1752 - Python與數據分析
Data Analysis with Python
教育目標 Course Target
本課程循序漸近帶領學生從 Python 基礎程式語言出發,逐步掌握資料匯入、清理整理、探索性分析與視覺化等完整數據分析流程,並延伸至網路資料擷取與基礎建模概念。透過實作練習與學期分組報告,培養學生運用程式解讀資料意義、解決問題,並能以清楚的圖表與文字呈現分析結果的能力。
完成本課程後,學生將能夠:
1. 建立程式思維與問題解決能力
2. 熟悉 Python 語言與資料分析常用工具
3. 掌握資料清理與整理,進行探索性資料分析與基礎統計解讀
4. 資料視覺化的詮釋與表達
5. 完成案例分析或學期分組報告
This course gradually leads students to start from the basic programming language of Python and gradually master the complete data analysis process such as data import, cleaning, exploratory analysis and visualization, and extends to network data acquisition and basic modeling concepts. Through practical exercises and semester group reports, students will develop their ability to use programs to interpret the meaning of data, solve problems, and present analysis results in clear charts and text.
After completing this course, students will be able to:
1. Establish procedural thinking and problem-solving skills
2. Familiar with Python language and common tools for data analysis
3. Master data cleaning and organization, conduct exploratory data analysis and basic statistical interpretation
4. Interpretation and expression of data visualization
5. Complete case analysis or semester group report
課程概述 Course Description
本課程旨在培養學生運用 Python 進行資料處理與數據分析的核心能力,從零開始建立程式思維,並透過實作練習熟悉完整的資料分析流程。課程內容包含基礎程式語法、資料取得與匯入、資料清理與整理、探索性資料與統計分析,以及資料視覺化的解讀與表達。學生將學習常見分析套件與工具(如 Pandas、NumPy、Matplotlib/Seaborn 等),並透過議題導向的練習,將資料轉化為可理解、可應用於決策的支持;最後整合所學,於期末完成一份分組報告。
This course aims to cultivate students' core abilities in using Python for data processing and data analysis, build programming thinking from scratch, and become familiar with the complete data analysis process through practical exercises. The course content includes basic programming syntax, data acquisition and import, data cleaning and organization, exploratory data and statistical analysis, and data visualization interpretation and expression. Students will learn common analysis packages and tools (such as Pandas, NumPy, Matplotlib/Seaborn, etc.), and through topic-oriented exercises, transform data into understandable support that can be applied to decision-making. Finally, students will integrate what they have learned and complete a group report at the end of the semester.
參考書目 Reference Books
無指定教科書,教師自行編製講義。
There is no designated textbook, teachers prepare their own handouts.
評分方式 Grading
| 評分項目 Grading Method |
配分比例 Percentage |
說明 Description |
|---|---|---|
|
作業 Homework |
20 | |
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期中實作考試 midterm practical exam |
25 | |
|
期末實作考試 Final practical exam |
25 | |
|
課堂參與 class participation |
20 |
授課大綱 Course Plan
點擊下方連結查看詳細授課大綱
Click the link below to view the detailed course plan
相似課程 Related Courses
無相似課程 No related courses found
課程資訊 Course Information
基本資料 Basic Information
- 課程代碼 Course Code: 1752
- 學分 Credit: 3-0
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上課時間 Course Time:Monday/2,3,4[SS106]
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授課教師 Teacher:游雅婷
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修課班級 Class:經濟系3,4
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選課備註 Memo:列入113學年度起入學、一經組、產經組之指定選修學分,不辦理教師簽名選課。
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