Summary: Data Exploration and Cleaning
Explore the essential steps of data exploration and cleaning to prepare datasets for analysis. Learn how to identify inconsistencies, handle missing values, and validate data integrity using pandas, enabling you to build reliable models and insights in data science projects.
We'll cover the following...
In this introductory chapter, we made extensive use of pandas to load and explore the case study data. We learned how to check for basic consistency and correctness by using a combination of statistical summaries and visualizations.
We answered questions like:
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Are the unique account IDs truly unique?
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Is there any missing data that has been given a fill value?
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Do the values of the features make sense given their definition?
You may notice that we spent nearly all of this chapter identifying and correcting issues with our dataset. This is ...