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Introduction to Python Data Analytics

Data Analytics

ISBN #978-1-952023-20-0

Introduction to Python Data Analytics

Mark Keith, PhD

Data science is changing the world. This resource provides an introduction to programming in Python, statistics, data cleaning, and automating the data analytics process to prepare students with critical skills and conceptual understanding in data science. It is targeted toward students who have a limited background in programming or statistics but want to build a thorough technical skillset.

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Course Objective

This resource offers an introduction to Python, statistics, data cleaning, and data analytics automation, equipping beginners with essential data science skills and concepts.

Table of Contents

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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