Python Fair-data Resources

Finds, downloads, parses, and standardizes public bikeshare data into a standard pandas dataframe format.

NYCT-GTFS - Real-time NYC subway data parsing for humans This python library provides a human-friendly, native python interface for dealing with the N

Emotional-Support-Conversation Copyright © 2021 CoAI Group, Tsinghua University. All rights reserved. Data and codes are for academic research use onl

Apocalypse Status Dashboard Purpose Climate change and resource depletion are grave long-term dangers. The code in this repository will pull data from

Compilation of resources and insights that helped me on my journey to data scientist

Everything Tech Resources & Projects About The Project Coming from an engineering background and looking to up skill yourself on a new field can be di

This is a Python program to Entity Linking by processing WARC files. We recognize entities from web pages and link them to a Knowledge Base(Wikidata).

timm_custom Description In the case of your data having only 1 channel while want to use timm models (with or without pretrained weights), run the fol

BBOX Problem definition: The spatial data users often are required to obtain the coordinates of the minimum bounding box of vector and raster data in

Cookiecutter Data Science A logical, reasonably standardized, but flexible project structure for doing and sharing data science work. Project homepage

PandasVault ⁠— Advanced Pandas Functions and Code Snippets The only Pandas utility package you would ever need. It has no exotic external dependencies

PandaPy "I came across PandaPy last week and have already used it in my current project. It is a fascinating Python library with a lot of potential to

A Python API for Intelligent Visual Discovery Lux is a Python library that facilitate fast and easy data exploration by automating the visualization a

Intel(R) Extension for Scikit-learn* Installation | Documentation | Examples | Support | FAQ With Intel(R) Extension for Scikit-learn you can accelera

Find relative paths from a project root directory Finding project directories in Python (data science) projects, just like there R here and rprojroot

Intake: A general interface for loading data Intake is a lightweight set of tools for loading and sharing data in data science projects. Intake helps

Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and many other libraries. Documenta

Unmaintained Package Notice Unfortunately, and due to lack of resources, the Blosc Development Team is unable to maintain this package anymore. During

An Open Source Project from the Data to AI Lab, at MIT Metrics for Synthetic Data Generation Projects Website: https://sdv.dev Documentation: https://

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

"Dataflow variables are spectacularly expressive in concurrent programming" Henri E. Bal , Jennifer G. Steiner , Andrew S. Tanenbaum Quick overview Ne

Purpose: This is integrate bus data from a variety of sources such as: csv, json api, sensor data ... into Relational Database (batch processing and r

dataset-division-to-train-val-test-python python script for dividing image data to train test and val If you have an image dataset in the following st

Our Data Data repo for one-among.us File Structure Directory /people/userid/: Data for a specific person info.json5: Profile information page.md: Pr

This library offers powerful mock data generation capabilities for pydantic based models. It can also be used with other libraries that use pydantic as a foundation, for example SQLModel, Beanie and ormar.

Procedural-Maze-Generator-Algorithms Check out my youtube channel : Auctux Ressources Thanks to Jamis Buck Book : Mazes for programmers Requirements P

PyDS CLI Helping you manage your data science projects sanely. Requirements Anaconda/Miniconda/Miniforge/Mambaforge (Mambaforge recommended!) git on y

Data Lake Demo Source code for video demonstration detailed in the post, Building a Simple Data Lake on AWS . Build a simple data lake on AWS using a

MultiModal-Collaborative (MMC) Learning Framework for integrating RGB and Thermal spectral modalities This is the official code for NeurIPS 2021 Machi

Generative Adversarial Network - Generating Universe This repository contains part of the code used to make the images visible in the article "How doe

Command line utilities for tabular data files This is a set of command line utilities for manipulating large tabular data files. Files of numeric and

Desafio Modulo 4 - Cloud Data Engineer Bootcamp - IGTI Objetivos Criar infraestrutura como código Utuilizando um cluster Kubernetes na Azure Ingestão

Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data. Then used Yahoo Finance to get the related stock data and displayed them in the form of charts.

English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc

FAIMED 3D use fastai to quickly train fully three-dimensional models on radiological data Classification from faimed3d.all import * Load data in vari

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF

Project5-Data-processing-system User just needed to copy both these file to a folder and open Project5.py using cmd or using any python ide. It is to

zEpid zEpid is an epidemiology analysis package, providing easy to use tools for epidemiologists coding in Python 3.5+. The purpose of this library is

Explorative Data Analysis Get data into a usable format! Find out if the following predictive modeling phase will be successful! Combine everything in

cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear

Impyute is a library of missing data imputation algorithms. This library was designed to be super lightweight, here's a sneak peak at what impyute can do.

Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.

Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas. Its objective is to ex

dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.

Pypeln Pypeln (pronounced as "pypeline") is a simple yet powerful Python library for creating concurrent data pipelines. Main Features Simple: Pypeln

Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and

Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm

MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data. We demonstrate its use

Dump Data from FTDI Serial Port to Binary File on MacOS

Crypto Stats and Tweets Data Pipeline using Airflow Introduction Project Overview This project was brought upon through Udacity's nanodegree program.

trRosetta This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicte

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

68 keypoint annotations for COFW test data This repository contains manually annotated 68 keypoints for COFW test data (original annotation of CFOW da

Whale Demo Instance: Bigquery Public Data This is a fully-functioning demo instance of the whale data catalog, actively scraping data from Bigquery's

FFT-accelerated Interpolation-based t-SNE (FIt-SNE) Introduction t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful method for dimensi

Code for an interactive UMAP visualization of the MNIST data set. Demo at https://grantcuster.github.io/umap-explorer/. You can read more about the de

giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G

Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It inc

Visualization of the Austrian Monuments Visualization of the monument landscape of the austrian monuments registry (Bundesdenkmalamt Denkmalverzeichni

Falcon: Interactive Visual Analysis for Big Data Crossfilter millions of records without latencies. This project is work in progress and not documente

Visdom A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Python. Overview Concepts Setup Usage API To

Make Complex Heatmaps Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. H

Colorcet: Collection of perceptually uniform colormaps Build Status Coverage Latest dev release Latest release Docs What is it? Colorcet is a collecti

Welcome to Streamlit 👋 The fastest way to build and share data apps. Streamlit lets you turn data scripts into sharable web apps in minutes, not week

Awesome Streamlit The fastest way to build Awesome Tools and Apps! Powered by Python! The purpose of this project is to share knowledge on how Awesome

Visdom A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Python. Overview Concepts Setup Usage API To

Sample Analytics In large-scale surveys, often complex random mechanisms are used to select samples. Estimates derived from such samples must reflect

Datashader is a data rasterization pipeline for automating the process of creating meaningful representations of large amounts of data.

An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu

Nuance I use Nuance to curate varied visualization thoughts during my data scientist career. It is not yet a package but a list of small ideas. Welcom

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Approximate Nearest Neighbor Search for Sparse Data in Python! This library is well suited to finding nearest neighbors in sparse, high dimensional spaces (like text documents).

Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.

A program that analyzes data from inertia measurement units installeed in aircraft and generates g-exceedance curves

radiale what if home-automation was also homoiconic? The upper or proximal row contains three bones, to which Gegenbaur has applied the terms radiale,

Byte Steganography Image/Data Injector. For artists or people to inject their own print/data into their images. TODO Add more file formats to support.

dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu

Facebook Scraper Use Flask API to wrap Facebook data. Grab the wapper of Facebook public pages without an API key. (Currently working 2021) Setup Befo

Stock and Index Beta Calculator Python script that calculates the beta (β) of a stock against the chosen index. The script retrieves the data and resa

accsr This lightweight library contains utilities for managing, loading, uploading, opening and generally wrangling data and configurations. It was ba

BENDR BErt-like Neurophysiological Data Representation This repository contains the source code for reproducing, or extending the BERT-like self-super

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite

ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T

Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat

Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c

MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant

sqliteBasics create a database, insert data and easily select it with Sqlite Watch on YouTube a step by step tutorial explaining this code: https://yo

insilico: A Python package to process & model ChEMBL data. ChEMBL is a manually curated chemical database of bioactive molecules with drug-like proper

foamTEX An open source utility for creating publication quality LaTex figures generated from OpenFOAM data files. Explore the docs » Report Bug · Requ

DBMS project- Hotel Franchise Data and application project By TEAM Kurukunda Bhargavi Pamulapati Pallavi Greeshma Amaraneni What is this project about

Sheet Data Image/PDF-to-CSV Converter

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

'db' within pydantic - A single model for shaping, creating, accessing, storing data within a Database Key Features Integrated Redis Caching Support A

This is a tool to help you quickly solve classification problems including: data analysis, training, report results and model explanation.

datasketch: Big Data Looks Small datasketch gives you probabilistic data structures that can process and search very large amount of data super fast,

AugMix Introduction We propose AugMix, a data processing technique that mixes augmented images and enforces consistent embeddings of the augmented ima

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Youtube video details analyser Steps to run this project Please set the AuthKey which you can fetch from google developer console and paste it in the