{"id":19016058,"url":"https://github.com/varunu28/aadhar-dataset-analysis","last_synced_at":"2025-04-23T01:57:58.014Z","repository":{"id":113371683,"uuid":"112507240","full_name":"varunu28/AADHAR-Dataset-Analysis","owner":"varunu28","description":"Data analysis of AADHAR dataset using Apache Spark","archived":false,"fork":false,"pushed_at":"2018-03-30T22:52:09.000Z","size":1908,"stargazers_count":7,"open_issues_count":1,"forks_count":9,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-23T01:57:51.087Z","etag":null,"topics":["analysis","scala","spark","spark-sql"],"latest_commit_sha":null,"homepage":null,"language":"Scala","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/varunu28.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":"2017-11-29T17:36:44.000Z","updated_at":"2024-12-29T10:57:25.000Z","dependencies_parsed_at":"2023-06-15T11:30:21.291Z","dependency_job_id":null,"html_url":"https://github.com/varunu28/AADHAR-Dataset-Analysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/varunu28%2FAADHAR-Dataset-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/varunu28%2FAADHAR-Dataset-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/varunu28%2FAADHAR-Dataset-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/varunu28%2FAADHAR-Dataset-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/varunu28","download_url":"https://codeload.github.com/varunu28/AADHAR-Dataset-Analysis/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250354302,"owners_count":21416751,"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":["analysis","scala","spark","spark-sql"],"created_at":"2024-11-08T19:40:43.661Z","updated_at":"2025-04-23T01:57:57.996Z","avatar_url":"https://github.com/varunu28.png","language":"Scala","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AADHAR-Dataset-Analysis\nData analysis of AADHAR dataset using Apache Spark\n\n#### Technologies Used\n - Spark \n - Scala\n - Spark SQL\n - Linux Shell Scripting\n\n#### Initial Data Cleaning\n\n- Removing the header containing column names (Done using scala)\n- Removing NULL values. Assumed them to be 0 (Done using UNIX SED)\n\n#### Creating a DataFrame\n\nCreating the DataFrame for starting the analysis using the case class corresponding to the column names in input data\n\n## Questions Answered about data\n\n#### Count for number of participants and count for each gender\n- Number of Male Participants = 102037\n- Number of Female Participants = 120225\n- Total Number of Participants = 222281\n- Number of records with unspecified gender(T) = 19\n\n#### Count the number of identities(Aadhaar) generated by each Enrollment Agency and get Top 3\n- CSC SPV : 85088\n- Rajcomp Info Services Ltd : 16356\n- Mahaonline Limited : 7749\n\n#### Top 10 districts with maximum identities generated for both Male and Female\n - East Champaran : 3700\n - Jaipur : 3144\n - West Champaran : 2619\n - East Khasi Hills : 2481\n - Siwan : 2402\n - Muzaffarpur : 2250\n - Bharatpur : 1999\n - Agra : 1865\n - Ahmedabad : 1851\n - Shrawasti : 1810\n \n#### Bottom 10 districts with maximum identities generated for both Male and Female\n - Serchhip : 0\n - Yanam : 1\n - Nicobar : 1\n - North Sikkim : 1\n - Dibang Valley : 1\n - Anjaw : 1\n - Tirap : 2\n - Mokokchung : 2\n - North Cachar Hills : 2\n - Narayanpur : 3\n \n*Seeing the top 10 and bottom 10 one thing we can notice that it is easy to bring well-known districts under the radar for issuing the aadhar but work still needs to be done in the remote areas*\n \n#### Top 3 State With number of identities generated for both Male and Female\n - Uttar Pradesh : 50254\n - Bihar : 29842\n - Rajasthan : 20744\n \n#### Bottom 3 State With number of identities generated for both Male and Female\n - Lakshadweep : 14\n - Dadra and Nagar Haveli : 27\n - Daman and Diu : 45\n\n#### Top 3 States With number of identities generated for Female\n - Uttar Pradesh : 26063\n - Bihar : 15353\n - Rajasthan : 11404\n \n#### Bottom 3 States With number of identities generated for Female\n - Lakshadweep - 6\n - Others - 17\n - Dadra and Nagar Haveli - 21\n\n#### Top 3 States With number identities generated for Male\n - Uttar Pradesh : 24191\n - Bihar : 14489\n - Rajasthan : 9340\n \n#### Bottom 3 States With number identities generated for Male\n - Dadra and Nagar Haveli - 6\n - Lakshadweep - 8\n - Daman and Diu - 17\n \n*The gender-wise distribution follows the same trend as that of same distribution*","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvarunu28%2Faadhar-dataset-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvarunu28%2Faadhar-dataset-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvarunu28%2Faadhar-dataset-analysis/lists"}