JKISeason 4-15 - Rocket Landing Success Analysis

<p><strong>Challenge 15: Rocket Landing Success Analysis</strong></p><p><strong>Level: </strong>Easy<br><br><strong>Description:&nbsp;</strong>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.<br><br><em>Beginner-friendly objectives:</em> 1. Parse the JSON file (<em>launches.json</em>) and extract the following fields:<br>flight_number, name, date_utc, success, rocket (ID)<br>payloads[0] (only the first payload per mission),<br>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 <em>Rocket_Details.csv</em> and (b) using the Payload ID to fetch payload_mass_kg and orbit from <em>Payload_Details.csv</em>. 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.<br><br><strong>Author: Keerthan Shetty</strong><br><br><strong>Dataset</strong>: <strong>Rocket Data on KNIME Community Hub</strong><br><br>Remember to upload your solution with tag&nbsp;<strong>JKISeason4-15</strong>&nbsp;to your public space on KNIME Community Hub. To increase the visibility of your solution, also post it to&nbsp;<strong>this challenge thread</strong>&nbsp;on KNIME Forum.</p>