Python Statistics Essential Training

Learn to use Python to unlock the power of data and use it to inform decisions.

Introduction

• Being a Python statistics MVP
• What you should know
• Using GitHub Codespaces with this course

1. Loading and Cleaning Data

• Loading data
• Strings and categories
• Cleaning numbers
• Shrinking numbers
• Challenge: Clean Ames
• Solution: Clean Ames

2. Exploring and Visualizing

• Categorical exploration
• Histograms and distributions
• Outliers and Z-scores
• Correlations
• Scatter plots
• Visualizing categorical and numerical values
• Comparing two categoricals
• Challenge: Explore Ames
• Solution: Explore Ames

3. Linear Regressions

• Linear regression
• Interpreting linear regression models
• Standardizing values
• Regression with XGBoost
• Challenge: Predict Ames
• Solution: Predict Ames

4. Hypothesis Tests

• Exploring data
• Visualizing distributions
• Running statistical tests
• Testing for normality
• Challenge: Checking square footage distributions
• Solution: Checking square footage distributions

Conclusion

• Next steps