Statistical package in Python based on Pandas
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Updated
Jul 23, 2024 - Python
Statistical package in Python based on Pandas
🔗 Methods for Correlation Analysis
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.
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.
A Python package to calculate, visualize and analyze correlation maps of proteins.
Statistical standard error estimation tools for correlated data
NeuroGNN is a state-of-the-art framework for precise seizure detection and classification from EEG data. It employs dynamic Graph Neural Networks (GNNs) to capture intricate spatial, temporal, semantic, and taxonomic correlations between EEG electrode locations and brain regions, resulting in improved accuracy. Presented at PAKDD '24.
Abinitio Dynamical Vertex Approximation
Data Mining project 2020/2021 @ University of Pisa
Fast and flexible two- and three-point correlation analysis for time series using spectral methods.
🔎Data Understanding, Visualization , Preparation & Cleaning - Clustering algorithms (unsupervised learning) - Classification algorithms (supervised learning) - Sequential Pattern Mining
Codes written in the course of a data science workshop at KIT in cooperation with FZI
An R package to explore and quality check data
Text Mining and Analysis with Biplots.
Util library to provide R-like dataframes and statistical functions over Parquet DataSet from parquet-dotnet
A Python utility for Cramer's V Correlation Analysis for Categorical Features in Pandas Dataframes.
Global sensitivity analysis that takes into account correlations and dependencies in the LCA model during uncertainty propagation with Monte Carlo approach.
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 structure
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