Reminder: Please complete the O’Reilly login steps (See the Accessing O’Reilly link in the Week 1 Resources area) where you get an email that will allow your browser to keep your password, solving future access limitations.
Fávero, L. P., & Belfiore, P. (2019). Data science for business and decision making. Academic Press.
Read Chapter 2: Types of Variables and Measurements and Accuracy Scales.
Chapter 2 discusses the importance of defining variable measurement scales during the process of analyzing and transforming data. The difference between quantitative and qualitative variables, scales of measurement, scales of accuracy is also explained in detail with examples.
Walker, M. (2020). Python data cleaning cookbook. Packt Publishing.
Read Chapter 1: Anticipating Data Cleaning Issues When Importing Tabular Data Into Pandas.
This chapter explains how to import and clean data using Python.
Read Chapter 3: Taking Measure of Your Data.
This chapter explains how to explore a dataset and perform basic statistics in Python. The concepts of data distribution and normal distribution are covered.
Read Chapter 4: Identifying Missing Values and Outliers in Subsets of Data
This chapter explains how find outliers in the dataset and discusses dealing with missing values.
Boschetti, A., & Massaron, L. (2016). Regression analysis with Python: learn the art of regression analysis with Python. Packt Publishing.
Read Chapter 5: Data Preparation.
This chapter covers various data preparation and transformation topics, including qualitative feature encoding, numeric feature transformation, missing data, and outliers.
