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grep is a command-line utility for searching plaintext datasets for lines that match a regular expression. Its name comes from the ed command g/re/p (global regular expression search and print), which has the same effect.
Additional functionality of pgrep is listing the process name as well as the PID (-l Lists the process name as well as the process ID) of all processes belonging to the group alice (-G Only match processes whose real group ID is listed. Either the numerical or symbolical value may be used): $
agrep (approximate grep) is an open-source approximate string matching program, developed by Udi Manber and Sun Wu between 1988 and 1991, [1] for use with the Unix operating system. It was later ported to OS/2 , DOS , and Windows .
Python has array index and array slicing expressions in lists, denoted as a[key], a [start: stop] or a [start: stop: step]. Indexes are zero-based , and negative indexes are relative to the end. Slices take elements from the start index up to, but not including, the stop index.
An array data structure can be mathematically modeled as an abstract data structure (an abstract array) with two operations get(A, I): the data stored in the element of the array A whose indices are the integer tuple I. set(A, I, V): the array that results by setting the value of that element to V. These operations are required to satisfy the ...
For referential integrity to hold in a relational database, any column in a base table that is declared a foreign key can only contain either null values or values from a parent table's primary key or a candidate key. [2] In other words, when a foreign key value is used it must reference a valid, existing primary key in the parent table.
Missing not at random (MNAR) (also known as nonignorable nonresponse) is data that is neither MAR nor MCAR (i.e. the value of the variable that's missing is related to the reason it's missing). [5] To extend the previous example, this would occur if men failed to fill in a depression survey because of their level of depression.
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]