{"id":22873866,"url":"https://github.com/itskshitija/lego-set-explorer","last_synced_at":"2025-06-12T23:36:28.200Z","repository":{"id":273846965,"uuid":"897819375","full_name":"itskshitija/Lego-Set-Explorer","owner":"itskshitija","description":"As a part of the Maven Analytics Lego challenge, I developed an interactive Power BI dashboard exploring the evolution of LEGO sets from 1970 to 2022. ","archived":false,"fork":false,"pushed_at":"2025-01-23T09:46:19.000Z","size":2461,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-02-06T18:46:18.883Z","etag":null,"topics":["data-analysis","data-science","data-visualization","dataanalysis","dataset","powerbi","powerbi-desktop","powerbi-report"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/itskshitija.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-12-03T09:46:58.000Z","updated_at":"2025-01-23T09:46:22.000Z","dependencies_parsed_at":"2025-01-23T10:42:59.666Z","dependency_job_id":null,"html_url":"https://github.com/itskshitija/Lego-Set-Explorer","commit_stats":null,"previous_names":["itskshitija/lego-set-explorer"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itskshitija%2FLego-Set-Explorer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itskshitija%2FLego-Set-Explorer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itskshitija%2FLego-Set-Explorer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/itskshitija%2FLego-Set-Explorer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/itskshitija","download_url":"https://codeload.github.com/itskshitija/Lego-Set-Explorer/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246472523,"owners_count":20783224,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["data-analysis","data-science","data-visualization","dataanalysis","dataset","powerbi","powerbi-desktop","powerbi-report"],"created_at":"2024-12-13T14:31:16.879Z","updated_at":"2025-03-31T12:41:11.076Z","avatar_url":"https://github.com/itskshitija.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ca href=\"https://www.linkedin.com/in/kshitija-chilbule-b98515309/\" target=\"_blank\"\u003e\n  \u003cimg src=\"https://img.shields.io/badge/LinkedIn-Connect-blue?style=flat\u0026logo=linkedin\" alt=\"LinkedIn Badge\" style=\"height: 30px; width: auto;\"\u003e\n\u003c/a\u003e\n\n# Lego Set Explorer 🧩\n\n## Table of Contents\n- [Overview](#overview)\n- [Data Dictonary](#data-dictionary)\n- [Data Cleaning](#data-cleaning)\n- [Important KPIs](#important-kpis)\n- [Dashboard Preview](#dashboard-preview)\n\n## Overview\nThe objective of this challenge is to create an interactive visual that lets users explore the history and evolution of LEGO sets from the past 50 years. The dashboard uses data from LEGO sets released from 1970 to 2022, including details on each set’s theme, pieces, recommended age, retail price, and image.\n \n## Data Dictionary\n\u003cb\u003eset_id:\u003c/b\u003e Official LEGO item number\n\n\u003cb\u003ename:\u003c/b\u003e Name of the LEGO set\n\n\u003cb\u003eyear: \u003c/b\u003e Release year\n\n\u003cb\u003etheme:\u003c/b\u003e LEGO theme the set belongs to\n\n\u003cb\u003esubtheme:\u003c/b\u003e Subtheme within the theme\n\n\u003cb\u003ethemeGroup:\u003c/b\u003e Overall group the theme belongs to\n\n\u003cb\u003ecategory:\u003c/b\u003e Type of set pieces\tNumber of pieces in the set\n\n\u003cb\u003eminifigs:\u003c/b\u003eNumber of mini figures included in the set\n\n\u003cb\u003eagerange_min:\u003c/b\u003e Minimum age recommended\n\n\u003cb\u003eUS_retailPrice:\u003c/b\u003e US retail price at launch\n\n\u003cb\u003ebricksetURL:\u003c/b\u003e URL for the set on brickset.com\n\n\u003cb\u003ethumbnailURL:\u003c/b\u003e Small image of the set\n\n\u003cb\u003eimageURL: \u003c/b\u003e Full size image of the set\n\n## Data Cleaning\nOnce the dataset is imported into Power BI, the next step is to clean it, as it often contains various inconsistencies. We will perform data cleaning using Power BI Query Editor, an inbuilt feature of Power BI that allows efficient data transformation and preparation. \n\nClick on the \u003cb\u003eTransform Data\u003c/b\u003e tab to access the Power Query Editor.\n\n- \u003cb\u003eRemoving Irrelevant Columns: \u003c/b\u003e In our analysis, certain columns are not needed, so it's important to remove them to ensure an effective analysis.\n  - Columns Removed: `thumbnailURL, bricksetURL, minifigs`\n\n- \u003cb\u003eChanging Type of columns: \u003c/b\u003e Our dataset includes columns with incorrect data types that need to be corrected for accurate analysis.\n  - The `agerange_min` column, initially in text format, is converted to a whole number type\n  - The `US_retailPrice` column, initially in text format is converted to a fixed decimal type\n\n- \u003cb\u003eHandling Missing Values: \u003c/b\u003e Our dataset consist of columns with missing values. For this analysis, we removed empty values.\n  - Columns: `pieces, agerange_min, US_retailPrice`\n \n- \u003cb\u003eRenaming Columns: \u003c/b\u003e For better identification of columns, we renamed some columns.\n  - `agerange_min`: age\n  - `US_retailPrice`: price\n\n## Important KPIs\n\n\u003cb\u003e1.Total Sets\u003c/b\u003e \n\n```\nTotal Sets = DISTINCTCOUNT(lego_sets[set_id])\n```\n\n\u003cb\u003e2.Total Groups\u003c/b\u003e\n\n```\nTotal Groups = DISTINCTCOUNT(lego_sets[themeGroup])\n```\n\n\u003cb\u003e3. Average Age \u003c/b\u003e\n\n```\nAvg. Age = AVERAGE(lego_sets[age])\n```\n\n\u003cb\u003e4. Average Price \u003c/b\u003e\n\n```\nAvg. Price = AVERAGE(lego_sets[price])\n```\n\n\u003cb\u003e5. Average Pieces \u003c/b\u003e\n\n```\nAvg. Pieces = AVERAGE(lego_sets[pieces])\n```\n\n## Dashboard Preview\n\n![1](https://github.com/user-attachments/assets/cf167a87-ba24-4c50-9881-8caa93bba362)\n\n![2](https://github.com/user-attachments/assets/c0b6fdbd-18cc-400b-8c84-0b56a1184de0)\n\n\n## Connect 🤝\n- 📩 \u003cb\u003eEmail:\u003c/b\u003e kshitijachilbule5@gmail.com\n- 👩‍💻 \u003cb\u003eGithub:\u003c/b\u003e https://github.com/itskshitija\n- 📶 \u003cb\u003eLinkedIn:\u003c/b\u003e https://www.linkedin.com/in/kshitija-chilbule-b98515309/\n- 🌐 \u003cb\u003eMedium:\u003c/b\u003e https://medium.com/@kshitijachilbule2\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fitskshitija%2Flego-set-explorer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fitskshitija%2Flego-set-explorer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fitskshitija%2Flego-set-explorer/lists"}