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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.
Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface (for Java, Python, Scala, .NET [16] and R) centered on the RDD abstraction (the Java API is available for other JVM languages, but is also usable for some other non-JVM languages that can connect to the ...
The name SPARK was derived from SPADE Ada Kernel, in reference to the SPADE subset of the Pascal programming language. [1] Subsequently the language was progressively extended and refined, first by Program Validation Limited and then by Praxis Critical Systems Limited.
The equivalent of ORMs for document-oriented databases are called object-document mappers (ODMs). Document-oriented databases also prevent the user from having to "shred" objects into table rows. Many of these systems also support the XQuery query language to retrieve datasets. Object-oriented databases tend to be used in complex, niche ...
A column may contain text values, numbers, or even pointers to files in the operating system. [2] Columns typically contain simple types, though some relational database systems allow columns to contain more complex data types, such as whole documents, images, or even video clips. [3] [better source needed] A column can also be called an attribute.
There is a Microsoft Excel object model for controlling Microsoft Excel from another program, and the ASCOM Telescope Driver is an object model for controlling an astronomical telescope. An object model consists of the following important features: Object reference Objects can be accessed via object references.
Examples of fact data include sales price, sale quantity, and time, distance, speed and weight measurements. Related dimension attribute examples include product models, product colors, product sizes, geographic locations, and salesperson names. A star schema that has many dimensions is sometimes called a centipede schema. [4]