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Introduction to Python Data...
Chapter 24
Title Page
Foreword: Why Data Science?
Chapter 1: Introduction
Chapter 2: Python: Variables
Chapter 3: Python: Flow Control
Chapter 4: Python: I-P-O
Chapter 5: Python: Collections
Chapter 6: Python: Iterations
Chapter 7: Python: Packages
Chapter 8: Python: DataFrames
Chapter 9: Python: Reading/Writing
Chapter 10: Python: Advanced DataFrames
Chapter 11: Python: Debugging
Chapter 12: Python: Functions
Chapter 13: Univariate: Statistics
Chapter 14: Univariate: Visualizations
Chapter 15: Bivariate: Num/Num: Stats
Chapter 16: Bivariate: Num/Num: Viz
Chapter 17: Bivariate: Cat/Num: Stats
Chapter 18: Bivariate: Cat/Num: Viz
Chapter 19: Bivariate: Cat/Cat: Stats and Viz
Chapter 20: Multivariate: Numeric
Chapter 21: Multivariate: Categorical
Chapter 22: Prep: Data Wrangling
Chapter 23: Prep: Skewness
Chapter 24: Prep: Outliers
Chapter 25: Prep: Missing Data
Supplement: Datasets
Supplement: Automation: Univariate Analyses
Supplement: Automation: Bivariate Analyses (in progress)
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Chapter 24: Prep: Outliers
24.1 Introduction
24.2 The Empirical Rule (68-95-99.7)
24.3 Tukey Box Plot
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24.4 Clustering-Based Outliers (optional)
24.5 Practice
24.6 Homework
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