https://github.com/qzcool/sac

中国证券业协会数据分析和可视化。Data Analysis and Visualization for Securities Association of China (SAC).
https://github.com/qzcool/sac

china data-analysis finance python

Last synced: 7 months ago
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中国证券业协会数据分析和可视化。Data Analysis and Visualization for Securities Association of China (SAC).

• Host: GitHub
• URL: https://github.com/qzcool/sac
• Owner: qzcool
• Created: 2018-09-17T00:34:05.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2019-03-04T10:09:48.000Z (almost 7 years ago)
• Last Synced: 2025-04-05T19:51:16.501Z (10 months ago)
• Topics: china, data-analysis, finance, python
• Language: Jupyter Notebook
• Homepage: https://qzcool.github.io/SAC/
• Size: 9.64 MB
• Stars: 7
• Watchers: 1
• Forks: 1
• Open Issues: 19
• Metadata Files:
  • Readme: README.md

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README

          
# 中国证券业协会数据分析和可视化 Data Analysis and Visualization for Securities Association of China (SAC)

[![Codacy Badge](https://api.codacy.com/project/badge/Grade/fca6cf377226493c9d9d9dee7c84e8a2)](https://app.codacy.com/app/qiao.zhang.qz/SAC?utm_source=github.com&utm_medium=referral&utm_content=qzcool/SAC&utm_campaign=Badge_Grade_Dashboard)

## 数据获取及开源 Open Data 

提供**经过整理的证券业协会公开数据和其他开源渠道数据**，格式为CSV，定期自动更新。

Open-source structured public data of SAC, in .csv format, regularly auto-updated.

1. 证券公司：全列表，大约8KB。

2. 从业人员：全列表，所有公司信息合并显示，大约30MB。

## [从业人员执业注册信息公示 SAC Publicity Report](http://exam.sac.net.cn/pages/registration/sac-publicity-report.html)

所有数据分析都会函数化并输出为JSON文件API，以便后续可视化等应用的调用。

## 安装和使用

请根据`requirements.txt`文件的声明安装所有依赖。`start.ipynb`文件包含所有函数的调用方法实例。若要直接使用数据，请下载`.csv`格式的数据文件。

## 技术栈 Tech Stack

| 模块 Module            | 使用的依赖 Dependencies                                  |

|-------------------------------|-------------------------------------------------|

| 数据开源 Open Data            | Selenium                                         |

| 数据分析 Data Analysis        | pandas                                           |

| 数据可视化 Data Visualization | Plotly/Dash, D3.JS/ECharts.JS, GitHub Pages |

## 反馈 Feedback

欢迎提出在issues中提出你感兴趣的问题。 Feel free to send a pull request or report an issue. Also, welcome to drop your questions about SAC and we will see if new features should be integrated.