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Dataset Metadata

Dataset metadata provides essential information about the structure, content, and characteristics of a dataset. It serves as a "data dictionary" that helps users understand the dataset's context, features, and potential use cases. Metadata is critical for ensuring proper data management, reproducibility, and collaboration.

Key Components of Dataset Metadata

  1. General Information
  2. Dataset ID: A unique identifier for the dataset.
  3. Source: The origin of the dataset (e.g., internal database, public repository).
  4. Creation Date: The date when the dataset was created or last updated.

  5. Feature Descriptions

  6. Column Names: The names of all features (columns) in the dataset.
  7. Data Types: The type of data for each feature (e.g., integer, float, string, datetime).

  8. Statistical Properties

  9. Summary Statistics: Key metrics such as mean, median, standard deviation, and range for numerical features.
  10. Unique Values: The number of unique values for categorical features.
  11. Missing Values: The count or percentage of missing values for each feature.