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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.
The library NumPy can be used for manipulating arrays, SciPy for scientific and mathematical analysis, Pandas for analyzing table data, Scikit-learn for various machine learning tasks, NLTK and spaCy for natural language processing, OpenCV for computer vision, and Matplotlib for data visualization. [3]
OptimJ is a mathematical Java-based modeling language for describing and solving high-complexity problems for large-scale optimization. Perl Data Language, [22] [23] also known as PDL, an array extension to Perl ver.5, used for data manipulation, statistics, numerical simulation and visualization.
Dataframe may refer to: A tabular data structure common to many data processing libraries: pandas (software) § DataFrames; The Dataframe API in Apache Spark; Data frames in the R programming language; Frame (networking)
A procedural program is composed of one or more units or modules, either user coded or provided in a code library; each module is composed of one or more procedures, also called a function, routine, subroutine, or method, depending on the language. Examples of procedural languages include:
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 ...
Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.
Folds can be regarded as consistently replacing the structural components of a data structure with functions and values. Lists, for example, are built up in many functional languages from two primitives: any list is either an empty list, commonly called nil ([]), or is constructed by prefixing an element in front of another list, creating what is called a cons node ( Cons(X1,Cons(X2,Cons ...