{"id":966355,"date":"2024-12-27T04:46:49","date_gmt":"2024-12-26T20:46:49","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/966355.html"},"modified":"2024-12-27T04:46:51","modified_gmt":"2024-12-26T20:46:51","slug":"%e5%a6%82%e4%bd%95%e6%89%b9%e9%87%8f%e6%89%93%e6%a0%87%e7%ad%be-python","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/966355.html","title":{"rendered":"\u5982\u4f55\u6279\u91cf\u6253\u6807\u7b7e python"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24182200\/79804f6c-c609-4afd-8483-22a94664b4bd.webp\" alt=\"\u5982\u4f55\u6279\u91cf\u6253\u6807\u7b7e python\" \/><\/p>\n<p><p> <strong>\u6279\u91cf\u6253\u6807\u7b7e\u53ef\u4ee5\u901a\u8fc7\u7f16\u5199Python\u811a\u672c\u5b9e\u73b0\uff0c\u5e38\u7528\u7684\u65b9\u6cd5\u5305\u62ec\u5229\u7528Pandas\u5bf9\u6570\u636e\u8fdb\u884c\u64cd\u4f5c\u3001\u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u8fdb\u884c\u6587\u672c\u5904\u7406\u3001\u901a\u8fc7<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u6a21\u578b\u8fdb\u884c\u81ea\u52a8\u5316\u6807\u6ce8\u7b49\u3002<\/strong>\u5176\u4e2d\uff0c\u5229\u7528Pandas\u8fdb\u884c\u6570\u636e\u5904\u7406\u662f\u6700\u4e3a\u76f4\u89c2\u4e14\u6613\u4e8e\u5b9e\u73b0\u7684\u65b9\u6cd5\u3002Pandas\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u6846\u67b6\u7ed3\u6784\uff0c\u53ef\u4ee5\u9ad8\u6548\u5730\u5bf9\u5927\u89c4\u6a21\u6570\u636e\u8fdb\u884c\u6279\u91cf\u64cd\u4f5c\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Pandas\u5bf9\u6570\u636e\u8fdb\u884c\u6279\u91cf\u6253\u6807\u7b7e\u3002<\/p>\n<\/p>\n<p><p>\u4e00\u3001PANDAS\u7684\u6570\u636e\u5904\u7406<\/p>\n<\/p>\n<p><p>Pandas\u662fPython\u4e2d\u6700\u53d7\u6b22\u8fce\u7684\u6570\u636e\u5206\u6790\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6027\u80fd\u3001\u6613\u4e8e\u4f7f\u7528\u7684\u6570\u636e\u7ed3\u6784\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002\u5728\u5904\u7406\u6279\u91cf\u6807\u7b7e\u65f6\uff0cPandas\u53ef\u4ee5\u901a\u8fc7DataFrame\u7684\u7075\u6d3b\u64cd\u4f5c\u6765\u5b9e\u73b0\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u52a0\u8f7d\u6570\u636e<\/strong><\/li>\n<\/ol>\n<p><p>\u5728\u5f00\u59cb\u6279\u91cf\u6253\u6807\u7b7e\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u52a0\u8f7d\u6570\u636e\u3002\u901a\u5e38\u6570\u636e\u4fdd\u5b58\u5728CSV\u3001Excel\u7b49\u683c\u5f0f\u7684\u6587\u4ef6\u4e2d\u3002Pandas\u63d0\u4f9b\u4e86<code>read_csv<\/code>\u3001<code>read_excel<\/code>\u7b49\u65b9\u6cd5\u6765\u8bfb\u53d6\u8fd9\u4e9b\u6587\u4ef6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<h2><strong>\u8bfb\u53d6CSV\u6587\u4ef6<\/strong><\/h2>\n<p>data = pd.read_csv(&#39;data.csv&#39;)<\/p>\n<h2><strong>\u6216\u8005\u8bfb\u53d6Excel\u6587\u4ef6<\/strong><\/h2>\n<h2><strong>data = pd.read_excel(&#39;data.xlsx&#39;)<\/strong><\/h2>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u6570\u636e\u6e05\u6d17\u4e0e\u9884\u5904\u7406<\/strong><\/li>\n<\/ol>\n<p><p>\u5728\u7ed9\u6570\u636e\u6253\u6807\u7b7e\u4e4b\u524d\uff0c\u53ef\u80fd\u9700\u8981\u5bf9\u6570\u636e\u8fdb\u884c\u4e00\u5b9a\u7684\u6e05\u6d17\u548c\u9884\u5904\u7406\uff0c\u6bd4\u5982\u53bb\u9664\u7a7a\u503c\u3001\u683c\u5f0f\u5316\u65e5\u671f\u3001\u6807\u51c6\u5316\u6587\u672c\u7b49\u3002\u8fd9\u4e9b\u6b65\u9aa4\u53ef\u4ee5\u5e2e\u52a9\u63d0\u9ad8\u6807\u7b7e\u7684\u51c6\u786e\u6027\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u53bb\u9664\u7a7a\u503c<\/p>\n<p>data.dropna(inplace=True)<\/p>\n<h2><strong>\u683c\u5f0f\u5316\u65e5\u671f<\/strong><\/h2>\n<p>data[&#39;date&#39;] = pd.to_datetime(data[&#39;date&#39;])<\/p>\n<h2><strong>\u6807\u51c6\u5316\u6587\u672c<\/strong><\/h2>\n<p>data[&#39;text&#39;] = data[&#39;text&#39;].str.lower()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li><strong>\u6279\u91cf\u6253\u6807\u7b7e<\/strong><\/li>\n<\/ol>\n<p><p>Pandas\u5141\u8bb8\u901a\u8fc7\u81ea\u5b9a\u4e49\u51fd\u6570\u4ee5\u53ca<code>apply<\/code>\u65b9\u6cd5\u5bf9\u6570\u636e\u8fdb\u884c\u6279\u91cf\u5904\u7406\u3002\u5728\u6253\u6807\u7b7e\u65f6\uff0c\u53ef\u4ee5\u6839\u636e\u67d0\u4e9b\u89c4\u5219\u5b9a\u4e49\u4e00\u4e2a\u51fd\u6570\uff0c\u7136\u540e\u5e94\u7528\u5230DataFrame\u7684\u6bcf\u4e00\u884c\u6216\u6bcf\u4e00\u5217\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5b9a\u4e49\u6253\u6807\u7b7e\u51fd\u6570<\/p>\n<p>def label_text(row):<\/p>\n<p>    if &#39;important&#39; in row[&#39;text&#39;]:<\/p>\n<p>        return &#39;important&#39;<\/p>\n<p>    elif &#39;normal&#39; in row[&#39;text&#39;]:<\/p>\n<p>        return &#39;normal&#39;<\/p>\n<p>    else:<\/p>\n<p>        return &#39;other&#39;<\/p>\n<h2><strong>\u5e94\u7528\u6253\u6807\u7b7e\u51fd\u6570<\/strong><\/h2>\n<p>data[&#39;label&#39;] = data.apply(label_text, axis=1)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e8c\u3001\u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u8fdb\u884c\u6587\u672c\u5904\u7406<\/p>\n<\/p>\n<p><p>\u6b63\u5219\u8868\u8fbe\u5f0f\u662f\u4e00\u79cd\u5f3a\u5927\u7684\u6587\u672c\u5904\u7406\u5de5\u5177\uff0c\u5e38\u7528\u4e8e\u6a21\u5f0f\u5339\u914d\u548c\u6587\u672c\u641c\u7d22\u3002\u5728\u9700\u8981\u6839\u636e\u7279\u5b9a\u6a21\u5f0f\u5bf9\u6587\u672c\u8fdb\u884c\u6253\u6807\u7b7e\u65f6\uff0c\u6b63\u5219\u8868\u8fbe\u5f0f\u53ef\u4ee5\u53d1\u6325\u91cd\u8981\u4f5c\u7528\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u5b9a\u4e49\u5339\u914d\u6a21\u5f0f<\/strong><\/li>\n<\/ol>\n<p><p>\u6839\u636e\u9700\u8981\uff0c\u5b9a\u4e49\u6b63\u5219\u8868\u8fbe\u5f0f\u6a21\u5f0f\u3002\u4f8b\u5982\uff0c\u5339\u914d\u67d0\u4e9b\u5173\u952e\u5b57\u6216\u7279\u5b9a\u7684\u6587\u672c\u7ed3\u6784\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import re<\/p>\n<h2><strong>\u5b9a\u4e49\u6b63\u5219\u8868\u8fbe\u5f0f\u6a21\u5f0f<\/strong><\/h2>\n<p>pattern_important = re.compile(r&#39;\\bimportant\\b&#39;)<\/p>\n<p>pattern_normal = re.compile(r&#39;\\bnormal\\b&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u5e94\u7528\u6b63\u5219\u8868\u8fbe\u5f0f<\/strong><\/li>\n<\/ol>\n<p><p>\u4f7f\u7528Pandas\u7684<code>apply<\/code>\u65b9\u6cd5\u7ed3\u5408\u6b63\u5219\u8868\u8fbe\u5f0f\uff0c\u53ef\u4ee5\u5bf9\u6bcf\u6761\u8bb0\u5f55\u8fdb\u884c\u68c0\u67e5\uff0c\u5e76\u6839\u636e\u5339\u914d\u7ed3\u679c\u6253\u4e0a\u76f8\u5e94\u7684\u6807\u7b7e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u5b9a\u4e49\u6253\u6807\u7b7e\u51fd\u6570<\/p>\n<p>def regex_label_text(text):<\/p>\n<p>    if pattern_important.search(text):<\/p>\n<p>        return &#39;important&#39;<\/p>\n<p>    elif pattern_normal.search(text):<\/p>\n<p>        return &#39;normal&#39;<\/p>\n<p>    else:<\/p>\n<p>        return &#39;other&#39;<\/p>\n<h2><strong>\u5e94\u7528\u6253\u6807\u7b7e\u51fd\u6570<\/strong><\/h2>\n<p>data[&#39;label&#39;] = data[&#39;text&#39;].apply(regex_label_text)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u4e09\u3001\u5229\u7528\u673a\u5668\u5b66\u4e60\u6a21\u578b\u8fdb\u884c\u81ea\u52a8\u5316\u6807\u6ce8<\/p>\n<\/p>\n<p><p>\u5728\u6570\u636e\u91cf\u8f83\u5927\u4e14\u89c4\u5219\u4e0d\u660e\u663e\u7684\u60c5\u51b5\u4e0b\uff0c\u4f7f\u7528\u673a\u5668\u5b66\u4e60\u6a21\u578b\u8fdb\u884c\u81ea\u52a8\u5316\u6807\u6ce8\u662f\u4e00\u79cd\u9ad8\u6548\u7684\u65b9\u6cd5\u3002\u53ef\u4ee5\u8bad\u7ec3\u4e00\u4e2a\u5206\u7c7b\u6a21\u578b\uff0c\u6839\u636e\u8f93\u5165\u6570\u636e\u7684\u7279\u5f81\u6765\u9884\u6d4b\u6807\u7b7e\u3002<\/p>\n<\/p>\n<ol>\n<li><strong>\u51c6\u5907\u6570\u636e\u96c6<\/strong><\/li>\n<\/ol>\n<p><p>\u9996\u5148\uff0c\u9700\u8981\u51c6\u5907\u4e00\u4e2a\u6807\u8bb0\u597d\u7684\u6570\u636e\u96c6\u7528\u4e8e\u8bad\u7ec3\u6a21\u578b\u3002\u8fd9\u4e2a\u6570\u636e\u96c6\u5e94\u8be5\u5305\u542b\u8f93\u5165\u7279\u5f81\u548c\u5bf9\u5e94\u7684\u6807\u7b7e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from sklearn.model_selection import tr<a href=\"https:\/\/docs.pingcode.com\/blog\/59162.html\" target=\"_blank\">AI<\/a>n_test_split<\/p>\n<h2><strong>\u5206\u5272\u6570\u636e\u96c6<\/strong><\/h2>\n<p>X = data[&#39;text&#39;]<\/p>\n<p>y = data[&#39;label&#39;]<\/p>\n<p>X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"2\">\n<li><strong>\u7279\u5f81\u63d0\u53d6<\/strong><\/li>\n<\/ol>\n<p><p>\u5bf9\u4e8e\u6587\u672c\u6570\u636e\uff0c\u901a\u5e38\u9700\u8981\u5c06\u5176\u8f6c\u6362\u4e3a\u6570\u503c\u7279\u5f81\u3002\u5e38\u7528\u7684\u65b9\u6cd5\u5305\u62ecTF-IDF\u3001\u8bcd\u888b\u6a21\u578b\u7b49\u3002Scikit-learn\u63d0\u4f9b\u4e86\u76f8\u5e94\u7684\u5de5\u5177\u8fdb\u884c\u7279\u5f81\u63d0\u53d6\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from sklearn.feature_extraction.text import TfidfVectorizer<\/p>\n<h2><strong>\u521d\u59cb\u5316\u5411\u91cf\u5316\u5668<\/strong><\/h2>\n<p>vectorizer = TfidfVectorizer()<\/p>\n<h2><strong>\u62df\u5408\u5e76\u8f6c\u6362\u8bad\u7ec3\u6570\u636e<\/strong><\/h2>\n<p>X_train_tfidf = vectorizer.fit_transform(X_train)<\/p>\n<p>X_test_tfidf = vectorizer.transform(X_test)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"3\">\n<li><strong>\u8bad\u7ec3\u6a21\u578b<\/strong><\/li>\n<\/ol>\n<p><p>\u9009\u62e9\u4e00\u4e2a\u9002\u5408\u7684\u673a\u5668\u5b66\u4e60\u6a21\u578b\u8fdb\u884c\u8bad\u7ec3\uff0c\u4f8b\u5982\u903b\u8f91\u56de\u5f52\u3001\u652f\u6301\u5411\u91cf\u673a\u7b49\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">from sklearn.linear_model import LogisticRegression<\/p>\n<h2><strong>\u521d\u59cb\u5316\u6a21\u578b<\/strong><\/h2>\n<p>model = LogisticRegression()<\/p>\n<h2><strong>\u8bad\u7ec3\u6a21\u578b<\/strong><\/h2>\n<p>model.fit(X_train_tfidf, y_train)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<ol start=\"4\">\n<li><strong>\u9884\u6d4b\u6807\u7b7e<\/strong><\/li>\n<\/ol>\n<p><p>\u4f7f\u7528\u8bad\u7ec3\u597d\u7684\u6a21\u578b\u5bf9\u65b0\u6570\u636e\u8fdb\u884c\u9884\u6d4b\uff0c\u4ece\u800c\u5b9e\u73b0\u81ea\u52a8\u5316\u6807\u6ce8\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u9884\u6d4b\u6d4b\u8bd5\u96c6<\/p>\n<p>y_pred = model.predict(X_test_tfidf)<\/p>\n<h2><strong>\u5bf9\u65b0\u6570\u636e\u8fdb\u884c\u9884\u6d4b<\/strong><\/h2>\n<p>new_data_tfidf = vectorizer.transform(data[&#39;text&#39;])<\/p>\n<p>data[&#39;predicted_label&#39;] = model.predict(new_data_tfidf)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><p>\u56db\u3001\u603b\u7ed3<\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u51e0\u79cd\u65b9\u6cd5\uff0c\u53ef\u4ee5\u9ad8\u6548\u5730\u5b9e\u73b0\u6279\u91cf\u6253\u6807\u7b7e\u3002\u5728\u9009\u62e9\u5177\u4f53\u65b9\u6cd5\u65f6\uff0c\u9700\u8981\u6839\u636e\u6570\u636e\u7684\u7279\u70b9\u548c\u4e1a\u52a1\u9700\u6c42\u8fdb\u884c\u5408\u7406\u9009\u62e9\u3002Pandas\u9002\u7528\u4e8e\u89c4\u5219\u660e\u786e\u7684\u6570\u636e\u5904\u7406\uff0c\u6b63\u5219\u8868\u8fbe\u5f0f\u9002\u5408\u4e8e\u7b80\u5355\u7684\u6a21\u5f0f\u5339\u914d\uff0c\u800c\u673a\u5668\u5b66\u4e60\u5219\u9002\u7528\u4e8e\u590d\u6742\u7684\u6587\u672c\u5206\u6790\u4efb\u52a1\u3002\u5728\u5b9e\u8df5\u4e2d\uff0c\u53ef\u80fd\u9700\u8981\u591a\u79cd\u65b9\u6cd5\u7ed3\u5408\u4f7f\u7528\uff0c\u4ee5\u8fbe\u5230\u6700\u4f73\u6548\u679c\u3002\u65e0\u8bba\u9009\u62e9\u54ea\u79cd\u65b9\u6cd5\uff0c\u90fd\u9700\u8981\u5728\u5b9e\u65bd\u524d\u5145\u5206\u7406\u89e3\u6570\u636e\u7684\u7ed3\u6784\u548c\u7279\u6027\uff0c\u4ee5\u4fdd\u8bc1\u6253\u6807\u7b7e\u7684\u51c6\u786e\u6027\u548c\u53ef\u9760\u6027\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u4f7f\u7528Python\u8fdb\u884c\u6279\u91cf\u6253\u6807\u7b7e\uff1f<\/strong><br \/>\u6279\u91cf\u6253\u6807\u7b7e\u53ef\u4ee5\u901a\u8fc7\u4f7f\u7528Python\u4e2d\u7684\u6570\u636e\u5904\u7406\u5e93\uff08\u5982Pandas\uff09\u548c\u673a\u5668\u5b66\u4e60\u5e93\uff08\u5982Scikit-learn\uff09\u6765\u5b9e\u73b0\u3002\u901a\u5e38\uff0c\u60a8\u4f1a\u5148\u52a0\u8f7d\u6570\u636e\u96c6\uff0c\u7136\u540e\u6839\u636e\u9700\u8981\u7684\u6807\u7b7e\u6761\u4ef6\u5b9a\u4e49\u51fd\u6570\uff0c\u6700\u540e\u5e94\u7528\u8be5\u51fd\u6570\u4e3a\u6bcf\u6761\u6570\u636e\u751f\u6210\u6807\u7b7e\u3002\u53ef\u4ee5\u8003\u8651\u4f7f\u7528\u5e76\u884c\u5904\u7406\u6765\u63d0\u9ad8\u6548\u7387\uff0c\u5c24\u5176\u662f\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\u3002<\/p>\n<p><strong>\u5728\u6279\u91cf\u6253\u6807\u7b7e\u65f6\uff0c\u5982\u4f55\u9009\u62e9\u5408\u9002\u7684\u6807\u7b7e\u7b56\u7565\uff1f<\/strong><br 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