

{"id":145240,"date":"2025-06-06T12:24:07","date_gmt":"2025-06-06T06:54:07","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=145240"},"modified":"2025-06-06T12:24:07","modified_gmt":"2025-06-06T06:54:07","slug":"histogram-plot-in-seaborn","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/","title":{"rendered":"Histogram Plot in Seaborn"},"content":{"rendered":"<h3>Program 1<\/h3>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">import seaborn as sns\r\nimport matplotlib.pyplot as plt\r\nimport pandas as pd\r\nimport numpy as np\r\n\r\n# Example DataFrame\r\ndf = pd.DataFrame({\"marks\": np.random.randint(40, 100, size=200)})\r\n#print(df['marks'])\r\nsns.histplot(df['marks'], bins=10, kde=True, color='orange')\r\nplt.title(\"Student Marks Distribution\")\r\nplt.xlabel(\"Marks\")\r\nplt.ylabel(\"Number of Students\")\r\nplt.show()<\/pre>\n<h3>Program 2<\/h3>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">import seaborn as sns\r\nimport matplotlib.pyplot as plt\r\nimport pandas as pd\r\nimport numpy as np\r\n# Sample data\r\ndf = sns.load_dataset('tips')  # Built-in dataset\r\n\r\n# print(df.head())\r\n\r\n# print(df.isnull().sum())\r\n# print(df.shape)\r\n#print(df.info())\r\n\r\n#Create histogram\r\n# sns.histplot(df['total_bill'], bins=10, kde=True, color='skyblue')\r\nsns.histplot(df['tip'], bins=10, kde=True, color='skyblue')\r\n# # Add title and labels\r\n# plt.title('Distribution of Total Bill')\r\n# plt.xlabel('Total Bill')\r\n# plt.ylabel('Frequency')\r\n\r\n# # Show plot\r\nplt.show()\r\n\r\n\r\n#df_tips=pd.read_csv(\"D:\/\/scikit_data\/Billing\/tips.csv\")\r\n<\/pre>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Program 1 import seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np # Example DataFrame df = pd.DataFrame({&#8220;marks&#8221;: np.random.randint(40, 100, size=200)}) #print(df[&#8216;marks&#8217;]) sns.histplot(df[&#8216;marks&#8217;], bins=10, kde=True, color=&#8217;orange&#8217;) plt.title(&#8220;Student Marks&#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":[34347,34344,34348,12666,34343,34345,33219,33220,34346,34326],"class_list":["post-145240","post","type-post","status-publish","format-standard","hentry","category-machine-learning","tag-histogram-plot","tag-histogram-plot-in-seaborn","tag-histogram-plot-method","tag-seaborn","tag-seaborn-histogram-plot","tag-seaborn-histplot-method","tag-seaborn-practical","tag-seaborn-program","tag-seaborn-program-on-histogram-plot","tag-seaborn-tutorial"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Histogram Plot in Seaborn - DataFlair<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Histogram Plot in Seaborn - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Program 1 import seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np # Example DataFrame df = pd.DataFrame({&quot;marks&quot;: np.random.randint(40, 100, size=200)}) #print(df[&#039;marks&#039;]) sns.histplot(df[&#039;marks&#039;], bins=10, kde=True, color=&#039;orange&#039;) plt.title(&quot;Student Marks&#046;&#046;&#046;\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/\" \/>\n<meta property=\"og:site_name\" content=\"DataFlair\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataFlairWS\/\" \/>\n<meta property=\"article:published_time\" content=\"2025-06-06T06:54:07+00:00\" \/>\n<meta name=\"author\" content=\"DataFlair Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:site\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"DataFlair Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Histogram Plot in Seaborn - DataFlair","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/","og_locale":"en_US","og_type":"article","og_title":"Histogram Plot in Seaborn - DataFlair","og_description":"Program 1 import seaborn as sns import matplotlib.pyplot as plt import pandas as pd import numpy as np # Example DataFrame df = pd.DataFrame({\"marks\": np.random.randint(40, 100, size=200)}) #print(df['marks']) sns.histplot(df['marks'], bins=10, kde=True, color='orange') plt.title(\"Student Marks&#46;&#46;&#46;","og_url":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2025-06-06T06:54:07+00:00","author":"DataFlair Team","twitter_card":"summary_large_image","twitter_creator":"@DataFlairWS","twitter_site":"@DataFlairWS","twitter_misc":{"Written by":"DataFlair Team","Est. reading time":"1 minute"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445"},"headline":"Histogram Plot in Seaborn","datePublished":"2025-06-06T06:54:07+00:00","mainEntityOfPage":{"@id":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/"},"wordCount":8,"commentCount":0,"publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"keywords":["histogram plot","histogram plot in seaborn","histogram plot method","seaborn","seaborn histogram plot","seaborn histplot method","seaborn practical","seaborn program","seaborn program on histogram plot","seaborn tutorial"],"articleSection":["Machine Learning Tutorials"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/","url":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/","name":"Histogram Plot in Seaborn - DataFlair","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/#website"},"datePublished":"2025-06-06T06:54:07+00:00","breadcrumb":{"@id":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/data-flair.training\/blogs\/histogram-plot-in-seaborn\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Blog Home","item":"https:\/\/data-flair.training\/blogs\/"},{"@type":"ListItem","position":2,"name":"Machine Learning Tutorials","item":"https:\/\/data-flair.training\/blogs\/category\/machine-learning\/"},{"@type":"ListItem","position":3,"name":"Histogram Plot in Seaborn"}]},{"@type":"WebSite","@id":"https:\/\/data-flair.training\/blogs\/#website","url":"https:\/\/data-flair.training\/blogs\/","name":"DataFlair","description":"Learn Today. Lead Tomorrow.","publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/data-flair.training\/blogs\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/data-flair.training\/blogs\/#organization","name":"DataFlair","url":"https:\/\/data-flair.training\/blogs\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/logo\/image\/","url":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/07\/Data-Flair.png","contentUrl":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2016\/07\/Data-Flair.png","width":106,"height":48,"caption":"DataFlair"},"image":{"@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/www.facebook.com\/DataFlairWS\/","https:\/\/x.com\/DataFlairWS","https:\/\/www.linkedin.com\/company\/dataflair-web-services-pvt-ltd\/","https:\/\/www.youtube.com\/user\/DataFlairWS"]},{"@type":"Person","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445","name":"DataFlair Team","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/2302ebc438084d2f1f993edc1996a0aae01332e81f3227cba8df0c48ec010ca4?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/2302ebc438084d2f1f993edc1996a0aae01332e81f3227cba8df0c48ec010ca4?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/2302ebc438084d2f1f993edc1996a0aae01332e81f3227cba8df0c48ec010ca4?s=96&d=mm&r=g","caption":"DataFlair Team"},"description":"DataFlair Team provides high-impact content on programming, Java, Python, C++, DSA, AI, ML, data Science, Android, Flutter, MERN, Web Development, and technology. We make complex concepts easy to grasp, helping learners of all levels succeed in their tech careers.","url":"https:\/\/data-flair.training\/blogs\/author\/dfteam6\/"}]}},"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/145240","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/users\/581"}],"replies":[{"embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/comments?post=145240"}],"version-history":[{"count":2,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/145240\/revisions"}],"predecessor-version":[{"id":145250,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/posts\/145240\/revisions\/145250"}],"wp:attachment":[{"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/media?parent=145240"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/categories?post=145240"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/data-flair.training\/blogs\/wp-json\/wp\/v2\/tags?post=145240"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}