{"id":26873638,"url":"https://github.com/vansh-py04/data-analysis-questions-pandas-numpy-sql","last_synced_at":"2026-04-18T02:06:49.462Z","repository":{"id":285269542,"uuid":"957567751","full_name":"vansh-py04/Data-Analysis-Questions-Pandas-NumPy-SQL","owner":"vansh-py04","description":"Solution to 450+ Data Science Tech Stack questions essential for Data Analysts and Scientists!","archived":false,"fork":false,"pushed_at":"2025-03-30T17:42:30.000Z","size":301,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-30T18:28:21.664Z","etag":null,"topics":["data-analysis","data-science","deepnote","machine-learning","numpy","pandas","python","sql"],"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/vansh-py04.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":"2025-03-30T17:25:24.000Z","updated_at":"2025-03-30T17:53:14.000Z","dependencies_parsed_at":"2025-03-30T18:38:30.952Z","dependency_job_id":null,"html_url":"https://github.com/vansh-py04/Data-Analysis-Questions-Pandas-NumPy-SQL","commit_stats":null,"previous_names":["vansh-py04/data-analysis-questions-pandas-numpy-sql"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/vansh-py04/Data-Analysis-Questions-Pandas-NumPy-SQL","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vansh-py04%2FData-Analysis-Questions-Pandas-NumPy-SQL","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vansh-py04%2FData-Analysis-Questions-Pandas-NumPy-SQL/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vansh-py04%2FData-Analysis-Questions-Pandas-NumPy-SQL/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vansh-py04%2FData-Analysis-Questions-Pandas-NumPy-SQL/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vansh-py04","download_url":"https://codeload.github.com/vansh-py04/Data-Analysis-Questions-Pandas-NumPy-SQL/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vansh-py04%2FData-Analysis-Questions-Pandas-NumPy-SQL/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31953517,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-18T00:39:45.007Z","status":"online","status_checked_at":"2026-04-18T02:00:07.018Z","response_time":103,"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-analysis","data-science","deepnote","machine-learning","numpy","pandas","python","sql"],"created_at":"2025-03-31T09:19:43.638Z","updated_at":"2026-04-18T02:06:49.414Z","avatar_url":"https://github.com/vansh-py04.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data-Analysis-Questions-Pandas-NumPy-SQL\n**This repository contains my solutions to questions originally created by the respective author.**\n# Description:\nThis repository contains 450 hands-on questions covering pandas, NumPy, and SQL, aimed at strengthening data analysis skills. These questions include:\n\n1. NumPy – Array manipulations, mathematical operations, and performance-efficient computations.\n\n2. Pandas – Data wrangling, transformations, aggregations, and performance optimizations.\n\n3. SQL – Querying, joins, subqueries, window functions, and advanced data retrieval techniques.\n\n---\n## Original Author: Avi Chawla\n\nLinkedIn: https://www.linkedin.com/in/avi-chawla/\n\n---\nIntroduction\n\nThis notebook has been created for you to practice three of the most common tools used in building any machine learning or data science applications, i.e., Pandas, NumPy, and SQL!\n\nThe practice questions provided will serve as a great resource for those who are looking to familiarize themselves with some of the most common functions used in these tools. \n\nThe whole exercise has been divided into nine separate notebooks. Below are the links to all the other notebooks for you to jump from one notebook to another:\n- **Pandas**\n\n1. Pandas Notebook 1: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/Pandas-Notebook-1-d693ac55-6455-40cf-ae34-867c6a02014e/notebook/6449493c84734151b11f4b6871f045d2#99f75bf946d04b9bb1daa9e14c2cfea9) \n2. Pandas Notebook 2: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/Pandas-Notebook-employee-dataset-7e3b6755-5d4b-464b-9b75-9c84667ae3bd/notebook/notebook-0de50f3b70834570b13b651dde44c491) \n\n3. Pandas Notebook 3: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/Pandas-Notebook-employee-part-2-adc5a3ee-5f61-4725-8e46-ccb07899acfc/notebook/notebook-78e3faf901da4f14881ef24e41c80bf6) \n\n4. Pandas Notebook 4: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/Pandas-after-employee-f84e02a1-fb6a-428e-af90-8dd99855749a/notebook/notebook-134ac20c38ef45e5a4432abd638e6c2e) \n\n- **NumPy**\n\n1. NumPy Notebook 1: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/Numpy-part-1-9b9979f2-b708-4292-b466-3d0157564c91/notebook/notebook-07232b5ebafe49b198a9c55c553414f1) \n\n2. NumPy Notebook 2: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/NumPy-Notebook-2-4456411e-2ddd-426d-8027-4881080027db/notebook/notebook-988aba30f33a45a3861adc4f6a6f338c)  \n\n3. NumPy Notebook 3: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/NumPy-Notebook-3-e6587114-b580-4249-b599-540de859e603/notebook/notebook-bb52759ea3f542eaaed9958b5df9c34b)\n\n- **SQL**\n\n1. SQL Notebook 1: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/SQL-Notebook-1-eac9d782-a9b1-4e84-a1f9-af14080a6121/notebook/notebook-697f04297c664d02901db0f85431512e) \n\n2. SQL Notebook 2: [Link](https://deepnote.com/workspace/avi-chawla-695b-aee6f4ef-2d50-4fb6-9ef2-20ee1022995a/project/SQL-Notebook-2-1914b214-be03-44a1-be63-ad99e98be639/notebook/notebook-e549236b988c42a5b53126a7ebb98127)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvansh-py04%2Fdata-analysis-questions-pandas-numpy-sql","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvansh-py04%2Fdata-analysis-questions-pandas-numpy-sql","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvansh-py04%2Fdata-analysis-questions-pandas-numpy-sql/lists"}