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4 cards from this section. Quick, good the night before a test.
What does data quality refer to?
Think about the characteristics that make data usable.
Name one technique to handle missing data.
Think about common approaches you've learned.
Which of the following is a common issue in data quality?
Consider what happens to data when there are repeated entries.
True or False: Normalization is used to scale data to a specific range.
What range are we typically targeting with normalization?
Given a dataset with missing values, outline a strategy to handle these issues while preserving the dataset's integrity.
Think about the context and significance of each data field.
How would you write a Python function that detects and removes duplicates based on specific columns?
Understand how to apply `drop_duplicates()` within a function context.
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