Q:

From the following table, create a view to count the number of unique customer, compute average and total purchase amount of customer orders by each date

hamza
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2022-05-18
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 From the following table, create a view to count the number of unique customer, compute average and total purchase amount of customer orders by each date.

Sample table: orders

ord_no      purch_amt   ord_date    customer_id  salesman_id
----------  ----------  ----------  -----------  -----------
70001       150.5       2012-10-05  3005         5002
70009       270.65      2012-09-10  3001         5005
70002       65.26       2012-10-05  3002         5001
70004       110.5       2012-08-17  3009         5003
70007       948.5       2012-09-10  3005         5002
70005       2400.6      2012-07-27  3007         5001
70008       5760        2012-09-10  3002         5001
70010       1983.43     2012-10-10  3004         5006
70003       2480.4      2012-10-10  3009         5003
70012       250.45      2012-06-27  3008         5002
70011       75.29       2012-08-17  3003         5007
70013       3045.6      2012-04-25  3002         5001
 customer_id |   cust_name    |    city    | grade | salesman_id 
-------------+----------------+------------+-------+-------------
        3002 | Nick Rimando   | New York   |   100 |        5001
        3007 | Brad Davis     | New York   |   200 |        5001
        3005 | Graham Zusi    | California |   200 |        5002
        3008 | Julian Green   | London     |   300 |        5002
        3004 | Fabian Johnson | Paris      |   300 |        5006
        3009 | Geoff Cameron  | Berlin     |   100 |        5003
        3003 | Jozy Altidor   | Moscow     |   200 |        5007
        3001 | Brad Guzan     | London     |       |        5005
Sql programming,
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hamza
2022-05-18
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CREATE VIEW totalforday
 AS SELECT ord_date, COUNT(DISTINCT customer_id),
 AVG(purch_amt), SUM(purch_amt)
 FROM orders
 GROUP BY ord_date;
output:
sqlpractice=# SELECT *
sqlpractice-# FROM totalforday;
  ord_date  | count |          avg          |   sum
------------+-------+-----------------------+---------
 2012-04-25 |     1 | 3045.6000000000000000 | 3045.60
 2012-06-27 |     1 |  250.4500000000000000 |  250.45
 2012-07-27 |     1 | 2400.6000000000000000 | 2400.60
 2012-08-17 |     3 |   95.2633333333333333 |  285.79
 2012-09-10 |     3 | 2326.3833333333333333 | 6979.15
 2012-09-22 |     1 |  322.0000000000000000 |  322.00
 2012-10-05 |     2 |  132.6300000000000000 |  265.26
 2012-10-10 |     2 | 2231.9150000000000000 | 4463.83
(8 rows)

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