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  2. dplyr - Wikipedia

    en.wikipedia.org/wiki/Dplyr

    dplyr is an R package whose set of functions are designed to enable dataframe (a spreadsheet-like data structure) manipulation in an intuitive, user-friendly way. It is one of the core packages of the popular tidyverse set of packages in the R programming language. [1]

  3. Data blending - Wikipedia

    en.wikipedia.org/wiki/Data_blending

    In tableau software, data blending is a technique to combine data from multiple data sources in the data visualization. [17] A key differentiator is the granularity of the data join. When blending data into a single data set, this would use a SQL database join, which would usually join at the most granular level, using an ID field where ...

  4. Multiple correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_correspondence...

    In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space .

  5. k-way merge algorithm - Wikipedia

    en.wikipedia.org/wiki/K-way_merge_algorithm

    The k-way merge problem consists of merging k sorted arrays to produce a single sorted array with the same elements.Denote by n the total number of elements. n is equal to the size of the output array and the sum of the sizes of the k input arrays.

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  7. Merge algorithm - Wikipedia

    en.wikipedia.org/wiki/Merge_algorithm

    Merge algorithms are a family of algorithms that take multiple sorted lists as input and produce a single list as output, containing all the elements of the inputs lists in sorted order. These algorithms are used as subroutines in various sorting algorithms , most famously merge sort .

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  9. R (programming language) - Wikipedia

    en.wikipedia.org/wiki/R_(programming_language)

    R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.