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Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.
Views also function as relational tables, but their data are calculated at query time. External tables (in Informix [ 3 ] or Oracle , [ 4 ] [ 5 ] for example) can also be thought of as views. In many systems for computational statistics, such as R and Python 's pandas , a data frame or data table is a data type supporting the table abstraction.
The pandas package in Python implements this operation as "melt" function which converts a wide table to a narrow one. The process of converting a narrow table to wide table is generally referred to as "pivoting" in the context of data transformations.
MarkLogic introduced bitemporal data support in version 8.0. Time stamps for Valid and System time are stored in JSON or XML documents. [2]XTDB [3] (formerly Crux) is an open source database that indexes documents using an EAV data model and provides point-in-time bitemporal SQL & Datalog queries.
The nested set model is a technique for representing nested set collections (also known as trees or hierarchies) in relational databases.. It is based on Nested Intervals, that "are immune to hierarchy reorganization problem, and allow answering ancestor path hierarchical queries algorithmically — without accessing the stored hierarchy relation".
A model is not just a way of structuring data: it also defines a set of operations that can be performed on the data. [1] The relational model, for example, defines operations such as select, project and join. Although these operations may not be explicit in a particular query language, they provide the foundation on which a query language is ...
A table in a SQL database schema corresponds to a predicate variable; the contents of a table to a relation; key constraints, other constraints, and SQL queries correspond to predicates. However, SQL databases deviate from the relational model in many details, and Codd fiercely argued against deviations that compromise the original principles. [3]
An object–relational database (ORD), or object–relational database management system (ORDBMS), is a database management system (DBMS) similar to a relational database, but with an object-oriented database model: objects, classes and inheritance are directly supported in database schemas and in the query language.