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Snake case (sometimes stylized autologically as snake_case) is the naming convention in which each space is replaced with an underscore (_) character, and words are written in lowercase. It is a commonly used naming convention in computing , for example for variable and subroutine names, and for filenames .
knitr is a software engine for dynamic report generation with R. [1] [2] It is a package in the programming language R that enables integration of R code into LaTeX, LyX, HTML, Markdown, AsciiDoc, and reStructuredText documents. The purpose of knitr is to allow reproducible research in R through the means of literate programming.
In C and C++, keywords and standard library identifiers are mostly lowercase. In the C standard library, abbreviated names are the most common (e.g. isalnum for a function testing whether a character is alphanumeric), while the C++ standard library often uses an underscore as a word separator (e.g. out_of_range).
double = CDbl(string) string = CStr(number) Visual Basic .NET (can use both VB syntax above and .NET methods shown right) integer = Integer.Parse (string) long = Long.Parse (string) float = Single.Parse (string) double = Double.Parse (string) string = number.ToString() Xojo: integer = Val(string) long = Val(string) double = Val(string) double ...
Blue highlights show the match results of the regular expression pattern: /r[aeiou]+/ g (lower case r followed by one or more lower-case vowels). A regular expression (shortened as regex or regexp ), [ 1 ] sometimes referred to as rational expression , [ 2 ] [ 3 ] is a sequence of characters that specifies a match pattern in text .
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]
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.
In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.