How to use avg function in SQL server

How to use avg function in SQL server

AVG() aggregate function in SQL Server: The AVG () aggregate function is used to display the average value of the records. The AVG () function returns the average value of the selected records. The AVG () function is used with the "SQL Select command" as well as "SQL Select Where Command". Ignore the NULL values.

AVG() function's Syntax:
            Select AVG[ALL | DISTINCT] From [TABLE_NAME]



AVG()  Syntax With Select Where Command:
              Select AVG[ALL | DISTINCT] From [TABLE_NAME] Where [COLUMN_NAME]='VALUE'



AVG() function's description:
               AVG(): It is a SQL Sever function.
           ALL: Applies for all values.
           DISTINCT: It specify the values. Removes the duplicate value and returns average value.
           From: SQL Server keyword.
           [COLUMN_NAME]=Name of column.
           Where: SQL Server keyword.



       
AVG() aggregate function Example:

Here a table named ItemDetails:

ItemCode	ItemName	ManufactureCompany	ItemSerialNo	ItemCategory	ItemQuantity	ItemPrice	ProductCountry
1	Samsung Mobile	Samsung	S12345	Mobile	500	240	Korea
2	Samsung Pro	Samsung	SP1234	Mobile	100	300	Korea
3	Samsung Headphone	Samsung	SH2345	Headphone	50	50	Korea
4	iPhone	iPone	iP12345	Mobile	1000	500	United Stat
5	Apple Mobile	Apple	A12345	Mobile	200	300	United Stat
6	Apple Computer	Apple	A12343	Computer	200	400	United Stat
7	Apple Macbook	Apple	AM2345	Macbook	50	600	United Stat
8	Dell Computer	DELL	D02345	Computer	200	240	United Stat
9	Dell Laptop	DELL	DL2345	Laptop	30	240	United Stat
10	Apple Laptop	Apple	AL2345	Laptop	500	100	United Stat
11	Apple Headphone	Apple	AH2345	Headphone	50	20	United Stat
12	Sony Camera	Sony	SN2345	Camera	200	240	Japan
13	Sony Headphone	Sony	SNH345	Headphone	500	50	Japan
14	Ascer Computer	Ascer	AC2345	Computer	100	600	China
16	Borother Printer	Brother	B12345	Printer	200	200	China
17	Ascer Printer	Ascer	AP2345	Printer	200	150	China
18	Brother Photocopy	Brother	BP2345	Printer	20	150	China

Now,
Select AVG(ItemQuantity)As ItemAverage from ItemDetails
Result:

ItemAverage

241

Select AVG(ItemPrice) As AveragePrice from ItemDetails

Result:

AveragePrice

257.6470588

AVG() aggregate function with Distinct keyword.
Select AVG(distinct ItemQuantity)As ItemAverage from ItemDetails
Result:

ItemAverage2

271

Select AVG(distinct ItemPrice) As AveragePrice from ItemDetails

Result:

AveragePrice2

256

AVG() aggregate function with SQL Where Statement Example:

Select AVG(ItemQuantity)As DELLItemAverage from ItemDetails Where ManufactureCompany='DELL'

Result:

DELLItemAverage

115

Select AVG(ItemPrice) As SamsungAveragePrice from ItemDetails Where ManufactureCompany='Samsung'
Result:

SamsungAveragePrice

196.6666667

AVG() aggregate function example in video:

AVG() aggregate function example in image:

[Note: We have created and inserted values into sql table in previous topic. For more details Click here.
OR
Execute the follow command in your sql query window for executing above sql select where statement]
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Create Table ItemDetails

(

ItemCode int,

ItemName varchar(30),

ManufactureCompany varchar(50),

ExpiredDate date,

ItemSearialNo varchar (30),

ItemCategory varchar(30),

ItemQuantity int,

ItemPrice float,

ProductCountry varchar(30),

ReceivedDate date,

ItemImage image

)

Insert into ItemDetails values('1','Samsung Mobile','Samsung','12-10-2024','12-01-2050','S12345','Mobile','500','240','Korea','12-10-2025')
Insert into ItemDetails values('2','Samsung Pro','Samsung','12-10-2024','12-01-2050','SP1234','Mobile','100','300','Korea','12-10-2025')
Insert into ItemDetails values('3','Samsung Headphone','Samsung','12-10-2023','12-01-2053','SH2345','Headphone','50','50','Korea','12-10-2025')
Insert into ItemDetails values('4','iPhone','iPone','12-01-2024','12-01-2049','iP12345','Mobile','1000','500','United Stat','12-10-2025')
Insert into ItemDetails values('5','Apple Mobile','Apple','12-11-2024','12-01-2049','A12345','Mobile','200','300','United Stat','12-10-2025')
Insert into ItemDetails values('6','Apple Computer','Apple','12-02-2024','12-01-2050','A12343','Computer','200','400','United Stat','12-10-2025')
Insert into ItemDetails values('7','Apple Macbook','Apple','12-11-2024','12-01-2050','AM2345','Macbook','50','600','United Stat','12-10-2025')
Insert into ItemDetails values('8','Dell Computer','DELL','12-09-2024','12-01-2050','D02345','Computer','200','240','United Stat','12-10-2025')
Insert into ItemDetails values('9','Dell Laptop','DELL','12-09-2024','12-01-2050','DL2345','Laptop','30','240','United Stat','12-10-2025')
Insert into ItemDetails values('10','Apple Laptop','Apple','12-08-2024','12-01-2050','AL2345','Laptop','500','100','United Stat','12-10-2025')
Insert into ItemDetails values('11','Apple Headphone','Apple','12-12-2024','12-01-2050','AH2345','Headphone','50','20','United Stat','12-10-2025')
Insert into ItemDetails values('12','Sony Camera','Sony','12-11-2024','12-11-2050','SN2345','Camera','200','240','Japan','12-11-2025')
Insert into ItemDetails values('13','Sony Headphone','Sony','12-09-2024','12-01-2050','SNH345','Headphone','500','50','Japan','12-11-2025')
Insert into ItemDetails values('14','Ascer Computer','Ascer','12-09-2024','12-07-2050','AC2345','Computer','100','600','China','12-10-2025')
Insert into ItemDetails values('16','Borother Printer','Brother','12-09-2024','12-01-2050','B12345','Printer','200','200','China','12-10-2025')

Insert into ItemDetails (ItemCode,ItemName,ManufactureCompany,ProductDate,ExpiredDate,ItemSearialNo,ItemCategory,ItemQuantity,ItemPrice,ProductCountry,ReceivedDate) values('17','Ascer Printer','Ascer','12-09-2024','12-07-2050','AP2345','Printer','200','150','China','12-10-2025')
Insert into ItemDetails (ItemCode,ItemName,ManufactureCompany,ProductDate,ExpiredDate,ItemSearialNo,ItemCategory,ItemQuantity,ItemPrice,ProductCountry,ReceivedDate) values('18','Brother Photocopy','Brother','12-08-2024','12-07-2050','BP2345','Printer','20','150','China','12-10-2025')

+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++