學習資源

Youtube Playlist

• R1082: for NTU Journalism

• R tutorial 2019: for NTU ECON students

• Workshop2019: Workshop for news media

Github repository

• https://github.com/P4CSS/R4CSS-Crawlers for learning crawler only, assuming audiences have sufficient R basic knowledge

• https://github.com/P4CSS/R4CSS: for most of students without sufficient statistical background

• https://github.com/P4CSS/R1081 to learn R including Machine learning

Books

1. Jared P. Lander著、鍾振蔚譯（2018）精通大數據！R 語言資料分析與應用 第二版

2. J.D Long, Paul Teetor著、張靜雯譯（2019）R 錦囊妙計(第二版; R Cookbook 2nd Edition)

3. Learning statistics with r (Online bookdown)

4. Econometrics with R (Online)

5. Tidy Text Mining with R （Online）by Julia Silge and David Robinson <- Highly-Recommended, especially for tidyverse programming style of R and exploratory analysis.

6. R for Data Science (Online）

7. Hang-on Machine Learning with R Introducing classical ML methods one by one by corresponding R packages. Not mlr. Introduced by author-owned datasets, better than An Introduction to Machine Learning with R.

8. An Introduction to Machine Learning with R: Using built-in dataset to introduce ML for R

9. Supervised Machine Learning for Text Analysis in R （Online but incomplete）Julia Silge's New book. Focusing more on text-based ML and pulling-in DL into.

10. Machine Learning with R, the tidyverse, and mlr Wohoho....with mlr.

11. https://jirlong.gitbook.io/r/ (Incomplete)

12. Big book for R A big collection for R e-books (including above all)

13. 時序預測：https://otexts.com/fpp2/

14. Learning from social media analytics with R

15. Mastering text mining with R

16. Text Mining in Practice with R

17. Introduction book by 長庚’s epidemiologist http://yijutseng.github.io/DataScienceRBook/

Online Courses

• UChicago computing for social scientists: topic modeling, regressions, classifications, …
• Course text mining for social scientists https://tm4ss.github.io/docs/ ← Very good tutorial of using openNLP and tm package for English text mining.

  • Tutorial 2 crawling thegurdian.com

  • Repository cloned to local folder.

Datacamp

本門課建議R的初學者一邊看Datacamp線上學習平台的課程單元，一邊看本網站所提供的教材。Datacamp會帶給你一些R的基礎與法的硬知識，也就是每個操作、功能要怎麼使用、是如何被定義的；而本網站的教材則會帶你進入實用。過去的學習者往往表示，看過Datacamp後再看本網站的課程會有豁然開朗的感覺。

但是Datacamp僅允許免費看每個單元的第一章節，如果你們是本學期的修課生的話，老師會幫這門課程申請半年的免費使用，助教會蒐集你們註冊的E-mail；如果你們是一個研究社群的話，建議可以請老師用他的名義申請開個課，就可以免費使用半年，通常兩三天便會核准，申請連結在此。

I strongly recommended new R programming language learners, especially in my class, should learn basic concept from a great online interactive learning platform DataCamp, then study my materials to learn problem-solving skills. Besides, learners can use my materials to learn Taiwan domestic cases and web crawlers.

• [Datacamp] Introduction to R: Vectors, Materics, Factors, Data frames, Lists
• [Datacamp] Intermediate R: Conditionals and Control Flow, Loops, Functions, The apply family (Optional), Utilities (Optional)
• [Datacamp] Data Manipulation with dplyr: glimpse(), select(), filter(), arrange(), mutate() count(), transmnute() group_by(), summarize():
• [Datacamp] Data Visualization with ggplot2: You can also learn by case with the 2nd unit of Exploratory Data Analysis in R: Case Study
• [Datacamp] Joining Data with dplyr: Joining multiple dataset with shared key by left_joing(), right_join(), full_join(), inner_join()
• [Datacamp] Cleaning data with R: Reshaping data table form by tidyr::gather(), tidyr::spread(), tidyr::separate(), Dealing with missing values
• [Datacamp] String Manipulation with stringr in R: Detecting, matching, splitting, replacing Regular expression\