Covid County Executive summary Setup Install miniconda, then in the command line, run conda create -n covid-county conda activate covid-county conda i

Overview OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase

reliabiliPy Summary Simple implementation in Python of the [reliability](https://en.wikipedia.org/wiki/Reliability_(statistics) measures for surveys:

The Spark Challenge Student Check-In/Out Tracking Script This Python Script uses the Student ID Database to match the entries with the ID Card Swipe a

Larch: Data Analysis Tools for X-ray Spectroscopy and More Documentation: http://xraypy.github.io/xraylarch Code: http://github.com/xraypy/xraylarch L

ETL Pipeline for AWS Project Description In this project, ETL pipeline is build on data warehouse hosted on AWS Redshift. The data is loaded from S3 t

Minimal Pandas API for Polars Install From PyPI: pip install minimal-pandas-api-for-polars Example Usage (see tests/test_minimal_pandas_api_for_polars

Binance Kline Data by seunghan(gingerthorp) reference https://github.com/binance/binance-public-data/ All intervals are supported: 1m, 3m, 5m, 15m, 30

Meltano is open source, self-hosted, CLI-first, debuggable, and extensible. Pipelines are code, ready to be version c

Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are st

Exploratory Data Analysis for Employee Retention Dataset Employee turn-over is a very costly problem for companies. The cost of replacing an employee

Spark-DeltaLake-Demo Reliable, Scalable Machine Learning (2022) This project was completed in an attempt to become better acquainted with the latest b

pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive.

The following Python scripts aim to use a Random Forest machine learning algorithm to predict the water affinity of Metal-Organic Frameworks (MOFs). The training set is extracted from the Cambridge S

Processing-data-with-python This is a simple example showing how to use Pandas to create a dataframe and the processing data with python. The jupyter

databooks is a package for reducing the friction data scientists while using Jupyter notebooks, by reducing the number of git conflicts between different notebooks and assisting in the resolution of

timeranges Time ranges. Read the Docs Installation pip timeranges is available on pip: pip install timeranges GitHub You can also install the latest v

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).

Data Analysis for First Year Laboratory at Imperial College, London. For personal reference only, and to reference in lab reports and lab books.

API to fetch elements of the periodic table in JSON format. Uses Pandas for dumping .csv data to .json and Flask for API Integration. Deployed on "pyt