{"id":19278971,"url":"https://github.com/mehraaaaa24/t20-data-analysis","last_synced_at":"2026-05-06T19:03:49.950Z","repository":{"id":223249701,"uuid":"759711248","full_name":"mehraaaaa24/T20-Data-Analysis","owner":"mehraaaaa24","description":null,"archived":false,"fork":false,"pushed_at":"2024-08-31T17:21:04.000Z","size":7418,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-05T16:23:05.268Z","etag":null,"topics":["csv-files","data-analysis","data-cleaning","data-modelling","data-preprocessing","data-transformation","data-visualization","excel","json","pandas","powerbi","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mehraaaaa24.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2024-02-19T07:33:00.000Z","updated_at":"2024-08-31T17:21:07.000Z","dependencies_parsed_at":null,"dependency_job_id":"7e4b57cd-88cf-41d5-a806-78237a5fb1ab","html_url":"https://github.com/mehraaaaa24/T20-Data-Analysis","commit_stats":null,"previous_names":["mehraaaaa24/t20-data-analysis"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mehraaaaa24%2FT20-Data-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mehraaaaa24%2FT20-Data-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mehraaaaa24%2FT20-Data-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mehraaaaa24%2FT20-Data-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mehraaaaa24","download_url":"https://codeload.github.com/mehraaaaa24/T20-Data-Analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240385201,"owners_count":19792980,"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":["csv-files","data-analysis","data-cleaning","data-modelling","data-preprocessing","data-transformation","data-visualization","excel","json","pandas","powerbi","python"],"created_at":"2024-11-09T21:12:49.375Z","updated_at":"2026-05-06T19:03:44.928Z","avatar_url":"https://github.com/mehraaaaa24.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"T20 World Cup 2022 Data Analysis Project\n\nWelcome to the T20 World Cup 2022 Data Analysis project! \nThis repository contains the code and resources used to analyze the T20 World Cup 2022 matches. Here's a breakdown of what this project entails:\n\n1. Data Preprocessing with Python\nThe initial dataset was provided in JSON format, containing information about T20 World Cup 2022 matches. To analyze and visualize this data effectively, we utilized Python with libraries such as Pandas. The preprocessing steps involved:\n\nImporting the JSON data into Python.\nUtilizing Pandas to manipulate the data, treating it as tables.\nRenaming columns to ensure clarity and consistency.\nConducting data cleaning tasks such as handling missing values, removing duplicates, and standardizing formats.\nPerforming transformations on the data to prepare it for analysis.\n\n2. Data Transformation in Power BI\nAfter preprocessing the data in Python, we converted it into CSV files. These CSV files were then imported into Power BI for further analysis. Within Power BI, we leveraged Power Query to perform additional data transformations. This included:\n\nSplitting the data into different tables based on relevant attributes.\nApplying filters and sorting operations to streamline the data.\nCreating calculated columns and measures using DAX to derive meaningful insights.\nHandling relationships between different tables to facilitate data modeling.\n\n3. Data Modeling and Parameterization with DAX\nIn addition to data transformation, we utilized Data Analysis Expressions (DAX) within Power BI to enhance our analysis. This involved:\n\nBuilding data models to establish relationships between different entities within the dataset.\nDefining parameters to enable dynamic filtering and analysis.\nImplementing complex calculations and business logic using DAX functions.\nFine-tuning the data model to optimize performance and usability.\n\n4. Visualization in Power BI Dashboard\nThe ultimate goal of this project was to create informative and visually appealing dashboards to present the insights gleaned from the T20 World Cup 2022 data. We designed interactive visualizations within Power BI to:\n\nDisplay key metrics and trends related to the T20 World Cup matches.\nProvide users with the ability to explore the data dynamically.\nCommunicate actionable insights effectively through intuitive charts, graphs, and tables.\nI hope this project provides valuable insights into the T20 World Cup 2022 matches and serves as a demonstration of data analysis techniques using Python and Power BI.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmehraaaaa24%2Ft20-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmehraaaaa24%2Ft20-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmehraaaaa24%2Ft20-data-analysis/lists"}