{"id":145200,"date":"2025-06-02T12:25:15","date_gmt":"2025-06-02T06:55:15","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=145200"},"modified":"2025-06-02T12:25:15","modified_gmt":"2025-06-02T06:55:15","slug":"pandas-dataframe-aggregate-method","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/","title":{"rendered":"Pandas DataFrame aggregate() Method"},"content":{"rendered":"

Program 1<\/h3>\n
# Advance Data Analysis \r\n#Aggrigate Functions \r\n# max(),min(),avg(),count(),sum(),mod(),mean()\r\n\r\nimport pandas as pd\r\nproduct=[('Limca',20,'Sanchi'),('Frooti',25,'Amul'),('Milk',10,'BK'),('Water',20,'BK'),\r\n       ('Limca',25,'AK'),('Frooti',20,'SK'),('Milk',28,'BK'),('Water',30,'Sanchi'),\r\n        ('Limca',27,'Sanchi'),('Frooti',29,'AK'),('Milk',25,'Amul'),('Water',45,'Sanchi'),\r\n        ('Water',29,'Amul'),('Limca',40,'DK'),('Frooti',12,'Amul'),('Water',40,'Sanchi')\r\n        ]\r\n#print(product)\r\ndf=pd.DataFrame(product,columns=['Product Name','Price','Distributor'])\r\n#print(df)\r\ndf1=df.groupby('Product Name')\r\n# for name,rows in df1:\r\n#     print(name)\r\n#     print(rows)\r\n#print(df1['Price'].agg(['max','min']))\r\n#print(df1['Price'].agg(['count']))\r\n#print(df1['Price'].agg(['sum']))\r\nprint(df1['Price'].agg(['mean']))<\/pre>\n
 <\/p>\n","protected":false},"excerpt":{"rendered":"
Program 1 # Advance Data Analysis #Aggrigate Functions # max(),min(),avg(),count(),sum(),mod(),mean() import pandas as pd product=[(‘Limca’,20,’Sanchi’),(‘Frooti’,25,’Amul’),(‘Milk’,10,’BK’),(‘Water’,20,’BK’), (‘Limca’,25,’AK’),(‘Frooti’,20,’SK’),(‘Milk’,28,’BK’),(‘Water’,30,’Sanchi’), (‘Limca’,27,’Sanchi’),(‘Frooti’,29,’AK’),(‘Milk’,25,’Amul’),(‘Water’,45,’Sanchi’), (‘Water’,29,’Amul’),(‘Limca’,40,’DK’),(‘Frooti’,12,’Amul’),(‘Water’,40,’Sanchi’) ] #print(product) df=pd.DataFrame(product,columns=[‘Product Name’,’Price’,’Distributor’]) #print(df) df1=df.groupby(‘Product Name’) # for name,rows in df1: # print(name) # print(rows)...<\/p>\n","protected":false},"author":581,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19475],"tags":[34308,34305,9393,30086,34304,34307,30038,34264,34306,9399],"class_list":["post-145200","post","type-post","status-publish","format-standard","hentry","category-pandas","tag-aggregate-function-in-pandas","tag-aggregate-method-in-pandas","tag-pandas","tag-pandas-aggregate-functions","tag-pandas-aggregate-method","tag-pandas-dataframe-aggregate-method","tag-pandas-practical","tag-pandas-program","tag-pandas-program-on-aggregate-method","tag-pandas-tutorial"],"yoast_head":"\nPandas DataFrame aggregate() 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\" href=\"https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pandas DataFrame aggregate() Method - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Program 1 # Advance Data Analysis #Aggrigate Functions # max(),min(),avg(),count(),sum(),mod(),mean() import pandas as pd product=[('Limca',20,'Sanchi'),('Frooti',25,'Amul'),('Milk',10,'BK'),('Water',20,'BK'), ('Limca',25,'AK'),('Frooti',20,'SK'),('Milk',28,'BK'),('Water',30,'Sanchi'), ('Limca',27,'Sanchi'),('Frooti',29,'AK'),('Milk',25,'Amul'),('Water',45,'Sanchi'), ('Water',29,'Amul'),('Limca',40,'DK'),('Frooti',12,'Amul'),('Water',40,'Sanchi') ] #print(product) df=pd.DataFrame(product,columns=['Product Name','Price','Distributor']) #print(df) df1=df.groupby('Product Name') # for name,rows in df1: # print(name) # print(rows)...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/\" \/>\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=\"2025-06-02T06:55:15+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":"Pandas DataFrame aggregate() Method - 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\/pandas-dataframe-aggregate-method\/","og_locale":"en_US","og_type":"article","og_title":"Pandas DataFrame aggregate() Method - DataFlair","og_description":"Program 1 # Advance Data Analysis #Aggrigate Functions # max(),min(),avg(),count(),sum(),mod(),mean() import pandas as pd product=[('Limca',20,'Sanchi'),('Frooti',25,'Amul'),('Milk',10,'BK'),('Water',20,'BK'), ('Limca',25,'AK'),('Frooti',20,'SK'),('Milk',28,'BK'),('Water',30,'Sanchi'), ('Limca',27,'Sanchi'),('Frooti',29,'AK'),('Milk',25,'Amul'),('Water',45,'Sanchi'), ('Water',29,'Amul'),('Limca',40,'DK'),('Frooti',12,'Amul'),('Water',40,'Sanchi') ] #print(product) df=pd.DataFrame(product,columns=['Product Name','Price','Distributor']) #print(df) df1=df.groupby('Product Name') # for name,rows in df1: # print(name) # print(rows)...","og_url":"https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2025-06-02T06:55:15+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\/pandas-dataframe-aggregate-method\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/c187795dc82ab948373cca526df7c445"},"headline":"Pandas DataFrame aggregate() Method","datePublished":"2025-06-02T06:55:15+00:00","mainEntityOfPage":{"@id":"https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/"},"wordCount":6,"commentCount":0,"publisher":{"@id":"https:\/\/data-flair.training\/blogs\/#organization"},"keywords":["aggregate function in pandas","aggregate method in pandas","Pandas","pandas aggregate functions","pandas aggregate method","pandas dataframe aggregate method","pandas practical","pandas program","pandas program on aggregate method","pandas tutorial"],"articleSection":["Pandas Tutorials"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/","url":"https:\/\/data-flair.training\/blogs\/pandas-dataframe-aggregate-method\/","name":"Pandas DataFrame aggregate() Method - 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