{"id":19318079,"url":"https://github.com/rahulsm20/storedata","last_synced_at":"2026-04-16T05:04:26.865Z","repository":{"id":151842470,"uuid":"567245302","full_name":"rahulsm20/storeData","owner":"rahulsm20","description":"A data analysis project aimed at analyzing the sales data of the super store and providing useful insight into customer preferences.","archived":false,"fork":false,"pushed_at":"2023-04-07T16:55:01.000Z","size":1062,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-06T04:27:01.665Z","etag":null,"topics":["data-analysis","matplotlib","numpy","pandas","python","streamlit"],"latest_commit_sha":null,"homepage":"https://rahulsm20-storedata-main-t64r4t.streamlit.app/","language":"Python","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/rahulsm20.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":"2022-11-17T11:39:19.000Z","updated_at":"2023-04-08T04:46:53.000Z","dependencies_parsed_at":"2023-06-25T23:09:14.987Z","dependency_job_id":null,"html_url":"https://github.com/rahulsm20/storeData","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/rahulsm20%2FstoreData","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rahulsm20%2FstoreData/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rahulsm20%2FstoreData/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rahulsm20%2FstoreData/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rahulsm20","download_url":"https://codeload.github.com/rahulsm20/storeData/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240420981,"owners_count":19798502,"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","matplotlib","numpy","pandas","python","streamlit"],"created_at":"2024-11-10T01:17:15.229Z","updated_at":"2026-04-16T05:04:21.838Z","avatar_url":"https://github.com/rahulsm20.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# SuperStore Data Analysis\n### [Website](https://rahulsm20-storedata-main-t64r4t.streamlit.app)\n\n### In this project, we have aimed to analyse the sales data of the super store and provide useful insight into customer preferences.\n\n## About the dataset\nThe dataset used for this analysis is an excel file containing the following columns:\n- Row ID\n- Order ID\n- Order Date\n- Ship Date\n- Ship Mode\n- Customer ID\n- Customer Name\n- Segment\n- Country\n- City\n- State\n- Postal Code\n- Region\n- Product ID\n- Category\n- Sub-Category\n- Product Name\n- Sales\n- Quantity\n- Discount\n- Profit\n\n## Methodology \nThe analysis was conducted in Python using the following libraries:\n* Pandas\n* Numpy\n* Matplotlib\n* Streamlit (for deployment)\n\n## Results \n* The stores makes the most revenue in terms of sales from the state of California, followed by New York, Texas, Washington and Pennsylvania in that order.\n* Over 50% of the store's revenue comes from consumer goods, followed by corporate and home-office in that order.\n* The store offers multiple types of shipping modes, but the standard class is by far the most popular.\n* The store has branches all over the country and the sales distribution is well spread out. The West brings in the most though, at 31.6% followed by East, Central and South.\n* Copiers are the most profitable sub-category of products, whereas tables are the least profitable, actually producing a net loss.\n* Continuing with sub-categories, Phones bring in the most revenue at 14.4% followed closely by Chairs at 14.3%","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frahulsm20%2Fstoredata","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frahulsm20%2Fstoredata","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frahulsm20%2Fstoredata/lists"}