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  2. Group by (SQL) - Wikipedia

    en.wikipedia.org/wiki/Group_by_(SQL)

    A GROUP BY statement in SQL specifies that a SQL SELECT statement partitions result rows into groups, based on their values in one or several columns. Typically, grouping is used to apply some sort of aggregate function for each group. [1] [2] The result of a query using a GROUP BY statement contains one row for

  3. Dask (software) - Wikipedia

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

    Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.

  4. Aggregate (data warehouse) - Wikipedia

    en.wikipedia.org/wiki/Aggregate_(data_warehouse)

    An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a query.

  5. Aggregate function - Wikipedia

    en.wikipedia.org/wiki/Aggregate_function

    In order to calculate the average and standard deviation from aggregate data, it is necessary to have available for each group: the total of values (Σx i = SUM(x)), the number of values (N=COUNT(x)) and the total of squares of the values (Σx i 2 =SUM(x 2)) of each groups.

  6. Dataframe - Wikipedia

    en.wikipedia.org/wiki/Dataframe

    Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark;

  7. Azure Data Explorer - Wikipedia

    en.wikipedia.org/wiki/Azure_Data_Explorer

    It supports complex analytics query operators, such as calculated columns, searching and filtering on rows, group by-aggregates and joins. [25] The engine service exposes a relational data model: At the top level there is a collection of databases, each database contains a collection of tables and stored functions.

  8. Lauren Betts scores a career-high 33 points as No. 1 UCLA ...

    www.aol.com/lauren-betts-scores-career-high...

    Lauren Betts scored a career-high 33 points, Kiki Rice added 19, and No. 1 UCLA defeated No. 8 Maryland 82-67 on Sunday. The Bruins (20-0, 8-0 Big Ten) have won their last 19 games by double figures.

  9. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    Accumulating snapshot tables record aggregate facts at a given point in time (e.g., total month-to-date sales for a product) Fact tables are generally assigned a surrogate key to ensure each row can be uniquely identified. This key is a simple primary key.