{"id":20673079,"url":"https://github.com/relph1119/python-data-analysis","last_synced_at":"2025-09-03T13:07:10.672Z","repository":{"id":37226743,"uuid":"245809274","full_name":"Relph1119/python-data-analysis","owner":"Relph1119","description":"python数据分析（包括pandas、numpy、seaborn）","archived":false,"fork":false,"pushed_at":"2022-08-23T18:05:05.000Z","size":27522,"stargazers_count":13,"open_issues_count":10,"forks_count":12,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-11-16T20:39:51.175Z","etag":null,"topics":[],"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/Relph1119.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}},"created_at":"2020-03-08T12:21:26.000Z","updated_at":"2024-09-23T07:27:39.000Z","dependencies_parsed_at":"2022-06-22T04:47:33.447Z","dependency_job_id":null,"html_url":"https://github.com/Relph1119/python-data-analysis","commit_stats":null,"previous_names":["relph1119/python-data-analysis"],"tags_count":null,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Relph1119%2Fpython-data-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Relph1119%2Fpython-data-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Relph1119%2Fpython-data-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Relph1119%2Fpython-data-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Relph1119","download_url":"https://codeload.github.com/Relph1119/python-data-analysis/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224970141,"owners_count":17400294,"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":[],"created_at":"2024-11-16T20:39:59.463Z","updated_at":"2024-11-16T20:40:04.558Z","avatar_url":"https://github.com/Relph1119.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 数据分析工具的学习记录\n\u0026emsp;\u0026emsp;其中包括pandas、numpy、seaborn的练习题和学习资料，均使用jupyter notebook编写。  \n\n## 文件目录\n\u003cpre\u003e\nnumpy_exercises---------------------numpy100题\npandas_exercises--------------------pandas练习题\nquestion----------------------------问题分析与总结\nseaborn_exercises-------------------seaborn学习资料（包括matplotlib）\n\u003c/pre\u003e\n\n## 版本\nnumpy：1.18.1  \npandas：1.0.1  \nseaborn：0.10.0  \nmatplotlib：3.2.0\n\n## 解题总结\n**numpy练习题：**      \n1. 第49题：将`np.set_printoptions(threshold=np.nan)`修改成`np.set_printoptions(threshold=np.inf)`\n2. 第75、80、98、100题不好理解\n\n**pandas练习题**  \n1. 第6章-Wind_Stats中的步骤7，将`data.shape[0] - data.isnull().sum()`修改成`data.notnull().sum()`\n2. 第6章-Wind_Stats中的步骤11，将`january_winds = data.query('month == 1')`修改成`january_winds = data[data.month == 1]`\n\n**seaborn练习题**  \n1. seaborn高于0.8版本，需要显式使用seaborn样式：`sns.set()`\n2. 第2章，需要安装ipyweights（一个jupyter的插件）\n3. 第4章，需要安装statsmodels库\n4. 第5章，2.7.1节中catplot通过kind设置图形显示类别，接口很简洁，也很方便\n\n## 主要贡献者（按首字母排名）\n[@胡锐锋-天国之影-Relph](https://github.com/Relph1119)\n\n## 未来计划\n1. scipy的学习\n\n## 参考资料\n1. [numpy练习题](https://github.com/rougier/numpy-100)\n2. [pandas练习题](https://github.com/guipsamora/pandas_exercises)\n3. [seaborn练习题](https://github.com/blueliberty/Seaborn)\n4. [Python数据分析，numpy、pandas及其思维导图](https://www.jianshu.com/p/9a9742693b0e)\n5. [这十套练习，教你如何用Pandas做数据分析](https://www.kesci.com/api/notebooks/5c69407b336a0d002c184f46/RenderedContent)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frelph1119%2Fpython-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frelph1119%2Fpython-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frelph1119%2Fpython-data-analysis/lists"}