{"id":145251,"date":"2025-06-09T11:25:53","date_gmt":"2025-06-09T05:55:53","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=145251"},"modified":"2025-06-09T12:17:35","modified_gmt":"2025-06-09T06:47:35","slug":"seaborn-ecdf-plot","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/seaborn-ecdf-plot\/","title":{"rendered":"Seaborn ECDF Plot Method"},"content":{"rendered":"<h3>Program 1<\/h3>\n<p><a href=\"https:\/\/drive.google.com\/file\/d\/1ZUYk3dMyfQ1bCYivRYv0gRXq1goCEh8e\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\"><strong>Seaborn Dataset 1<\/strong><\/a><\/p>\n<p><a href=\"https:\/\/drive.google.com\/file\/d\/13TYdifef9ZqzPECkwI83-e_xttXr0Bcq\/view?usp=sharing\" target=\"_blank\" rel=\"noopener\"><strong>Seaborn Dataset 2<\/strong><\/a><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">#ecdf= Empirical Cumulative Distribution Function plot\r\nimport numpy as np\r\nimport pandas as pd\r\nimport matplotlib.pyplot as plt\r\nimport seaborn as sns\r\n\r\n# df_value=pd.read_csv(\"D:\/\/scikit_data\/Billing\/data.csv\")\r\n# print(df_value)\r\n# sns.set_style('dark')\r\n# sns.ecdfplot(x='value',data=df_value)\r\n# plt.show()\r\ndf_value=pd.read_csv(\"D:\/\/scikit_data\/Billing\/tips.csv\")\r\nsns.ecdfplot(x='total_bill',data=df_value,hue='time')\r\nplt.show()\r\n# #print(df_value)\r\n# print(df_value.tip.max())\r\n# print(df_value.tip.min())\r\n# #sns.ecdfplot(y='tip',data=df_value,hue='time')\r\n# #plt.axvline(4,c='black')\r\n# p=sns.ecdfplot(x='tip',data=df_value,hue='day',lw=3)\r\n# #print(type(p))\r\n# p.legend(['Thursday','Firday','Saturday','Sunday'],title=\"Days of Week\",loc=2)\r\n# plt.show()\r\n<\/pre>\n<p>&nbsp;<span hidden class=\"__iawmlf-post-loop-links\" 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07:16:45&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-08-07 07:10:27&quot;,&quot;http_code&quot;:200}],&quot;broken&quot;:false,&quot;last_checked&quot;:{&quot;date&quot;:&quot;2026-08-07 07:10:27&quot;,&quot;http_code&quot;:200},&quot;process&quot;:&quot;done&quot;},{&quot;id&quot;:56,&quot;href&quot;:&quot;https:\\\/\\\/drive.google.com\\\/file\\\/d\\\/13TYdifef9ZqzPECkwI83-e_xttXr0Bcq\\\/view?usp=sharing&quot;,&quot;archived_href&quot;:&quot;http:\\\/\\\/web-wp.archive.org\\\/web\\\/20251205134524\\\/https:\\\/\\\/drive.google.com\\\/file\\\/d\\\/13TYdifef9ZqzPECkwI83-e_xttXr0Bcq\\\/view?usp=sharing&quot;,&quot;redirect_href&quot;:&quot;&quot;,&quot;checks&quot;:[{&quot;date&quot;:&quot;2025-12-10 17:43:55&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2025-12-14 23:49:24&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2025-12-26 04:25:02&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2025-12-29 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13:36:13&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-02 15:54:57&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-06 15:35:48&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-12 10:29:19&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-19 06:16:10&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-06-29 23:21:20&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-07-04 10:49:24&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-07-09 10:30:43&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-07-15 09:48:30&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-07-21 03:18:06&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-07-24 11:44:33&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-08-01 20:40:47&quot;,&quot;http_code&quot;:200},{&quot;date&quot;:&quot;2026-08-05 03:03:23&quot;,&quot;http_code&quot;:200}],&quot;broken&quot;:false,&quot;last_checked&quot;:{&quot;date&quot;:&quot;2026-08-05 03:03:23&quot;,&quot;http_code&quot;:200},&quot;process&quot;:&quot;done&quot;}]\"><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Program 1 Seaborn Dataset 1 Seaborn Dataset 2 #ecdf= Empirical Cumulative Distribution Function plot import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns # df_value=pd.read_csv(&#8220;D:\/\/scikit_data\/Billing\/data.csv&#8221;) # print(df_value)&#46;&#46;&#46;<\/p>\n","protected":false},"author":581,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[36],"tags":[33235,34351,34352,12666,34349,33219,33220,34350],"class_list":["post-145251","post","type-post","status-publish","format-standard","hentry","category-machine-learning","tag-ecdf-plot-in-seaborn","tag-ecdf-plot-method","tag-empirical-cumulative-distribution-function-plot","tag-seaborn","tag-seaborn-ecdf-plot-method","tag-seaborn-practical","tag-seaborn-program","tag-seaborn-program-on-ecdf-plot"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Seaborn ECDF Plot Method - DataFlair<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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