Data Wrangling in 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 Python. In particular, we will focus on pandas, a versatile library for data analysis, which often serves as the first building block in many data-science pipelines.

Required Readings

• 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;
• 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 pandas library.

Assignment 4 (Blackboard)

• Data Wrangling and Classes in Python.
• Due at 12:00 on Monday, 1st December (submission on Blackboard);
• Rename the file from 04_assignment.ipynb to 04_assignment_lastname_firstname_studentnumber.ipynb before submission.