教學大綱表 (111學年度 第1學期)
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課程名稱
Course Title		 (中文) Python數據分析
(英文) Data Analysis With Python 		開課單位
Departments		 電機工程研究所
課程代碼
Course No.		 E4560B
授課教師
Instructor		 陳建華
學分數
Credit		 3.0 必/選修
core required/optional		 選修 開課年級
Level		 研究所
先修科目或先備能力(Course Pre-requisites)：
課程概述與目標(Course Overview and Goals)：This course is about processing, cleaning, and crunching data in Python. The goal is to offer a guide to the Python programming language and its data-oriented library ecosystem and tools.
教科書(Textbook) Python for Data Analysis, 2nd Ed., 2017, by Wes McKinney,
O'Reilly Media.
參考教材(Reference)
圖書館電子書(E-book of the Library) Data Analysis and Visualization Using Python,
https://link.springer.com/book/10.1007/978-1-4842-4109-7

Numerical Python,
https://link.springer.com/book/10.1007/978-1-4842-4246-9

Python Data Analytics,
https://link.springer.com/book/10.1007/978-1-4842-0958-5
課程大綱 Syllabus 學生學習目標
Learning Objectives		 單元學習活動
Learning Activities		 學習成效評量
Evaluation		 備註
Notes
序
No.		 單元主題
Unit topic		 內容綱要
Content summary
1 Preliminaries (week 1) - why python
- environment setup 		set up the development environment  
2 Python basics (weeks 2~3) - IPython basics
- Python language basics 		learn the scalar types and control flow  
3 Built-in data structures, functions and files (weeks 4~5) - data structures
- functions
- files 		learn the built-in data structures  
4 NumPy basics (weeks 6~7) - array
- vectorized computation
- linear algebra 		learn NumPy  
5 期中考 (week 8) 期中考 期中考  
6 pandas basics (weeks 9-10) - pandas data structures
- pandas functionality
- descriptive statistics 		learn pandas basics  
7 Data loading and file formats (weeks 11-12) - text data formats
- binary data format
- web API
- database 		learn different data formats  
8 Data Cleaning (weeks 13-14) - missing data
- data transformation
- string manipulation 		learn data preparation  
9 Data wrangling (week 15) - hierarchical indexing
- combining and merging
- reshaping and pivoting 		learn data wrangling  
10 Visualization (week 16) - matplotlib API
- plotting with pandas and seaborn 		learn data plotting  
11 time series (week 17) - time series basics
- period arithmetic
- resampling and frequency conversion
- moving window functions 		learn time series  
12 期末考 (week 18) 期末考 期末考  


教學要點概述：
1.自編教材 Handout by Instructor：
□ 1-1.簡報 Slids
□ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
□ 1-4.教科書 Textbook
□ 1-5.其他 Other
□ 2.自編評量工具/量表 Educational Assessment
□ 3.教科書作者提供 Textbook

成績考核 Performance Evaluation： 期末考：30%   期中考：30%   作業：40%  

教學資源(Teaching Resources)：
□ 教材電子檔(Soft Copy of the Handout or the Textbook)
□ 課程網站(Website)
課程網站(Website)：https://iclass.ttu.edu.tw
扣考規定：https://curri.ttu.edu.tw/p/412-1033-1254.php