Showing 10 open source projects for "data analysis free"

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  • Gemini 3 and 200+ AI Models on One Platform Icon
    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

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    Catch Bugs Before Your Customers Do

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  • 1
    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: 5 This Week
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  • 2
    NYC Taxi Data

    NYC Taxi Data

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

    The nyc-taxi-data repository is a rich dataset and exploratory project around New York City taxi trip records. It collects and preprocesses large-scale trip datasets (fares, pickup/dropoff, timestamps, locations, passenger counts) to enable data analysis, modeling, and visualization efforts. The project includes scripts and notebooks for cleaning and filtering the raw data, memory-efficient processing for large CSV/Parquet files, and aggregation workflows (e.g. trips per hour, heatmaps of pickups/dropoffs). ...
    Downloads: 2 This Week
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  • 3
    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: 8 This Week
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  • 4
    Statistical Rethinking 2024

    Statistical Rethinking 2024

    This course teaches data analysis

    The 2024 repository is the most recent version of the course, reflecting ongoing refinements in pedagogy, statistical modeling techniques, and coding practices. It provides updated notebooks, R scripts, and model examples, some streamlined and restructured compared to previous years. The 2024 repo also highlights the transition toward more robust Stan models and integration with newer Bayesian workflow practices, continuing to emphasize accessibility for learners while modernizing the tools....
    Downloads: 0 This Week
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  • AI-generated apps that pass security review Icon
    AI-generated apps that pass security review

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  • 5
    Statistical Rethinking 2023

    Statistical Rethinking 2023

    Statistical Rethinking Course for Jan-Mar 2023

    ...It continues to provide scripts for lectures and tutorials, while integrating refinements to examples, notation, and computational workflows introduced that year. Compared with 2022, some models are rewritten for clarity, and teaching materials reflect refinements in McElreath’s evolving presentation of Bayesian data analysis. Students following the 2023 lecture videos use this repository as their coding reference. There are 10 weeks of instruction. Links to lecture recordings will appear in this table. Weekly problem sets are assigned on Fridays and due the next Friday, when we discuss the solutions in the weekly online meeting.
    Downloads: 0 This Week
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  • 6
    AI-Agent-Host

    AI-Agent-Host

    The AI Agent Host is a module-based development environment.

    ...Being data-aware involves connecting a language model to other sources of data, enabling a comprehensive understanding and analysis of information.
    Downloads: 0 This Week
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  • 7
    Statistical Rethinking 2022

    Statistical Rethinking 2022

    Statistical Rethinking course winter 2022

    This repository hosts the 2022 version of the Statistical Rethinking course. It contains course materials such as R scripts, notebooks, and worked examples aligned with McElreath’s textbook. The code emphasizes Bayesian data analysis using R, the rethinking package, and Stan models. It includes lecture code files, example datasets, and structured exercises that parallel the topics covered in the lectures (probability, regression, model comparison, Bayesian updating). The repo functions as a direct hands-on reference for students following the 2022 recorded lecture series. ...
    Downloads: 1 This Week
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  • 8
    Reproducible-research

    Reproducible-research

    A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.

    ...The workflow ensures meeting the primary goals that 1) the reporting of statistical results is consistent with the actual statistical results (dynamic report generation), 2) the analysis exactly reproduces at a later point in time even if the computing platform or software is changed (computational reproducibility), and 3) changes at any time (during development and post-publication) are tracked, tagged, and documented while earlier versions of both data and code remain accessible.
    Downloads: 0 This Week
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  • 9
    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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    MongoDB Atlas runs apps anywhere

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  • 10
    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 positive returns, even accounting for extreme market crashes and recessions. ...
    Downloads: 0 This Week
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