{"id":16656,"date":"2024-01-29T02:44:53","date_gmt":"2024-01-28T23:14:53","guid":{"rendered":"https:\/\/rasanegar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/"},"modified":"2024-01-29T02:44:53","modified_gmt":"2024-01-28T23:14:53","slug":"%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2","status":"publish","type":"post","link":"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/","title":{"rendered":"\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 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href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/#%d8%a2%d8%b4%d9%86%d8%a7%db%8c%db%8c_%d9%85%d8%ac%d8%af%d8%af_%d8%a8%d8%a7_%d9%85%d8%ac%d9%85%d9%88%d8%b9%d9%87_%d8%af%d8%a7%d8%af%d9%87\" >\u0622\u0634\u0646\u0627\u06cc\u06cc \u0645\u062c\u062f\u062f \u0628\u0627 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/#%d8%b2%d9%85%db%8c%d9%86%d9%87_%d8%b1%d9%88%db%8c_%d8%b1%da%af%d8%b1%d8%b3%db%8c%d9%88%d9%86_%d8%ae%d8%b7%db%8c_%d8%a8%d8%a7_%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d8%ad%d8%af%d8%a7%d9%82%d9%84_%d9%85%d8%b1%d8%a8%d8%b9%d8%a7%d8%aa_%d9%85%d8%b9%d9%85%d9%88%d9%84%db%8c\" >\u0632\u0645\u06cc\u0646\u0647 \u0631\u0648\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062d\u062f\u0627\u0642\u0644 \u0645\u0631\u0628\u0639\u0627\u062a \u0645\u0639\u0645\u0648\u0644\u06cc<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/#%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c_%d9%87%d8%a7_%d8%a8%d8%b1%d8%a7%db%8c_%d9%85%d8%af%d9%84_%d9%85%d8%a7\" >\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0628\u0631\u0627\u06cc \u0645\u062f\u0644 \u0645\u0627<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/#%d8%aa%d8%ac%d8%b3%d9%85_%d8%b1%d9%88%d8%a7%d8%a8%d8%b7\" >\u062a\u062c\u0633\u0645 \u0631\u0648\u0627\u0628\u0637<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/#%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d8%b1%da%af%d8%b1%d8%b3%db%8c%d9%88%d9%86_%da%af%d8%a7%d9%85_%d8%a8%d9%87_%da%af%d8%a7%d9%85_%d8%a8%d8%b1%d8%a7%db%8c_%d8%b3%d8%a7%d8%ae%d8%aa_%db%8c%da%a9_%d9%85%d8%af%d9%84_%d9%82%d9%88%db%8c\" >\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645 \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u06cc\u06a9 \u0645\u062f\u0644 \u0642\u0648\u06cc<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/#%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d9%85%d8%a7%da%98%d9%88%d9%84_%d8%b1%da%af%d8%b1%d8%b3%db%8c%d9%88%d9%86_%d8%ae%d8%b7%db%8c_scikit-learn_%d8%a8%d8%b1%d8%a7%db%8c_%d9%be%db%8c%d8%b4_%d8%a8%db%8c%d9%86%db%8c_%d8%a2%d8%a8_%d9%88_%d9%87%d9%88%d8%a7\" >\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0645\u0627\u0698\u0648\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc SciKit-Learn \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0622\u0628 \u0648 \u0647\u0648\u0627<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/#%d9%85%d9%86%d8%a7%d8%a8%d8%b9\" >\u0645\u0646\u0627\u0628\u0639<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87-%d8%a7%d8%b2-%db%8c%d8%a7%d8%af%da%af%db%8c%d8%b1%db%8c-%d9%85%d8%a7%d8%b4%db%8c%d9%86%db%8c-%d8%a8%d8%b1%d8%a7%db%8c-%d9%be%db%8c%d8%b4-%d8%a8%db%8c%d9%86-2\/#%d9%86%d8%aa%db%8c%d8%ac%d9%87\" >\u0646\u062a\u06cc\u062c\u0647<\/a><\/li><\/ul><\/nav><\/div>\n<span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">\u0632\u0645\u0627\u0646 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u0645\u0637\u0627\u0644\u0639\u0647: <\/span> <span class=\"rt-time\"> 13<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span><p> <br \/>\n<\/p>\n<div><noscript><\/noscript><\/p>\n<p>\u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u062f\u0627\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 \u0642\u0628\u0644\u06cc \u062f\u0631 \u06cc\u06a9 \u0633\u0631\u06cc \u0633\u0647 \u0642\u0633\u0645\u062a\u06cc \u0627\u0633\u062a \u0631\u0648\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u062f\u0645\u0627\u06cc \u0622\u0628 \u0648 \u0647\u0648\u0627 \u062f\u0631 \u0634\u0647\u0631 \u0644\u06cc\u0646\u06a9\u0644\u0646\u060c \u0646\u0628\u0631\u0627\u0633\u06a9\u0627 \u062f\u0631 \u0627\u06cc\u0627\u0644\u0627\u062a \u0645\u062a\u062d\u062f\u0647 \u0628\u0631 \u0627\u0633\u0627\u0633 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\u062e\u0637\u06cc \u062f\u0642\u06cc\u0642 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0645\u0642\u0627\u062f\u06cc\u0631 \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u062f\u0645\u0627\u06cc \u0631\u0648\u0632\u0627\u0646\u0647 \u0622\u06cc\u0646\u062f\u0647 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0633\u0627\u062e\u062a\u0647 \u0634\u062f\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u0642\u0628\u0644\u06cc \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f.  \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a\u0646 \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc\u060c \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062f\u0648 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0645\u0647\u0645 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0631\u0627 \u062f\u0631 \u0635\u0646\u0639\u062a \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0646\u0634\u0627\u0646 \u062e\u0648\u0627\u0647\u0645 \u062f\u0627\u062f: Scikit-Learn \u0648 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"http:\/\/www.statsmodels.org\/\">StatsModels<\/a>.<\/p>\n<p>\u062f\u0631 \u0633\u0648\u0645\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0632 \u0627\u06cc\u0646 \u0633\u0631\u06cc\u060c \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0622\u0628 \u0648 \u0647\u0648\u0627: \u0642\u0633\u0645\u062a 3\u060c \u0631\u0648\u0634 \u0641\u0631\u0622\u06cc\u0646\u062f\u0647\u0627 \u0648 \u0645\u0631\u0627\u062d\u0644 \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a\u0646 \u06cc\u06a9 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 TensorFlow \u06af\u0648\u06af\u0644 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u062f\u0645\u0627\u06cc \u0631\u0648\u0632\u0627\u0646\u0647 \u062f\u0631 \u0622\u06cc\u0646\u062f\u0647 \u0631\u0627 \u062a\u0648\u0636\u06cc\u062d \u0645\u06cc\u200c\u062f\u0647\u0645.  \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0627\u06cc\u0646 \u0631\u0648\u0634 \u0645\u06cc \u062a\u0648\u0627\u0646\u0645 \u0646\u062a\u0627\u06cc\u062c \u0631\u0627 \u0628\u0627 \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0645\u0642\u0627\u06cc\u0633\u0647 \u06a9\u0646\u0645.<\/p>\n<h2 id=\"refamiliarizingourselveswiththedataset\"><span class=\"ez-toc-section\" id=\"%d8%a2%d8%b4%d9%86%d8%a7%db%8c%db%8c_%d9%85%d8%ac%d8%af%d8%af_%d8%a8%d8%a7_%d9%85%d8%ac%d9%85%d9%88%d8%b9%d9%87_%d8%af%d8%a7%d8%af%d9%87\"><\/span>\u0622\u0634\u0646\u0627\u06cc\u06cc \u0645\u062c\u062f\u062f \u0628\u0627 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u06a9\u0647 \u062f\u0631 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/github.com\/amcquistan\/WeatherPredictPythonML\">\u0627\u06cc\u0646 \u0645\u062e\u0632\u0646 GitHub<\/a> a \u0631\u0627 \u062e\u0648\u0627\u0647\u06cc\u062f \u06cc\u0627\u0641\u062a Jupyter \u0646\u0648\u062a \u0628\u0648\u06a9 \u0628\u0627 \u0646\u0627\u0645 \u0641\u0627\u06cc\u0644 <em>Weather Underground API.ipynb<\/em> \u06a9\u0647 \u0627\u0642\u062f\u0627\u0645\u0627\u062a \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645 \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0628\u0631\u0627\u06cc \u062c\u0645\u0639 \u0622\u0648\u0631\u06cc \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0627\u06cc \u0631\u0627 \u06a9\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0648 \u0645\u0642\u0627\u0644\u0647 \u0646\u0647\u0627\u06cc\u06cc \u0628\u0627 \u0622\u0646 \u06a9\u0627\u0631 \u062e\u0648\u0627\u0647\u06cc\u0645 \u06a9\u0631\u062f\u060c \u0634\u0631\u062d \u0645\u06cc \u062f\u0647\u062f.  \u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646\u060c \u062f\u0631 \u0627\u06cc\u0646 \u0645\u062e\u0632\u0646 \u06cc\u06a9 \u0641\u0627\u06cc\u0644 \u062a\u0631\u0634\u06cc Pandas DataFrame \u0628\u0647 \u0646\u0627\u0645 \u067e\u06cc\u062f\u0627 \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f <em>end-part1_df.pkl<\/em>.  \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646\u060c \u0627\u06af\u0631 \u0645\u06cc\u200c\u062e\u0648\u0627\u0647\u06cc\u062f \u0628\u062f\u0648\u0646 \u062a\u062c\u0631\u0628\u0647 \u062f\u0631\u062f\u0646\u0627\u06a9 \u062c\u0645\u0639\u200c\u0622\u0648\u0631\u06cc\u060c \u067e\u0631\u062f\u0627\u0632\u0634 \u0648 \u062a\u0645\u06cc\u0632 \u06a9\u0631\u062f\u0646 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc\u06cc \u06a9\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u0642\u0628\u0644\u06cc \u062a\u0648\u0636\u06cc\u062d \u062f\u0627\u062f\u0647 \u0634\u062f\u060c \u0627\u062f\u0627\u0645\u0647 \u062f\u0647\u06cc\u062f\u060c \u0641\u0627\u06cc\u0644 pickle \u0631\u0627 \u067e\u0627\u06cc\u06cc\u0646 \u0628\u06cc\u0627\u0648\u0631\u06cc\u062f \u0648 \u0627\u0632 \u06a9\u062f \u0632\u06cc\u0631 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f \u062a\u0627 \u062f\u0627\u062f\u0647\u200c\u0647\u0627 \u0631\u0627 \u062f\u0648\u0628\u0627\u0631\u0647 \u0628\u0647 \u06cc\u06a9 Pandas DataFrame \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u062f. \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0628\u062e\u0634<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> pickle\n<span class=\"hljs-keyword\">with<\/span> <span class=\"hljs-built_in\">open<\/span>(<span class=\"hljs-string\">'end-part1_df.pkl'<\/span>, <span class=\"hljs-string\">'rb'<\/span>) <span class=\"hljs-keyword\">as<\/span> fp:\n    df = pickle.load(fp)\n<\/code><\/pre>\n<p>\u0627\u06af\u0631 \u062e\u0637\u0627\u06cc\u06cc \u062f\u0631\u06cc\u0627\u0641\u062a \u06a9\u0631\u062f\u06cc\u062f \u06a9\u0647 \u0628\u06cc\u0627\u0646 \u0645\u06cc \u06a9\u0646\u062f <em>\u0647\u06cc\u0686 \u0645\u0627\u0698\u0648\u0644\u06cc \u0628\u0647 \u0646\u0627\u0645 &#8220;pandas.indexes&#8221; \u0648\u062c\u0648\u062f \u0646\u062f\u0627\u0631\u062f<\/em> \u0627\u06cc\u0646 \u0628\u0647 \u0627\u06cc\u0646 \u062f\u0644\u06cc\u0644 \u0627\u0633\u062a \u06a9\u0647 \u0634\u0645\u0627 \u0627\u062d\u062a\u0645\u0627\u0644\u0627\u064b \u0627\u0632 \u06cc\u06a9 \u0646\u0633\u062e\u0647 \u062c\u062f\u06cc\u062f\u062a\u0631 \u0627\u0632 \u067e\u0627\u0646\u062f\u0627\u0647\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u06cc\u062f \u06a9\u0647 \u0645\u0646 \u062f\u0631 \u0632\u0645\u0627\u0646 \u0646\u0648\u0634\u062a\u0646 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0631\u062f\u0645 (\u0646\u0633\u062e\u0647 18.1).<\/p>\n<p>\u0628\u0631\u0627\u06cc \u062c\u0644\u0648\u06af\u06cc\u0631\u06cc \u0627\u0632 \u0627\u06cc\u0646 \u0627\u0645\u0631\u060c \u0627\u0632 \u0622\u0646 \u0632\u0645\u0627\u0646 \u06cc\u06a9 \u0641\u0627\u06cc\u0644 CSV \u0631\u0627 \u062f\u0631 \u0645\u062e\u0632\u0646 \u0642\u0631\u0627\u0631 \u062f\u0627\u062f\u0647 \u0627\u0645 \u06a9\u0647 \u062d\u0627\u0648\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0627\u0646\u062a\u0647\u0627\u06cc \u0642\u0633\u0645\u062a 1 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06a9\u062f \u0632\u06cc\u0631 \u0628\u062e\u0648\u0627\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> pandas <span class=\"hljs-keyword\">as<\/span> pd\ndf = pd.read_csv(<span class=\"hljs-string\">'end-part2_df.csv'<\/span>).set_index(<span class=\"hljs-string\">'date'<\/span>)\n<\/code><\/pre>\n<h2 id=\"backgroundonlinearregressionusingordinaryleastsquares\"><span class=\"ez-toc-section\" id=\"%d8%b2%d9%85%db%8c%d9%86%d9%87_%d8%b1%d9%88%db%8c_%d8%b1%da%af%d8%b1%d8%b3%db%8c%d9%88%d9%86_%d8%ae%d8%b7%db%8c_%d8%a8%d8%a7_%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d8%ad%d8%af%d8%a7%d9%82%d9%84_%d9%85%d8%b1%d8%a8%d8%b9%d8%a7%d8%aa_%d9%85%d8%b9%d9%85%d9%88%d9%84%db%8c\"><\/span>\u0632\u0645\u06cc\u0646\u0647 \u0631\u0648\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062d\u062f\u0627\u0642\u0644 \u0645\u0631\u0628\u0639\u0627\u062a \u0645\u0639\u0645\u0648\u0644\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0647\u062f\u0641 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0627\u0639\u0645\u0627\u0644 \u0645\u062c\u0645\u0648\u0639\u0647 \u0627\u06cc \u0627\u0632 \u0645\u0641\u0631\u0648\u0636\u0627\u062a \u0627\u0648\u0644\u06cc\u0647 \u062f\u0631 \u0631\u0627\u0628\u0637\u0647 \u0628\u0627 \u0631\u0648\u0627\u0628\u0637 \u062e\u0637\u06cc \u0648 \u062a\u06a9\u0646\u06cc\u06a9 \u0647\u0627\u06cc \u0639\u062f\u062f\u06cc \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06cc\u06a9 \u0646\u062a\u06cc\u062c\u0647 (Y \u06cc\u0627 \u0645\u062a\u063a\u06cc\u0631 \u0648\u0627\u0628\u0633\u062a\u0647) \u0628\u0631 \u0627\u0633\u0627\u0633 \u06cc\u06a9 \u06cc\u0627 \u0686\u0646\u062f \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u0646\u062f\u0647 (\u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0645\u0633\u062a\u0642\u0644 X) \u0628\u0627 \u0647\u062f\u0641 \u0646\u0647\u0627\u06cc\u06cc \u0627\u06cc\u062c\u0627\u062f \u06cc\u06a9 \u0645\u062f\u0644 (\u0631\u06cc\u0627\u0636\u06cc) \u0627\u0633\u062a. \u0641\u0631\u0645\u0648\u0644) \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0646\u062a\u0627\u06cc\u062c \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u0646\u062f\u0647 \u0628\u0627 \u0645\u0642\u062f\u0627\u0631\u06cc \u0639\u062f\u0645 \u0642\u0637\u0639\u06cc\u062a.<\/p>\n<p>\u0641\u0631\u0645\u0648\u0644 \u062a\u0639\u0645\u06cc\u0645 \u06cc\u0627\u0641\u062a\u0647 \u0628\u0631\u0627\u06cc \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0628\u0647 \u0635\u0648\u0631\u062a \u0632\u06cc\u0631 \u0627\u0633\u062a:<\/p>\n<pre>    <code>\n\u0177 = \u03b2<sub>0<\/sub> + \u03b2<sub>1<\/sub> * x<sub>1<\/sub> + \u03b2<sub>2<\/sub> * x<sub>2<\/sub> + ... + \u03b2<sub>(p-n)<\/sub> x<sub>(p-n)<\/sub> + \u0395\n    <\/code>\n<\/pre>\n<p>\u062c\u0627\u06cc\u06cc \u06a9\u0647:<\/p>\n<ul>\n<li><code>\u0177<\/code>  \u0645\u062a\u063a\u06cc\u0631 \u0646\u062a\u06cc\u062c\u0647 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u062f\u0647 \u0627\u0633\u062a (\u0645\u062a\u063a\u06cc\u0631 \u0648\u0627\u0628\u0633\u062a\u0647)<\/li>\n<li><code>x<sub>j<\/sub><\/code>  \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u0646\u062f\u0647 (\u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0645\u0633\u062a\u0642\u0644) \u0628\u0631\u0627\u06cc \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627\u06cc j = 1,2,&#8230;, p-1 \u0647\u0633\u062a\u0646\u062f.<\/li>\n<li><code>\u03b2<sub>0<\/sub><\/code>  \u0642\u0637\u0639 \u06cc\u0627 \u0645\u0642\u062f\u0627\u0631 \u0627\u0633\u062a <code>\u0177<\/code> \u0632\u0645\u0627\u0646\u06cc \u06a9\u0647 \u0647\u0631 \u06a9\u062f\u0627\u0645 <code>x<sub>j<\/sub><\/code> \u0628\u0631\u0627\u0628\u0631 \u0628\u0627 \u0635\u0641\u0631 \u0627\u0633\u062a<\/li>\n<li><code>\u03b2<sub>j<\/sub><\/code>  \u062a\u063a\u06cc\u06cc\u0631 \u062f\u0631 \u0627\u0633\u062a <code>\u0177<\/code> \u0645\u0633\u062a\u0642\u0631 \u0631\u0648\u06cc \u06cc\u06a9 \u0648\u0627\u062d\u062f \u062a\u063a\u06cc\u06cc\u0631 \u062f\u0631 \u06cc\u06a9\u06cc \u0627\u0632 \u0645\u0648\u0627\u0631\u062f \u0645\u0631\u0628\u0648\u0637\u0647 <code>x<sub>j<\/sub><\/code><\/li>\n<li><code>\u0395<\/code>  \u06cc\u06a9 \u0639\u0628\u0627\u0631\u062a \u062e\u0637\u0627\u06cc \u062a\u0635\u0627\u062f\u0641\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0628\u0627 \u062a\u0641\u0627\u0648\u062a \u0628\u06cc\u0646 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u062f\u0647 \u0645\u0631\u062a\u0628\u0637 \u0627\u0633\u062a <code>\u0177<sub>i<\/sub><\/code> \u0627\u0631\u0632\u0634 \u0648 \u0648\u0627\u0642\u0639\u06cc <code>y<sub>i<\/sub><\/code> \u0627\u0631\u0632\u0634<\/li>\n<\/ul>\n<p>\u0622\u062e\u0631\u06cc\u0646 \u062c\u0645\u0644\u0647 \u062f\u0631 \u0645\u0639\u0627\u062f\u0644\u0647 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u06cc\u06a9 \u062c\u0645\u0644\u0647 \u0628\u0633\u06cc\u0627\u0631 \u0645\u0647\u0645 \u0627\u0633\u062a.  \u0627\u0633\u0627\u0633\u06cc \u062a\u0631\u06cc\u0646 \u0634\u06a9\u0644 \u0633\u0627\u062e\u062a \u06cc\u06a9 \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0645\u062a\u06a9\u06cc \u0627\u0633\u062a \u0631\u0648\u06cc \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645\u06cc \u0628\u0647 \u0646\u0627\u0645 \u062d\u062f\u0627\u0642\u0644 \u0645\u0631\u0628\u0639\u0627\u062a \u0645\u0639\u0645\u0648\u0644\u06cc \u06a9\u0647 \u062a\u0631\u06a9\u06cc\u0628\u06cc \u0627\u0632 <code>\u03b2<sub>j<\/sub><\/code>\u0645\u0642\u0627\u062f\u06cc\u0631\u06cc \u06a9\u0647 \u0645\u0642\u062f\u0627\u0631 \u0631\u0627 \u0628\u0647 \u062d\u062f\u0627\u0642\u0644 \u0645\u06cc \u0631\u0633\u0627\u0646\u062f <code>\u0395<\/code> \u0645\u062f\u062a\u060c \u0627\u0635\u0637\u0644\u0627\u062d.<\/p>\n<h2 id=\"selectingfeaturesforourmodel\"><span class=\"ez-toc-section\" id=\"%d8%a7%d9%86%d8%aa%d8%ae%d8%a7%d8%a8_%d9%88%db%8c%da%98%da%af%db%8c_%d9%87%d8%a7_%d8%a8%d8%b1%d8%a7%db%8c_%d9%85%d8%af%d9%84_%d9%85%d8%a7\"><\/span>\u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627 \u0628\u0631\u0627\u06cc \u0645\u062f\u0644 \u0645\u0627<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u06cc\u06a9 \u0641\u0631\u0636 \u06a9\u0644\u06cc\u062f\u06cc \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u062a\u06a9\u0646\u06cc\u06a9 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0634\u0645\u0627 \u06cc\u06a9 \u0631\u0627\u0628\u0637\u0647 \u062e\u0637\u06cc \u0628\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631 \u0648\u0627\u0628\u0633\u062a\u0647 \u0648 \u0647\u0631 \u0645\u062a\u063a\u06cc\u0631 \u0645\u0633\u062a\u0642\u0644 \u062f\u0627\u0631\u06cc\u062f.  \u06cc\u06a9 \u0631\u0627\u0647 \u0628\u0631\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u062e\u0637\u06cc \u0628\u0648\u062f\u0646 \u0628\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631 \u0645\u0633\u062a\u0642\u0644 \u0645\u0627 \u06a9\u0647 \u062f\u0631 \u062d\u0627\u0644 \u062d\u0627\u0636\u0631 \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u062f\u0645\u0627 \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f \u0648 \u0633\u0627\u06cc\u0631 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0645\u0633\u062a\u0642\u0644 \u0645\u062d\u0627\u0633\u0628\u0647 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Pearson_correlation_coefficient\">\u0636\u0631\u06cc\u0628 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u067e\u06cc\u0631\u0633\u0648\u0646<\/a>.<\/p>\n<p>\u0636\u0631\u06cc\u0628 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u067e\u06cc\u0631\u0633\u0648\u0646 (r) \u0627\u0646\u062f\u0627\u0632\u0647\u200c\u06af\u06cc\u0631\u06cc \u0645\u0642\u062f\u0627\u0631 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u062e\u0637\u06cc \u0628\u06cc\u0646 \u0622\u0631\u0627\u06cc\u0647\u200c\u0647\u0627\u06cc \u0637\u0648\u0644 \u0645\u0633\u0627\u0648\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0645\u0642\u062f\u0627\u0631\u06cc \u0627\u0632 1- \u062a\u0627 1 \u0631\u0627 \u0628\u0647 \u062f\u0633\u062a \u0645\u06cc\u200c\u062f\u0647\u062f. \u0645\u0642\u0627\u062f\u06cc\u0631 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0627\u0632 0 \u062a\u0627 1 \u0646\u0634\u0627\u0646 \u062f\u0647\u0646\u062f\u0647 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0645\u062b\u0628\u062a \u0641\u0632\u0627\u06cc\u0646\u062f\u0647 \u0642\u0648\u06cc \u0627\u0633\u062a.  \u0645\u0646\u0638\u0648\u0631 \u0645\u0646 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0648\u0642\u062a\u06cc \u0645\u0642\u0627\u062f\u06cc\u0631 \u06cc\u06a9 \u0633\u0631\u06cc \u062f\u0627\u062f\u0647 \u0628\u0647 \u0637\u0648\u0631 \u0647\u0645\u0632\u0645\u0627\u0646 \u0628\u0627 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0633\u0631\u06cc \u062f\u06cc\u06af\u0631 \u0627\u0641\u0632\u0627\u06cc\u0634 \u0645\u06cc\u200c\u06cc\u0627\u0628\u0646\u062f\u060c \u062f\u0648 \u0633\u0631\u06cc \u062f\u0627\u062f\u0647 \u0628\u0647 \u0637\u0648\u0631 \u0645\u062b\u0628\u062a \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u062f\u0627\u0631\u0646\u062f \u0648 \u0648\u0642\u062a\u06cc \u0647\u0631 \u062f\u0648 \u0628\u0627 \u0642\u062f\u0631 \u0641\u0632\u0627\u06cc\u0646\u062f\u0647\u200c\u0627\u06cc \u0628\u0631\u0627\u0628\u0631 \u0628\u0627\u0644\u0627 \u0645\u06cc\u200c\u0631\u0648\u0646\u062f\u060c \u0645\u0642\u062f\u0627\u0631 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u067e\u06cc\u0631\u0633\u0648\u0646 \u0628\u0647 1 \u0646\u0632\u062f\u06cc\u06a9 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/p>\n<p>\u0645\u0642\u0627\u062f\u06cc\u0631 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0627\u0632 0 \u062a\u0627 -1 \u0628\u0647 \u0635\u0648\u0631\u062a \u0645\u0639\u06a9\u0648\u0633 \u06cc\u0627 \u0645\u0646\u0641\u06cc \u06af\u0641\u062a\u0647 \u0645\u06cc \u0634\u0648\u062f \u06a9\u0647 \u0648\u0642\u062a\u06cc \u0645\u0642\u0627\u062f\u06cc\u0631 \u06cc\u06a9 \u0633\u0631\u06cc \u0627\u0641\u0632\u0627\u06cc\u0634 \u0645\u06cc \u06cc\u0627\u0628\u062f \u0645\u0642\u0627\u062f\u06cc\u0631 \u0645\u062a\u0646\u0627\u0638\u0631 \u062f\u0631 \u0633\u0631\u06cc \u0645\u0642\u0627\u0628\u0644 \u06a9\u0627\u0647\u0634 \u0645\u06cc \u06cc\u0627\u0628\u062f \u0627\u0645\u0627 \u0628\u0627 \u062a\u063a\u06cc\u06cc\u0631 \u0627\u0646\u062f\u0627\u0632\u0647 \u0628\u06cc\u0646 \u0633\u0631\u06cc \u0647\u0627 \u0628\u0631\u0627\u0628\u0631 \u0645\u06cc \u0634\u0648\u062f (\u0628\u0627 \u062c\u0647\u062a \u0645\u062e\u0627\u0644\u0641). \u0645\u0642\u062f\u0627\u0631 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0628\u0647 -1 \u0646\u0632\u062f\u06cc\u06a9 \u062e\u0648\u0627\u0647\u062f \u0634\u062f.  \u0645\u0642\u0627\u062f\u06cc\u0631 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u067e\u06cc\u0631\u0633\u0648\u0646 \u06a9\u0647 \u0646\u0632\u062f\u06cc\u06a9 \u0628\u0647 \u062f\u0648 \u0637\u0631\u0641 \u0635\u0641\u0631 \u0642\u0631\u0627\u0631 \u062f\u0627\u0631\u0646\u062f\u060c \u0646\u0634\u0627\u0646\u200c\u062f\u0647\u0646\u062f\u0647 \u062f\u0627\u0634\u062a\u0646 \u06cc\u06a9 \u0631\u0627\u0628\u0637\u0647 \u062e\u0637\u06cc \u0636\u0639\u06cc\u0641 \u0647\u0633\u062a\u0646\u062f \u0648 \u0628\u0627 \u0646\u0632\u062f\u06cc\u06a9 \u0634\u062f\u0646 \u0645\u0642\u062f\u0627\u0631 \u0628\u0647 \u0635\u0641\u0631 \u0636\u0639\u06cc\u0641\u200c\u062a\u0631 \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/p>\n<p>\u0646\u0638\u0631\u0627\u062a \u062f\u0631 \u0645\u06cc\u0627\u0646 \u0622\u0645\u0627\u0631\u062f\u0627\u0646\u0627\u0646 \u0648 \u06a9\u062a\u0627\u0628 \u0647\u0627\u06cc \u0622\u0645\u0627\u0631 \u0645\u062a\u0641\u0627\u0648\u062a \u0627\u0633\u062a \u0631\u0648\u06cc \u0645\u0631\u0632\u0647\u0627\u06cc \u0648\u0627\u0636\u062d \u0628\u0631\u0627\u06cc \u0633\u0637\u0648\u062d \u0642\u062f\u0631\u062a \u06cc\u06a9 \u0636\u0631\u06cc\u0628 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc.  \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u0645\u062a\u0648\u062c\u0647 \u0634\u062f\u0647 \u0627\u0645 \u06a9\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u0627\u06cc \u0627\u0632 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0647\u0627\u06cc \u067e\u0630\u06cc\u0631\u0641\u062a\u0647 \u0634\u062f\u0647 \u0628\u0631\u0627\u06cc \u0646\u0642\u0627\u0637 \u0642\u0648\u062a \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0628\u0647 \u0634\u0631\u062d \u0632\u06cc\u0631 \u0627\u0633\u062a:<\/p>\n<table class=\"table table-bordered\">\n<thead>\n<tr>\n<th>\u0627\u0631\u0632\u0634 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc<\/th>\n<th>\u062a\u0641\u0633\u06cc\u0631<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>0.8 &#8211; 1.0<\/td>\n<td>\u0628\u0633\u06cc\u0627\u0631 \u0642\u0648\u06cc<\/td>\n<\/tr>\n<tr>\n<td>0.6 &#8211; 0.8<\/td>\n<td>\u0642\u0648\u06cc<\/td>\n<\/tr>\n<tr>\n<td>0.4 &#8211; 0.6<\/td>\n<td>\u062f\u0631 \u062d\u062f \u0645\u062a\u0648\u0633\u0637<\/td>\n<\/tr>\n<tr>\n<td>0.2 &#8211; 0.4<\/td>\n<td>\u0636\u0639\u06cc\u0641<\/td>\n<\/tr>\n<tr>\n<td>0.0 &#8211; 0.2<\/td>\n<td>\u062e\u06cc\u0644\u06cc \u0636\u0639\u06cc\u0641<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u0628\u0631\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u062f\u0631 \u0627\u06cc\u0646 \u062f\u0627\u062f\u0647 \u0647\u0627\u060c \u0645\u0646 \u0628\u0627 \u0622\u0646 \u062a\u0645\u0627\u0633 \u062e\u0648\u0627\u0647\u0645 \u06af\u0631\u0641\u062a <code>corr()<\/code> \u0645\u062a\u062f \u0634\u06cc Pandas DataFrame.  \u0628\u0647 \u0627\u06cc\u0646 \u0632\u0646\u062c\u06cc\u0631 \u0634\u062f\u0647 <code>corr()<\/code> \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u0645\u062a\u062f \u0633\u067e\u0633 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u0645 \u0633\u062a\u0648\u0646 \u0645\u0648\u0631\u062f \u0639\u0644\u0627\u0642\u0647 (&#8220;meantempm&#8221;) \u0631\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u06a9\u0646\u0645 \u0648 \u062f\u0648\u0628\u0627\u0631\u0647 \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u0645\u062a\u062f \u062f\u06cc\u06af\u0631\u06cc \u0631\u0627 \u0632\u0646\u062c\u06cc\u0631\u0647 \u06a9\u0646\u0645 <code>sort_values()<\/code> \u0631\u0648\u06cc  \u0634\u06cc\u0621 \u062d\u0627\u0635\u0644 \u0627\u0632 \u0633\u0631\u06cc \u067e\u0627\u0646\u062f\u0627\u0647\u0627.  \u0627\u06cc\u0646 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0631\u0627 \u0627\u0632 \u0628\u06cc\u0634\u062a\u0631\u06cc\u0646 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0645\u0646\u0641\u06cc \u0628\u0647 \u0645\u062b\u0628\u062a \u062a\u0631\u06cc\u0646 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u062e\u0631\u0648\u062c\u06cc \u0645\u06cc \u062f\u0647\u062f.<\/p>\n<pre><code class=\"hljs\">df.corr()((<span class=\"hljs-string\">'meantempm'<\/span>)).sort_values(<span class=\"hljs-string\">'meantempm'<\/span>)\n<\/code><\/pre>\n<table class=\"table table-bordered\">\n<thead>\n<tr style=\"text-align:right\">\n<th><\/th>\n<th>meantempm<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>maxpressurem_1<\/th>\n<td>-0.519699<\/td>\n<\/tr>\n<tr>\n<th>maxpressurem_2<\/th>\n<td>-0.425666<\/td>\n<\/tr>\n<tr>\n<th>maxpressurem_3<\/th>\n<td>-0.408902<\/td>\n<\/tr>\n<tr>\n<th>meanpressurem_1<\/th>\n<td>-0.365682<\/td>\n<\/tr>\n<tr>\n<th>\u0641\u0634\u0627\u0631 \u0645\u062a\u0648\u0633\u0637_2<\/th>\n<td>-0.269896<\/td>\n<\/tr>\n<tr>\n<th>meanpressurem_3<\/th>\n<td>-0.263008<\/td>\n<\/tr>\n<tr>\n<th>minpressurem_1<\/th>\n<td>-0.201003<\/td>\n<\/tr>\n<tr>\n<th>\u062d\u062f\u0627\u0642\u0644 \u0631\u0637\u0648\u0628\u062a_1<\/th>\n<td>-0.148602<\/td>\n<\/tr>\n<tr>\n<th>\u062d\u062f\u0627\u0642\u0644 \u0631\u0637\u0648\u0628\u062a_2<\/th>\n<td>-0.143211<\/td>\n<\/tr>\n<tr>\n<th>\u062d\u062f\u0627\u0642\u0644 \u0631\u0637\u0648\u0628\u062a_3<\/th>\n<td>-0.118564<\/td>\n<\/tr>\n<tr>\n<th>minpressurem_2<\/th>\n<td>-0.104455<\/td>\n<\/tr>\n<tr>\n<th>minpressurem_3<\/th>\n<td>-0.102955<\/td>\n<\/tr>\n<tr>\n<th>precipm_2<\/th>\n<td>0.084394<\/td>\n<\/tr>\n<tr>\n<th>precipm_1<\/th>\n<td>0.086617<\/td>\n<\/tr>\n<tr>\n<th>precipm_3<\/th>\n<td>0.098684<\/td>\n<\/tr>\n<tr>\n<th>\u062d\u062f\u0627\u06a9\u062b\u0631 \u0631\u0637\u0648\u0628\u062a_1<\/th>\n<td>0.132466<\/td>\n<\/tr>\n<tr>\n<th>\u062d\u062f\u0627\u06a9\u062b\u0631 \u0631\u0637\u0648\u0628\u062a_2<\/th>\n<td>0.151358<\/td>\n<\/tr>\n<tr>\n<th>\u062d\u062f\u0627\u06a9\u062b\u0631 \u0631\u0637\u0648\u0628\u062a_3<\/th>\n<td>0.167035<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_3<\/th>\n<td>0.829230<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_3<\/th>\n<td>0.832974<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_3<\/th>\n<td>0.833546<\/td>\n<\/tr>\n<tr>\n<th>meandewptm_3<\/th>\n<td>0.834251<\/td>\n<\/tr>\n<tr>\n<th>mintempm_3<\/th>\n<td>0.836340<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_2<\/th>\n<td>0.839893<\/td>\n<\/tr>\n<tr>\n<th>meandewptm_2<\/th>\n<td>0.848907<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_2<\/th>\n<td>0.852760<\/td>\n<\/tr>\n<tr>\n<th>mintempm_2<\/th>\n<td>0.854320<\/td>\n<\/tr>\n<tr>\n<th>meantempm_3<\/th>\n<td>0.855662<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_2<\/th>\n<td>0.863906<\/td>\n<\/tr>\n<tr>\n<th>meantempm_2<\/th>\n<td>0.881221<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_1<\/th>\n<td>0.887235<\/td>\n<\/tr>\n<tr>\n<th>meandewptm_1<\/th>\n<td>0.896681<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_1<\/th>\n<td>0.899000<\/td>\n<\/tr>\n<tr>\n<th>mintempm_1<\/th>\n<td>0.905423<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_1<\/th>\n<td>0.923787<\/td>\n<\/tr>\n<tr>\n<th>meantempm_1<\/th>\n<td>0.937563<\/td>\n<\/tr>\n<tr>\n<th>mintempm<\/th>\n<td>0.973122<\/td>\n<\/tr>\n<tr>\n<th>maxtempm<\/th>\n<td>0.976328<\/td>\n<\/tr>\n<tr>\n<th>meantempm<\/th>\n<td>1.000000<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u062f\u0631 \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc\u06cc \u06a9\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u06af\u0646\u062c\u0627\u0646\u062f\u0647 \u0634\u0648\u062f\u060c \u0645\u06cc \u062e\u0648\u0627\u0647\u0645 \u062e\u0637\u0627 \u06a9\u0646\u0645 \u0631\u0648\u06cc \u0627\u0632 \u0637\u0631\u0641\u06cc \u062f\u0631 \u06af\u0646\u062c\u0627\u0646\u062f\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc\u06cc \u0628\u0627 \u0636\u0631\u0627\u06cc\u0628 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u0645\u062a\u0648\u0633\u0637 \u200b\u200b\u06cc\u0627 \u067e\u0627\u06cc\u06cc\u0646\u200c\u062a\u0631\u060c \u0633\u0647\u0644\u200c\u0627\u0646\u06af\u06cc\u0632\u062a\u0631 \u0627\u0633\u062a.  \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0645\u0646 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc\u06cc \u0631\u0627 \u06a9\u0647 \u062f\u0627\u0631\u0627\u06cc \u0645\u0642\u0627\u062f\u06cc\u0631 \u0647\u0645\u0628\u0633\u062a\u06af\u06cc \u06a9\u0645\u062a\u0631 \u0627\u0632 \u0645\u0642\u062f\u0627\u0631 \u0645\u0637\u0644\u0642 0.6 \u0647\u0633\u062a\u0646\u062f \u062d\u0630\u0641 \u062e\u0648\u0627\u0647\u0645 \u06a9\u0631\u062f.  \u0647\u0645\u0686\u0646\u06cc\u0646\u060c \u0627\u0632 \u0622\u0646\u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u00abmintempm\u00bb \u0648 \u00abmaxtempm\u00bb \u0628\u0631\u0627\u06cc \u0647\u0645\u0627\u0646 \u0631\u0648\u0632 \u0645\u062a\u063a\u06cc\u0631 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u00abmeantempm\u00bb \u0647\u0633\u062a\u0646\u062f\u060c \u0645\u0646 \u0622\u0646\u200c\u0647\u0627 \u0631\u0627 \u0646\u06cc\u0632 \u062d\u0630\u0641 \u062e\u0648\u0627\u0647\u0645 \u06a9\u0631\u062f (\u06cc\u0639\u0646\u06cc \u0627\u06af\u0631 \u0627\u0632 \u0642\u0628\u0644 \u062d\u062f\u0627\u0642\u0644 \u0648 \u062d\u062f\u0627\u06a9\u062b\u0631 \u062f\u0645\u0627 \u0631\u0627 \u0645\u06cc\u200c\u062f\u0627\u0646\u0645\u060c \u067e\u0633 \u0627\u0632 \u0642\u0628\u0644 \u067e\u0627\u0633\u062e\u06cc \u0631\u0627 \u062f\u0627\u0631\u0645. \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc).<\/p>\n<p>\u0628\u0627 \u0627\u06cc\u0646 \u0627\u0637\u0644\u0627\u0639\u0627\u062a\u060c \u0627\u06a9\u0646\u0648\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u0645 \u06cc\u06a9 DataFrame \u062c\u062f\u06cc\u062f \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u0645 \u06a9\u0647 \u0641\u0642\u0637 \u0634\u0627\u0645\u0644 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0645\u0648\u0631\u062f \u0639\u0644\u0627\u0642\u0647 \u0645\u0646 \u0628\u0627\u0634\u062f.<\/p>\n<pre><code class=\"hljs\">predictors = (<span class=\"hljs-string\">'meantempm_1'<\/span>,  <span class=\"hljs-string\">'meantempm_2'<\/span>,  <span class=\"hljs-string\">'meantempm_3'<\/span>, \n              <span class=\"hljs-string\">'mintempm_1'<\/span>,   <span class=\"hljs-string\">'mintempm_2'<\/span>,   <span class=\"hljs-string\">'mintempm_3'<\/span>,\n              <span class=\"hljs-string\">'meandewptm_1'<\/span>, <span class=\"hljs-string\">'meandewptm_2'<\/span>, <span class=\"hljs-string\">'meandewptm_3'<\/span>,\n              <span class=\"hljs-string\">'maxdewptm_1'<\/span>,  <span class=\"hljs-string\">'maxdewptm_2'<\/span>,  <span class=\"hljs-string\">'maxdewptm_3'<\/span>,\n              <span class=\"hljs-string\">'mindewptm_1'<\/span>,  <span class=\"hljs-string\">'mindewptm_2'<\/span>,  <span class=\"hljs-string\">'mindewptm_3'<\/span>,\n              <span class=\"hljs-string\">'maxtempm_1'<\/span>,   <span class=\"hljs-string\">'maxtempm_2'<\/span>,   <span class=\"hljs-string\">'maxtempm_3'<\/span>)\ndf2 = df((<span class=\"hljs-string\">'meantempm'<\/span>) + predictors)\n<\/code><\/pre>\n<h2 id=\"visualizingtherelationships\"><span class=\"ez-toc-section\" id=\"%d8%aa%d8%ac%d8%b3%d9%85_%d8%b1%d9%88%d8%a7%d8%a8%d8%b7\"><\/span>\u062a\u062c\u0633\u0645 \u0631\u0648\u0627\u0628\u0637<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0627\u0632 \u0622\u0646\u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0627\u06a9\u062b\u0631 \u0645\u0631\u062f\u0645\u060c \u0627\u0632 \u062c\u0645\u0644\u0647 \u0645\u0646\u060c \u0628\u0633\u06cc\u0627\u0631 \u0628\u0647 \u062f\u06cc\u062f\u0646 \u062a\u0635\u0627\u0648\u06cc\u0631 \u0628\u0631\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0648 \u062a\u0623\u06cc\u06cc\u062f \u0627\u0644\u06af\u0648\u0647\u0627 \u0639\u0627\u062f\u062a \u062f\u0627\u0631\u0646\u062f\u060c \u0645\u0646 \u0647\u0631 \u06cc\u06a9 \u0627\u0632 \u0627\u06cc\u0646 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc\u200c\u06a9\u0646\u0646\u062f\u0647\u200c\u0647\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628\u06cc \u0631\u0627 \u0646\u0645\u0648\u062f\u0627\u0631 \u0645\u06cc\u200c\u06a9\u0646\u0645 \u062a\u0627 \u0628\u0647 \u062e\u0648\u062f\u0645 \u062b\u0627\u0628\u062a \u06a9\u0646\u0645 \u06a9\u0647 \u062f\u0631 \u0648\u0627\u0642\u0639 \u06cc\u06a9 \u0631\u0627\u0628\u0637\u0647 \u062e\u0637\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.  \u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u0627\u0632 matplotlib \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u0645 \u06a9\u0631\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/matplotlib.org\/api\/pyplot_api.html\">\u067e\u0627\u06cc \u0637\u0631\u062d<\/a> \u0645\u062f\u0648\u0644.<\/p>\n<p>\u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0646\u0645\u0648\u062f\u0627\u0631\u060c \u0645\u06cc\u200c\u062e\u0648\u0627\u0647\u0645 \u0645\u062a\u063a\u06cc\u0631 \u0648\u0627\u0628\u0633\u062a\u0647 &#8220;meantempm&#8221; \u0645\u062d\u0648\u0631 y \u062b\u0627\u0628\u062a \u062f\u0631 \u0627\u0645\u062a\u062f\u0627\u062f \u062a\u0645\u0627\u0645 \u0646\u0645\u0648\u062f\u0627\u0631\u0647\u0627\u06cc 18 \u0645\u062a\u063a\u06cc\u0631 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646 \u0628\u0627\u0634\u062f.  \u06cc\u06a9\u06cc \u0627\u0632 \u0631\u0627\u0647\u200c\u0647\u0627\u06cc \u0627\u0646\u062c\u0627\u0645 \u0627\u06cc\u0646 \u06a9\u0627\u0631\u060c \u0627\u06cc\u062c\u0627\u062f \u0634\u0628\u06a9\u0647\u200c\u0627\u06cc \u0627\u0632 \u0646\u0645\u0648\u062f\u0627\u0631\u0647\u0627 \u0627\u0633\u062a.  \u067e\u0627\u0646\u062f\u0627\u0647\u0627 \u0628\u0627 \u06cc\u06a9 \u062a\u0627\u0628\u0639 \u0631\u0633\u0645 \u0645\u0641\u06cc\u062f\u06cc \u0628\u0647 \u0646\u0627\u0645 the \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc \u0634\u0648\u0646\u062f <code>scatter_plot()<\/code>\u060c \u0627\u0645\u0627 \u0645\u0646 \u0645\u0639\u0645\u0648\u0644\u0627\u064b \u0641\u0642\u0637 \u0632\u0645\u0627\u0646\u06cc \u0627\u0632 \u0622\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u0645 \u06a9\u0647 \u0641\u0642\u0637 \u062a\u0627 \u062d\u062f\u0648\u062f 5 \u0645\u062a\u063a\u06cc\u0631 \u0648\u062c\u0648\u062f \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u062f \u0632\u06cc\u0631\u0627 \u0646\u0645\u0648\u062f\u0627\u0631 \u0631\u0627 \u0628\u0647 \u06cc\u06a9 \u0645\u0627\u062a\u0631\u06cc\u0633 N x N \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u06a9\u0646\u062f (\u062f\u0631 \u0645\u0648\u0631\u062f \u0645\u0627 18 x 18) \u06a9\u0647 \u062f\u06cc\u062f\u0646 \u062c\u0632\u0626\u06cc\u0627\u062a \u062f\u0631 \u062f\u0627\u062f\u0647 \u0647\u0627 \u062f\u0634\u0648\u0627\u0631 \u0645\u06cc \u0634\u0648\u062f.  \u062f\u0631 \u0639\u0648\u0636\u060c \u0645\u0646 \u06cc\u06a9 \u0633\u0627\u062e\u062a\u0627\u0631 \u0634\u0628\u06a9\u0647 \u0627\u06cc \u0628\u0627 \u0634\u0634 \u0631\u062f\u06cc\u0641 \u0627\u0632 \u0633\u0647 \u0633\u062a\u0648\u0646 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u06a9\u0646\u0645 \u062a\u0627 \u0627\u0632 \u0648\u0636\u0648\u062d \u062f\u0631 \u0646\u0645\u0648\u062f\u0627\u0631\u0647\u0627 \u062c\u0644\u0648\u06af\u06cc\u0631\u06cc \u06a9\u0646\u0645.<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> matplotlib\n<span class=\"hljs-keyword\">import<\/span> matplotlib.pyplot <span class=\"hljs-keyword\">as<\/span> plt\n<span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\n<\/code><\/pre>\n<pre><code class=\"hljs\">%matplotlib inline\n\n\nplt.rcParams(<span class=\"hljs-string\">'figure.figsize'<\/span>) = (<span class=\"hljs-number\">16<\/span>, <span class=\"hljs-number\">22<\/span>)\n\n\n\nfig, axes = plt.subplots(nrows=<span class=\"hljs-number\">6<\/span>, ncols=<span class=\"hljs-number\">3<\/span>, sharey=<span class=\"hljs-literal\">True<\/span>)\n\n\n\narr = np.array(predictors).reshape(<span class=\"hljs-number\">6<\/span>, <span class=\"hljs-number\">3<\/span>)\n\n\n\n<span class=\"hljs-keyword\">for<\/span> row, col_arr <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">enumerate<\/span>(arr):\n    <span class=\"hljs-keyword\">for<\/span> col, feature <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">enumerate<\/span>(col_arr):\n        axes(row, col).scatter(df2(feature), df2(<span class=\"hljs-string\">'meantempm'<\/span>))\n        <span class=\"hljs-keyword\">if<\/span> col == <span class=\"hljs-number\">0<\/span>:\n            axes(row, col).<span class=\"hljs-built_in\">set<\/span>(xlabel=feature, ylabel=<span class=\"hljs-string\">'meantempm'<\/span>)\n        <span class=\"hljs-keyword\">else<\/span>:\n            axes(row, col).<span class=\"hljs-built_in\">set<\/span>(xlabel=feature)\nplt.show()\n<\/code><\/pre>\n<p><img decoding=\"async\" class=\"img-responsive\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/using-machine-learning-predict-weather-part-2-1.png\" alt=\"\u0646\u0645\u0648\u062f\u0627\u0631 \u067e\u0631\u0627\u06a9\u0646\u062f\u06af\u06cc meantempm\" title=\"\"><\/p>\n<p>\u0627\u0632 \u0646\u0645\u0648\u062f\u0627\u0631\u0647\u0627\u06cc \u0628\u0627\u0644\u0627 \u0642\u0627\u0628\u0644 \u062a\u0634\u062e\u06cc\u0635 \u0627\u0633\u062a \u06a9\u0647 \u0647\u0645\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0628\u0627\u0642\u06cc \u0645\u0627\u0646\u062f\u0647 \u06cc\u06a9 \u0631\u0627\u0628\u0637\u0647 \u062e\u0637\u06cc \u062e\u0648\u0628 \u0628\u0627 \u0645\u062a\u063a\u06cc\u0631 \u067e\u0627\u0633\u062e (&#8220;meantempm&#8221;) \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u0646\u062f.  \u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646\u060c \u0647\u0645\u0686\u0646\u06cc\u0646 \u0634\u0627\u06cc\u0627\u0646 \u0630\u06a9\u0631 \u0627\u0633\u062a \u06a9\u0647 \u0631\u0648\u0627\u0628\u0637 \u0647\u0645\u0647 \u0628\u0647 \u0637\u0648\u0631 \u06cc\u06a9\u0646\u0648\u0627\u062e\u062a \u0628\u0647 \u0635\u0648\u0631\u062a \u062a\u0635\u0627\u062f\u0641\u06cc \u062a\u0648\u0632\u06cc\u0639 \u0634\u062f\u0647 \u0627\u0646\u062f.  \u0645\u0646\u0638\u0648\u0631 \u0645\u0646 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0628\u0647 \u0646\u0638\u0631 \u0645\u06cc \u0631\u0633\u062f \u062a\u0646\u0648\u0639 \u0646\u0633\u0628\u062a\u0627\u064b \u0645\u0633\u0627\u0648\u06cc \u062f\u0631 \u06af\u0633\u062a\u0631\u0634 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0628\u062f\u0648\u0646 \u0647\u0631 \u06af\u0648\u0646\u0647 \u0628\u0627\u062f\u06a9\u0634 \u06cc\u0627 \u0645\u062e\u0631\u0648\u0637 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f.  \u062a\u0648\u0632\u06cc\u0639 \u062a\u0635\u0627\u062f\u0641\u06cc \u06cc\u06a9\u0646\u0648\u0627\u062e\u062a \u06af\u0633\u062a\u0631\u0634 \u062f\u0631 \u0627\u0645\u062a\u062f\u0627\u062f \u0646\u0642\u0627\u0637 \u0646\u06cc\u0632 \u06cc\u06a9\u06cc \u062f\u06cc\u06af\u0631 \u0627\u0632 \u0641\u0631\u0636\u06cc\u0627\u062a \u0645\u0647\u0645 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0646 \u0627\u0633\u062a <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Ordinary_least_squares\">\u062d\u062f\u0627\u0642\u0644 \u0645\u0631\u0628\u0639\u0627\u062a \u0645\u0639\u0645\u0648\u0644\u06cc<\/a> \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645<\/p>\n<h2 id=\"usingstepwiseregressiontobuildarobustmodel\"><span class=\"ez-toc-section\" id=\"%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d8%b1%da%af%d8%b1%d8%b3%db%8c%d9%88%d9%86_%da%af%d8%a7%d9%85_%d8%a8%d9%87_%da%af%d8%a7%d9%85_%d8%a8%d8%b1%d8%a7%db%8c_%d8%b3%d8%a7%d8%ae%d8%aa_%db%8c%da%a9_%d9%85%d8%af%d9%84_%d9%82%d9%88%db%8c\"><\/span>\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645 \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u06cc\u06a9 \u0645\u062f\u0644 \u0642\u0648\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u06cc\u06a9 \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0642\u0648\u06cc \u0628\u0627\u06cc\u062f \u0627\u0632 \u0622\u0632\u0645\u0648\u0646\u200c\u0647\u0627\u06cc \u0622\u0645\u0627\u0631\u06cc \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc\u200c\u06a9\u0646\u0646\u062f\u0647\u200c\u0647\u0627\u06cc \u0645\u0639\u0646\u0627\u062f\u0627\u0631 \u0648 \u0645\u0639\u0646\u06cc\u200c\u062f\u0627\u0631 \u0622\u0645\u0627\u0631\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u062f.  \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0622\u0645\u0627\u0631\u06cc \u0645\u0647\u0645\u060c \u0627\u0632 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u0645 <code>statsmodels<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647  \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u0642\u0628\u0644 \u0627\u0632 \u0627\u06cc\u0646\u06a9\u0647 \u0645\u0646 \u0628\u0647 \u0627\u062c\u0631\u0627\u06cc \u0639\u0645\u0644\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <code>statsmodels<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0645\u0646 \u0645\u06cc \u062e\u0648\u0627\u0647\u0645 \u06cc\u06a9 \u0642\u062f\u0645 \u0628\u0647 \u0639\u0642\u0628 \u0628\u0631\u06af\u0631\u062f\u0645 \u0648 \u0628\u0631\u062e\u06cc \u0627\u0632 \u0645\u0639\u0646\u06cc \u0648 \u0647\u062f\u0641 \u0646\u0638\u0631\u06cc \u0627\u062a\u062e\u0627\u0630 \u0627\u06cc\u0646 \u0631\u0648\u06cc\u06a9\u0631\u062f \u0631\u0627 \u062a\u0648\u0636\u06cc\u062d \u062f\u0647\u0645.<\/p>\n<p>\u06cc\u06a9\u06cc \u0627\u0632 \u062c\u0646\u0628\u0647\u200c\u0647\u0627\u06cc \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u0622\u0645\u0627\u0631\u06cc \u0645\u0627\u0646\u0646\u062f \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u062f\u0631 \u06cc\u06a9 \u067e\u0631\u0648\u0698\u0647 \u062a\u062d\u0644\u06cc\u0644\u06cc\u060c \u0627\u06cc\u062c\u0627\u062f \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634 \u0622\u0632\u0645\u0648\u0646\u200c\u0647\u0627\u06cc \u0641\u0631\u0636\u06cc\u0647 \u0628\u0631\u0627\u06cc \u062a\u0623\u06cc\u06cc\u062f \u0627\u0647\u0645\u06cc\u062a \u0645\u0641\u0631\u0648\u0636\u0627\u062a \u0633\u0627\u062e\u062a\u0647 \u0634\u062f\u0647 \u062f\u0631 \u0645\u0648\u0631\u062f \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0645\u0648\u0631\u062f \u0645\u0637\u0627\u0644\u0639\u0647 \u0627\u0633\u062a.  \u0622\u0632\u0645\u0648\u0646\u200c\u0647\u0627\u06cc \u0641\u0631\u0636\u06cc\u0647\u200c\u0647\u0627\u06cc \u0645\u062a\u0639\u062f\u062f\u06cc \u0628\u0631\u0627\u06cc \u0622\u0632\u0645\u0627\u06cc\u0634 \u0627\u0633\u062a\u062d\u06a9\u0627\u0645 \u06cc\u06a9 \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u062f\u0631 \u0628\u0631\u0627\u0628\u0631 \u0645\u0641\u0631\u0648\u0636\u0627\u062a \u0645\u062e\u062a\u0644\u0641 \u0627\u06cc\u062c\u0627\u062f \u0634\u062f\u0647\u200c\u0627\u0646\u062f.  \u06cc\u06a9\u06cc \u0627\u0632 \u0627\u06cc\u0646 \u0622\u0632\u0645\u0648\u0646\u200c\u0647\u0627\u060c \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0627\u0647\u0645\u06cc\u062a \u0647\u0631 \u06cc\u06a9 \u0627\u0632 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc\u200c\u06a9\u0646\u0646\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<p>\u062a\u0639\u0631\u06cc\u0641 \u0631\u0633\u0645\u06cc \u0622\u0632\u0645\u0648\u0646 \u0641\u0631\u0636\u06cc\u0647 \u0628\u0631\u0627\u06cc \u0645\u0639\u0646\u0627\u062f\u0627\u0631\u06cc \u0627\u0644\u0641 <code>\u03b2<sub>j<\/sub><\/code> \u067e\u0627\u0631\u0627\u0645\u062a\u0631\u0647\u0627 \u0628\u0647 \u0634\u0631\u062d \u0632\u06cc\u0631 \u0627\u0633\u062a:<\/p>\n<ul>\n<li><code>H<sub>0<\/sub><\/code>: <code>\u03b2<sub>j<\/sub> = 0<\/code>\u060c \u0641\u0631\u0636\u06cc\u0647 \u0635\u0641\u0631 \u0628\u06cc\u0627\u0646 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u0646\u062f\u0647 \u062a\u0627\u062b\u06cc\u0631\u06cc \u0646\u062f\u0627\u0631\u062f \u0631\u0648\u06cc \u0645\u0642\u062f\u0627\u0631 \u0645\u062a\u063a\u06cc\u0631 \u0646\u062a\u06cc\u062c\u0647<\/li>\n<li><code>H<sub>a<\/sub><\/code>: <code>\u03b2<sub>j<\/sub> \u2260 0<\/code>\u060c \u0641\u0631\u0636\u06cc\u0647 \u062c\u0627\u06cc\u06af\u0632\u06cc\u0646 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u0646\u062f\u0647 \u062a\u0623\u062b\u06cc\u0631 \u0645\u0639\u0646\u06cc \u062f\u0627\u0631\u06cc \u062f\u0627\u0631\u062f \u0631\u0648\u06cc \u0645\u0642\u062f\u0627\u0631 \u0645\u062a\u063a\u06cc\u0631 \u0646\u062a\u06cc\u062c\u0647<\/li>\n<\/ul>\n<p>\u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0632\u0645\u0648\u0646 \u0647\u0627\u06cc \u0627\u062d\u062a\u0645\u0627\u0644 \u0628\u0631\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0627\u062d\u062a\u0645\u0627\u0644 \u0647\u0631 \u06cc\u06a9 <code>\u03b2<sub>j<\/sub><\/code> \u0641\u0631\u0627\u062a\u0631 \u0627\u0632 \u0634\u0627\u0646\u0633 \u062a\u0635\u0627\u062f\u0641\u06cc \u0633\u0627\u062f\u0647 \u062f\u0631 \u06cc\u06a9 \u0622\u0633\u062a\u0627\u0646\u0647 \u0627\u0646\u062a\u062e\u0627\u0628 \u0634\u062f\u0647 \u0642\u0627\u0628\u0644 \u062a\u0648\u062c\u0647 \u0627\u0633\u062a <code>\u0391<\/code> \u0645\u0627 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u0645 \u062f\u0631 \u0627\u0646\u062a\u062e\u0627\u0628 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc\u06cc \u06a9\u0647 \u0634\u0627\u0645\u0644 \u0645\u062f\u0644\u06cc \u0642\u0648\u06cc\u200c\u062a\u0631 \u0645\u06cc\u200c\u0634\u0648\u0646\u062f\u060c \u062f\u0642\u06cc\u0642\u200c\u062a\u0631 \u0639\u0645\u0644 \u06a9\u0646\u06cc\u0645.<\/p>\n<p>\u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u062f\u0631 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647\u200c\u0647\u0627\u06cc \u062f\u0627\u062f\u0647 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u062f \u062a\u0639\u0627\u0645\u0644\u0627\u062a\u06cc \u0628\u06cc\u0646 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u0648\u062c\u0648\u062f \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u062f \u06a9\u0647 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u062f \u0645\u0646\u062c\u0631 \u0628\u0647 \u062a\u0641\u0633\u06cc\u0631\u0647\u0627\u06cc \u0646\u0627\u062f\u0631\u0633\u062a \u0627\u0632 \u0627\u06cc\u0646 \u0622\u0632\u0645\u0648\u0646\u200c\u0647\u0627\u06cc \u0641\u0631\u0636\u06cc\u0647 \u0633\u0627\u062f\u0647 \u0634\u0648\u062f.  \u0628\u0631\u0627\u06cc \u0622\u0632\u0645\u0627\u06cc\u0634 \u0627\u062b\u0631\u0627\u062a \u0645\u062a\u0642\u0627\u0628\u0644 \u0631\u0648\u06cc \u0627\u0647\u0645\u06cc\u062a \u0647\u0631 \u06cc\u06a9 \u0627\u0632 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627 \u062f\u0631 \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc\u060c \u0627\u063a\u0644\u0628 \u0627\u0632 \u062a\u06a9\u0646\u06cc\u06a9\u06cc \u0628\u0647 \u0646\u0627\u0645 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f.  \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc\u06cc \u0631\u0627 \u0627\u0632 \u0645\u062f\u0644 \u0627\u0636\u0627\u0641\u0647 \u06cc\u0627 \u062d\u0630\u0641 \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0648 \u0627\u0647\u0645\u06cc\u062a \u0622\u0645\u0627\u0631\u06cc \u0647\u0631 \u0645\u062a\u063a\u06cc\u0631 \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f. \u0631\u0648\u06cc \u0645\u062f\u0644 \u062d\u0627\u0635\u0644<\/p>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0632 \u062a\u06a9\u0646\u06cc\u06a9\u06cc \u0628\u0647 \u0646\u0627\u0645 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u0645 \u06a9\u0631\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Stepwise_regression#Main_approaches\">\u062d\u0630\u0641 \u0639\u0642\u0628 \u0645\u0627\u0646\u062f\u0647<\/a>\u060c \u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0645\u0646 \u0628\u0627 \u06cc\u06a9 \u0645\u062f\u0644 \u06a9\u0644\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u0634\u062f\u0647 \u0634\u0631\u0648\u0639 \u0645\u06cc \u06a9\u0646\u0645 \u06a9\u0647 \u0634\u0627\u0645\u0644 \u0647\u0645\u0647 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0645\u0648\u0631\u062f \u0639\u0644\u0627\u0642\u0647 \u0645\u0646 \u0627\u0633\u062a.<\/p>\n<p>\u062d\u0630\u0641 \u0628\u0647 \u0639\u0642\u0628 \u0628\u0647 \u0635\u0648\u0631\u062a \u0632\u06cc\u0631 \u0639\u0645\u0644 \u0645\u06cc \u06a9\u0646\u062f:<\/p>\n<ol>\n<li>\u0633\u0637\u062d \u0645\u0639\u0646\u0627\u062f\u0627\u0631\u06cc \u0631\u0627 \u0627\u0646\u062a\u062e\u0627\u0628 \u06a9\u0646\u06cc\u062f <code>\u0391<\/code> \u06a9\u0647 \u0628\u0631\u0627\u06cc \u062a\u0639\u06cc\u06cc\u0646 \u0627\u06cc\u0646\u06a9\u0647 \u0622\u06cc\u0627 \u06cc\u06a9 \u0645\u062a\u063a\u06cc\u0631 \u0628\u0627\u06cc\u062f \u062f\u0631 \u0645\u062f\u0644 \u0628\u0645\u0627\u0646\u062f \u06cc\u0627 \u062e\u06cc\u0631\u060c \u0641\u0631\u0636\u06cc\u0647 \u062e\u0648\u062f \u0631\u0627 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0622\u0646 \u0622\u0632\u0645\u0627\u06cc\u0634 \u0645\u06cc \u06a9\u0646\u06cc\u062f<\/li>\n<li>\u0645\u062f\u0644 \u0631\u0627 \u0628\u0627 \u062a\u0645\u0627\u0645 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u0646\u062f\u0647 \u0645\u0637\u0627\u0628\u0642\u062a \u062f\u0647\u06cc\u062f<\/li>\n<li>\u0645\u0642\u0627\u062f\u06cc\u0631 p \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0646\u06cc\u062f <code>\u03b2<sub>j<\/sub><\/code> \u0636\u0631\u0627\u06cc\u0628 \u0648 \u0628\u0631\u0627\u06cc \u06cc\u06a9\u06cc \u0628\u0627 \u0628\u06cc\u0634\u062a\u0631\u06cc\u0646 \u0645\u0642\u062f\u0627\u0631 p\u060c \u0627\u06af\u0631 p-value > <code>\u0391<\/code> \u0628\u0647 \u0645\u0631\u062d\u0644\u0647 4 \u0628\u0631\u0648\u06cc\u062f\u060c \u0627\u06af\u0631 \u0646\u0647\u060c \u0645\u062f\u0644 \u0646\u0647\u0627\u06cc\u06cc \u062e\u0648\u062f \u0631\u0627 \u062f\u0627\u0631\u06cc\u062f<\/li>\n<li>\u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u0646\u0627\u0633\u0627\u06cc\u06cc \u0634\u062f\u0647 \u062f\u0631 \u0645\u0631\u062d\u0644\u0647 3 \u0631\u0627 \u062d\u0630\u0641 \u06a9\u0646\u06cc\u062f<\/li>\n<li>\u062f\u0648\u0628\u0627\u0631\u0647 \u0645\u062f\u0644 \u0631\u0627 \u062c\u0627\u0628\u062c\u0627 \u06a9\u0646\u06cc\u062f\u060c \u0627\u0645\u0627 \u0627\u06cc\u0646 \u0628\u0627\u0631 \u0628\u062f\u0648\u0646 \u0645\u062a\u063a\u06cc\u0631 \u062d\u0630\u0641 \u0634\u062f\u0647 \u0648 \u0628\u0647 \u0645\u0631\u062d\u0644\u0647 3 \u0628\u0631\u06af\u0631\u062f\u06cc\u062f<\/li>\n<\/ol>\n<p>\u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646\u060c \u0628\u062f\u0648\u0646 \u062a\u0623\u062e\u06cc\u0631 \u0628\u06cc\u0634\u062a\u0631\u060c \u0627\u062c\u0627\u0632\u0647 \u062f\u0647\u06cc\u062f \u0627\u06cc\u0646 \u0645\u062f\u0644 \u062a\u0639\u0645\u06cc\u0645 \u06cc\u0627\u0641\u062a\u0647 \u06a9\u0627\u0645\u0644\u0627\u064b \u0628\u0627\u0631\u06af\u0630\u0627\u0631\u06cc \u0634\u062f\u0647 \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0646 \u0628\u0633\u0627\u0632\u06cc\u0645 <code>statsmodels<\/code> \u0628\u0647 \u062f\u0646\u0628\u0627\u0644 \u0645\u0631\u0627\u062d\u0644 \u0628\u0627\u0644\u0627<\/p>\n<pre><code class=\"hljs\">\n<span class=\"hljs-keyword\">import<\/span> statsmodels.api <span class=\"hljs-keyword\">as<\/span> sm\n\n\nX = df2(predictors)\ny = df2(<span class=\"hljs-string\">'meantempm'<\/span>)\n\n\nX = sm.add_constant(X)\nX.ix(:<span class=\"hljs-number\">5<\/span>, :<span class=\"hljs-number\">5<\/span>)\n<\/code><\/pre>\n<table class=\"table table-bordered\">\n<thead>\n<tr style=\"text-align:right\">\n<th><\/th>\n<th>\u067e\u0627\u06cc\u0627\u0646<\/th>\n<th>meantempm_1<\/th>\n<th>meantempm_2<\/th>\n<th>meantempm_3<\/th>\n<th>mintempm_1<\/th>\n<\/tr>\n<tr>\n<th>\u062a\u0627\u0631\u06cc\u062e<\/th>\n<th><\/th>\n<th><\/th>\n<th><\/th>\n<th><\/th>\n<th><\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<th>04\/01\/2015<\/th>\n<td>1.0<\/td>\n<td>-4.0<\/td>\n<td>-6.0<\/td>\n<td>-6.0<\/td>\n<td>-13.0<\/td>\n<\/tr>\n<tr>\n<th>05\/01\/2015<\/th>\n<td>1.0<\/td>\n<td>-14.0<\/td>\n<td>-4.0<\/td>\n<td>-6.0<\/td>\n<td>-18.0<\/td>\n<\/tr>\n<tr>\n<th>06\/01\/2015<\/th>\n<td>1.0<\/td>\n<td>-9.0<\/td>\n<td>-14.0<\/td>\n<td>-4.0<\/td>\n<td>-14.0<\/td>\n<\/tr>\n<tr>\n<th>07\/01\/2015<\/th>\n<td>1.0<\/td>\n<td>-10.0<\/td>\n<td>-9.0<\/td>\n<td>-14.0<\/td>\n<td>-14.0<\/td>\n<\/tr>\n<tr>\n<th>08\/01\/2015<\/th>\n<td>1.0<\/td>\n<td>-16.0<\/td>\n<td>-10.0<\/td>\n<td>-9.0<\/td>\n<td>-19.0<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<pre><code class=\"hljs\">\nalpha = <span class=\"hljs-number\">0.05<\/span>\n\n\nmodel = sm.OLS(y, X).fit()\n\n\nmodel.summary()\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646 <code>summary()<\/code> \u062a\u0645\u0627\u0633 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0632\u06cc\u0631 \u0631\u0627 \u062f\u0631 \u0634\u0645\u0627 \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc \u06a9\u0646\u062f Jupyter notebook:<\/p>\n<table class=\"table\">\n<caption>\u0646\u062a\u0627\u06cc\u062c \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 OLS<\/caption>\n<tbody>\n<tr>\n<th>\u0628\u062e\u0634  \u0645\u062a\u063a\u06cc\u0631:<\/th>\n<td>meantempm<\/td>\n<th>    R-squared:         <\/th>\n<td>      0.895<\/td>\n<\/tr>\n<tr>\n<th>\u0645\u062f\u0644:<\/th>\n<td>OLS<\/td>\n<th>    \u0635\u0641\u062a  R-squared:    <\/th>\n<td>      0.893<\/td>\n<\/tr>\n<tr>\n<th>\u0631\u0648\u0634:<\/th>\n<td>\u06a9\u0645\u062a\u0631\u06cc\u0646 \u0645\u0631\u0628\u0639\u0627\u062a<\/td>\n<th>    \u0622\u0645\u0627\u0631 F:       <\/th>\n<td>      462.7<\/td>\n<\/tr>\n<tr>\n<th>\u062a\u0627\u0631\u06cc\u062e:<\/th>\n<td>\u067e\u0646\u062c\u0634\u0646\u0628\u0647\u060c 16 \u0646\u0648\u0627\u0645\u0628\u0631 2017<\/td>\n<th>    \u0645\u0634\u06a9\u0644 (\u0622\u0645\u0627\u0631 F):<\/th>\n<td>    0.00<\/td>\n<\/tr>\n<tr>\n<th>\u0632\u0645\u0627\u0646:<\/th>\n<td>20:55:25<\/td>\n<th>    \u0627\u062d\u062a\u0645\u0627\u0644 \u0648\u0631\u0648\u062f:    <\/th>\n<td>  -2679.2<\/td>\n<\/tr>\n<tr>\n<th>\u0634\u0645\u0627\u0631\u0647 \u0645\u0634\u0627\u0647\u062f\u0627\u062a:<\/th>\n<td>      997<\/td>\n<th>    AIC:               <\/th>\n<td>      5396.<\/td>\n<\/tr>\n<tr>\n<th>\u0628\u0627\u0642\u06cc\u0645\u0627\u0646\u062f\u0647 \u0647\u0627\u06cc Df:<\/th>\n<td>      978<\/td>\n<th>    BIC:               <\/th>\n<td>      5490.<\/td>\n<\/tr>\n<tr>\n<th>\u0645\u062f\u0644 Df:<\/th>\n<td>        18<\/td>\n<th>                     <\/th>\n<td> <\/td>\n<\/tr>\n<tr>\n<th>\u0646\u0648\u0639 \u06a9\u0648\u0648\u0627\u0631\u06cc\u0627\u0646\u0633:<\/th>\n<td>\u063a\u06cc\u0631 \u0645\u0633\u062a\u062d\u06a9\u0645<\/td>\n<th>                     <\/th>\n<td> <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table class=\"table\">\n<tbody>\n<tr>\n<td><\/td>\n<th>\u0636\u0631\u06cc\u0628<\/th>\n<th>std err<\/th>\n<th>\u062a\u06cc<\/th>\n<th>P>|t|<\/th>\n<th>(0.025<\/th>\n<th>0.975)<\/th>\n<\/tr>\n<tr>\n<th>\u067e\u0627\u06cc\u0627\u0646<\/th>\n<td>        1.0769<\/td>\n<td>        0.526<\/td>\n<td>        2.049<\/td>\n<td>  0.041<\/td>\n<td>        0.046<\/td>\n<td>        2.108<\/td>\n<\/tr>\n<tr>\n<th>meantempm_1<\/th>\n<td>        0.1047<\/td>\n<td>        0.287<\/td>\n<td>        0.364<\/td>\n<td>  0.716<\/td>\n<td>      -0.459<\/td>\n<td>        0.669<\/td>\n<\/tr>\n<tr>\n<th>meantempm_2<\/th>\n<td>        0.3512<\/td>\n<td>        0.287<\/td>\n<td>        1.225<\/td>\n<td>  0.221<\/td>\n<td>      -0.211<\/td>\n<td>        0.914<\/td>\n<\/tr>\n<tr>\n<th>meantempm_3<\/th>\n<td>      -0.1084<\/td>\n<td>        0.286<\/td>\n<td>      -0.379<\/td>\n<td>  0.705<\/td>\n<td>      -0.669<\/td>\n<td>        0.453<\/td>\n<\/tr>\n<tr>\n<th>mintempm_1<\/th>\n<td>        0.0805<\/td>\n<td>        0.149<\/td>\n<td>        0.539<\/td>\n<td>  0.590<\/td>\n<td>      -0.213<\/td>\n<td>        0.373<\/td>\n<\/tr>\n<tr>\n<th>mintempm_2<\/th>\n<td>      -0.2371<\/td>\n<td>        0.149<\/td>\n<td>      -1.587<\/td>\n<td>  0.113<\/td>\n<td>      -0.530<\/td>\n<td>        0.056<\/td>\n<\/tr>\n<tr>\n<th>mintempm_3<\/th>\n<td>        0.1521<\/td>\n<td>        0.148<\/td>\n<td>        1.028<\/td>\n<td>  0.304<\/td>\n<td>      -0.138<\/td>\n<td>        0.443<\/td>\n<\/tr>\n<tr>\n<th>meandewptm_1<\/th>\n<td>      -0.0418<\/td>\n<td>        0.138<\/td>\n<td>      -0.304<\/td>\n<td>  0.761<\/td>\n<td>      -0.312<\/td>\n<td>        0.228<\/td>\n<\/tr>\n<tr>\n<th>meandewptm_2<\/th>\n<td>      -0.0121<\/td>\n<td>        0.138<\/td>\n<td>      -0.088<\/td>\n<td>  0.930<\/td>\n<td>      -0.282<\/td>\n<td>        0.258<\/td>\n<\/tr>\n<tr>\n<th>meandewptm_3<\/th>\n<td>      -0.0060<\/td>\n<td>        0.137<\/td>\n<td>      -0.044<\/td>\n<td>  0.965<\/td>\n<td>      -0.275<\/td>\n<td>        0.263<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_1<\/th>\n<td>      -0.1592<\/td>\n<td>        0.091<\/td>\n<td>      -1.756<\/td>\n<td>  0.079<\/td>\n<td>      -0.337<\/td>\n<td>        0.019<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_2<\/th>\n<td>      -0.0113<\/td>\n<td>        0.091<\/td>\n<td>      -0.125<\/td>\n<td>  0.900<\/td>\n<td>      -0.189<\/td>\n<td>        0.166<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_3<\/th>\n<td>        0.1326<\/td>\n<td>        0.089<\/td>\n<td>        1.492<\/td>\n<td>  0.136<\/td>\n<td>      -0.042<\/td>\n<td>        0.307<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_1<\/th>\n<td>        0.3638<\/td>\n<td>        0.084<\/td>\n<td>        4.346<\/td>\n<td>  0.000<\/td>\n<td>        0.200<\/td>\n<td>        0.528<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_2<\/th>\n<td>      -0.0119<\/td>\n<td>        0.088<\/td>\n<td>      -0.136<\/td>\n<td>  0.892<\/td>\n<td>      -0.184<\/td>\n<td>        0.160<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_3<\/th>\n<td>      -0.0239<\/td>\n<td>        0.086<\/td>\n<td>      -0.279<\/td>\n<td>  0.780<\/td>\n<td>      -0.192<\/td>\n<td>        0.144<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_1<\/th>\n<td>        0.5042<\/td>\n<td>        0.147<\/td>\n<td>        3.438<\/td>\n<td>  0.001<\/td>\n<td>        0.216<\/td>\n<td>        0.792<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_2<\/th>\n<td>      -0.2154<\/td>\n<td>        0.147<\/td>\n<td>      -1.464<\/td>\n<td>  0.143<\/td>\n<td>      -0.504<\/td>\n<td>        0.073<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_3<\/th>\n<td>        0.0809<\/td>\n<td>        0.146<\/td>\n<td>        0.555<\/td>\n<td>  0.579<\/td>\n<td>      -0.205<\/td>\n<td>        0.367<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table class=\"table\">\n<tbody>\n<tr>\n<th>Omnibus:<\/th>\n<td>13.252<\/td>\n<th>    \u062f\u0648\u0631\u0628\u06cc\u0646 \u0648\u0627\u062a\u0633\u0648\u0646:     <\/th>\n<td>      2.015<\/td>\n<\/tr>\n<tr>\n<th>\u067e\u0631\u0648\u0628 (Omnibus):<\/th>\n<td>  0.001<\/td>\n<th>    Jarque-Bera (JB):  <\/th>\n<td>    17.097<\/td>\n<\/tr>\n<tr>\n<th>\u06a9\u062c:<\/th>\n<td>-0.163<\/td>\n<th>    \u0645\u0634\u06a9\u0644 (JB):          <\/th>\n<td>0.000194<\/td>\n<\/tr>\n<tr>\n<th>\u06a9\u0648\u0631\u062a\u0648\u0632:<\/th>\n<td>  3.552<\/td>\n<th>    \u0634\u0631\u0637  \u062e\u06cc\u0631         <\/th>\n<td>        291.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u062e\u0648\u0628\u060c \u0645\u0646 \u0645\u062a\u0648\u062c\u0647 \u0634\u062f\u0645 \u06a9\u0647 \u062a\u0645\u0627\u0633 \u0628\u0647 <code>summary()<\/code> \u0641\u0642\u0637 \u062a\u0639\u062f\u0627\u062f \u0632\u06cc\u0627\u062f\u06cc \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0631\u0648\u06cc \u0635\u0641\u062d\u0647 \u0646\u0645\u0627\u06cc\u0634 \u062f\u0627\u062f\u0647 \u0634\u062f.  \u063a\u0631\u0642 \u0646\u0634\u0648!  \u0645\u0627 \u0641\u0642\u0637 \u062a\u0645\u0631\u06a9\u0632 \u0645\u06cc \u06a9\u0646\u06cc\u0645 \u0631\u0648\u06cc \u062d\u062f\u0648\u062f 2-3 \u0645\u0642\u062f\u0627\u0631 \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647:<\/p>\n<ol>\n<li>P>|t|  &#8211; \u0627\u06cc\u0646 \u0645\u0642\u062f\u0627\u0631 p \u0627\u0633\u062a \u06a9\u0647 \u062f\u0631 \u0628\u0627\u0644\u0627 \u0630\u06a9\u0631 \u06a9\u0631\u062f\u0645 \u0648 \u0628\u0631\u0627\u06cc \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0622\u0632\u0645\u0648\u0646 \u0641\u0631\u0636\u06cc\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062e\u0648\u0627\u0647\u0645 \u06a9\u0631\u062f.  \u0627\u06cc\u0646 \u0645\u0642\u062f\u0627\u0631\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0645\u0627 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u0645 \u0628\u0631\u0627\u06cc \u062a\u0639\u06cc\u06cc\u0646 \u0627\u06cc\u0646\u06a9\u0647 \u0622\u06cc\u0627 \u06cc\u06a9 \u0645\u062a\u063a\u06cc\u0631 \u0631\u0627 \u062f\u0631 \u0627\u06cc\u0646 \u062a\u06a9\u0646\u06cc\u06a9 \u062d\u0630\u0641 \u06af\u0627\u0645 \u0628\u0647 \u06af\u0627\u0645 \u0628\u0647 \u0639\u0642\u0628 \u062d\u0630\u0641 \u06a9\u0646\u06cc\u0645 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u0645.<\/li>\n<li>R-squared &#8211; \u0645\u0639\u06cc\u0627\u0631\u06cc \u06a9\u0647 \u0628\u06cc\u0627\u0646 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u0645\u062f\u0644 \u0645\u0627 \u0686\u0642\u062f\u0631 \u0627\u0632 \u0648\u0627\u0631\u06cc\u0627\u0646\u0633 \u06a9\u0644\u06cc \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u062a\u0648\u0636\u06cc\u062d \u062f\u0647\u062f.<\/li>\n<li>\u0635\u0641\u062a  R-squared &#8211; \u0647\u0645\u0627\u0646 R-squared\u060c \u0627\u0645\u0627 \u0628\u0631\u0627\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0686\u0646\u062f\u06af\u0627\u0646\u0647\u060c \u0627\u06cc\u0646 \u0645\u0642\u062f\u0627\u0631 \u0628\u0631 \u0627\u0633\u0627\u0633 \u062a\u0639\u062f\u0627\u062f \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc\u06cc \u06a9\u0647 \u0628\u0631\u0627\u06cc \u062a\u0648\u0636\u06cc\u062d \u0633\u0637\u062d \u0627\u0636\u0627\u0641\u0647 \u0628\u0631\u0627\u0632\u0634 \u06af\u0646\u062c\u0627\u0646\u062f\u0647 \u0634\u062f\u0647 \u0627\u0646\u062f\u060c \u062c\u0631\u06cc\u0645\u0647 \u0627\u06cc \u0628\u0631\u0627\u06cc \u0622\u0646 \u0627\u0639\u0645\u0627\u0644 \u0645\u06cc \u0634\u0648\u062f.<\/li>\n<\/ol>\n<p>\u0627\u06cc\u0646 \u0628\u062f\u0627\u0646 \u0645\u0639\u0646\u0627 \u0646\u06cc\u0633\u062a \u06a9\u0647 \u0645\u0642\u0627\u062f\u06cc\u0631 \u062f\u06cc\u06af\u0631 \u062f\u0631 \u0627\u06cc\u0646 \u062e\u0631\u0648\u062c\u06cc \u0628\u06cc \u0627\u0631\u0632\u0634 \u0647\u0633\u062a\u0646\u062f\u060c \u0628\u0644\u06a9\u0647 \u0628\u0631\u0639\u06a9\u0633.  \u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u0622\u0646\u0647\u0627 \u0631\u0627 \u0644\u0645\u0633 \u0645\u06cc \u06a9\u0646\u0646\u062f \u0631\u0648\u06cc \u0648\u06cc\u0698\u06af\u06cc\u200c\u0647\u0627\u06cc \u0628\u0627\u0637\u0646\u06cc\u200c\u062a\u0631 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u06a9\u0647 \u0627\u06a9\u0646\u0648\u0646 \u0632\u0645\u0627\u0646 \u06a9\u0627\u0641\u06cc \u0628\u0631\u0627\u06cc \u0648\u0631\u0648\u062f \u0628\u0647 \u0622\u0646 \u0631\u0627 \u0646\u062f\u0627\u0631\u06cc\u0645.  \u0628\u0631\u0627\u06cc \u062a\u0648\u0636\u06cc\u062d \u06a9\u0627\u0645\u0644 \u0622\u0646\u0647\u0627 \u0634\u0645\u0627 \u0631\u0627 \u0628\u0647 \u06cc\u06a9 \u06a9\u062a\u0627\u0628 \u062f\u0631\u0633\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u067e\u06cc\u0634\u0631\u0641\u062a\u0647 \u0645\u0627\u0646\u0646\u062f \u06a9\u062a\u0627\u0628 \u06a9\u0627\u062a\u0646\u0631 \u0645\u0648\u06a9\u0648\u0644 \u0645\u06cc \u06a9\u0646\u0645 <a class=\"amazon-link\" rel=\"nofollow noopener\" target=\"_blank\" href=\"http:\/\/stackabu.se\/applied-linear-regression-models\">\u0645\u062f\u0644 \u0647\u0627\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u06a9\u0627\u0631\u0628\u0631\u062f\u06cc\u060c \u0648\u06cc\u0631\u0627\u06cc\u0634 \u067e\u0646\u062c\u0645.<\/a> \u0628\u0647 \u0647\u0645\u0627\u0646 \u062e\u0648\u0628\u06cc <code>statsmodels<\/code> \u0645\u0633\u062a\u0646\u062f\u0627\u062a.<\/p>\n<pre><code class=\"hljs\">\n\n\n\n\nX = X.drop(<span class=\"hljs-string\">'meandewptm_3'<\/span>, axis=<span class=\"hljs-number\">1<\/span>)\n\n\nmodel = sm.OLS(y, X).fit()\n\nmodel.summary()\n<\/code><\/pre>\n<table class=\"table\">\n<caption>\u0646\u062a\u0627\u06cc\u062c \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 OLS<\/caption>\n<tbody>\n<tr>\n<th>\u0628\u062e\u0634  \u0645\u062a\u063a\u06cc\u0631:<\/th>\n<td>meantempm<\/td>\n<th>    R-squared:         <\/th>\n<td>      0.895<\/td>\n<\/tr>\n<tr>\n<th>\u0645\u062f\u0644:<\/th>\n<td>OLS<\/td>\n<th>    \u0635\u0641\u062a  R-squared:    <\/th>\n<td>      0.893<\/td>\n<\/tr>\n<tr>\n<th>\u0631\u0648\u0634:<\/th>\n<td>\u06a9\u0645\u062a\u0631\u06cc\u0646 \u0645\u0631\u0628\u0639\u0627\u062a<\/td>\n<th>    \u0622\u0645\u0627\u0631 F:       <\/th>\n<td>      490.4<\/td>\n<\/tr>\n<tr>\n<th>\u062a\u0627\u0631\u06cc\u062e:<\/th>\n<td>\u067e\u0646\u062c\u0634\u0646\u0628\u0647\u060c 16 \u0646\u0648\u0627\u0645\u0628\u0631 2017<\/td>\n<th>    \u0645\u0634\u06a9\u0644 (\u0622\u0645\u0627\u0631 F):<\/th>\n<td>    0.00<\/td>\n<\/tr>\n<tr>\n<th>\u0632\u0645\u0627\u0646:<\/th>\n<td>20:55:41<\/td>\n<th>    \u0627\u062d\u062a\u0645\u0627\u0644 \u0648\u0631\u0648\u062f:    <\/th>\n<td>  -2679.2<\/td>\n<\/tr>\n<tr>\n<th>\u0634\u0645\u0627\u0631\u0647 \u0645\u0634\u0627\u0647\u062f\u0627\u062a:<\/th>\n<td>      997<\/td>\n<th>    AIC:               <\/th>\n<td>      5394.<\/td>\n<\/tr>\n<tr>\n<th>\u0628\u0627\u0642\u06cc\u0645\u0627\u0646\u062f\u0647 \u0647\u0627\u06cc Df:<\/th>\n<td>      979<\/td>\n<th>    BIC:               <\/th>\n<td>      5483.<\/td>\n<\/tr>\n<tr>\n<th>\u0645\u062f\u0644 Df:<\/th>\n<td>        17<\/td>\n<th>                     <\/th>\n<td> <\/td>\n<\/tr>\n<tr>\n<th>\u0646\u0648\u0639 \u06a9\u0648\u0648\u0627\u0631\u06cc\u0627\u0646\u0633:<\/th>\n<td>\u063a\u06cc\u0631 \u0645\u0633\u062a\u062d\u06a9\u0645<\/td>\n<th>                     <\/th>\n<td> <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table class=\"table\">\n<tbody>\n<tr>\n<td><\/td>\n<th>\u0636\u0631\u06cc\u0628<\/th>\n<th>std err<\/th>\n<th>\u062a\u06cc<\/th>\n<th>P>|t|<\/th>\n<th>(0.025<\/th>\n<th>0.975)<\/th>\n<\/tr>\n<tr>\n<th>\u067e\u0627\u06cc\u0627\u0646<\/th>\n<td>        1.0771<\/td>\n<td>        0.525<\/td>\n<td>        2.051<\/td>\n<td>  0.041<\/td>\n<td>        0.046<\/td>\n<td>        2.108<\/td>\n<\/tr>\n<tr>\n<th>meantempm_1<\/th>\n<td>        0.1040<\/td>\n<td>        0.287<\/td>\n<td>        0.363<\/td>\n<td>  0.717<\/td>\n<td>      -0.459<\/td>\n<td>        0.667<\/td>\n<\/tr>\n<tr>\n<th>meantempm_2<\/th>\n<td>        0.3513<\/td>\n<td>        0.286<\/td>\n<td>        1.226<\/td>\n<td>  0.220<\/td>\n<td>      -0.211<\/td>\n<td>        0.913<\/td>\n<\/tr>\n<tr>\n<th>meantempm_3<\/th>\n<td>      -0.1082<\/td>\n<td>        0.286<\/td>\n<td>      -0.379<\/td>\n<td>  0.705<\/td>\n<td>      -0.669<\/td>\n<td>        0.452<\/td>\n<\/tr>\n<tr>\n<th>mintempm_1<\/th>\n<td>        0.0809<\/td>\n<td>        0.149<\/td>\n<td>        0.543<\/td>\n<td>  0.587<\/td>\n<td>      -0.211<\/td>\n<td>        0.373<\/td>\n<\/tr>\n<tr>\n<th>mintempm_2<\/th>\n<td>      -0.2371<\/td>\n<td>        0.149<\/td>\n<td>      -1.588<\/td>\n<td>  0.113<\/td>\n<td>      -0.530<\/td>\n<td>        0.056<\/td>\n<\/tr>\n<tr>\n<th>mintempm_3<\/th>\n<td>        0.1520<\/td>\n<td>        0.148<\/td>\n<td>        1.028<\/td>\n<td>  0.304<\/td>\n<td>      -0.138<\/td>\n<td>        0.442<\/td>\n<\/tr>\n<tr>\n<th>meandewptm_1<\/th>\n<td>      -0.0419<\/td>\n<td>        0.137<\/td>\n<td>      -0.305<\/td>\n<td>  0.761<\/td>\n<td>      -0.312<\/td>\n<td>        0.228<\/td>\n<\/tr>\n<tr>\n<th>meandewptm_2<\/th>\n<td>      -0.0121<\/td>\n<td>        0.138<\/td>\n<td>      -0.088<\/td>\n<td>  0.930<\/td>\n<td>      -0.282<\/td>\n<td>        0.258<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_1<\/th>\n<td>      -0.1592<\/td>\n<td>        0.091<\/td>\n<td>      -1.757<\/td>\n<td>  0.079<\/td>\n<td>      -0.337<\/td>\n<td>        0.019<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_2<\/th>\n<td>      -0.0115<\/td>\n<td>        0.090<\/td>\n<td>      -0.127<\/td>\n<td>  0.899<\/td>\n<td>      -0.189<\/td>\n<td>        0.166<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_3<\/th>\n<td>        0.1293<\/td>\n<td>        0.048<\/td>\n<td>        2.705<\/td>\n<td>  0.007<\/td>\n<td>        0.036<\/td>\n<td>        0.223<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_1<\/th>\n<td>        0.3638<\/td>\n<td>        0.084<\/td>\n<td>        4.349<\/td>\n<td>  0.000<\/td>\n<td>        0.200<\/td>\n<td>        0.528<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_2<\/th>\n<td>      -0.0119<\/td>\n<td>        0.088<\/td>\n<td>      -0.135<\/td>\n<td>  0.892<\/td>\n<td>      -0.184<\/td>\n<td>        0.160<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_3<\/th>\n<td>      -0.0266<\/td>\n<td>        0.058<\/td>\n<td>      -0.456<\/td>\n<td>  0.648<\/td>\n<td>      -0.141<\/td>\n<td>        0.088<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_1<\/th>\n<td>        0.5046<\/td>\n<td>        0.146<\/td>\n<td>        3.448<\/td>\n<td>  0.001<\/td>\n<td>        0.217<\/td>\n<td>        0.792<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_2<\/th>\n<td>      -0.2154<\/td>\n<td>        0.147<\/td>\n<td>      -1.465<\/td>\n<td>  0.143<\/td>\n<td>      -0.504<\/td>\n<td>        0.073<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_3<\/th>\n<td>        0.0809<\/td>\n<td>        0.146<\/td>\n<td>        0.556<\/td>\n<td>  0.579<\/td>\n<td>      -0.205<\/td>\n<td>        0.367<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table class=\"table\">\n<tbody>\n<tr>\n<th>Omnibus:<\/th>\n<td>13.254<\/td>\n<th>    \u062f\u0648\u0631\u0628\u06cc\u0646 \u0648\u0627\u062a\u0633\u0648\u0646:     <\/th>\n<td>      2.015<\/td>\n<\/tr>\n<tr>\n<th>\u067e\u0631\u0648\u0628 (Omnibus):<\/th>\n<td>  0.001<\/td>\n<th>    Jarque-Bera (JB):  <\/th>\n<td>    17.105<\/td>\n<\/tr>\n<tr>\n<th>\u06a9\u062c:<\/th>\n<td>-0.163<\/td>\n<th>    \u0645\u0634\u06a9\u0644 (JB):          <\/th>\n<td>0.000193<\/td>\n<\/tr>\n<tr>\n<th>\u06a9\u0648\u0631\u062a\u0648\u0632:<\/th>\n<td>  3.553<\/td>\n<th>    \u0634\u0631\u0637  \u062e\u06cc\u0631         <\/th>\n<td>        286.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u0632\u0645\u0627\u0646 \u0645\u0637\u0627\u0644\u0639\u0647 \u0634\u0645\u0627 \u0648 \u062f\u0631 \u062a\u0644\u0627\u0634 \u0628\u0631\u0627\u06cc \u0646\u06af\u0647 \u062f\u0627\u0634\u062a\u0646 \u0645\u0642\u0627\u0644\u0647 \u062f\u0631 \u0637\u0648\u0644 \u0645\u0639\u0642\u0648\u0644\u060c \u0645\u06cc \u062e\u0648\u0627\u0647\u0645 \u0686\u0631\u062e\u0647 \u0647\u0627\u06cc \u062d\u0630\u0641 \u0628\u0627\u0642\u06cc\u0645\u0627\u0646\u062f\u0647 \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u0647\u0631 \u0645\u062f\u0644 \u062c\u062f\u06cc\u062f \u0631\u0627 \u062d\u0630\u0641 \u06a9\u0646\u0645\u060c \u0645\u0642\u0627\u062f\u06cc\u0631 p \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0631\u062f\u0647 \u0648 \u06a9\u0645\u062a\u0631\u06cc\u0646 \u0645\u0642\u062f\u0627\u0631 \u0642\u0627\u0628\u0644 \u062a\u0648\u062c\u0647 \u0631\u0627 \u062d\u0630\u0641 \u06a9\u0646\u0645.  \u062f\u0631 \u0639\u0648\u0636 \u0645\u0646 \u0645\u0633\u062a\u0642\u06cc\u0645\u0627\u064b \u0628\u0647 \u0622\u062e\u0631\u06cc\u0646 \u0686\u0631\u062e\u0647 \u0645\u06cc \u067e\u0631\u0645 \u0648 \u0645\u062f\u0644 \u0646\u0647\u0627\u06cc\u06cc \u0631\u0627 \u062f\u0631 \u0627\u062e\u062a\u06cc\u0627\u0631 \u0634\u0645\u0627 \u0642\u0631\u0627\u0631 \u0645\u06cc \u062f\u0647\u0645.  \u067e\u0633 \u0627\u0632 \u0647\u0645\u0647\u060c \u0647\u062f\u0641 \u0627\u0635\u0644\u06cc \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u062a\u0648\u0635\u06cc\u0641 \u0622\u0646 \u0628\u0648\u062f process \u0648 \u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u067e\u0634\u062a \u0622\u0646<\/p>\n<p>\u062f\u0631 \u0632\u06cc\u0631 \u062e\u0631\u0648\u062c\u06cc \u0645\u062f\u0644 \u0646\u0647\u0627\u06cc\u06cc \u0631\u0627 \u06a9\u0647 \u0645\u0646 \u0647\u0645\u06af\u0631\u0627 \u06a9\u0631\u062f\u0645 \u0631\u0627 \u062e\u0648\u0627\u0647\u06cc\u062f \u062f\u06cc\u062f \u0631\u0648\u06cc \u067e\u0633 \u0627\u0632 \u0627\u0639\u0645\u0627\u0644 \u062a\u06a9\u0646\u06cc\u06a9 \u062d\u0630\u0641 \u0645\u0639\u06a9\u0648\u0633.  \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u062e\u0631\u0648\u062c\u06cc \u0628\u0628\u06cc\u0646\u06cc\u062f \u06a9\u0647 \u0647\u0645\u0647 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc\u200c\u06a9\u0646\u0646\u062f\u0647\u200c\u0647\u0627\u06cc \u0628\u0627\u0642\u06cc\u200c\u0645\u0627\u0646\u062f\u0647 \u062f\u0627\u0631\u0627\u06cc p-value \u0628\u0647\u200c\u0637\u0648\u0631 \u0642\u0627\u0628\u0644\u200c\u062a\u0648\u062c\u0647\u06cc \u06a9\u0645\u062a\u0631 \u0627\u0632 \u0645\u0627 \u0647\u0633\u062a\u0646\u062f <code>\u0391<\/code> \u0627\u0632 0.05.  \u0686\u06cc\u0632 \u062f\u06cc\u06af\u0631\u06cc \u06a9\u0647 \u0627\u0631\u0632\u0634 \u062a\u0648\u062c\u0647 \u062f\u0627\u0631\u062f \u0645\u0642\u0627\u062f\u06cc\u0631 \u0645\u0631\u0628\u0639 R \u062f\u0631 \u062e\u0631\u0648\u062c\u06cc \u0646\u0647\u0627\u06cc\u06cc \u0627\u0633\u062a.  \u062f\u0648 \u0686\u06cc\u0632 \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0628\u0627\u06cc\u062f \u0628\u0647 \u0622\u0646 \u062a\u0648\u062c\u0647 \u0634\u0648\u062f (1) R-squared \u0648 Adj.  \u0645\u0642\u0627\u062f\u06cc\u0631 R-squared \u0647\u0631 \u062f\u0648 \u0628\u0631\u0627\u0628\u0631 \u0647\u0633\u062a\u0646\u062f \u06a9\u0647 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0645\u062a\u0631\u06cc\u0646 \u062e\u0637\u0631\u06cc \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f \u06a9\u0647 \u0645\u062f\u0644 \u0645\u0627 \u0628\u0627 \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0628\u06cc\u0634 \u0627\u0632 \u062d\u062f \u0628\u0631\u0627\u0632\u0634 \u062f\u0627\u062f\u0647 \u0634\u0648\u062f \u0648 (2) \u0645\u0642\u062f\u0627\u0631 0.894 \u0628\u0647 \u06af\u0648\u0646\u0647 \u0627\u06cc \u062a\u0641\u0633\u06cc\u0631 \u0645\u06cc \u0634\u0648\u062f \u06a9\u0647 \u0645\u062f\u0644 \u0646\u0647\u0627\u06cc\u06cc \u0645\u0627 \u062d\u062f\u0648\u062f 90\u066a \u0627\u0632 \u062a\u063a\u06cc\u06cc\u0631\u0627\u062a \u0645\u0634\u0627\u0647\u062f\u0647 \u0634\u062f\u0647 \u0631\u0627 \u062f\u0631 \u0645\u062a\u063a\u06cc\u0631 \u0646\u062a\u06cc\u062c\u0647 \u062a\u0648\u0636\u06cc\u062d \u0645\u06cc \u062f\u0647\u062f. \u060c &#8220;meantempm&#8221;.<\/p>\n<pre><code class=\"hljs\">model = sm.OLS(y, X).fit()\nmodel.summary()\n<\/code><\/pre>\n<table class=\"table\">\n<caption>\u0646\u062a\u0627\u06cc\u062c \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 OLS<\/caption>\n<tbody>\n<tr>\n<th>\u0628\u062e\u0634  \u0645\u062a\u063a\u06cc\u0631:<\/th>\n<td>meantempm<\/td>\n<th>    \u0645\u0631\u0628\u0639 R:         <\/th>\n<td>      0.894<\/td>\n<\/tr>\n<tr>\n<th>\u0645\u062f\u0644:<\/th>\n<td>OLS<\/td>\n<th>    \u0635\u0641\u062a  R-squared:    <\/th>\n<td>      0.894<\/td>\n<\/tr>\n<tr>\n<th>\u0631\u0648\u0634:<\/th>\n<td>\u06a9\u0645\u062a\u0631\u06cc\u0646 \u0645\u0631\u0628\u0639\u0627\u062a<\/td>\n<th>    \u0622\u0645\u0627\u0631 F:       <\/th>\n<td>      1196.<\/td>\n<\/tr>\n<tr>\n<th>\u062a\u0627\u0631\u06cc\u062e:<\/th>\n<td>\u067e\u0646\u062c\u0634\u0646\u0628\u0647\u060c 16 \u0646\u0648\u0627\u0645\u0628\u0631 2017<\/td>\n<th>    \u0645\u0634\u06a9\u0644 (\u0622\u0645\u0627\u0631 F):<\/th>\n<td>    0.00<\/td>\n<\/tr>\n<tr>\n<th>\u0632\u0645\u0627\u0646:<\/th>\n<td>20:55:47<\/td>\n<th>    \u0627\u062d\u062a\u0645\u0627\u0644 \u0648\u0631\u0648\u062f:    <\/th>\n<td>  -2681.7<\/td>\n<\/tr>\n<tr>\n<th>\u0634\u0645\u0627\u0631\u0647 \u0645\u0634\u0627\u0647\u062f\u0627\u062a:<\/th>\n<td>      997<\/td>\n<th>    AIC:               <\/th>\n<td>      5379.<\/td>\n<\/tr>\n<tr>\n<th>\u0628\u0627\u0642\u06cc\u0645\u0627\u0646\u062f\u0647 \u0647\u0627\u06cc Df:<\/th>\n<td>      989<\/td>\n<th>    BIC:               <\/th>\n<td>      5419.<\/td>\n<\/tr>\n<tr>\n<th>\u0645\u062f\u0644 Df:<\/th>\n<td>          7<\/td>\n<th>                     <\/th>\n<td> <\/td>\n<\/tr>\n<tr>\n<th>\u0646\u0648\u0639 \u06a9\u0648\u0648\u0627\u0631\u06cc\u0627\u0646\u0633:<\/th>\n<td>\u063a\u06cc\u0631 \u0645\u0633\u062a\u062d\u06a9\u0645<\/td>\n<th>                     <\/th>\n<td> <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table class=\"table\">\n<tbody>\n<tr>\n<td><\/td>\n<th>\u0636\u0631\u06cc\u0628<\/th>\n<th>std err<\/th>\n<th>\u062a\u06cc<\/th>\n<th>P>|t|<\/th>\n<th>(0.025<\/th>\n<th>0.975)<\/th>\n<\/tr>\n<tr>\n<th>\u067e\u0627\u06cc\u0627\u0646<\/th>\n<td>        1.1534<\/td>\n<td>        0.411<\/td>\n<td>        2.804<\/td>\n<td>  0.005<\/td>\n<td>        0.346<\/td>\n<td>        1.961<\/td>\n<\/tr>\n<tr>\n<th>mintempm_1<\/th>\n<td>        0.1310<\/td>\n<td>        0.053<\/td>\n<td>        2.458<\/td>\n<td>  0.014<\/td>\n<td>        0.026<\/td>\n<td>        0.236<\/td>\n<\/tr>\n<tr>\n<th>mintempm_2<\/th>\n<td>      -0.0964<\/td>\n<td>        0.037<\/td>\n<td>      -2.620<\/td>\n<td>  0.009<\/td>\n<td>      -0.169<\/td>\n<td>      -0.024<\/td>\n<\/tr>\n<tr>\n<th>mintempm_3<\/th>\n<td>        0.0886<\/td>\n<td>        0.041<\/td>\n<td>        2.183<\/td>\n<td>  0.029<\/td>\n<td>        0.009<\/td>\n<td>        0.168<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_1<\/th>\n<td>      -0.1939<\/td>\n<td>        0.047<\/td>\n<td>      -4.117<\/td>\n<td>  0.000<\/td>\n<td>      -0.286<\/td>\n<td>      -0.101<\/td>\n<\/tr>\n<tr>\n<th>maxdewptm_3<\/th>\n<td>        0.1269<\/td>\n<td>        0.040<\/td>\n<td>        3.191<\/td>\n<td>  0.001<\/td>\n<td>        0.049<\/td>\n<td>        0.205<\/td>\n<\/tr>\n<tr>\n<th>mindewptm_1<\/th>\n<td>        0.3352<\/td>\n<td>        0.051<\/td>\n<td>        6.605<\/td>\n<td>  0.000<\/td>\n<td>        0.236<\/td>\n<td>        0.435<\/td>\n<\/tr>\n<tr>\n<th>maxtempm_1<\/th>\n<td>        0.5506<\/td>\n<td>        0.024<\/td>\n<td>      22.507<\/td>\n<td>  0.000<\/td>\n<td>        0.503<\/td>\n<td>        0.599<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<table class=\"table\">\n<tbody>\n<tr>\n<th>Omnibus:<\/th>\n<td>13.123<\/td>\n<th>    \u062f\u0648\u0631\u0628\u06cc\u0646 \u0648\u0627\u062a\u0633\u0648\u0646:     <\/th>\n<td>      1.969<\/td>\n<\/tr>\n<tr>\n<th>\u067e\u0631\u0648\u0628 (Omnibus):<\/th>\n<td>  0.001<\/td>\n<th>    Jarque-Bera (JB):  <\/th>\n<td>    16.871<\/td>\n<\/tr>\n<tr>\n<th>\u06a9\u062c:<\/th>\n<td>-0.163<\/td>\n<th>    \u0645\u0634\u06a9\u0644 (JB):          <\/th>\n<td>0.000217<\/td>\n<\/tr>\n<tr>\n<th>\u06a9\u0648\u0631\u062a\u0648\u0632:<\/th>\n<td>  3.548<\/td>\n<th>    \u0634\u0631\u0637  \u062e\u06cc\u0631         <\/th>\n<td>        134.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2 id=\"usingscikitlearnslinearregressionmoduletopredicttheweather\"><span class=\"ez-toc-section\" id=\"%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d9%85%d8%a7%da%98%d9%88%d9%84_%d8%b1%da%af%d8%b1%d8%b3%db%8c%d9%88%d9%86_%d8%ae%d8%b7%db%8c_scikit-learn_%d8%a8%d8%b1%d8%a7%db%8c_%d9%be%db%8c%d8%b4_%d8%a8%db%8c%d9%86%db%8c_%d8%a2%d8%a8_%d9%88_%d9%87%d9%88%d8%a7\"><\/span>\u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0645\u0627\u0698\u0648\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc SciKit-Learn \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0622\u0628 \u0648 \u0647\u0648\u0627<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0627\u06a9\u0646\u0648\u0646 \u06a9\u0647 \u0645\u0631\u0627\u062d\u0644 \u0627\u0646\u062a\u062e\u0627\u0628 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u0646\u062f\u0647 \u0647\u0627\u06cc \u0645\u0639\u0646\u06cc \u062f\u0627\u0631 \u0622\u0645\u0627\u0631\u06cc (\u0648\u06cc\u0698\u06af\u06cc \u0647\u0627) \u0631\u0627 \u0637\u06cc \u06a9\u0631\u062f\u0647 \u0627\u06cc\u0645\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0627\u0632 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"http:\/\/scikit-learn.org\/\">SciKit-Learn<\/a> \u0628\u0631\u0627\u06cc \u0627\u06cc\u062c\u0627\u062f \u06cc\u06a9 \u0645\u062f\u0644 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634 \u062a\u0648\u0627\u0646\u0627\u06cc\u06cc \u0622\u0646 \u062f\u0631 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u062f\u0645\u0627\u06cc \u0645\u062a\u0648\u0633\u0637.  SciKit-Learn \u06cc\u06a9 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0628\u0633\u06cc\u0627\u0631 \u062e\u0648\u0628 \u0627\u0633\u062a \u06a9\u0647 \u0628\u0647 \u0637\u0648\u0631 \u06af\u0633\u062a\u0631\u062f\u0647 \u062f\u0631 \u0635\u0646\u0639\u062a \u0648 \u062f\u0627\u0646\u0634\u06af\u0627\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f.  \u06cc\u06a9\u06cc \u0627\u0632 \u0686\u06cc\u0632\u0647\u0627\u06cc\u06cc \u06a9\u0647 \u062f\u0631 \u0645\u0648\u0631\u062f SciKit-Learn \u0628\u0633\u06cc\u0627\u0631 \u0686\u0634\u0645\u06af\u06cc\u0631 \u0627\u0633\u062a \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u06cc\u06a9 API \u0628\u0633\u06cc\u0627\u0631 \u0633\u0627\u0632\u06af\u0627\u0631 \u0627\u0632 &#8220;\u0645\u0646\u0627\u0633\u0628&#8221;\u060c &#8220;\u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc&#8221; \u0648 &#8220;\u062a\u0633\u062a&#8221; \u0631\u0627 \u062f\u0631 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062a\u06a9\u0646\u06cc\u06a9 \u0647\u0627 \u0648 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u0647\u0627\u06cc \u0639\u062f\u062f\u06cc \u062d\u0641\u0638 \u0645\u06cc \u06a9\u0646\u062f \u06a9\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0646 \u0631\u0627 \u0628\u0633\u06cc\u0627\u0631 \u0633\u0627\u062f\u0647 \u0645\u06cc \u06a9\u0646\u062f.  \u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646 \u0637\u0631\u0627\u062d\u06cc API \u0633\u0627\u0632\u06af\u0627\u0631\u060c SciKit-Learn \u0647\u0645\u0686\u0646\u06cc\u0646 \u062f\u0627\u0631\u0627\u06cc \u0686\u0646\u062f\u06cc\u0646 \u0627\u0628\u0632\u0627\u0631 \u0645\u0641\u06cc\u062f \u0628\u0631\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0631\u0627\u06cc\u062c \u062f\u0631 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u067e\u0631\u0648\u0698\u0647\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0627\u0633\u062a.<\/p>\n<p>\u0645\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 SciKit-Learn \u0628\u0631\u0627\u06cc \u062a\u0642\u0633\u06cc\u0645 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u062e\u0648\u062f \u0628\u0647 \u0645\u062c\u0645\u0648\u0639\u0647 \u0647\u0627\u06cc \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0648 \u0622\u0645\u0648\u0632\u0634\u06cc \u0628\u0627 \u0648\u0627\u0631\u062f \u06a9\u0631\u062f\u0646 <code>train_test_split()<\/code> \u062a\u0627\u0628\u0639 \u0627\u0632 <code>sklearn.model_selection<\/code> \u0645\u062f\u0648\u0644.  \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0648 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u0631\u0627 \u0628\u0647 80% \u0622\u0645\u0648\u0632\u0634 \u0648 20% \u062a\u0633\u062a \u062a\u0642\u0633\u06cc\u0645 \u0645\u06cc\u200c\u06a9\u0646\u0645 \u0648 \u06cc\u06a9 <code>random_state<\/code> \u0627\u0632 12 \u062a\u0627 \u0627\u0637\u0645\u06cc\u0646\u0627\u0646 \u062d\u0627\u0635\u0644 \u0634\u0648\u062f \u06a9\u0647 \u0634\u0645\u0627 \u0647\u0645\u0627\u0646 \u0627\u0646\u062a\u062e\u0627\u0628 \u062a\u0635\u0627\u062f\u0641\u06cc \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0627 \u0645\u0627\u0646\u0646\u062f \u0645\u0646 \u062f\u0631\u06cc\u0627\u0641\u062a \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f.  \u0627\u06cc\u0646 <code>random_state<\/code> \u067e\u0627\u0631\u0627\u0645\u062a\u0631 \u0628\u0631\u0627\u06cc \u062a\u06a9\u0631\u0627\u0631\u067e\u0630\u06cc\u0631\u06cc \u0646\u062a\u0627\u06cc\u062c \u0628\u0633\u06cc\u0627\u0631 \u0645\u0641\u06cc\u062f \u0627\u0633\u062a.<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.model_selection <span class=\"hljs-keyword\">import<\/span> train_test_split\n<\/code><\/pre>\n<pre><code class=\"hljs\">\nX = X.drop(<span class=\"hljs-string\">'const'<\/span>, axis=<span class=\"hljs-number\">1<\/span>)\n\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=<span class=\"hljs-number\">0.2<\/span>, random_state=<span class=\"hljs-number\">12<\/span>)\n<\/code><\/pre>\n<p>\u0627\u0642\u062f\u0627\u0645 \u0628\u0639\u062f\u06cc \u0633\u0627\u062e\u062a \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0622\u0645\u0648\u0632\u0634\u06cc \u0627\u0633\u062a.  \u0628\u0631\u0627\u06cc \u0627\u0646\u062c\u0627\u0645 \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u062e\u0648\u0627\u0647\u0645 \u06a9\u0631\u062f import \u0648 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f <code>LinearRegression<\/code> \u06a9\u0644\u0627\u0633 \u0627\u0632 <code>sklearn.linear_model<\/code> \u0645\u062f\u0648\u0644.  \u0647\u0645\u0627\u0646\u0637\u0648\u0631 \u06a9\u0647 \u0642\u0628\u0644\u0627\u064b \u0630\u06a9\u0631 \u0634\u062f\u060c scikit-learn \u0628\u0627 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u06cc\u06a9 \u0646\u06a9\u062a\u0647 \u0645\u0634\u062a\u0631\u06a9\u060c \u0627\u0645\u062a\u06cc\u0627\u0632\u0647\u0627\u06cc \u0645\u0647\u0645\u06cc \u0631\u0627 \u0628\u0647 \u062f\u0633\u062a \u0645\u06cc\u200c\u0622\u0648\u0631\u062f <code>fit()<\/code> \u0648 <code>predict()<\/code> API \u062f\u0631 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062a\u06a9\u0646\u06cc\u06a9 \u0647\u0627\u06cc \u0639\u062f\u062f\u06cc \u062e\u0648\u062f \u06a9\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0631\u0627 \u0628\u0633\u06cc\u0627\u0631 \u06a9\u0627\u0631\u0628\u0631 \u067e\u0633\u0646\u062f \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">from<\/span> sklearn.linear_model <span class=\"hljs-keyword\">import<\/span> LinearRegression\n<\/code><\/pre>\n<pre><code class=\"hljs\">\nregressor = LinearRegression()\n\n\nregressor.fit(X_train, y_train)\n\n\nprediction = regressor.predict(X_test)\n\n\n<span class=\"hljs-keyword\">from<\/span> sklearn.metrics <span class=\"hljs-keyword\">import<\/span> mean_absolute_error, median_absolute_error\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">\"The Explained Variance: %.2f\"<\/span> % regressor.score(X_test, y_test))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">\"The Mean Absolute Error: %.2f degrees celsius\"<\/span> % mean_absolute_error(y_test, prediction))\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">\"The Median Absolute Error: %.2f degrees celsius\"<\/span> % median_absolute_error(y_test, prediction))\n<\/code><\/pre>\n<pre><code class=\"hljs\">The Explained Variance: 0.90\nThe Mean Absolute Error: 2.69 degrees celsius\nThe Median Absolute Error: 2.17 degrees celsius\n<\/code><\/pre>\n<p>\u0647\u0645\u0627\u0646\u0637\u0648\u0631 \u06a9\u0647 \u062f\u0631 \u0686\u0646\u062f \u062e\u0637 \u06a9\u062f \u0628\u0627\u0644\u0627 \u0645\u06cc \u0628\u06cc\u0646\u06cc\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 scikit-learn \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u06cc\u06a9 \u0645\u062f\u0644 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0628\u0633\u06cc\u0627\u0631 \u0633\u0627\u062f\u0647 \u0627\u0633\u062a.  \u0627\u06cc\u0646\u062c\u0627 \u0648\u0627\u0642\u0639\u0627\u064b \u062c\u0627\u06cc\u06cc \u0627\u0633\u062a \u06a9\u0647 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u062f\u0631 \u062a\u0648\u0627\u0646\u0627\u06cc\u06cc \u062e\u0648\u062f \u062f\u0631 \u062a\u0637\u0628\u06cc\u0642 \u0622\u0633\u0627\u0646 \u06cc\u06a9 \u0645\u062f\u0644 \u0648 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u062f\u0631 \u0645\u0648\u0631\u062f \u06cc\u06a9 \u0646\u062a\u06cc\u062c\u0647 \u0645\u0648\u0631\u062f \u0639\u0644\u0627\u0642\u0647 \u0645\u06cc \u062f\u0631\u062e\u0634\u062f.<\/p>\n<p>\u0628\u0631\u0627\u06cc \u0628\u0647 \u062f\u0633\u062a \u0622\u0648\u0631\u062f\u0646 \u062f\u0631\u06a9 \u062a\u0641\u0633\u06cc\u0631\u06cc \u0627\u0632 \u0627\u0639\u062a\u0628\u0627\u0631 \u0645\u062f\u0644 \u0647\u0627 \u0627\u0632 \u0645\u062f\u0644 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f\u0645 <code>score()<\/code> \u062a\u0627\u0628\u0639 \u0628\u0631\u0627\u06cc \u062a\u0639\u06cc\u06cc\u0646 \u0627\u06cc\u0646\u06a9\u0647 \u0645\u062f\u0644 \u0642\u0627\u062f\u0631 \u0628\u0647 \u062a\u0648\u0636\u06cc\u062d \u062d\u062f\u0648\u062f 90 \u062f\u0631\u0635\u062f \u0627\u0632 \u0648\u0627\u0631\u06cc\u0627\u0646\u0633 \u0645\u0634\u0627\u0647\u062f\u0647 \u0634\u062f\u0647 \u062f\u0631 \u0645\u062a\u063a\u06cc\u0631 \u0646\u062a\u06cc\u062c\u0647 \u06cc\u0639\u0646\u06cc \u062f\u0645\u0627\u06cc \u0645\u062a\u0648\u0633\u0637 \u200b\u200b\u0627\u0633\u062a.  \u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646\u060c \u0645\u0646 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f\u0645 <code>mean_absolute_error()<\/code> \u0648 <code>median_absolute_error()<\/code> \u0627\u0632 <code>sklearn.metrics<\/code> \u0645\u0627\u0698\u0648\u0644 \u0628\u0631\u0627\u06cc \u062a\u0639\u06cc\u06cc\u0646 \u0622\u0646 \u0631\u0648\u06cc \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u0645\u0642\u062f\u0627\u0631 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0634\u062f\u0647 \u062d\u062f\u0648\u062f 3 \u062f\u0631\u062c\u0647 \u0633\u0627\u0646\u062a\u06cc\u06af\u0631\u0627\u062f \u062e\u0627\u0645\u0648\u0634 \u0627\u0633\u062a \u0648 \u0646\u06cc\u0645\u06cc \u0627\u0632 \u0645\u0648\u0627\u0642\u0639 \u062d\u062f\u0648\u062f 2 \u062f\u0631\u062c\u0647 \u0633\u0627\u0646\u062a\u06cc\u06af\u0631\u0627\u062f \u062e\u0627\u0645\u0648\u0634 \u0627\u0633\u062a.<\/p>\n<h2 id=\"resources\"><span class=\"ez-toc-section\" id=\"%d9%85%d9%86%d8%a7%d8%a8%d8%b9\"><\/span>\u0645\u0646\u0627\u0628\u0639<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0622\u06cc\u0627 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u060c \u062a\u06a9\u0646\u06cc\u06a9 \u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u0648 \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0645\u0648\u0631\u062f \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0622\u0645\u0648\u0632\u0634 \u0631\u0627 \u06cc\u0627\u062f \u0628\u06af\u06cc\u0631\u06cc\u062f\u061f  \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0686\u0646\u062f \u0645\u0646\u0628\u0639 \u0639\u0627\u0644\u06cc \u0628\u0631\u0627\u06cc \u0634\u0631\u0648\u0639 \u0634\u0645\u0627 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f:<\/p>\n<h2 id=\"conclusion\"><span class=\"ez-toc-section\" id=\"%d9%86%d8%aa%db%8c%d8%ac%d9%87\"><\/span>\u0646\u062a\u06cc\u062c\u0647<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647\u060c \u0631\u0648\u0634 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0627\u0644\u06af\u0648\u0631\u06cc\u062a\u0645 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0631\u06af\u0631\u0633\u06cc\u0648\u0646 \u062e\u0637\u06cc \u0631\u0627 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0645\u06cc\u0627\u0646\u06af\u06cc\u0646 \u062f\u0645\u0627\u06cc \u0647\u0648\u0627 \u062f\u0631 \u0622\u06cc\u0646\u062f\u0647 \u0628\u0631 \u0627\u0633\u0627\u0633 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u062c\u0645\u0639\u200c\u0622\u0648\u0631\u06cc\u200c\u0634\u062f\u0647 \u062f\u0631 \u0645\u0642\u0627\u0644\u0647 \u0642\u0628\u0644\u06cc \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0645.  \u0645\u0646 \u0631\u0648\u0634 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0622\u0646 \u0631\u0627 \u0646\u0634\u0627\u0646 \u062f\u0627\u062f\u0645 <code>statsmodels<\/code> \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u0627\u06cc \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u06a9\u0646\u0646\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0627\u0631\u06cc \u0645\u0639\u0646\u06cc \u062f\u0627\u0631 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0631\u0648\u0634 \u0647\u0627\u06cc \u0622\u0645\u0627\u0631\u06cc \u0635\u062d\u06cc\u062d.  \u0633\u067e\u0633 \u0627\u0632 \u0627\u06cc\u0646 \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0628\u0631\u0627\u06cc \u0628\u0631\u0627\u0632\u0634 \u06cc\u06a9 \u0645\u062f\u0644 \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 \u06cc\u06a9 \u0632\u06cc\u0631 \u0645\u062c\u0645\u0648\u0639\u0647 \u0622\u0645\u0648\u0632\u0634\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 Scikit-Learn \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0631\u062f\u0645. <code>LinearRegression<\/code> \u06a9\u0644\u0627\u0633  \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u062f\u0644 \u0628\u0631\u0627\u0632\u0634 \u0634\u062f\u0647\u060c \u0633\u067e\u0633 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u0645 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0645\u0648\u0631\u062f \u0627\u0646\u062a\u0638\u0627\u0631 \u0631\u0627 \u0628\u0631 \u0627\u0633\u0627\u0633 \u0648\u0631\u0648\u062f\u06cc\u200c\u0647\u0627\u06cc \u06cc\u06a9 \u0632\u06cc\u0631\u0645\u062c\u0645\u0648\u0639\u0647 \u0622\u0632\u0645\u0627\u06cc\u0634\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u06a9\u0646\u0645 \u0648 \u062f\u0642\u062a \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u0631\u0627 \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u06a9\u0646\u0645\u060c \u06a9\u0647 \u0646\u0634\u0627\u0646\u200c\u062f\u0647\u0646\u062f\u0647 \u0645\u0642\u062f\u0627\u0631 \u0645\u0639\u0642\u0648\u0644\u06cc \u0627\u0632 \u062f\u0642\u062a \u0627\u0633\u062a.<\/p>\n<p>\u0645\u0646 \u0645\u06cc \u062e\u0648\u0627\u0647\u0645 \u0627\u0632 \u0634\u0645\u0627 \u0628\u0631\u0627\u06cc \u062e\u0648\u0627\u0646\u062f\u0646 \u0645\u0642\u0627\u0644\u0647 \u0645\u0646 \u062a\u0634\u06a9\u0631 \u06a9\u0646\u0645 \u0648 \u0627\u0645\u06cc\u062f\u0648\u0627\u0631\u0645 \u06a9\u0647 \u0645\u0646\u062a\u0638\u0631 \u0645\u0642\u0627\u0644\u0647 \u0646\u0647\u0627\u06cc\u06cc \u0622\u06cc\u0646\u062f\u0647 \u062f\u0631 \u0627\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u0628\u0627\u0634\u06cc\u062f \u06a9\u0647 \u062f\u0631 \u0622\u0646 \u0631\u0648\u0634 \u0633\u0627\u062e\u062a \u06cc\u06a9 \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u062f\u0645\u0627\u06cc \u0647\u0648\u0627 \u0631\u0627 \u062a\u0648\u0636\u06cc\u062d \u0645\u06cc \u062f\u0647\u0645.<\/p>\n<\/div>\n<p><script>\n                        !function(f,b,e,v,n,t,s)\n                        {if(f.fbq)return;n=f.fbq=function(){n.callMethod?\n                        n.callMethod.apply(n,arguments):n.queue.push(arguments)};\n                        if(!f._fbq)f._fbq=n;n.push=n;n.loaded=!0;n.version='2.0';\n                        n.queue=();t=b.createElement(e);t.async=!0;\n                        t.src=v;s=b.getElementsByTagName(e)(0);\n                        s.parentNode.insertBefore(t,s)}(window, document,'script',\n                 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class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n    <\/div>\n<\/div>\n                \n\n<div class=\"kksr-legend\" style=\"font-size: 24px;\">\n            <span class=\"kksr-muted\">\u0627\u0645\u062a\u06cc\u0627\u0632 \u0634\u0645\u0627 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0637\u0644\u0628<\/span>\n    <\/div>\n    <\/div>\n","protected":false},"excerpt":{"rendered":"<p><span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">\u0632\u0645\u0627\u0646 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u0645\u0637\u0627\u0644\u0639\u0647: <\/span> <span class=\"rt-time\"> 13<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span>\u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u062f\u0627\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 \u0642\u0628\u0644\u06cc \u062f\u0631 \u06cc\u06a9 \u0633\u0631\u06cc \u0633\u0647 \u0642\u0633\u0645\u062a\u06cc \u0627\u0633\u062a \u0631\u0648\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u062f\u0631 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634\u200c\u0628\u06cc\u0646\u06cc \u062f\u0645\u0627\u06cc \u0622\u0628 \u0648 \u0647\u0648\u0627 \u062f\u0631 \u0634\u0647\u0631 \u0644\u06cc\u0646\u06a9\u0644\u0646\u060c \u0646\u0628\u0631\u0627\u0633\u06a9\u0627 \u062f\u0631 \u0627\u06cc\u0627\u0644\u0627\u062a \u0645\u062a\u062d\u062f\u0647 \u0628\u0631 \u0627\u0633\u0627\u0633 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u062c\u0645\u0639\u200c\u0622\u0648\u0631\u06cc\u200c\u0634\u062f\u0647 \u0627\u0632 \u0633\u0631\u0648\u06cc\u0633\u200c\u0647\u0627\u06cc API Weather Underground. \u062f\u0631 \u0627\u0648\u0644\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647\u060c \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u0628\u0631\u0627\u06cc \u067e\u06cc\u0634 \u0628\u06cc\u0646\u06cc \u0622\u0628 \u0648 [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1743,620],"tags":[],"class_list":["post-16656","post","type-post","status-publish","format-standard","hentry","category-python","category-programming"],"acf":[],"_links":{"self":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/16656","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/comments?post=16656"}],"version-history":[{"count":0,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/16656\/revisions"}],"wp:attachment":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media?parent=16656"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/categories?post=16656"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/tags?post=16656"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}