Immediate Dispatch Preference Percentage

Easy

A delivery platform stores order and delivery preference metadata in one table: delivery columns: delivery_id: unique order identifier customer_id: customer identifier order_date: date when the order was placed customer_pref_delivery_date: customer's requested delivery date Order types: immediate order: customer_pref_delivery_date is the same as order_date scheduled order: customer_pref_delivery_date is later than order_date Task: Compute the percentage of immediate orders across all rows in delivery. Round the result to 2 decimal places. If there are no rows in the table, return 0.00. Output requirements: Return exactly one row. Return exactly one column named immediate_percentage. Supported submission environments: SQL (SQLite 3.27.2) Pandas (Python)

Example 1

Input

delivery:
| delivery_id | customer_id | order_date | customer_pref_delivery_date |
|-------------|-------------|------------|-----------------------------|
| 1           | 101         | 2022-05-01 | 2022-05-01                  |
| 2           | 102         | 2022-05-01 | 2022-05-03                  |
| 3           | 103         | 2022-05-02 | 2022-05-02                  |
| 4           | 104         | 2022-05-03 | 2022-05-06                  |

Output

[
  {"immediate_percentage":50.0}
]

Explanation

2 of 4 orders are immediate, so the percentage is 50.00.

Example 2

Input

delivery:
[]

Output

[
  {"immediate_percentage":0.0}
]

Explanation

When there are no orders, return 0.00 by definition.

Example 3

Input

delivery:
| delivery_id | customer_id | order_date | customer_pref_delivery_date |
|-------------|-------------|------------|-----------------------------|
| 10          | 8           | 2023-01-10 | 2023-01-12                  |
| 11          | 8           | 2023-01-11 | 2023-01-11                  |
| 12          | 9           | 2023-01-12 | 2023-01-16                  |
| 13          | 9           | 2023-01-13 | 2023-01-13                  |
| 14          | 9           | 2023-01-14 | 2023-01-14                  |

Output

[
  {"immediate_percentage":60.0}
]

Explanation

Orders 11, 13, and 14 are immediate. 3/5 * 100 = 60.00.

Constraints

0 <= number of rows in delivery <= 100000
delivery_id is unique
1 <= customer_id <= 1000000000
order_date and customer_pref_delivery_date are valid dates in YYYY-MM-DD format
customer_pref_delivery_date is on or after order_date
Return exactly one column: immediate_percentage
Round to exactly 2 decimal places
If delivery has zero rows, return 0.00
For SQL submissions, use SQLite 3.27.2 semantics
For Pandas submissions, return a DataFrame with one row and one column: immediate_percentage

delivery: | delivery_id | customer_id | order_date | customer_pref_delivery_date | |-------------|-------------|------------|-----------------------------| | 1 | 101 | 2022-05-01 | 2022-05-01 | | 2 | 102 | 2022-05-01 | 2022-05-03 | | 3 | 103 | 2022-05-02 | 2022-05-02 | | 4 | 104 | 2022-05-03 | 2022-05-06 |

delivery: | delivery_id | customer_id | order_date | customer_pref_delivery_date | |-------------|-------------|------------|-----------------------------| | 10 | 8 | 2023-01-10 | 2023-01-12 | | 11 | 8 | 2023-01-11 | 2023-01-11 | | 12 | 9 | 2023-01-12 | 2023-01-16 | | 13 | 9 | 2023-01-13 | 2023-01-13 | | 14 | 9 | 2023-01-14 | 2023-01-14 |