1B013(01734080): Data Analysis Tools and Practice (Spring 2017)

Time: Wednesday 14:00-17:00 Pm

Location: 3205, Teaching Builing, DaXing

Class web site: http://sunhp.org/da2017

Instructor: Huiping Sun (sunhp(at)ss.pku.edu.cn)

TA: Xuwen Han

Course Description

This course will introduces the feature of data analysis with R and RStudio as well as common methods of data analysis based on combination of essential operation experiments and specific case experiments. It covers R and RStudio software, R programming language, R basic graphics methods, data management, data visualization with ggplot2, statical modeling and procedures, and others useful R packages. This course helps students improve the ability of conducting data analysis in related fields independently and finishing analysis report.

Course Textbook

Course Schedule




February 22

01. Course Overview [Slides]

March 01

02. R Object I [Slides]]

March 08

03. R Object II [Slides]

  • Textbook. Charpter 4: Basic Data Management.
  • Textbook. Charpter 5: Advanced Data Management.

March 15

04. R Language I [Slides]

  • Textbook. Charpter 2.3: Data Input.
  • Textbook. Charpter 5.4: Control Flow.
  • Textbook. Charpter 5.5: User-written Functions.
  • Data: Data04

March 22

05. R Graphics I [Slides]

  • Textbook. Charpter 3: Getting Started with Graphs.
  • Textbook. Charpter 6: Basic Graphs (6.1-6.3).
  • Hrishi V. Mittal. R Graphs Cookbook. Charpter 1: Basic Graph Functions. PACKET. 2011
  • Hrishi V. Mittal. R Graphs Cookbook. Charpter 2: Beyond Basics: Adjusting Key Parameters. PACKET. 2011
  • Data: Data05

March 29

06. R Graphics II [Slides]

  • Hrishi V. Mittal. R Graphs Cookbook. Charpter 3, 4, 5, 6, 7. PACKET. 2011
  • Data: Data06

April 05

07. ggplot2 I [Slides]

  • Hadley Wickham. ggplot2: Elegant Graphics for Data Analysis. Charpter 1-4. Springer. 2009
  • Winston Cbang. R Graphics Cookbook. Charpter 2-5. O'RELLY. 2013
  • Data: Data07

April 12

08. R Statistics I [Slides]

  • Textbook. Charpter 7: Basic Statistics.
  • Textbook. Charpter 8: Regression.
  • Textbook. Charpter 14: Principal Components and Factor Analysis.
  • Data: Data08

April 19

09. R Statistics II [Slides]

  • Textbook. Charpter 9: Analysis of Variance.

April 26

10. R Packages I: Time Series

[lubridate, forecast, zoo, TSA, TimeSeires]

  • Textbook v2. Charpter 15: Time Series.

May 03

11. R Packages II: String, Word Segmentation, Crawler, etc.

[stringr, Rwordseg&wordcloud2, jiebaR, RCurl, RVEST, glm]


May 10

12. ggplot2 II [Slides]

  • Hadley Wickham. ggplot2. Elegant Graphics for Data Analysis. Springer. 2009
  • Hrishi V. Mittal. R Graphs Cookbook. PACKET. 2011
  • Data: Data12

May 17

13. R Packages III:

[quantmod1, quantmod2, ez, reshape2, manipulate, ggvis, shiny]


May 24

14. R Packages IV:

[ctree, randomForest, tm, rpart, e1071, nnet, Rhadoop, REmap]


Mar 31

15. R Packages V:

[mclust, Rworldmap, leaflet, coin, dplyr]


June 7

16. Summary [Slides]


Course Grading

The grading scheme is as follows:

Course Projects

Course References