With many businesses turning to Python’s powerful data science ecosystem to analyze their data, understanding how to avoid introducing bias into datasets is absolutely vital. If you’ve studied some statistics, then you’re probably familiar with terms like reporting bias, selection bias, and sampling bias. There’s another type of bias that plays an important role when you’re dealing with numeric data: rounding bias.
Understanding how rounding works in Python can help you avoid biasing your dataset. This is an important skill. After all, drawing conclusions from biased data can lead to costly mistakes.
In this video course, you’ll learn:
- Why the way you round numbers is important
- How to round a number according to various rounding strategies
- How to implement each strategy in pure Python
- How rounding affects data and which rounding strategy minimizes this effect
- How to round numbers in NumPy arrays and pandas DataFrames
- When to apply different rounding strategies
What’s Included:
- 10 Lessons
- Video Subtitles and Full Transcripts
- 2 Downloadable Resources
- Accompanying Text-Based Tutorial
- Q&A With Python Experts: Ask a Question
- Certificate of Completion
Downloadable Resources:
