correlations

Statistical package in Python based on Pandas

🔗 Methods for Correlation Analysis

Python package to generate Gaussian (1/f)**beta noise (e.g. pink noise)

Compute interstation correlations of seismic ambient noise, including fast implementations of the standard, 1-bit and phase cross-correlations.

Statistical standard error estimation tools for correlated data

A Python package to calculate, visualize and analyze correlation maps of proteins.

Abinitio Dynamical Vertex Approximation

Fast and flexible two- and three-point correlation analysis for time series using spectral methods.

Rust Statistics and Vector Algebra Library

Codes written in the course of a data science workshop at KIT in cooperation with FZI

Text Mining and Analysis with Biplots.

Util library to provide R-like dataframes and statistical functions over Parquet DataSet from parquet-dotnet

Data Mining project 2020/2021 @ UniPi

A hub that contains notebooks that perform elementary descriptive statistics of populations and samples and demonstrates 3 hypothesis tests- Welch t-test, Correlation, and Chi-square test. It shows how to run them in python and understand the results

Data Understanding, Visualization , Preparation & Cleaning - Clustering algorithms (unsupervised learning) - Classification algorithms (supervised learning) - Sequential Pattern Mining

An R package to explore and quality check data

This contains R Script to calculate Top-down Correlation Iman & Conover Tecnometrics 1987

A web scraper and some ML analysis scripts for recipe data

Code repository for New J. Phys. 20, 043034 (2018) [arXiv:1708.06363]

Identifying relationships between Spotify popularity score and audio features, webscrape Billboards, test classification algorithms

Visualization project of diabetes rates along Age, Income, Food Security, and Urban/Rural settings.

This repository includes my Liver Disease Machine Learning-Flatiron School Module 3 Project. For this project I used libraries such as Pandas, Matplotlib, and Seaborn for visualizations and Scikit-Learn for the machine learning portion of the project. I implemented various classification algorithms on the data including some hyperparameter tuning.

Binary classification of residential utility problems in NYC; Capstone project for the IBM Certificate in Data Science

A basic analysis of poverty with a special emphasis on the United States.

A dive into undefined criteria to analyze highlighted season statistics to predict the MVP of the NBA.

To explore the given dataset for all basic statistics such as the distributions, correlations, outliers, missing values, etc.

A New Parametrization of Correlation Matrices

App para calcular la ecuación de regresión lineal simple, leyendo los datos desde un archivo CSV

The project aims to better understand the company's customers and make more effective marketing strategies when modifying products to customers in different segments.

Web scraping additional data to building a model to predict football coaches' salaries