Table: Delivery
+-----------------------------+---------+ | Column Name | Type | +-----------------------------+---------+ | delivery_id | int | | customer_id | int | | order_date | date | | customer_pref_delivery_date | date | +-----------------------------+---------+ delivery_id is the primary key (column with unique values) of this table. The table holds information about food delivery to customers that make orders at some date and specify a preferred delivery date (on the same order date or after it).
If the customer's preferred delivery date is the same as the order date, then the order is called immediate; otherwise, it is called scheduled.
Write a solution to find the percentage of immediate orders in the table, rounded to 2 decimal places.
The result format is in the following example.
Example 1:
Input: Delivery table: +-------------+-------------+------------+-----------------------------+ | delivery_id | customer_id | order_date | customer_pref_delivery_date | +-------------+-------------+------------+-----------------------------+ | 1 | 1 | 2019-08-01 | 2019-08-02 | | 2 | 5 | 2019-08-02 | 2019-08-02 | | 3 | 1 | 2019-08-11 | 2019-08-11 | | 4 | 3 | 2019-08-24 | 2019-08-26 | | 5 | 4 | 2019-08-21 | 2019-08-22 | | 6 | 2 | 2019-08-11 | 2019-08-13 | +-------------+-------------+------------+-----------------------------+ Output: +----------------------+ | immediate_percentage | +----------------------+ | 33.33 | +----------------------+ Explanation: The orders with delivery id 2 and 3 are immediate while the others are scheduled.
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{"headers":{"Delivery":["delivery_id","customer_id","order_date","customer_pref_delivery_date"]},"rows":{"Delivery":[[1,1,"2019-08-01","2019-08-02"],[2,5,"2019-08-02","2019-08-02"],[3,1,"2019-08-11","2019-08-11"],[4,3,"2019-08-24","2019-08-26"],[5,4,"2019-08-21","2019-08-22"],[6,2,"2019-08-11","2019-08-13"]]}}