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Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark;
[4]: 114 A DataFrame is a 2-dimensional data structure of rows and columns, similar to a spreadsheet, and analogous to a Python dictionary mapping column names (keys) to Series (values), with each Series sharing an index. [4]: 115 DataFrames can be concatenated together or "merged" on columns or indices in a manner similar to joins in SQL.
From 2005 to December 2012, Van Rossum worked at Google, where he spent half of his time developing the Python language. At Google, he developed Mondrian, a web-based code review system written in Python and used within the company. He named the software after the Dutch painter Piet Mondrian. [20]
A query language, also known as data query language or database query language (DQL), is a computer language used to make queries in databases and information systems. In database systems, query languages rely on strict theory to retrieve information. [1] A well known example is the Structured Query Language (SQL).
Query by Example (QBE) is a database query language for relational databases. It was devised by Moshé M. Zloof at IBM Research during the mid-1970s, in parallel to the development of SQL . [ 1 ] It is the first graphical query language, using visual tables where the user would enter commands, example elements and conditions.
SPARQL (pronounced "sparkle", a recursive acronym [2] for SPARQL Protocol and RDF Query Language) is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format.
Power Query is an ETL tool created by Microsoft for data extraction, loading and transformation, and is used to retrieve data from sources, process it, and load them into one or more target systems. Power Query is available in several variations within the Microsoft Power Platform , and is used for business intelligence on fully or partially ...
Standard examples of data-driven languages are the text-processing languages sed and AWK, [1] and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.