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Install this application on your home screen for quick and easy access when you’re on the go.
Just tap then “Add to Home Screen”
Menu
Install this application on your home screen for quick and easy access when you’re on the go.
Just tap then “Add to Home Screen”
Friday 14 February 13:00–15:00 and 15:30–18:00
Saturday 15 February 09:00–12:30 and 14:00–17:30
On the first day we learn how to operate an efficient software environment using terminal commands, installing programming packages with Anaconda, and running code in the Jupyter Notebooks and Pycharm. We then learn about the different data types in Python.
On the second day you will learn how to scrape simple websites, and analyse and visualise data with Pandas.
1 credit (pass/fail grade). Attend at least 90% of course hours, participate fully in in-class activities, and carry out the necessary reading and/or other work prior to, and after, class.
Orsolya Vasarhelyi is an assistant professor at the Center for Collective Learning, and at the Institute of Data Analytics and Information Systems at Corvinus University in Budapest, Hungary.
Her research focuses on the gender differences in career development in project-based environments.
She is a Python enthusiast!
Day 1
We build the basics of a working Python programming environment, which will help later to advance in the language.
You will learn how to use the terminal to move between directories, copy and delete files, and run programs with bash/shell scripts.
After getting familiar with the terminal, we will look deeper into the Anaconda environment; learning how to run Jupyter notebooks and scripts from the terminal, and to manage packages and environments.
During the second part of the day you will learn about different data types (strings, integers, floats, lists, sets, dictionaries) and practice using them with fun programming games.
Day 2
We will learn the basics of web scraping using the Request and Beautiful soup libraries. We will introduce how to write functions, and help you get familiar with loops.
The last part of the day will give a gentle introduction to Pandas, focusing on importing and exporting data, running descriptive statistics, and basic data visualisation with Seaborn/Matplotlib.
No previous knowledge of programming is required.
This course is especially recommended for those who have limited or no programming experience, and who are planning to take the one-week course Python Programming for Social Sciences: Collecting, Managing, and Analysing Social Media Data
| Day | Topic | Details |
|---|---|---|
| 1 | Software environment Introduction to Python | |
| 2 | Introduction to scraping Introduction to Pandas and data visualisation |
| Day | Readings |
|---|---|
| 1 & 2 |
Given the practical nature of the class there is no necessary reading but these online tutorials might be useful, and the blog will give you an idea why Python is particularly useful for data analysis. |
Please prepare the open source / free software environment on your laptop by following these step-by-step instructions
Python 3: version > 3.5.
I recommend using Anaconda to install Python
Please also download the Python editor PyCharm (Community version)
Please bring your own laptop with the relevant software installed, as specified above.
Introduction to R
Python Programming for Social Sciences: Collecting, Managing and Analysing Social Media Data