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tidyr – help transform data specifically into tidy data, where each variable is a column, each observation is a row; each row is an observation, and each value is a cell. readr – help read in common delimited, text files with data; purrr – a functional programming toolkit; tibble – a modern implementation of the built-in data frame data ...
In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the ...
An entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforeseeable using a fixed design. The use-case targets applications which offer a large ...
Because both orientations represent the same data, it is possible to convert a row-oriented dataset to a column-oriented dataset and vice-versa at the expense of compute. In particular, advanced query engines often leverage each orientation's advantages, and convert from one orientation to the other as part of their execution.
A pivot table is a table of values which are aggregations of groups of individual values from a more extensive table (such as from a database, spreadsheet, or business intelligence program) within one or more discrete categories. The aggregations or summaries of the groups of the individual terms might include sums, averages, counts, or other ...
k-anonymity is a property possessed by certain anonymized data.The term k-anonymity was first introduced by Pierangela Samarati and Latanya Sweeney in a paper published in 1998, [1] although the concept dates to a 1986 paper by Tore Dalenius.
Imputation – Similar to single imputation, missing values are imputed. However, the imputed values are drawn m times from a distribution rather than just once. At the end of this step, there should be m completed datasets. Analysis – Each of the m datasets is analyzed. At the end of this step there should be m analyses.