Showing 21 open source projects for "data science"

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  • 1
    NYC Taxi Data

    NYC Taxi Data

    Import public NYC taxi and for-hire vehicle (Uber, Lyft)

    ...It also contains example analyses—spatial and temporal visualizations like maps, time-series plots, and hotspot detection—highlighting insights such as patterns of demand, peak times, and geospatial distributions. The repository is often used as a benchmark dataset and example for teaching, benchmarking, and demonstration purposes in the data science and urban analytics communities.
    Downloads: 1 This Week
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  • 2
    MHNs Data Science Examples

    MHNs Data Science Examples

    Collection of data science examples.

    Downloads: 0 This Week
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  • 3
    ggplot2

    ggplot2

    An implementation of the Grammar of Graphics in R

    ...ggplot2 is a part of the tidyverse, an ecosystem of R packages designed for data science.
    Downloads: 24 This Week
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  • 4
    targets

    targets

    Function-oriented Make-like declarative workflows for R

    The targets package is a pipeline / workflow management tool in R, designed to coordinate multi‐step computational workflows in data science / statistics. It tracks dependencies between “targets” (computational steps), skips steps whose upstream data or code hasn’t changed, supports parallel computation, branching (dynamic generation of sub‐targets), file format abstractions, and encourages reproducible and efficient analyses. It’s something like GNU Make for R, but more integrated. ...
    Downloads: 0 This Week
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  • 5
    dplyr

    dplyr

    dplyr: A grammar of data manipulation

    dplyr is an R package that provides a consistent and intuitive grammar for data manipulation, enabling users to filter, arrange, summarize, and transform data efficiently. Part of the tidyverse ecosystem, dplyr simplifies complex data operations through a clear and readable syntax, whether working with data frames, tibbles, or databases. It is widely used in data science and statistical analysis workflows.
    Downloads: 3 This Week
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  • 6
    RStudio Cheatsheets

    RStudio Cheatsheets

    Curated collection of official cheat sheets for data science tools

    The cheatsheets repository from RStudio is a curated collection of official cheat sheets for R, RStudio, the tidyverse, Shiny, and related data science tools. Each cheat sheet is a single (or double) page PDF that condenses important syntax, functions, workflows, and best practices into a visually organized format ideal for quick reference. The repository contains source files (R Markdown or LaTeX) that generate the cheat sheets, version history, and metadata (title, author, description) for each. ...
    Downloads: 2 This Week
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  • 7
    forecast

    forecast

    Forecasting Functions for Time Series and Linear Models

    The forecast package is a comprehensive R package for time series analysis and forecasting. It provides functions for building, assessing, and using univariate forecasting models (e.g. ARIMA, exponential smoothing, etc.), tools for automatic model selection, diagnostics, plotting, forecasting future values, etc. It's widely used in statistics, economics, business forecasting, environmental science, etc. Exponential smoothing state space models (ETS) including seasonal components. Residual...
    Downloads: 0 This Week
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  • 8
    rmarkdown

    rmarkdown

    Dynamic Documents for R

    R Markdown is an R package for creating dynamic, reproducible documents that combine code (R, Python, SQL, etc.), results (figures, tables), and narrative text. Built on Knitr and Pandoc, it supports generating HTML, PDF, Word, slideshows, dashboards, and more. It’s widely used in data science and reproducible reporting workflows.
    Downloads: 5 This Week
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  • 9
    workflowr

    workflowr

    Organize your project into a research website

    workflowr is an R package that helps researchers organize, version, and share their data science projects in a reproducible and transparent manner. It combines R Markdown, Git, and a structured file system to create a research website that tracks analysis, results, and code changes over time. It’s ideal for academic and collaborative research workflows.
    Downloads: 0 This Week
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  • 10
    LabPlot

    LabPlot

    Data Visualization and Analysis

    LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone.
    Downloads: 16 This Week
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  • 11
    Awesome Network Analysis

    Awesome Network Analysis

    A curated list of awesome network analysis resources

    awesome-network-analysis is a curated list of resources focused on network and graph analysis, including libraries, frameworks, visualization tools, datasets, and academic papers. It covers multiple programming languages and domains like sociology, biology, and computer science. This repository serves as a central reference for researchers, analysts, and developers working with network data.
    Downloads: 0 This Week
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  • 12
    Amplicon_Sequencing_Worfklow

    Amplicon_Sequencing_Worfklow

    Analyzing amplicon data from sequences to stats

    This is a collection of scripts and instructions on how to analyzing amplicon sequence data (i.e., 16S, ITS2, & other marker genes). I created this workflow to create a consistent set of methods for analyzing amplicon sequence data, from when you first receive the sequence data to statistical analyses & data visualization. All you need is to have the latest version of R installed, some experience with the command line & shell, and enough memory to run all of the programs. There are also...
    Downloads: 0 This Week
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  • 13
    tidyverse

    tidyverse

    Easily install and load packages from the tidyverse

    tidyverse is a meta‑package that installs and loads a cohesive suite of R packages designed for data science, sharing underlying design principles, grammar, and data structures. Core components include ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, forcats, and more. It promotes tidy data workflows and consistency across tasks.
    Downloads: 1 This Week
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  • 14
    Statistics for Data Scientists

    Statistics for Data Scientists

    "Statistics for Data Scientists: 50 Essential Concepts"

    The “statistics-for-data-scientists” repository is a pedagogical resource designed to bridge rigorous statistics theory and practical data science workflows. The code and materials are intended to help data scientists and analysts grasp statistical principles (e.g. inference, regressions, hypothesis testing, probability, confidence intervals) in contexts relevant to real data analysis tasks.
    Downloads: 0 This Week
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  • 15
    KidneyExplorer

    KidneyExplorer

    Kidney proteomics data explorer enables you to investigate diseases

    KidneyExplorer enables you to interactively survey kidney proteomics datasets from different kidney disease models. Here you can download the corresponding SQL database dumps. The original website for the shiny app is: https://kidneyapp.shinyapps.io/kidneyorganoids/
    Downloads: 0 This Week
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  • 16
    R4DS (R for Data Science)

    R4DS (R for Data Science)

    R for data science: a book

    “R for Data Science” (r4ds) is the source material (book + examples) by Hadley Wickham et al., intended to teach data science using R and the tidyverse. It covers the workflow from importing data, tidying, transforming, visualizing, modelling, communicating results, and programming in R. The repository contains the source files (Quarto / RMarkdown), example datasets, visualizations, exercises, and all content needed to build the book.
    Downloads: 3 This Week
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  • 17
    MitoSAlt

    MitoSAlt

    Identification of mitochondrial structural alterations

    MitoSAlt is a pipeline to identify large deletions and duplications in human and mouse mitochondrial genomes from next generation whole genome/exome sequencing data. The pipeline is capable of analyzing any circular genome in principle, as long as a proper configuration file is provided.
    Downloads: 5 This Week
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  • 18
    swirl

    swirl

    Learn R, in R

    swirl is an R package that allows interactive, in-R learning of statistics, data science, R programming etc. The idea is that you load swirl in R, and it presents you with lessons (within R’s console or RStudio) that ask you to type commands, check results, and progress through tutorial material—without leaving the R environment. It is used for teaching R, especially for beginners, as well as for self-paced learning of packages, data manipulation, visualization, etc. ...
    Downloads: 0 This Week
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  • 19
    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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  • 20
    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, and reproducible workflows. ...
    Downloads: 0 This Week
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  • 21
    Data Science Specialization

    Data Science Specialization

    Course materials for the Data Science Specialization on Coursera

    The Data Science Specialization Courses repository is a collection of materials that support the Johns Hopkins University Data Science Specialization on Coursera. It contains the source code and resources used throughout the specialization’s courses, covering a broad range of data science concepts and techniques. The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. ...
    Downloads: 7 This Week
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