Data Wrangling in R and Python

Lecture Slides Lecture Slides (pdf) Lecture Slides (ipynb)

Tutorial Exercise Tutorial Exercise (pdf) Tutorial Exercise (ipynb)

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This week we will turn from broader programming and software engineering concepts to practical approaches of working with data in R and Python.

Required Readings

• Wickham, Çetinkaya-Rundel & Grolemund Chs 4 Data transformation, 6 Data tidying, 8 Data import;
• McKinney Chs 4: NumPy Basics, 5: Getting Started with Pandas, 6: Data Loading, Storage and File Formats, 7: Data Cleaning and Preparation, 8: Data Wrangling: Join, Combine and Reshape;

Additional Readings

• Guttag Ch 23: Exploring Data with Pandas;
• Peng Chs 13: Managing Data Frames, 18: Loop Functions.
• Charles R. Harris et al. 2020. Array programming with NumPy. Nature 585 (7825): 357-362. https://doi.org/10.1038/s41586-020-2649-2

Tutorial

• Data input and output;
• Working with data manipulation library.