Data Cleaning
Missing values, duplicates, outliers, business rules, transformation, data quality
1What is a missing value in a dataset?
What is a missing value in a dataset?
Answer
A missing value represents absent or unfilled data in a field. It can appear as an empty cell, NULL in a database, or NaN in a DataFrame. Identifying missing values is the first step in data cleaning because they can distort statistical analyses and aggregations.
2What is the difference between a NULL value and an empty string in a database?
What is the difference between a NULL value and an empty string in a database?
Answer
NULL means the value is unknown or does not exist, while an empty string is a known value that happens to be empty. This distinction is fundamental in SQL because NULL cannot be compared with the = operator (IS NULL must be used), whereas an empty string can be compared normally with = ''.
3What is a duplicate in a dataset?
What is a duplicate in a dataset?
Answer
A duplicate is a record that appears more than once in a dataset, either exactly (all columns identical) or partially (certain key columns identical). Duplicates distort counts, sums, and averages. Their detection typically relies on identifying key columns that should be unique.
Which technique allows detecting exact duplicates in SQL?
What is an outlier in a dataset?
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