Showing 5 open source projects for "gmail source code"

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  • Stop Storing Third-Party Tokens in Your Database Icon
    Stop Storing Third-Party Tokens in Your Database

    Auth0 Token Vault handles secure token storage, exchange, and refresh for external providers so you don't have to build it yourself.

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    Atera - an All-in-one platform for IT management

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  • 1
    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: 2 This Week
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  • 2
    QBPWCF

    QBPWCF

    PHP library for not only web-based application in Fedora Linux

    此專案的目的是要建立簡單、易用、參數說明完整且富有調整性的PHP元件庫,讓PHP程式設計開發者可以輕鬆地建立高度客製化的應用。 套用當代的術語而言,就是要作為LOW CODE平台的函式庫。
    Downloads: 1 This Week
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  • 3
    R Packages (r-pkgs)

    R Packages (r-pkgs)

    Building R packages

    rpkgs (in GitHub via hadley/r-pkgs) is the source (text + examples) for the book R Packages by Hadley Wickham and Jenny Bryan. The book teaches how to develop, document, test, and share R packages: the practices, tools, infrastructure, workflows, and best practices around package development in R. The repository contains the code, text, site content for building the book, examples, exercises, etc.
    Downloads: 0 This Week
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  • 4
    DataScienceR

    DataScienceR

    a curated list of R tutorials for Data Science, NLP

    The DataScienceR repository is a curated collection of tutorials, sample code, and project templates for learning data science using the R programming language. It includes an assortment of exercises, sample datasets, and instructional code that cover the core steps of a data science project: data ingestion, cleaning, exploratory analysis, modeling, evaluation, and visualization. Many of the modules demonstrate best practices in R, such as using the tidyverse, R Markdown, modular scripting,...
    Downloads: 0 This Week
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  • $300 Free Credits for Your Google Cloud Projects Icon
    $300 Free Credits for Your Google Cloud Projects

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  • 5
    Investing

    Investing

    Investing Returns on the Market as a Whole

    This repository, owned by the user zonination (Zoni Nation), presents a data visualization and analysis project on long-term returns from broad stock market indexes, especially the S&P 500. The author gathers historical price data (adjusted for inflation and dividends) and computes growth trajectories under a “buy and hold” strategy over decades. The key insight illustrated is that over sufficiently long holding periods (e.g. 40 years), the stock market stabilizes and nearly always yields...
    Downloads: 0 This Week
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