Processing data in Python -ZIP

ogólnouniwersyteckie

The course assumes that participants already know Python at a basic level, like for example after the “Introduction to programming in Python” course.

The aim of this course is the introduction to processing data in Python. We will learn more advanced Python elements as well as how to process files and how to use specialized libraries for data processing: NumPy and pandas.

Classes are offered as part of the Integrated Development Programme of the University of Warsaw (ZIP), co-financed from the European Social Fund under POWER 3.5. The rules for the use of general university courses for Ph.D. students within the ZIP framework (UW Ph.D. Students' Regulations) are available at: www.zip.uw.edu.pl.

We will learn how to process data in Python by creating programs at each meeting.

The course enables acquiring analytical and Python programming competencies and gives participants insight into the English vocabulary from the computer science domain.

Topics presented during the course:

• Revision of the Python programming language and code writing standards,

• Introduction to Linux with emphasis on its command-line interface,

• Version control with Git,

• Modules in Python,

• Jupyter and its use in Python environment,

• File processing in Python,

• Regular expressions,

• The NumPy library,

• The pandas library,

• Software testing,

• Work with debugger and profiler,

• Cython as a tool for speeding up Python programs,

• Algorithms and programs,

• Use of modern IDEs (with PyCharm as an example).

The course has 30 teaching hours (7*4h + 1*2h meetings).

Course on various methods for processing data in Python. Python is a very flexible, popular, and powerful language enabling the processing of large amounts of data stored in different formats.

The teacher for many years has had the pleasure of teaching programming (and not only) during numerous classes at the University of Warsaw (and not only), mainly at the Faculty of Mathematics, Informatics and Mechanics (and not only)

- Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter, Wes McKinney, 3rd ed., 2022;

- Python Crash Course, a hands-on, project-based introduction to programming, 2nd ed. Eric Matthes, 2019;

- Learning Python, Mark Lutz, 5th ed., 2013;

- Programming Python, Mark Lutz, 4th ed., 2011;

- Pro Git , Scott Chacon i Ben Straub, 2nd ed., 2014.

Students, after finishing the course, will be able to write Python programs processing large data files.

Programs written during classes