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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]
"Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.
In computing, data deduplication is a technique for eliminating duplicate copies of repeating data. Successful implementation of the technique can improve storage utilization, which may in turn lower capital expenditure by reducing the overall amount of storage media required to meet storage capacity needs.
In computer programming, duplicate code is a sequence of source code that occurs more than once, either within a program or across different programs owned or maintained by the same entity. Duplicate code is generally considered undesirable for a number of reasons. [ 1 ]
Unix or Linux scripts may start with a shebang ("#!", 23 21) followed by the path to an interpreter, if the interpreter is likely to be different from the one from which the script was invoked. ELF executables start with the byte 7F followed by "ELF" (7F 45 4C 46). PostScript files and programs start with "%!" (25 21).
Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [ 2 ] [ 3 ] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical ...
Decomposing a complex programming task into simpler steps: this is one of the two main tools of structured programming, along with data structures; Reducing duplicate code within a program; Enabling reuse of code across multiple programs; Dividing a large programming task among various programmers or various stages of a project
If you simply divide the numbers by 16 and take the remainder, you will find that the numbers 0–3 occur about 17% more often than others. This is because 16 does not evenly divide 100: the largest multiple of 16 less than or equal to 100 is 6×16 = 96, and it is the numbers in the incomplete range 96–99 that cause the bias.