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  2. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    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.

  3. Table (database) - Wikipedia

    en.wikipedia.org/wiki/Table_(database)

    In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]

  4. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package. 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 ...

  5. Relational database - Wikipedia

    en.wikipedia.org/wiki/Relational_database

    In SQL, an INNER JOIN prevents a cartesian product from occurring when there are two tables in a query. For each table added to a SQL Query, one additional INNER JOIN is added to prevent a cartesian product. Thus, for N tables in an SQL query, there must be N−1 INNER JOINS to prevent a cartesian product.

  6. Data orientation - Wikipedia

    en.wikipedia.org/wiki/Data_orientation

    Data orientation refers to how tabular data is represented in a linear memory model such as in-disk or in-memory.The two most common representations are column-oriented (columnar format) and row-oriented (row format). [1] [2] The choice of data orientation is a trade-off and an architectural decision in databases, query engines, and numerical ...

  7. Trino (SQL query engine) - Wikipedia

    en.wikipedia.org/wiki/Trino_(SQL_query_engine)

    Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain a variety of file formats such as simple row-oriented CSV and JSON data files to more performant open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like ...

  8. Comparison of relational database management systems - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_relational...

    A true fully (database, schema, and table) qualified query is exemplified as such: SELECT * FROM database. schema. table. Both a schema and a database can be used to isolate one table, "foo", from another like-named table "foo". The following is pseudo code: SELECT * FROM database1. foo vs. SELECT * FROM database2. foo (no explicit schema ...

  9. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    Database normalization is the process of structuring a relational database accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .