Python/R for Data Science

Lecture notes for Fall 2023 at Arkansas Tech University

Author

Xinli Xiao

Published

November 6, 2023

Preface

This is the lecture notes for STAT 2304 Programming languages for Data Science Fall 2023 at ATU. If you have any comments/suggetions/concerns about the notes please contact me at .

References

[1]
Klosterman, S. (2021). Data science projects with python: A case study approach to gaining valuable insights from real data with machine learning. Packt Publishing, Limited.
[2]
McKinney, W. (2017). Python for data analysis: Data wrangling with pandas, NumPy, and IPython. O’Reilly Media.
[3]
Shaw, Z. A. (2017). Learn python 3 the hard way. Addison Wesley.
[4]
Sweigart, A. (2020). Automate the boring stuff with python, 2nd edition practical programming for total beginners: Practical programming for total beginners. No Starch Press.
[5]
Prabhakaran, S. (2018). 101 NumPy exercises for data analysis (python).
[6]
Grolemund, G. (2014). Hands-on programming with r: Write your own functions and simulations. O’Reilly Media.
[7]
Prabhakaran, S. (2018). 101 pandas exercises for data analysis.
[8]
Beuzen, T. and Timbers, T. (2022). Python packages. Taylor & Francis Group.
[9]
Wickham, H. and Grolemund, G. (2017). R for data science: Import, tidy, transform, visualize, and model data. O’Reilly Media.
[10]
Youens-Clark, K. (2020). Tiny python projects. Manning Publications.