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梁英宏 / 数据分析与可视化

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Apache-2.0

数据分析与可视化

介绍

该仓库资料由广东财经大学梁英宏老师编写,用于广东财经大学信息学院专业课程《数据可视化技术》(课程号:20110103)课程教学。

课程内容(持续更新,2024-05-23)

  1. 第一讲:数据分析与可视化介绍
  2. 第一次作业
  3. 第二讲:Numpy多维数组
  4. 第二次作业
  5. 第三讲:Pandas基础
  6. 第三次作业
  7. 第四讲:Pandas高级应用
  8. 第四次作业
  9. 第五讲:Matplotlib可视化
  10. Pandas练习
  11. 第五次作业
  12. 第六讲:matplotlib高级功能与数据可视化应用
  13. 第六次作业
  14. 第七讲:时间序列分析与可视化
  15. 第七次作业
  16. 第八讲:高级时序分析方法
  17. 第八次作业
  18. 第九讲:Seaborn可视化 Seaborn绘图思维导图
  19. 第九次作业
  20. 第十讲:SciPy科学计算与可视化
  21. 第十次作业
  22. 第十一讲:PyEcharts可视化
  23. 第十一次作业
  24. 第十二讲:sklearn机器学习与可视化
  25. 第十二次作业
  26. 第十三讲:opencv可视化技术

课程所需软件

  1. anancondaminiconda,用于使用jupyter交互式笔记本工具,并采用markdown语法和LaTeX排版工具编辑交互式笔记。
  2. 课程中示例以及作业的代码编写测试可在jupyter notebook中完成,亦可使用VS CodePyCharm( Community Edition)此类集成开发环境编写。
  3. 需要安装的Python库包括:numpy、Pandas、Matplotlib、 statsmodels、Prophet、PyFlux、Seaborn、PyeCharts、SKLearn、SciPy、request、cv2、jieba、wordcloud等。

授课老师

  1. 梁英宏老师 lyhwin@yeah.net lyh@gdufe.edu.cn 微信号:lyhwin_6160027

先修课程

  1. python程序设计
  2. 需要部分机器学习知识

在线资料

  1. python123

推荐参考教材

  1. 《Python数据分析与可视化》 清华大学出版社 ISBN9787302577584
  2. 《神经网络与深度学习》 机械工业出版社 ISBN9787111686859

参与贡献

  1. 课件与作业错误修正
  2. 编写相关章节的思维导图。
  3. 编写相关章节习题。
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