{"id":4303,"date":"2023-07-12T03:45:46","date_gmt":"2023-07-12T03:45:46","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d0%b3%d0%b8%d1%81%d1%82%d0%be%d0%b3%d1%80%d0%b0%d0%bc%d0%bc%d0%b0-pandas-%d1%82%d0%be%d0%bf-10\/"},"modified":"2023-07-12T03:45:46","modified_gmt":"2023-07-12T03:45:46","slug":"%d0%b3%d0%b8%d1%81%d1%82%d0%be%d0%b3%d1%80%d0%b0%d0%bc%d0%bc%d0%b0-pandas-%d1%82%d0%be%d0%bf-10","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d0%b3%d0%b8%d1%81%d1%82%d0%be%d0%b3%d1%80%d0%b0%d0%bc%d0%bc%d0%b0-pandas-%d1%82%d0%be%d0%bf-10\/","title":{"rendered":"Pandas: \u043a\u0430\u043a \u0441\u043e\u0437\u0434\u0430\u0442\u044c \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0443 \u0434\u043b\u044f \u0432\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 10 \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0412\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u044f \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u044b \u0432 pandas, \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u0432\u043a\u043b\u044e\u0447\u0430\u0435\u0442 \u0442\u043e\u043b\u044c\u043a\u043e 10 \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0447\u0430\u0441\u0442\u043e \u0432\u0441\u0442\u0440\u0435\u0447\u0430\u044e\u0449\u0438\u0445\u0441\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0435:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n<span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n\n<span style=\"color: #008080;\">#find values with top 10 occurrences in 'my_column'\n<\/span>top_10 = (df[' <span style=\"color: #ff0000;\">my_column<\/span> ']. <span style=\"color: #3366ff;\">value_counts<\/span> ()). <span style=\"color: #3366ff;\">iloc<\/span> [:10]\n\n<span style=\"color: #008080;\">#create bar chart to visualize top 10 values\n<\/span>top_10. <span style=\"color: #3366ff;\">plot<\/span> (kind='bar')\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044d\u0442\u043e\u0442 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440. \u0421\u043e\u0437\u0434\u0430\u0439\u0442\u0435 \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0443 \u0432 Pandas \u0434\u043b\u044f \u0432\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 10 \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 DataFrame pandas, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u0442 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044e \u043e \u043d\u0430\u0437\u0432\u0430\u043d\u0438\u0438 \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u0438 \u043e\u0447\u043a\u0430\u0445, \u043d\u0430\u0431\u0440\u0430\u043d\u043d\u044b\u0445 500 \u0440\u0430\u0437\u043d\u044b\u043c\u0438 \u0431\u0430\u0441\u043a\u0435\u0442\u0431\u043e\u043b\u0438\u0441\u0442\u0430\u043c\u0438:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">from<\/span> string <span style=\"color: #008000;\">import<\/span> ascii_uppercase\n<span style=\"color: #008000;\">import<\/span> random\n<span style=\"color: #008000;\">from<\/span> random <span style=\"color: #008000;\">import<\/span> choice\n\n<span style=\"color: #008080;\">#make this example reproducible\n<\/span>random. <span style=\"color: #3366ff;\">seeds<\/span> (1)\nn.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (1)\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': [choice(ascii_uppercase) <span style=\"color: #008000;\">for<\/span> _ <span style=\"color: #008000;\">in<\/span> range(500)],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">uniform<\/span> (0, 20, 500)})\n\n<span style=\"color: #008080;\">#view first five rows of DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">df.head<\/span> ())\n\n  team points\n0 E 8.340440\n1 S 14.406490\n2 Z 0.002287\n3 Y 6.046651\n4 C 2.935118<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041c\u044b \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u044f \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u044b, \u043e\u0442\u043e\u0431\u0440\u0430\u0436\u0430\u044e\u0449\u0435\u0439 10 \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0447\u0430\u0441\u0442\u043e \u0432\u0441\u0442\u0440\u0435\u0447\u0430\u044e\u0449\u0438\u0445\u0441\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 <strong>\u043a\u043e\u043c\u0430\u043d\u0434\u044b<\/strong> :<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n\n<span style=\"color: #008080;\">#find teams with top 10 occurrences\n<\/span>top_10_teams = (df[' <span style=\"color: #ff0000;\">team<\/span> ']. <span style=\"color: #3366ff;\">value_counts<\/span> ()).[:10]\n\n<span style=\"color: #008080;\">#create bar chart of top 10 teams\n<\/span>top_10_teams. <span style=\"color: #3366ff;\">plot<\/span> (kind=' <span style=\"color: #ff0000;\">bar<\/span> ')<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-33884 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/bartop1.jpg\" alt=\"\" width=\"511\" height=\"379\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\u0413\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0430 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u0442 \u0442\u043e\u043b\u044c\u043a\u043e \u043d\u0430\u0437\u0432\u0430\u043d\u0438\u044f 10 \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0447\u0430\u0441\u0442\u043e \u0432\u0441\u0442\u0440\u0435\u0447\u0430\u044e\u0449\u0438\u0445\u0441\u044f \u043a\u043e\u043c\u0430\u043d\u0434.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041f\u043e \u043e\u0441\u0438 X \u043e\u0442\u043e\u0431\u0440\u0430\u0436\u0430\u0435\u0442\u0441\u044f \u043d\u0430\u0437\u0432\u0430\u043d\u0438\u0435 \u043a\u043e\u043c\u0430\u043d\u0434\u044b, \u0430 \u043f\u043e \u043e\u0441\u0438 Y \u2014 \u0447\u0430\u0441\u0442\u043e\u0442\u0430.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u043c\u044b \u0442\u0430\u043a\u0436\u0435 \u043c\u043e\u0436\u0435\u043c \u043d\u0430\u0441\u0442\u0440\u043e\u0438\u0442\u044c \u0441\u044e\u0436\u0435\u0442, \u0447\u0442\u043e\u0431\u044b \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0435\u0433\u043e \u0431\u043e\u043b\u0435\u0435 \u044d\u0441\u0442\u0435\u0442\u0438\u0447\u043d\u044b\u043c:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n\n<span style=\"color: #008080;\">#find teams with top 10 occurrences\n<\/span>top_10_teams = (df[' <span style=\"color: #ff0000;\">team<\/span> ']. <span style=\"color: #3366ff;\">value_counts<\/span> ()).[:10]\n\n<span style=\"color: #008080;\">#create bar chart of top 10 teams\n<\/span>top_10_teams. <span style=\"color: #3366ff;\">plot<\/span> (kind=' <span style=\"color: #ff0000;\">bar<\/span> ', edgecolor=' <span style=\"color: #ff0000;\">black<\/span> ', rot=0)\n\n<span style=\"color: #008080;\">#add axis labels<\/span><\/strong>\n<strong>plt. <span style=\"color: #3366ff;\">xlabel<\/span> (' <span style=\"color: #ff0000;\">Team<\/span> ')\nplt. <span style=\"color: #3366ff;\">ylabel<\/span> (' <span style=\"color: #ff0000;\">Frequency<\/span> ')\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-33885 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/bartop2.jpg\" alt=\"\" width=\"522\" height=\"404\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442 <strong>\u0446\u0432\u0435\u0442\u0430 \u043a\u0440\u0430\u044f<\/strong> \u0434\u043e\u0431\u0430\u0432\u0438\u043b \u0447\u0435\u0440\u043d\u0443\u044e \u0440\u0430\u043c\u043a\u0443 \u0432\u043e\u043a\u0440\u0443\u0433 \u043a\u0430\u0436\u0434\u043e\u0439 \u043f\u043e\u043b\u043e\u0441\u044b, \u0430 \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442 <strong>rot<\/strong> \u043f\u043e\u0432\u0435\u0440\u043d\u0443\u043b \u043c\u0435\u0442\u043a\u0438 \u043f\u043e \u043e\u0441\u0438 X \u043d\u0430 90 \u0433\u0440\u0430\u0434\u0443\u0441\u043e\u0432, \u0447\u0442\u043e\u0431\u044b \u0438\u0445 \u0431\u044b\u043b\u043e \u043b\u0435\u0433\u0447\u0435 \u0447\u0438\u0442\u0430\u0442\u044c.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0440\u0435\u0441\u0443\u0440\u0441\u044b<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0445 \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0430\u0445 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c \u0434\u0440\u0443\u0433\u0438\u0435 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u043d\u044b\u0435 \u0437\u0430\u0434\u0430\u0447\u0438 \u0432 pandas:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ru\/\u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0430-\u043f\u0430\u043d\u0434-\u0441-\u043d\u0430\u043a\u043e\u043f\u043b\u0435\u043d\u0438\u0435\u043c\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u043a\u0430\u043a \u0441\u043e\u0437\u0434\u0430\u0442\u044c \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0443 \u0441 \u043d\u0430\u043a\u043e\u043f\u043b\u0435\u043d\u0438\u0435\u043c<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u043f\u0430\u043d\u0434\u044b-\u0430\u043d\u043d\u043e\u0442\u0438\u0440\u0443\u044e\u0442-\u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0443\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u043a\u0430\u043a \u0430\u043d\u043d\u043e\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0441\u0442\u043e\u043b\u0431\u0446\u044b \u043d\u0430 \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0435<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u043c\u043d\u043e\u0433\u043e\u0441\u0442\u043e\u043b\u0431\u0447\u0430\u0442\u0430\u044f-\u0434\u0438\u0430\u0433\u0440\u0430\u043c\u043c\u0430-pandas\/\" target=\"_blank\" rel=\"noopener\">Pandas: \u043a\u0430\u043a \u043f\u043e\u0441\u0442\u0440\u043e\u0438\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u043d\u0430 \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0435<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0412\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0441\u043e\u0437\u0434\u0430\u043d\u0438\u044f \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u044b \u0432 pandas, \u043a\u043e\u0442\u043e\u0440\u0430\u044f \u0432\u043a\u043b\u044e\u0447\u0430\u0435\u0442 \u0442\u043e\u043b\u044c\u043a\u043e 10 \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0447\u0430\u0441\u0442\u043e \u0432\u0441\u0442\u0440\u0435\u0447\u0430\u044e\u0449\u0438\u0445\u0441\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u043c \u0441\u0442\u043e\u043b\u0431\u0446\u0435: import pandas as pd import matplotlib. pyplot as plt #find values with top 10 occurrences in &#8216;my_column&#8217; top_10 = (df[&#8216; my_column &#8216;]. value_counts ()). iloc [:10] #create bar chart to visualize top 10 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-4303","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pandas: \u043a\u0430\u043a \u0441\u043e\u0437\u0434\u0430\u0442\u044c \u0433\u0438\u0441\u0442\u043e\u0433\u0440\u0430\u043c\u043c\u0443 \u0434\u043b\u044f \u0432\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 10 \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439<\/title>\n<meta name=\"description\" content=\"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, 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