Showing 9 open source projects for "read"

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  • 1
    Readr

    Readr

    Read flat files (csv, tsv, fwf) into R

    readr is an R package that provides a fast and friendly way to read rectangular data, such as CSV and TSV files. Part of the Tidyverse, it simplifies data import and parsing tasks in R.​
    Downloads: 3 This Week
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  • 2
    Introduction to Zig

    Introduction to Zig

    An open, technical and introductory book for the Zig programming lang

    This is the official repository for the book "Introduction to Zig: a project-based Book", written by Pedro Duarte Faria. To know more about the book, check out the About this book section below. You can read the current version of the book in your web browser. The book is built using the publishing system Quarto in conjunction with a little bit of R code (zig_engine.R), which is responsible for calling the Zig compiler to compile and run the Zig code examples.
    Downloads: 7 This Week
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  • 3
    plotly

    plotly

    An interactive graphing library for R

    This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of...
    Downloads: 19 This Week
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  • 4
    R Source

    R Source

    Read-only mirror of R source code

    The wch/r-source repository is a read-only mirror of the official R language source code, maintained to reflect the upstream Subversion (SVN) R core development tree. This mirror provides public visibility into R’s internals—everything from the interpreter, base and recommended packages, documentation, and C/Fortran code under the hood. It is updated hourly to stay in sync with the upstream SVN.
    Downloads: 0 This Week
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  • 5
    latex2exp

    latex2exp

    Use LaTeX in R graphics

    latex2exp is an R package that lets you use LaTeX in plots. It parses and converts LaTeX to R’s custom plotmath expressions. You can read the full documentation on the package’s website. Expressions returned by latex2exp can be used to create formatted text and mathematical formulas and symbols to be rendered as axis labels, annotations, legends, titles, etc. throughout R’s plotting system.
    Downloads: 0 This Week
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  • 6
    activAnalyzer
    ...In addition to an analysis of physical behavior, the app also allows to implement the Daily- and Clinical visit-PROactive Physical Activity in COPD (chronic obstructive pulmonary disease) instruments (D-PPAC and C-PPAC). Please read the user’s guide for details about how the app works.
    Downloads: 0 This Week
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  • 7
    osm4scala

    osm4scala

    Reading OpenStreetMap Pbf files.

    Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files.
    Downloads: 0 This Week
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  • 8
    R Markdown Cookbook

    R Markdown Cookbook

    R Markdown Cookbook

    R Markdown Cookbook. A range of tips and tricks to make better use of R Markdown. R Markdown is a powerful tool for combining analysis and reporting into the same document. Since the birth of the rmarkdown package (Allaire, Xie, Dervieux, McPherson, et al. 2023) in early 2014, R Markdown has grown substantially from a package that supports a few output formats, to an extensive and diverse ecosystem that supports the creation of books, blogs, scientific articles, websites, and even resumes.
    Downloads: 0 This Week
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  • 9
    Stats 337

    Stats 337

    Readings in applied data science

    Stats 337 is the repository for a Stanford discussion course titled Readings in Applied Data Science, taught in Spring 2018. Students were expected to read several papers or equivalent resources each week and discuss their implications in class. The reading list focuses on applied topics that the instructor considered important but often underrepresented in traditional data science curricula. Subjects include data collection, collaboration, software engineering, DevOps, teaching, reproducibility, ethics, careers, industry practice, and workflow design. ...
    Downloads: 0 This Week
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