Search results
Results from the WOW.Com Content Network
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]
Instead, more complex data structures like objects and arrays are implemented using references. The language does not provide any explicit pointer manipulation operators. It is still possible for code to attempt to dereference a null reference (null pointer), however, which results in a run-time exception being thrown.
A reference is an abstract data type and may be implemented in many ways. Typically, a reference refers to data stored in memory on a given system, and its internal value is the memory address of the data, i.e. a reference is implemented as a pointer. For this reason a reference is often said to "point to" the data.
The reference count of a string is checked before mutating a string. This allows reference count 1 strings to be mutated directly whilst higher reference count strings are copied before mutation. This allows the general behaviour of old style pascal strings to be preserved whilst eliminating the cost of copying the string on every assignment.
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.
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 ...
The compiler computes the total number of memory cells occupied by each row, uses the first index to find the address of the desired row, and then uses the second index to find the address of the desired element in the row. When the third method is used, the programmer declares the table to be an array of pointers, like in elementtype *tablename[];
the other piece maintains the data associated to that address. A single (fast) lookup is performed to read the tag in the lookup table at the index specified by the lowest bits of the desired external storage address, and to determine if the memory address is hit by the cache.