Data Frame

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"# Data Frame Coding 3 — Problem Statement A logistics company wants to identify shipments that are at risk of delayed delivery. The company stores shipment details, route profiles, tracking events, weather alerts, and warehouse-processing logs. Your task is to analyse these records and print shipments whose delay risk level is HIGH or MEDIUM. The delay risk must be calculated using tracking activity, delay events, route weather impact, warehouse processing time, route-level comparison, and expected delivery time. Read input from STDIN and print output to STDOUT. Do not print arbitrary strings anywhere in the program, as these contribute to standard output and test cases will fail. ## Data Structures **Shipments Table** | Field | Description | |---|---| | shipmentId | Unique identifier of the shipment | | shipmentName | Name or reference of the shipment | | routeId | Route assigned to the shipment | | dispatchDay | Day on which the shipment was dispatched | Every routeId in the Shipments table has exactly one matching entry in the Route Profiles table. **Route Profiles Table** | Field | Description | |---|---| | routeId | Unique identifier of the route | | standardTransitDays | Standard number of days required to complete the route | | maxWarehouseProcessingHours | Maximum allowed total warehouse-processing hours for a shipment on that route | **Tracking Events Table** | Field | Description | |---|---| | eventId | Unique identifier of the tracking event | | shipmentId | Shipment to which the event belongs | | eventDay | Day on which the event was recorded | | status | IN_TRANSIT, DELAYED, or DELIVERED | **Weather Alerts Table** | Field | Description | |---|---| | alertId | Unique identifier of the weather alert | | routeId | Route affected by the alert | | alertDay | Day on which the alert was recorded | | severity | LOW, MEDIUM, or HIGH | **Warehouse Processing Logs Table** | Field | Description | |---|---| | processId | Unique identifier of the processing log | | shipmentId | Shipment processed at the warehouse | | processDay | Day on which processing was recorded | | processingHours | Number of processing hours recorded | ## Valid Record Rules **A tracking event is valid only when all conditions are satisfied:** 1. Its shipmentId exists in the Shipments table. 2. Its eventDay is between the shipment's dispatchDay and referenceDay, inclusive. 3. Its status is IN_TRANSIT, DELAYED, or DELIVERED. **A weather alert is valid only when all conditions are satisfied:** 1. Its routeId exists in the Route Profiles table. 2. Its alertDay is between 1 and referenceDay, inclusive. 3. Its severity is LOW, MEDIUM, or HIGH. **A warehouse processing log is valid only when all conditions are satisfied:** 1. Its shipmentId exists in the Shipments table. 2. Its processDay is between the shipment's dispatchDay and referenceDay, inclusive. 3. Its processingHours is greater than or equal to 0. Invalid records must be ignored completely. Every input record must be processed independently. If identical records appear more than once, each occurrence must be counted separately. ## Features to Calculate For every shipment, calculate the following values using only valid records. 1. **validTrackingEventCount**: Count the number of valid tracking events for the shipment. 2. **latestTrackingDay**: Find the latest eventDay among valid tracking events. 3. **daysWithoutUpdate**: `daysWithoutUpdate = referenceDay - latestTrackingDay`. If validTrackingEventCount is 0, `daysWithoutUpdate = referenceDay + 1`. 4. **delayEventCount**: Count valid tracking events whose status is DELAYED. 5. **isDelivered**: True if at least one valid tracking event has status DELIVERED; otherwise false. 6. **totalWarehouseProcessingHours**: Sum of processingHours from all valid warehouse-processing logs for the shipment. 7. **routeWeatherAlertScore**: For each route, add the following weights for all valid weather alerts recorded for that route. The total is the routeWeatherAlertScore for every shipment on that route. | Severity | Weight | |---|---| | LOW | 1 | | MEDIUM | 2 | | HIGH | 3 | 8. **routeAverageDelayEventCount**: For each route, `= total delayEventCount of all shipments on that route // number of shipments on that route`. All shipments on the route must be considered, including delivered shipments and shipments with no tracking events. 9. **aboveRouteDelayBaseline**: A shipment is above the route delay baseline when `delayEventCount > routeAverageDelayEventCount`. 10. **expectedDeliveryDay**: `= dispatchDay + standardTransitDays`. ## Delay Risk Score Calculate the delay risk score for every shipment: | Condition | Score Added | |---|---| | daysWithoutUpdate >= 5 | 4 | | validTrackingEventCount == 0 | 3 | | delayEventCount >= 2 | 3 | | routeWeatherAlertScore >= 4 | 2 | | totalWarehouseProcessingHours > maxWarehouseProcessingHours | 3 | | shipment is above the route delay baseline | 2 | | referenceDay > expectedDeliveryDay and isDelivered is false | 4 | `riskScore = staleUpdateScore + noTrackingScore + delayEventScore + weatherScore + warehouseScore + routeBaselineScore + overdueScore` ## Delay Risk Level | Risk Score | Risk Level | |---|---| | 10 or more | HIGH | | 6 to 9 | MEDIUM | | Less than 6 | LOW | A delivered shipment must never be printed, even if its calculated risk score is HIGH or MEDIUM. Only non-delivered shipments with HIGH or MEDIUM risk must be printed. ## Constraints - 2 <= numberOfShipments <= 100000 - 1 <= numberOfRouteProfiles <= 100 - 0 <= numberOfTrackingEvents <= 200000 - 0 <= numberOfWeatherAlerts <= 200000 - 0 <= numberOfWarehouseLogs <= 200000 - 1 <= referenceDay <= 1000000 - 1 <= dispatchDay, alertDay <= 1000000 - -1000000 <= eventDay, processDay <= 1000000 - -1000000 <= processingHours <= 1000000 All IDs, names, route IDs, statuses, and severity values contain no spaces. ## Input Format - Line 1: integer `referenceDay`, the fixed analysis day. - Line 2: number of records in the Shipments table. - Line 3: number of records in the Route Profiles table. - Line 4: number of records in the Tracking Events table. - Line 5: number of records in the Weather Alerts table. - Line 6: number of records in the Warehouse Processing Logs table. Records follow in this order: 1. Shipments table: `shipmentId shipmentName routeId dispatchDay` 2. Route Profiles table: `routeId standardTransitDays maxWarehouseProcessingHours` 3. Tracking Events table: `eventId shipmentId eventDay status` 4. Weather Alerts table: `alertId routeId alertDay severity` 5. Warehouse Processing Logs table: `processId shipmentId processDay processingHours` ## Output Format Print all eligible shipments in the following format: ``` shipmentName-riskLevel-riskScore-daysWithoutUpdate ``` If multiple shipments must be displayed, separate them with a hash symbol (`#`). **Sort order** (apply next condition only when previous is a tie): 1. HIGH risk shipments before MEDIUM risk shipments 2. Higher riskScore first 3. Higher daysWithoutUpdate first 4. Original input sequence of the Shipments table when all previous values are equal Print `NA` if no shipment qualifies. ## Sample Input 1 ``` 100 3 2 4 3 3 S1 Parcel_A R1 10 S2 Parcel_B R1 10 S3 Parcel_C R2 80 R1 20 10 R2 30 8 E1 S1 70 DELAYED E2 S1 80 DELAYED E3 S2 99 IN_TRANSIT E4 S3 90 IN_TRANSIT W1 R1 30 HIGH W2 R1 50 MEDIUM W3 R2 85 LOW P1 S1 60 15 P2 S2 20 5 P3 S3 85 9 ``` ## Sample Output 1 ``` Parcel_A-HIGH-18-20#Parcel_C-MEDIUM-7-10#Parcel_B-MEDIUM-6-1 ``` ## Sample Input 2 ``` 50 4 2 6 6 5 S1 Alpha R1 10 S2 Beta R1 10 S3 Gamma R2 20 S4 Delta R2 20 R1 20 5 R2 15 8 E1 S1 51 DELAYED E2 S2 30 DELIVERED E3 S3 25 UNKNOWN E4 X9 30 DELAYED E5 S4 40 DELAYED E6 S4 41 DELAYED W1 R1 5 HIGH W2 R1 20 HIGH W3 R1 30 MEDIUM W4 R2 30 HIGH W5 X9 30 HIGH W6 R2 51 HIGH P1 S1 20 6 P2 S2 51 10 P3 S3 30 -1 P4 S4 30 9 P5 X9 25 10 ``` ## Sample Output 2 ``` Alpha-HIGH-16-51#Delta-HIGH-16-9#Gamma-HIGH-11-51 ```"