Python conditionals, loops, functions, aggregating (continued)
Description
This lecture discusses the general strategic impact of data, open data, data encoding, data provenance, data wrangling, includeing merging, aggregation, filtering. Continued introduction to coding includes conditionals, loops, functions, missing values, filtering, group-by. We will also introduce a basic Kaggle model for the Titantic dataset.
Learning Objectives
None
Readings (and Tasks to Be Completed Before Class)
The Hitchhikers Guide to Python - Code Style
Getting Started with Python Environments
Install Anaconda’s Python (3.X)