For this, use aggregate function SUM() along with GROUP BY. Let us first create a table −
mysql> create table DemoTable1522 -> ( -> ProductPurchaseDate date, -> NumberOfProduct int -> ); Query OK, 0 rows affected (1.51 sec)
Insert some records in the table using insert command −
mysql> insert into DemoTable1522 values('2019-01-21',45);
Query OK, 1 row affected (0.14 sec)
mysql> insert into DemoTable1522 values('2018-12-31',78);
Query OK, 1 row affected (0.12 sec)
mysql> insert into DemoTable1522 values('2019-01-21',67);
Query OK, 1 row affected (0.12 sec)
mysql> insert into DemoTable1522 values('2019-03-01',56);
Query OK, 1 row affected (0.19 sec)
mysql> insert into DemoTable1522 values('2018-01-21',97);
Query OK, 1 row affected (0.10 sec)
mysql> insert into DemoTable1522 values('2019-01-21',47);
Query OK, 1 row affected (0.15 sec)Display all records from the table using select statement −
mysql> select * from DemoTable1522;
This will produce the following output −
+---------------------+-----------------+ | ProductPurchaseDate | NumberOfProduct | +---------------------+-----------------+ | 2019-01-21 | 45 | | 2018-12-31 | 78 | | 2019-01-21 | 67 | | 2019-03-01 | 56 | | 2018-01-21 | 97 | | 2019-01-21 | 47 | +---------------------+-----------------+ 6 rows in set (0.00 sec)
Following is the query to count columns according to dates in MySQL −
mysql> select ProductPurchaseDate,sum(NumberOfProduct) from DemoTable1522 -> group by ProductPurchaseDate;
This will produce the following output −
+---------------------+----------------------+ | ProductPurchaseDate | sum(NumberOfProduct) | +---------------------+----------------------+ | 2019-01-21 | 159 | | 2018-12-31 | 78 | | 2019-03-01 | 56 | | 2018-01-21 | 97 | +---------------------+----------------------+ 4 rows in set (0.00 sec)