資料科學程式設計（一）
課程大綱
Course Objectives
Assesment
Before you start
GitHub in-class practice repo
平時成績
教師資訊
1
Introduction
1.1
Data Science v.s. Data Engineering
1.2
What should a full-scope data scientist know?
1.3
Data Service Development
1.4
Goal of this course
2
R and RStudio
2.1
主要參考書籍
2.2
What is R? What is RStudio?
R: programming language
RStudio
R-bloggers
2.3
RStudio environment
Editor
2.4
R Markdown
3
Start a Project
3.1
Project
Start a new project
Start a new file
Save with Encoding
3.2
GitHub Desktop
Add local repository
Publish repository
4
R Basics
4.1
主要參考書籍
4.2
Numeric (vector)
Operations on numeric objects
4.3
Character/String (vector)
Understand function usage
4.4
Factor
Change class
Ordered factor
4.5
Date and Time
Two different classes
Two ways to call functions
Generate date-time sequence
4.6
Operation on Strings
Subset
Join/Split
4.7
Taiwan date-time
4.8
練習題
線上練習
作業
作業repo下載方式
5
Data Frame
5.1
主要參考資料
5.2
Develop a Project
Lay out your strategy
Google G Suite
Retrieve useful packages
Import Google Sheets
5.3
Understand your packages
From RStudio help
Google the package
5.4
Data Frame
5.4.1
Create a data frame
5.4.2
Column/Row names
5.4.3
Extract observations: numerical/logical index
5.4.4
Relational operators
5.4.5
Logical operators
5.4.6
Object extraction:
$
and
[ ]
5.4.7
Generic replacement
5.5
練習題
課堂練習
作業
6
Data Transformation
6.1
主要參考資料
6.2
Pipe operator
6.3
Data cleaning
6.3.1
mutate
6.3.2
Parsing characters
6.3.3
Apply to multiple variables
参考資料
國立臺北大學 經濟學系
教師資訊
林茂廷老師
辦公室：社3F01
諮詢時間：（四）11am-12noon 請點Google月曆預約
email:
mtlin@gm.ntpu.edu.tw
