{"id":20448926,"url":"https://github.com/shriram-vibhute/data-analysis","last_synced_at":"2025-08-02T08:39:35.824Z","repository":{"id":254166483,"uuid":"843554600","full_name":"Shriram-Vibhute/Data-Analysis","owner":"Shriram-Vibhute","description":"This repository offers a comprehensive collection of data analysis techniques using NumPy Pandas, Matplotlib and Seaborn.","archived":false,"fork":false,"pushed_at":"2024-12-04T05:26:58.000Z","size":6221,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-28T00:04:21.108Z","etag":null,"topics":["data-aggregation","data-analysis","data-visualization","data-wrangling","matplotlib","numpy","pandas","seaborn"],"latest_commit_sha":null,"homepage":"https://github.com/Shriram-Vibhute/Data-Analysis","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/Shriram-Vibhute.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":"2024-08-16T19:19:07.000Z","updated_at":"2024-12-04T05:27:01.000Z","dependencies_parsed_at":"2025-01-15T21:27:42.943Z","dependency_job_id":"31b46902-45a4-454c-a80d-a5af25b316e4","html_url":"https://github.com/Shriram-Vibhute/Data-Analysis","commit_stats":null,"previous_names":["shriram-vibhute/data-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Shriram-Vibhute/Data-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shriram-Vibhute%2FData-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shriram-Vibhute%2FData-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shriram-Vibhute%2FData-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shriram-Vibhute%2FData-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Shriram-Vibhute","download_url":"https://codeload.github.com/Shriram-Vibhute/Data-Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shriram-Vibhute%2FData-Analysis/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":268355821,"owners_count":24237371,"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","status":"online","status_checked_at":"2025-08-02T02:00:12.353Z","response_time":74,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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-aggregation","data-analysis","data-visualization","data-wrangling","matplotlib","numpy","pandas","seaborn"],"created_at":"2024-11-15T10:37:47.052Z","updated_at":"2025-08-02T08:39:35.799Z","avatar_url":"https://github.com/Shriram-Vibhute.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Complete Data Analysis with Numpy, Pandas, Matplotlib, and Seaborn.\nThis repository contains Jupyter notebooks for learning and practicing data analysis.\n\n### Numpy\n- **numpy**: Introduction to Numpy, covering array creation methods and key functionalities for numerical operations.\n\n### Pandas\n- **1 - Series and DataFrames**\n  - **Series**: Introduction to Pandas Series and its creation methods.\n  - **Dataframe**: Overview of DataFrame creation and manipulation.\n  \n- **2 - Data Loading, Storage and File Formats**\n  - **Data_Loading**: Techniques for loading data from various formats (CSV, JSON, etc.).\n\n- **3 - Data Cleaning and Preprocessing**\n  - **data_cleaning_and_preperation**: Methods for handling missing data and data transformation.\n\n- **4 - Data Wrangling - Join Combine \u0026 Reshape**\n  - **data_wrangling**: Techniques for hierarchical indexing, merging datasets, and reshaping data.\n\n- **5 - Data Aggregation and Group Operation**\n  - **data_aggregation**: GroupBy mechanics and data aggregation techniques.\n\n### Matplotlib\n- **Matplotlib**: Introduction to Matplotlib for data visualization.\n- **QQ_Plots**: Creating QQ plots to assess normality of data distributions.\n\n### Seaborn\n- **seaborn_plots**: Visualization techniques using Seaborn, including pair plots and distribution plots.\n\nHope you find this repository helpful in your data analysis journey!\nHappy analyzing! 🎉","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshriram-vibhute%2Fdata-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshriram-vibhute%2Fdata-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshriram-vibhute%2Fdata-analysis/lists"}