Dataseries

A dataseries is a sequence of data points arranged in a specific order, typically indexed by a position or an identifier. It is a broad concept used in data analysis to refer to a one-dimensional collection of observations. Unlike a time series, which emphasizes regular temporal spacing, a dataseries may have irregular intervals or non-temporal indices and focuses on the ordered data itself.

Dataseries can be univariate, containing a single value for each index, or multivariate, storing multiple variables per index (often as records). The index can be numeric, categorical, or temporal, and the values may be numeric, textual, or other data types.

In software, dataseries are typically represented as labeled arrays or vectors with an associated index. Common implementations include language-specific Series objects and similar structures in other ecosystems. Files may store dataseries in formats such as CSV, JSON, Parquet, or HDF5, often with metadata describing units and sampling details.

Operations on dataseries include accessing elements by position or label, slicing, aligning multiple series by their index, and performing aggregations, transformations, or windowed computations. Handling missing values and ensuring consistent indexing are important considerations for reliable analysis.

Applications span data exploration, feature engineering for machine learning, statistical analysis, and forecasting. The term remains generic; specific tools may impose additional structure, such as strict index uniqueness or fixed-length samples, depending on the domain and library.