![]() ![]() First Normal Form data forms a relation in the technical sense. Relational theory defines “tidy data” in more precise terms as First Normal Form data. Armed with these tools, you are ready to improve your business outcomes. The pandas library supports this critical need with built-in methods to find and remove duplicate rows and columns. Each type of observational unit forms a table. A major part of improving data quality is removing duplicate data, which can skew the results of data analysis and take up unnecessary storage space. ![]() These structural problems generally prevent easy analysis. Tidiness issues pertain to the structure of data.
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