課程大綱

課程資訊

課程名稱

資料分析與視覺化
Data Analysis and Visualization

開課學期

106-2

授課對象

授課教師

鄭瑋

課號

LIS5087

課程識別碼

106 50900

班次

學分

3.0

全/半年

半年

必/選修

選修

上課時間

星期一2,3,4(9:10~12:10)

上課地點

圖資編目室

備註

兼通識A6*。。A6*:量化分析與數學素養領域。可充抵通識
總人數上限：35人
外系人數限制：8人

Ceiba 課程網頁

http://ceiba.ntu.edu.tw/1062LIS5087_

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課程概述

This introductory course will prepare non-CS undergraduate students to analyze digital data and create effective visualizations. Students will learn analytic and visualization techniques drawn from various areas, including information design, visual art, and cognitive principles. This course consists of five mini-modules.
- Concepts around digital data lifecycle
- Data analysis basics
- Visualization basics and storytelling with data
- Data labs: Python
- Thematic data analysis & viz labs

These mini-modules are designed to guide students through the key steps in an execution of a data storytelling project, which involves identify needs, collect, cleanse, process, analyze, visualize, and communicate with digital data.
The course is comprised of hand-on activities, assigned readings, assignments, final project, and class activities. Students will be expected to work with various software applications and Python throughout the semester.

課程目標

At the conclusion of this course, students will be able to
- Engage in academic and technical discussions on concepts and techniques related to digital data
- Describe different natures of data (e.g., types, format, disciplines) and their corresponding analysis solutions
- Apply major technologies of data visualization in different themes and data format
- Execute a data storytelling project which involves collect, cleanse, process, analyze, visualize, and communicate digital data.

課程要求

Prerequisite (recommended but not mandatory): Any introductory courses of statistics

預期每週課後學習時數

Office Hours

指定閱讀

待補

參考書目

Recommended books:
1. Knaflic, C. N. (2015). Storytelling with data: A data visualization guide for business
professionals. John Wiley & Sons.
2. Cairo, A. (2012). The Functional Art: An introduction to information graphics and
visualization. New Riders.
3. Cairo, A. (2016). The truthful art: Data, charts, and maps for communication. New
Riders.

評量方式
(僅供參考)

No.	項目	百分比	說明
1.	Class participation and weekly Labs	45%
2.	Mid-term (take home)	25%
3.	Term project: Digital storytelling	30%	The term project is designed for students to integrate and extend knowledge acquired throughout the course and to apply that knowledge to present a digital story with collected data. Students are required to work in groups of 1-2 people (TBD). Experience suggests that successful teams require expertise in data selection, design, implementation, and project management. Rubric break-down in this part (40 points): Write-ups: - Data source selection, gathering and cleansing process (8 points) - Data analysis process (8 points) - Data visualization (8 points) Presentation: - Storytelling in the oral presentation (16 points)

課程進度

週次	日期	單元主題
第1週	2/26	Intro; course overview
第2週	3/05	Digital data: concepts and basics; Descriptive statistics
第3週	3/12	Exploratory data analysis
第4週	3/19	Visualization principles and critics
第5週	3/26	Python Lab I: Setting up Python working environment
第6週	4/02	Spring break (no class)
第7週	4/09	Effective data visualization: chart types and hands-on practice
第8週	4/16	Finding data sources; Discover, Access and Distill (DAD); data cleansing with OpenRefine
第9週	4/23	Python Lab II: Common string operations, RE (ATTN- Hours expended: 09:20 to 1:00 PM)
第10週	4/30	Mid-term week (take home)
第11週	5/07	Python Lab III: Viz libraries-Pandas (ATTN- Hours expended: 09:20 to 1:00 PM)
第12週	5/14	Data storytelling; Data journalism
第13週	5/21	Thematic DAV Labs: Network concepts and visualization; Gephi
第14週	5/28	Final Project Prep week
第15週	6/04	Student showcase (ATTN- Hours expended: 09:20 to 1:00 PM)
第16週	6/11	Student debriefing in Office 17 (by appointment)
第17週	6/18	National holiday