This is an open source text book for communication students to learn Python and data skills. The purpose of this course is to motivate the students to become a T-shape talent in communications field. The course involves intensive training of Python and quest in solving practical problems. This open source book collects all the materials related with lab exercises covering basic Python, data scraping, table manipulation and data mining.
You can get started by reading Week 00 note. This note requires no background in programming or technology. It walks you through our learning environment so you know how to find learning materials and seek for help effectively. You are also welcome to contact the Fall 2018 team for any questions, suggestions or discussions. The best way to ask question is to create an issue in this repo. Our teaching team stands by and regularly checks the issue tracker.
This repo is the text book by Pili Hu's offering of COMM7780/ JOUR7280 in HKBU.
- Notes: Week 00 - GitHub and markdown
- Notes: Week 01 - Kickoff: Terminal, shell and "hello world"
- Notes: Week 02 - Python as a powerful caculator: basics and arithmetics
- Notes: Week 03 - Python for everything: Data structure, control flow and code reuse
- Notes: Week 04 - Get structured data: CSV, JSON and API
- Notes: Week 05 - Get semi-structured data: Web scraping
- Notes: Week 06 - Advanced scraping: browser emulation, anti-crawler and other nitty gritties
- Notes: Week 07 - Work with table: data cleaning and pre-processing
- Notes: Week 08 - Work with table: 1D analysis and 2D analysis
- Notes: Week 09 - Present findings: data visualization and reproducible report
- Notes: Week 10 - Handle special data type: text, graph, time series, geographical
- Notes: Week 11 - Machine learning primer: clustering, classification, regression
You can search through our whole repo, including all the notes and FAQs using the built-in GitHub search function. For example, you can search for "encoding".
- Course Admin
- Setup Python Environment on Windows and MAC
- Shell
- Python Language Basics
- Python 2 v.s. Python 3
- Dataprep
- Pro Tips
- Resources
- Guide for contributor
- GitHub
- HTML
- Encoding
- pip
- module: geopy
- module: requests
- module: csv
- module: BeautifulSoup
- module: jupyter
- module: pandas
- module: seaborn
- module: matplotlib
- module: lxml
- module: python-twitter
- module: datetime
- module: selenium
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