{"id":893,"date":"2023-07-28T09:32:44","date_gmt":"2023-07-28T09:32:44","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%bf%d0%b5%d1%80%d0%b5%d1%82%d0%b2%d0%be%d1%80%d0%b8%d1%82%d0%b8-%d1%80%d1%8f%d0%b4%d0%be%d0%ba-%d0%bd%d0%b0-%d0%bf%d0%bb%d0%b0%d0%b2%d0%b0%d1%8e%d1%87%d0%b8%d1%85-%d0%bf%d0%b0%d0%bd%d0%b4\/"},"modified":"2023-07-28T09:32:44","modified_gmt":"2023-07-28T09:32:44","slug":"%d0%bf%d0%b5%d1%80%d0%b5%d1%82%d0%b2%d0%be%d1%80%d0%b8%d1%82%d0%b8-%d1%80%d1%8f%d0%b4%d0%be%d0%ba-%d0%bd%d0%b0-%d0%bf%d0%bb%d0%b0%d0%b2%d0%b0%d1%8e%d1%87%d0%b8%d1%85-%d0%bf%d0%b0%d0%bd%d0%b4","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%bf%d0%b5%d1%80%d0%b5%d1%82%d0%b2%d0%be%d1%80%d0%b8%d1%82%d0%b8-%d1%80%d1%8f%d0%b4%d0%be%d0%ba-%d0%bd%d0%b0-%d0%bf%d0%bb%d0%b0%d0%b2%d0%b0%d1%8e%d1%87%d0%b8%d1%85-%d0%bf%d0%b0%d0%bd%d0%b4\/","title":{"rendered":"\u042f\u043a \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0440\u044f\u0434\u043a\u0438 \u043d\u0430 float \u0443 pandas"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043c\u0435\u0442\u043e\u0434\u0438, \u0449\u043e\u0431 \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0440\u044f\u0434\u043e\u043a \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0438\u0439 \u0443 pandas:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u0421\u043f\u043e\u0441\u0456\u0431 1: \u041f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0435\u043d\u043d\u044f \u043e\u0434\u043d\u043e\u0433\u043e \u0441\u0442\u043e\u0432\u043f\u0446\u044f \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0438\u0439<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert \"assists\" column from string to float<\/span>\ndf[' <span style=\"color: #ff0000;\">assists<\/span> '] = df[' <span style=\"color: #ff0000;\">assists<\/span> ']. <span style=\"color: #3366ff;\">astype<\/span> (float)\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u0421\u043f\u043e\u0441\u0456\u0431 2. \u041f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0456\u0442\u044c \u043a\u0456\u043b\u044c\u043a\u0430 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0443<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert both \"assists\" and \"rebounds\" from strings to floats\n<\/span>df[[' <span style=\"color: #ff0000;\">assists<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']] = df[[' <span style=\"color: #ff0000;\">assists<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']]. <span style=\"color: #3366ff;\">astype<\/span> (float)<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u0421\u043f\u043e\u0441\u0456\u0431 3: \u041f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0435\u043d\u043d\u044f \u0432\u0441\u0456\u0445 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0443<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert all columns to float\n<\/span>df = df. <span style=\"color: #3366ff;\">astype<\/span> (float)<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u043f\u043e\u043a\u0430\u0437\u0443\u044e\u0442\u044c, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043a\u043e\u0436\u0435\u043d \u043c\u0435\u0442\u043e\u0434 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456 \u0437 \u0442\u0430\u043a\u0438\u043c\u0438 pandas DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n<span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">points<\/span> ': [np.nan, 12, 15, 14, 19],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': ['5', np.nan, '7', '9', '12'],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': ['11', '8', '10', '6', '6']})  \n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n \tpoints assists rebounds\n0 NaN 5.0 11\n1 12.0 NaN 8\n2 15.0 7.0 10\n3 14.0 9.0 6\n4 19.0 12.0 6\n\n<span style=\"color: #008080;\">#view column data types\n<\/span>df. <span style=\"color: #3366ff;\">dtypes\n\n<span style=\"color: #000000;\">float64 points\nassists object\nrebound object\ndtype:object<\/span><\/span><\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 1: \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0435\u043d\u043d\u044f \u043e\u0434\u043d\u043e\u0433\u043e \u0441\u0442\u043e\u0432\u043f\u0446\u044f \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0435<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 <strong>\u0434\u043e\u043f\u043e\u043c\u0456\u0436\u043d\u0438\u0439<\/strong> \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u0456\u0437 \u0440\u044f\u0434\u043a\u0430 \u043d\u0430 \u0447\u0438\u0441\u043b\u043e \u0437 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u043e\u044e \u0442\u043e\u0447\u043a\u043e\u044e:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert \"assists\" from string to float<\/span>\ndf[' <span style=\"color: #ff0000;\">assists<\/span> '] = df[' <span style=\"color: #ff0000;\">assists<\/span> ']. <span style=\"color: #3366ff;\">astype<\/span> (float)\n\n<span style=\"color: #008080;\">#view column data types<\/span>\ndf. <span style=\"color: #3366ff;\">dtypes<\/span>\n\nfloat64 points\nassist float64\nrebound object\ndtype:object\n<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 2. \u041f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0456\u0442\u044c \u043a\u0456\u043b\u044c\u043a\u0430 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u043d\u0430 float<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 <strong>\u0434\u043e\u043f\u043e\u043c\u0456\u0436\u043d\u0456<\/strong> \u0442\u0430 <strong>\u0432\u0456\u0434\u0441\u043a\u043e\u0447\u0435\u043d\u0456<\/strong> \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0437 \u0440\u044f\u0434\u043a\u0456\u0432 \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0456:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert both \"assists\" and \"rebounds\" from strings to floats\n<\/span>df[[' <span style=\"color: #ff0000;\">assists<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']] = df[[' <span style=\"color: #ff0000;\">assists<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']]. <span style=\"color: #3366ff;\">astype<\/span> (float)\n\n<span style=\"color: #008080;\">#view column data types\n<\/span>df. <span style=\"color: #3366ff;\">dtypes\n\n<\/span>float64 points\nassist float64\nrebounds float64\ndtype:object\n<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 3: \u041f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0432\u0441\u0456 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u043d\u0430 float<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0432\u0441\u0456 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0432 DataFrame \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0456 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert all columns to float\n<\/span>df = df. <span style=\"color: #3366ff;\">astype<\/span> (float)\n\n<span style=\"color: #008080;\">#view column data types\n<\/span>df. <span style=\"color: #3366ff;\">dtypes\n\n<\/span>float64 points\nassist float64\nrebounds float64\ndtype:object<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\u0411\u043e\u043d\u0443\u0441: \u043a\u043e\u043d\u0432\u0435\u0440\u0442\u0443\u0439\u0442\u0435 \u0440\u044f\u0434\u043e\u043a \u0443 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0437 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u043e\u044e \u0442\u043e\u0447\u043a\u043e\u044e \u0442\u0430 \u0437\u0430\u043f\u043e\u0432\u043d\u044e\u0439\u0442\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f NaN<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 <strong>\u0434\u043e\u043f\u043e\u043c\u0456\u0436\u043d\u0438\u0439<\/strong> \u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c \u0456\u0437 \u0440\u044f\u0434\u043a\u0430 \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0443 \u0432\u0435\u043b\u0438\u0447\u0438\u043d\u0443 \u0442\u0430 \u043e\u0434\u043d\u043e\u0447\u0430\u0441\u043d\u043e \u0434\u043e\u043f\u043e\u0432\u043d\u0438\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f NaN \u043d\u0443\u043b\u044f\u043c\u0438:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#convert \"assists\" from string to float and fill in NaN values with zeros\n<\/span>df[' <span style=\"color: #ff0000;\">assists<\/span> '] = df[' <span style=\"color: #ff0000;\">assists<\/span> ']. <span style=\"color: #3366ff;\">astype<\/span> (float). <span style=\"color: #3366ff;\">fillna<\/span> (0)\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #000000;\">df\n<\/span>\n        points assists rebounds\n0 NaN 5.0 11\n1 12.0 0.0 8\n2 15.0 7.0 10\n3 14.0 9.0 6\n4 19.0 12.0 6<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>\u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h2>\n<p> \u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0445 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0430\u0445 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0456\u043d\u0448\u0456 \u0442\u0438\u043f\u043e\u0432\u0456 \u0437\u0430\u0432\u0434\u0430\u043d\u043d\u044f \u0432 pandas:<\/p>\n<p> <a href=\"https:\/\/statorials.org\/uk\/pandas-\u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u044e\u0454-\u043e\u0431\u0454\u043a\u0442-\u043d\u0430-int\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u042f\u043a \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u043e\u0431\u2019\u0454\u043a\u0442 \u043d\u0430 \u0446\u0456\u043b\u0435 \u0447\u0438\u0441\u043b\u043e<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/pandas-\u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u044e\u0454-float-\u043d\u0430-int\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u042f\u043a \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0447\u0438\u0441\u043b\u0430 \u0437 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u043e\u044e \u0442\u043e\u0447\u043a\u043e\u044e \u043d\u0430 \u0446\u0456\u043b\u0456<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u0441\u0442\u043e\u0432\u043f\u0435\u0446\u044c-pandas-\u0434\u043e-\u043c\u0430\u0441\u0438\u0432\u0443-numpy\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u042f\u043a \u043a\u043e\u043d\u0432\u0435\u0440\u0442\u0443\u0432\u0430\u0442\u0438 \u043f\u0435\u0432\u043d\u0456 \u0441\u0442\u043e\u0432\u043f\u0446\u0456 \u0432 \u043c\u0430\u0441\u0438\u0432 NumPy<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043c\u0435\u0442\u043e\u0434\u0438, \u0449\u043e\u0431 \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0440\u044f\u0434\u043e\u043a \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0438\u0439 \u0443 pandas: \u0421\u043f\u043e\u0441\u0456\u0431 1: \u041f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0435\u043d\u043d\u044f \u043e\u0434\u043d\u043e\u0433\u043e \u0441\u0442\u043e\u0432\u043f\u0446\u044f \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0438\u0439 #convert &#8220;assists&#8221; column from string to float df[&#8216; assists &#8216;] = df[&#8216; assists &#8216;]. astype (float) \u0421\u043f\u043e\u0441\u0456\u0431 2. \u041f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0456\u0442\u044c \u043a\u0456\u043b\u044c\u043a\u0430 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u043d\u0430 \u043f\u043b\u0430\u0432\u0430\u044e\u0447\u0443 #convert both &#8220;assists&#8221; and &#8220;rebounds&#8221; from strings to floats df[[&#8216; assists &#8216;, &#8216; [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u042f\u043a \u043f\u0435\u0440\u0435\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0440\u044f\u0434\u043a\u0438 \u043d\u0430 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