Intro to Python for Data Analysis
Workshop at General Assembly (Washington, DC) on October 20, 2014.
Instructor: Kevin Markham
- Why Python? (10 min.)
- Characteristics of Python
- Python vs. R
- Why Anaconda?
- Just Enough Python Basics (45 min.)
- Getting Data (20 min.)
- Looking at Data (5 min.)
- Pandas for Data Exploration (70 min.)
- Brief Tour of Other Modules for Data Science (5 min.)
- Recommended Resources for Self-Learning (10 min.)
- Basic Python: Codecademy, Google's Python Class, Python Tutor (to visualize code execution)
- Pandas: tutorial, book: "Python for Data Analysis" (includes numpy and basic Python)
- Web scraping: tutorial
- Command line: tutorial
- Git and GitHub: video series
- Machine learning: book and videos: "An Introduction to Statistical Learning", scikit-learn tutorials, Data Science as a Sport (video), Kaggle Titanic competition
- Data science in general: ebook: "Analyzing the Analyzers"
- Data-focused newsletters: Center for Data Innovation, O'Reilly Data Newsletter, Data Community DC
- Full-fledged courses: Data Science Specialization (9 short courses by JHU in R), Machine Learning (1 course by Andrew Ng in Matlab/Octave), Learning from Data (1 course, programming language not specified)
- General Assembly's Data Science Course (5 min.)
- Ask Me Anything