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Walker, M. (2020). Python data cleaning cookbook. Packt Publishing.
Read Chapter 3: Taking the Measure of Your Data.
This chapter provides a step-by-step approach to generating frequencies for categorical variables and statistics for continuous variables in Python.
Read Chapter 4: Identifying Missing Values and Outliers in Subsets of Data.
This chapter provides a step-by-step approach to identifying and cleaning data in Python.
Read Chapter 5: Using Visualizations for the Identification of Unexpected Values.
This chapter provides a step-by-step approach to creating visualizations in Python to reveal data anomalies.
Read Chapter 6: Cleaning and Exploring Data with Series Operations.
This chapter provides a step-by-step approach to identifying and cleaning datasets, including imputation techniques for missing data.
Google, Inc. (n.d.). Welcome to Colaboratory. Google, Inc. Set up a Google account to use this open-source Python platform to support data science and machine learning projects. The Getting Started document is a mini-tutorial that explains how Colab notebooks are created and provides sample starter code in Python.
