Challenge 15: Rocket Landing Success Analysis
Level: Easy
Description: You are a data analyst working for a private space exploration company analyzing the landing performance of its flagship rocket. Your task is to understand what factors drive successful first-stage landings and generate insights that could improve future landing attempts.
Beginner-friendly objectives: 1. Parse the JSON file (launches.json) and extract the following fields:
flight_number, name, date_utc, success, rocket (ID)
payloads[0] (only the first payload per mission),
cores[0].gridfins, cores[0].legs, cores[0].reused, cores[0].landing_attempt, and cores[0].landing_success. 2. Retain records where landing_attempt AND mission success is true (focus on actual landing attempts from successful missions), and enrich the dataset by (a) using Rocket ID to fetch rocket_name from Rocket_Details.csv and (b) using the Payload ID to fetch payload_mass_kg and orbit from Payload_Details.csv. 3. Clean and preprocess the integrated dataset by handling missing or null values appropriately. Focus your analysis on missions involving "Explorer XI" (i.e., rocket_001). 4. Create visualizations: show total landing successes, total flights, max payload mass, and percentage of missions with core reuse. Visuals should be arranged in a dashboard layout within a component.
Author: Keerthan Shetty
Dataset: Rocket Data on KNIME Community Hub
Remember to upload your solution with tag JKISeason4-15 to your public space on KNIME Community Hub. To increase the visibility of your solution, also post it to this challenge thread on KNIME Forum.