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pip (also known by Python 3's alias pip3) is a package-management system written in Python and is used to install and manage software packages. [4] The Python Software Foundation recommends using pip for installing Python applications and its dependencies during deployment. [5] Pip connects to an online repository of public packages, called the ...
The tidyverse is a collection of open source packages for the R programming language introduced by Hadley Wickham [1] and his team that "share an underlying design philosophy, grammar, and data structures" of tidy data. [2] Characteristic features of tidyverse packages include extensive use of non-standard evaluation and encouraging piping. [3 ...
The Python Package Index, abbreviated as PyPI (/ ˌ p aɪ p i ˈ aɪ /) and also known as the Cheese Shop (a reference to the Monty Python's Flying Circus sketch "Cheese Shop"), [2]: 8 [3]: 742 is the official third-party software repository for Python. [4] It is analogous to the CPAN repository for Perl [5]: 36 and to the CRAN repository for R.
The Raspberry Pi 5 uses a 64-bit 2.4 GHz quad-core ARM Cortex-A76 processor. The Raspberry Pi 5 uses the Broadcom BCM2712 SoC, which is a chip designed in collaboration with Raspberry Pi. The SoC features a quad-core ARM Cortex-A76 processor clocked at 2.4 GHz, alongside a VideoCore VII GPU clocked at 800 MHz.
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
Precompiled packages, since version 1.9, can be up to hundreds of times faster on first use (e.g. for CSV.jl and DataFrames.jl), and to improve precompilation of packages a new package PrecompileTools.jl has been introduced. Julia 1.10 was released on 25 December 2023 with many new features, e.g. parallel garbage collection, and improved ...
The group of packages strives to provide a cohesive collection of functions to deal with common data science tasks, including data import, cleaning, transformation and visualisation (notably with the ggplot2 package). The R Infrastructure packages [31] support coding and the development of R packages and as of 2021-05-04, Metacran [17] lists 16 ...
On 21 March 2017, the PyPy project released version 5.7 of both PyPy and PyPy3, with the latter introducing beta-quality support for Python 3.5. [25] On 26 April 2018, version 6.0 was released, with support for Python 2.7 and 3.5 (still beta-quality on Windows). [26] On 11 February 2019, version 7.0 was released, with support for Python 2.7 and ...