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)

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

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

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

Statistical standard error estimation tools for correlated data

Abinitio Dynamical Vertex Approximation

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

Data Mining project 2020/2021 @ University of Pisa

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

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

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

Text Mining and Analysis with Biplots.

An R package to explore and quality check data

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

A network model for studying the relation between temporal dynamics and connectivity structures

A Python library for implementing pairwise Cramer's V Correlation for all Categorical Features in Pandas Dataframe (along with heatmap).

This repository contains the code for an R function that will report p-values for pairwise correlation coefficient comparisons and that will report corresponding separation lettering.

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.