xzzhang2 / 201901_budmc_dmhpy

This is the workshop for the Data and Media Hack 2019 on Python for data exploration and visualization.

Data & Media Hack 2019 Workshop: Python for data exploration and visualization

This repository stores the slides and code examples for the Data and Media Hack 2019 Event webpage on Python for data exploration and visualization at HKBU, 26 Jan 2019.

About the workshop

This 45-min lightening workshop, as one of the workshops for the Data and Media Hack 2019 Event webpage, attempts to explore fundamental issues on the intersection of programming, data exploration, and data visualization (based on a ready-made data), data-driven stories, and comparative political studies. It will also make a whirlwind tour of three Python data analytics packages, namely, Pandas, Matplotlib, and Seaborn. Topics include package installation, program execution, as well as data processing, and what this workshop tries to convey as "problem-driven data visualization and data-driven exploration."

Contents

1. Installing Python
2. Data processing & its five steps
3. Importing and knowing your data
   1. Pandas, Matplotlib, and Seaborn
   2. Getting the attributes of the your data
   3. Case selection
   4. Basic statistics
   5. Pivot table
4. Data exploration: exploring the data by visualization
   1. Univariate (unidimensional) and bivariate (two-way) data visualization
   2. Multivariate (multidimensional) problem-driven data visualization and data-driven exploration

Documents

1. The Slide
2. The Notebook

About the facilitator

Dr Xinzhi ZHANG (M.A. & Ph.D., CityU HK) is a Research Assistant Professor at JOUR. His research interests include comparative political communication, emerging technologies and social change, digital humanities, and data-driven journalism. His research works have been published on journals such as Computers in Human Behavior, International Political Science Review, and Digital Journalism. He teaches several interdisciplinary courses such as Social Media Data Acquisition and Processing with Python (Course Repo), AI for Digital Communication, and Algorithmic Culture. He is the Director of the Data and Media Communication Concentration at JOUR.

Acknowledgement

The codes in this notebook are modified from various sources, including the official tutorial and tutorial 01. Miss He Can and Mr Xu Chen, both from the Department of Computer Science at Hong Kong Baptist University, helped to fine tune and test the codes. All codes are for educational purposes only and released under the MIT licence.