ca\u672a\u4f86\u767c\u5c55\u3002\u5e38\u898b\u7684\u57fa\u672c\u9762\u6307\u6a19\u5305\u62ec\uff1a
\n– **\u80a1\u606f\u6536\u76ca\u7387 (Dividend Yield)**
\n– **\u5e02\u503c\u6bd4 (Price-to-Book Ratio)**
\n– **\u6bcf\u80a1\u6536\u76ca (Earnings Per Share)**<\/p>\n

\u4f7f\u7528\u8da8\u52e2\u6307\u6a19\u5206\u6790\u80a1\u7968\u8d70\u52e2\u53ca\u6295\u8cc7\u6642\u6a5f\uff0c\u80fd\u6709\u6548\u628a\u63e1\u6295\u8cc7\u6a5f\u6703\u4e26\u6e1b\u5c11\u98a8\u96aa\u3002\u63a5\u4e0b\u4f86\u5c07\u4ecb\u7d39\u5982\u4f55\u4f7f\u7528 Python \u9032\u884c\u8da8\u52e2\u6307\u6a19\u7684\u5206\u6790\u8207\u8996\u89ba\u5316\u3002<\/p>\n

\u4f7f\u7528 Python \u5206\u6790\u8da8\u52e2\u6307\u6a19<\/h2>\n

\u5728 Python \u4e2d\uff0c\u6211\u5011\u53ef\u4ee5\u5229\u7528\u79d1\u5b78\u8a08\u7b97\u5eab\u5982 NumPy \u548c Pandas \u4f86\u8a08\u7b97\u5404\u7a2e\u6280\u8853\u6307\u6a19\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u57fa\u672c\u7684\u7bc4\u4f8b\uff1a<\/p>\n

“`python
\nimport numpy as np
\nimport pandas as pd
\nimport talib # \u78ba\u4fdd\u5df2\u5b89\u88dd TA-Lib<\/p>\n

# \u8b80\u53d6\u80a1\u7968\u6578\u64da
\ndf = pd.read_csv(‘stock_data.csv’)<\/p>\n

# \u8a08\u7b97\u5747\u7dda
\ndf[‘MA20’] = df[‘Close’].rolling(window=20).mean()<\/p>\n

# \u8a08\u7b97\u6307\u6578\u5e73\u6ed1\u79fb\u52d5\u5e73\u5747\uff08EMA\uff09
\ndf[‘EMA20’] = df[‘Close’].ewm(span=20).mean()<\/p>\n

# \u8a08\u7b97\u5e03\u6797\u5e36
\ndf[‘Upper_Band’], df[‘Middle_Band’], df[‘Lower_Band’] = talib.BBANDS(df[‘Close’], timeperiod=20, nbdevup=2, nbdevdn=2, matype=0)<\/p>\n

# \u8a08\u7b97\u91cf\u80fd\u6307\u6a19
\ndf[‘AD’] = talib.AD(df[‘High’], df[‘Low’], df[‘Close’], df[‘Volume’])<\/p>\n

# \u8a08\u7b97\u80a1\u606f\u6536\u76ca\u7387
\ndf[‘Dividend Yield’] = df[‘Dividend’] \/ df[‘Close’]\n

# \u8a08\u7b97\u5e02\u503c\u6bd4
\ndf[‘Price-to-Book Ratio’] = df[‘Market Cap’] \/ df[‘Book Value’]\n

# \u8a08\u7b97\u6bcf\u80a1\u6536\u76ca
\ndf[‘Earnings Per Share’] = df[‘Net Income’] \/ df[‘Shares Outstanding’]\n“`<\/p>\n

\u4ee5\u4e0a\u7bc4\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5f9e CSV \u6a94\u6848\u4e2d\u8b80\u53d6\u80a1\u7968\u6578\u64da\u4e26\u8a08\u7b97\u6280\u8853\u6307\u6a19\u3002\u63a5\u4e0b\u4f86\uff0c\u53ef\u4ee5\u4f7f\u7528 Matplotlib \u6216 Seaborn \u9032\u884c\u6578\u64da\u7684\u8996\u89ba\u5316\u3002<\/p>\n

\u5224\u65b7\u6295\u8cc7\u6642\u6a5f<\/h2>\n

\u6839\u64da\u8da8\u52e2\u6307\u6a19\u7684\u8b8a\u5316\uff0c\u6295\u8cc7\u8005\u53ef\u4ee5\u5224\u65b7\u80a1\u7968\u7684\u8d70\u52e2\u53ca\u4ea4\u6613\u6642\u6a5f\uff1a<\/p>\n

– **\u5747\u7dda**\uff1a\u7576\u80a1\u7968\u50f9\u683c\u4e0a\u7a7f\u5747\u7dda\u6642\uff0c\u8868\u793a\u8d70\u52e2\u8f49\u5411\u4e0a\u6f32\uff0c\u8003\u616e\u8cb7\u5165\uff1b\u4e0b\u7a7f\u5747\u7dda\u5247\u8003\u616e\u8ce3\u51fa\u3002
\n– **\u6307\u6578\u5e73\u6ed1\u79fb\u52d5\u5e73\u5747\uff08EMA\uff09**\uff1a\u50f9\u683c\u4e0a\u7a7f EMA \u6642\uff0c\u8003\u616e\u8cb7\u5165\uff1b\u4e0b\u7a7f\u5247\u8003\u616e\u8ce3\u51fa\u3002
\n– **\u5e03\u6797\u5e36**\uff1a\u4e0a\u7a7f\u4e0a\u8f68\u6642\u8003\u616e\u8cb7\u5165\uff1b\u4e0b\u7a7f\u4e0b\u8f68\u5247\u8003\u616e\u8ce3\u51fa\u3002
\n– **\u91cf\u80fd\u6307\u6a19**\uff1a\u91cf\u80fd\u6307\u6a19\u4e0a\u5347\u8868\u793a\u8d70\u52e2\u4e0a\u6f32\uff0c\u8003\u616e\u8cb7\u5165\uff1b\u4e0b\u964d\u5247\u8003\u616e\u8ce3\u51fa\u3002
\n– **\u57fa\u672c\u9762\u6307\u6a19**\uff1a\u57fa\u672c\u9762\u6307\u6a19\u4e0a\u5347\u6642\uff0c\u516c\u53f8\u7684\u8ca1\u52d9\u72c0\u6cc1\u770b\u597d\uff0c\u8003\u616e\u8cb7\u5165\uff1b\u4e0b\u964d\u5247\u8003\u616e\u8ce3\u51fa\u3002<\/p>\n

\u900f\u904e\u8da8\u52e2\u6307\u6a19\u7684\u5206\u6790\uff0c\u6295\u8cc7\u8005\u80fd\u66f4\u597d\u5730\u628a\u63e1\u6295\u8cc7\u6a5f\u6703\uff0c\u4e26\u964d\u4f4e\u98a8\u96aa\u3002<\/p>\n

\u4e86\u89e3\u66f4\u591a Python \u7a0b\u5f0f\u8a2d\u8a08\u7684\u6280\u5de7\u8207\u6559\u5b78\uff0c\u8acb\u53c3\u8003 [\u9019\u88e1](https:\/\/vocus.cc) \u7684\u76f8\u95dc\u6587\u7ae0\u3002<\/p>\n

### Q&A\uff08\u5e38\u898b\u554f\u984c\u89e3\u7b54\uff09<\/p>\n

**1. \u5982\u4f55\u9078\u64c7\u9069\u5408\u7684\u8da8\u52e2\u6307\u6a19\uff1f**
\n\u9078\u64c7\u6307\u6a19\u6642\uff0c\u61c9\u6839\u64da\u81ea\u5df1\u7684\u4ea4\u6613\u98a8\u683c\u53ca\u5e02\u5834\u74b0\u5883\u4f86\u9078\u64c7\uff0c\u5e38\u898b\u7684\u7b56\u7565\u5305\u62ec\u7d50\u5408\u591a\u500b\u6307\u6a19\u4ee5\u63d0\u9ad8\u6e96\u78ba\u6027\u3002<\/p>\n

**2. Python \u4e2d\u6709\u4ec0\u9ebc\u5eab\u53ef\u4ee5\u7528\u4f86\u9032\u884c\u6280\u8853\u5206\u6790\uff1f**
\n\u5e38\u7528\u7684\u5eab\u5305\u62ec Pandas\u3001NumPy\u3001TA-Lib \u548c Matplotlib\uff0c\u9019\u4e9b\u5eab\u63d0\u4f9b\u4e86\u8c50\u5bcc\u7684\u6578\u64da\u5206\u6790\u8207\u8996\u89ba\u5316\u5de5\u5177\u3002<\/p>\n

**3. \u5982\u4f55\u8655\u7406\u80a1\u5e02\u6578\u64da\u7684\u7f3a\u5931\u503c\uff1f**
\n\u53ef\u4ee5\u4f7f\u7528 Pandas \u5167\u5efa\u7684 `fillna()` \u51fd\u6578\u9032\u884c\u7f3a\u5931\u503c\u8655\u7406\uff0c\u9078\u64c7\u586b\u5145\u7684\u65b9\u5f0f\u5982\u524d\u5411\u586b\u5145\u6216\u5e73\u5747\u503c\u586b\u5145\u7b49\u3002<\/p>\n

—<\/p>\n","protected":false},"excerpt":{"rendered":"

\u6587\u7ae0\u6458\u8981\uff1a\u8da8\u52e2\u6307\u6a19\u4ea4\u6613\u6307\u6a19\u662f\u4e00\u7a2e\u5e38\u7528\u7684\u6280\u8853\u5206\u6790\u5de5\u5177\uff0c\u53ef\u4ee5\u5e6b\u52a9\u6295\u8cc7\u8005\u66f4\u597d\u5730\u5206\u6790\u5e02\u5834\u8da8\u52e2\uff0c\u4e26\u63d0\u4f9b\u6295\u8cc7\u8005\u66f4\u597d\u7684\u4ea4\u6613\u6c7a\u7b56\u3002\u672c\u6587\u5c07\u4ecb\u7d39\u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528\u8da8\u52e2\u6307\u6a19\u4ea4\u6613\u6307\u6a19\uff0c\u4ee5\u53ca\u5b83\u5011\u7684\u61c9\u7528\u3002<\/p>\n","protected":false},"author":1,"featured_media":2518,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[18,189],"tags":[15,188],"class_list":["post-6256","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","category-189","tag-python","tag-188"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/badgameshow.com\/steven\/wp-content\/uploads\/2022\/12\/DALL\u00b7E-2022-12-28-14.25.55-\u62f7\u8c9d2.png","jetpack-related-posts":[],"jetpack_shortlink":"https:\/\/wp.me\/pcFK27-1CU","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/posts\/6256","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/comments?post=6256"}],"version-history":[{"count":1,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/posts\/6256\/revisions"}],"predecessor-version":[{"id":6257,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/posts\/6256\/revisions\/6257"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/media\/2518"}],"wp:attachment":[{"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/media?parent=6256"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/categories?post=6256"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/badgameshow.com\/steven\/wp-json\/wp\/v2\/tags?post=6256"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}