{"id":27446308,"url":"https://github.com/sumit-sinha9/sales-analysis","last_synced_at":"2026-05-08T10:36:22.723Z","repository":{"id":287921655,"uuid":"966244657","full_name":"sumit-sinha9/Sales-Analysis","owner":"sumit-sinha9","description":"Analyzing 12 months worth fo Sales data","archived":false,"fork":false,"pushed_at":"2025-04-14T16:17:42.000Z","size":6437,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-15T04:15:59.630Z","etag":null,"topics":["data-analysis","pandas","python","visualization"],"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/sumit-sinha9.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,"zenodo":null}},"created_at":"2025-04-14T16:13:40.000Z","updated_at":"2025-04-14T16:18:44.000Z","dependencies_parsed_at":"2025-04-14T17:39:32.561Z","dependency_job_id":null,"html_url":"https://github.com/sumit-sinha9/Sales-Analysis","commit_stats":null,"previous_names":["sumit-sinha9/sales-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sumit-sinha9/Sales-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sumit-sinha9%2FSales-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sumit-sinha9%2FSales-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sumit-sinha9%2FSales-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sumit-sinha9%2FSales-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sumit-sinha9","download_url":"https://codeload.github.com/sumit-sinha9/Sales-Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sumit-sinha9%2FSales-Analysis/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259926928,"owners_count":22933131,"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","pandas","python","visualization"],"created_at":"2025-04-15T04:15:58.485Z","updated_at":"2026-05-08T10:36:22.649Z","avatar_url":"https://github.com/sumit-sinha9.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sales-Analysis\nHere I have taken 12 months worth of Sales Data and made some cleaning, preprocessing, analysis and visualisation on product sales.\n## Datasets used\nMonthly Sales data for all 12 months, files can be found in \u003cb\u003eSales Data\u003c/b\u003e folder\n## Process\n\u003cul\u003e\n  \u003cli\u003eAs a first step I have gathered data from all 12 month datasets and stored it in \u003ci\u003eall_data.csv\u003c/i\u003e file\u003c/li\u003e\n  \u003cli\u003eNext is \u003cb\u003eData cleaning \u0026 Preprocessing\u003c/b\u003e to get clean and proper dataset. As a part of pre processing I have added some new columns in datasets to make it more meaningfull\u003c/li\u003e\n  \u003cli\u003eAfter getting complete dataset, I started to explore deep into dataset to find answers to below questions.\u003c/li\u003e\n  \u003col\u003e\n    \u003cli\u003eFinding which month produced max sales\u003c/li\u003e\n    \u003cli\u003eFinding which city produced maximum sales\u003c/li\u003e\n    \u003cli\u003eWhat time should we display advertisements to maximise sales\u003c/li\u003e\n    \u003cli\u003eWhat products are often sold together\u003c/li\u003e\n    \u003cli\u003eFinding which product had maximum sales and why\u003c/li\u003e\n  \u003c/ol\u003e\n  \u003cli\u003eAnd I visualized below data as graphs in ipynb file\u003c/li\u003e\n  \u003col\u003e\n    \u003cli\u003eVisualizing monthly Sales data\u003c/li\u003e\n    \u003cli\u003eVisualizing Sales data on each city\u003c/li\u003e\n    \u003cli\u003eSales acheived by hours (for all cities and specifically for San Fransisco)\u003c/li\u003e\n    \u003cli\u003eProduct sales - count\u003c/li\u003e\n    \u003cli\u003eProduct sales - count and adding Price as secondary y axis\u003c/li\u003e\n  \u003c/ol\u003e\n\u003c/ul\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsumit-sinha9%2Fsales-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsumit-sinha9%2Fsales-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsumit-sinha9%2Fsales-analysis/lists"}