Programming for Data Analytics (using R and Python)

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Course description

We have entered a big-data era. Thus, it is quite important for a business school student to learn how to process, relatively speaking, big data. Among many open-source statistical software, R and Python are the top two. In this course, students learn both R and Python. For the first half semester, students learn how to install R, define a variable, write simple functions, run a loop to process hundred or thousand data sets, and more. After understanding basic concepts and functionalities, R packages will be discussed. Then students learn Python. In terms of data, students learn how to download, and process public data associated with economics, finance and accounting, such as FRED (Federal Reserve Economic Data), UCI Machine Learning Data Depository, SEC quarterly index files, SEC Financial Statement Data Sets, and French’s Data Library.

DANL100: syllabus

Text book: Learning R and Python for Business School Students by Yuxing Yan (2023):

    Publisher: Cambridge Scholars Publishing, website | ( preface | or here )

Course learning goals:

After successfully completing this course, students are expected to demonstrate their ability to:

  • Understand the principles of probability. (LG1)
  • Understand the properties of distributions. (LG1, LG2)
  • Apply statistical concepts to many business applications. (LG4)
  • Collect, organize, describe data and make statistical inference. (LG3).
  • Understand the concept of confidence interval and use it to make inference about the data. (LG1, LG2)

    • All chapters

      ------R for the first half semester ----------------------

    •                     Chapter |                                              videos ⇩ |       ⇩ List of code
    •   Chapter #1: R installation and basics |                  video #1 | code1
    •   Chapter #2: Simple R functions |                          video #2 | code2
    •   Chapter #3: Open data |                                         video #3 | code3
    •   Chapter #4: Data input using R |                           video #4| code4
    •   Chapter #5: Simple data manipulation using R |   video #5| code5
    •   Chapter #6: Data output using R |                         video #6| code6
    •   Chapter #7: R loops and conditons |                      videos #7| [2] | code7
    •   Chapter #8: Date varariable, simple plot               video #8| code8
    •   Chapter #9: subset,merge data sets                        video #9| code9
    •   Chapter #10: Matrix manipulation                         video #10| code10
    •   Chapter #11: String manipulation                          video #11| code11
    •   Chapter #12: Introduction to R packages              video #12| code12
    •   Chapter #13: Zip,SAS,Pickle,Google Drive          video #13| code13

      • ------Python for the second half semester ----------------------

    •   Chapter #14: Python basics                                     video #14| code14
    •   Chapter #15: Introduction to Python modules        video #15| code15
    •   Chapter #16: Data input                                          video #16| code16
    •   Chapter #17:Data and output                                  video #17| code17
    •   Chapter #18: Python loops, conditions                   video #18| code18
    •   Chapter #19: Data minipulation                              video #19| code19
    •   Chapter #20: Grphs, plots,data visualization          video #20| code20
    •   Chapter #21: Python string manipulations             video #21| code21

      • ------R and Python for various projects ------

    •   Chapter #22: There types of project: Project #1       video #22| code21
    •   Chapter #23: Project 2: SEC filings       code23
    •   Chapter #24: Projdct 2: Census data       code24
    •   Chapter #30: Term projects

    Download and Install R

    My videos for this course

    Links

    Economics & Finance Dept | add later | add later