{"id":22937645,"url":"https://github.com/rickiepark/hg-da","last_synced_at":"2025-04-06T19:11:17.646Z","repository":{"id":44327255,"uuid":"372652733","full_name":"rickiepark/hg-da","owner":"rickiepark","description":"\u003c혼자 공부하는 데이터 분석 with 파이썬\u003e의 코드 저장소","archived":false,"fork":false,"pushed_at":"2024-12-15T04:36:23.000Z","size":27174,"stargazers_count":64,"open_issues_count":0,"forks_count":52,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-03-30T18:08:49.249Z","etag":null,"topics":["data-analysis","data-science","data-visualization","machine-learning","matplotlib","numpy","pandas","scikit-learn","scipy"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rickiepark.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2021-05-31T23:41:34.000Z","updated_at":"2025-03-30T08:43:46.000Z","dependencies_parsed_at":"2023-11-13T05:32:05.328Z","dependency_job_id":"638ac6fa-c8d9-4f93-a307-1dbf40674aa5","html_url":"https://github.com/rickiepark/hg-da","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/rickiepark%2Fhg-da","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rickiepark%2Fhg-da/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rickiepark%2Fhg-da/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rickiepark%2Fhg-da/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rickiepark","download_url":"https://codeload.github.com/rickiepark/hg-da/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247535516,"owners_count":20954576,"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","data-science","data-visualization","machine-learning","matplotlib","numpy","pandas","scikit-learn","scipy"],"created_at":"2024-12-14T12:13:53.910Z","updated_at":"2025-04-06T19:11:17.622Z","avatar_url":"https://github.com/rickiepark.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 혼자 공부하는 데이터 분석 with 파이썬\n\n\u003ckbd\u003e\u003cimg src=\"https://tensorflowkorea.files.wordpress.com/2022/12/ed98bcec9e90-eab3b5ebb680ed9598eb8a94-eb8db0ec9db4ed84b0-ebb684ec849d-with-ed8c8cec9db4ec8dac_ecbba4ebb284.png\" height=\"700\"\u003e\u003c/kbd\u003e\n\n이 저장소는 \u003c혼자 공부하는 데이터 분석 with 파이썬\u003e(한빛미디어, 2022)의 코드를 담고 있습니다.\n\n각 절의 코드는 독립된 하나의 노트북으로 제공됩니다. 예를 들어 1장 3절의 코드는 01-3.ipynb에 있습니다. 모든 노트북은 구글 코랩을 사용해 실행해 볼 수 있습니다. 노트북을 클릭하면 구글 코랩으로 열 수 있는 링크를 볼 수 있습니다.\n\n상세 목차와 해당 절의 주피터 노트북 링크는 다음과 같습니다.\n\n- 1장 데이터 분석을 시작하며\n  - 데이터 분석이란\n  - 구글 코랩과 주피터 노트북\n  - [3절 이 도서가 얼마나 인기가 좋을까요?](01-3.ipynb)\n- 2장 데이터 수집하기\n  - [1절 API 사용하기](02-1.ipynb)\n  - [2절 웹 스크래핑 사용하기](02-2.ipynb)\n- 3장 데이터 정제하기\n  - [1절 불필요한 데이터 삭제하기](03-1.ipynb)\n  - [2절 잘못된 데이터 수정하기](03-2.ipynb)\n- 4장 데이터 요약하기\n  - [1절 통계로 요약하기](04-1.ipynb)\n  - [2절 분포 요약하기](04-2.ipynb)\n- 5장 데이터 시각화하기\n  - [1절 맷플롯립 기본 요소 알아보기](05-1.ipynb)\n  - [2절 선 그래프와 막대 그래프 그리기](05-2.ipynb)\n- 6장 복잡한 데이터 표현하기\n  - [1절 객체지향 API로 그래프 꾸미기](06-1.ipynb)\n  - [2절 맷플롯립의 고급 기능 배우기](06-2.ipynb)\n- 7장 검증하고 예측하기\n  - [1절 통계적으로 추론하기](07-1.ipynb)\n  - [2절 머신러닝으로 예측하기](07-2.ipynb)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frickiepark%2Fhg-da","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frickiepark%2Fhg-da","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frickiepark%2Fhg-da/lists"}