Practice/Uber/Leetcode 262. Trips and Users

Leetcode 262. Trips and Users

CodingOptional

Problem

You are building an analytics dashboard for a ride-sharing platform. The platform needs to monitor the daily cancellation rate of rides to identify operational issues and maintain service quality.

Given two data tables and a date range, calculate the cancellation rate for each day that has at least one valid trip. A trip is considered valid only if both the client and driver associated with it are not banned from the platform.

The cancellation rate for a given day is defined as:

• (Number of cancelled trips) / (Total number of valid trips)
• Rounded to exactly 2 decimal places

A trip is considered cancelled if its status is either "cancelled_by_client" or "cancelled_by_driver". Completed trips have status "completed".

Requirements

1. Filter trips to only include those within the specified date range (inclusive)
2. Exclude any trip where either the client or driver is banned
3. For each day with at least one valid trip, compute the cancellation rate
4. Round all cancellation rates to exactly 2 decimal places
5. Return results as a dictionary mapping date strings to their cancellation rates
6. Days with no valid trips should not appear in the output

Constraints

• 1 ≤ number of trips ≤ 1000
• 1 ≤ number of users ≤ 500
• All user IDs in trips exist in the users table
• Dates are in "YYYY-MM-DD" format
• Status values are: "completed", "cancelled_by_client", or "cancelled_by_driver"
• Banned values are: "Yes" or "No"
• Role values are: "client" or "driver"

Examples

Example 1:

` Trips: | trip_id | client_id | driver_id | request_date | status | |---------|-----------|-----------|--------------|--------| | 1 | 101 | 201 | 2024-01-15 | completed | | 2 | 102 | 202 | 2024-01-15 | cancelled_by_driver | | 3 | 103 | 201 | 2024-01-16 | cancelled_by_client | | 4 | 104 | 202 | 2024-01-16 | completed |

Users: | user_id | banned | role | |---------|--------|------| | 101 | No | client | | 102 | No | client | | 103 | No | client | | 104 | Yes | client | | 201 | No | driver | | 202 | No | driver |

Date range: 2024-01-15 to 2024-01-16

Output: {'2024-01-15': 0.50, '2024-01-16': 1.00}

Explanation:

• 2024-01-15: Trips 1 and 2 are valid (both users unbanned). 1 cancelled out of 2 = 0.50
• 2024-01-16: Trip 4 excluded (client 104 is banned). Only trip 3 is valid. 1 cancelled out of 1 = 1.00 `

Example 2:

` Trips: | trip_id | client_id | driver_id | request_date | status | |---------|-----------|-----------|--------------|--------| | 1 | 101 | 201 | 2024-02-01 | completed | | 2 | 102 | 202 | 2024-02-01 | completed | | 3 | 103 | 201 | 2024-02-01 | completed |

Users: | user_id | banned | role | |---------|--------|------| | 101 | No | client | | 102 | No | client | | 103 | No | client | | 201 | No | driver | | 202 | No | driver |

Date range: 2024-02-01 to 2024-02-01

Output: {'2024-02-01': 0.00}

Explanation: All 3 trips are valid and completed, so cancellation rate is 0/3 = 0.00 `