Reverse Dependencies of statsmodels

The following projects have a declared dependency on statsmodels:

• dnntime — An end-to-end, modular deep learning package time-series predictive modeling.
• docko — no summary
• doex — Python library for conducting design of experiments
• dominance-analysis — Dominance Analysis
• domino-code-assist — no summary
• dorkylever-lama-phenotype-detection — Phenotype detection pipeline for finding abnormalities in mouse embryos
• DoubleML — Double Machine Learning in Python
• dowhy — DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions
• doyle — doyle description
• dpi-sc — An end-to-end single-cell multimodal analysis model with deep parameter inference.
• dpkits — A small package for data processing
• dpks — Data processing package for the analysis of omics data
• dplpy — Dendrochronology Program Library for Python
• dreegdl — Depression Rest EEG Deep Learning - Deep Learning tools for Depression Rest EEG signals
• dretools — A software package for finding differential RNA editing.
• drexml — (DRExM³L) Drug REpurposing using and eXplainable Machine Learning and Mechanistic Models of signal transduction"
• drfetools — A package for preforming dynamic recursive feature elimination with sklearn.
• drfsc — A Python package implementing a distributed randomised feature selection algorithm.
• drifter-ml — Testing for models confirming to the scikit-learn api
• Driver2Comm — A computational framework for associating cancer cell-intrinsic driver genes with -extrinsic cell-cell communication
• DriverPower — Combined burden and functional test for coding and noncoding cancer drivers
• drug2cell — Gene group activity utility functions for scanpy
• drug2ways — Reasoning over polar paths in biological networks for drug discovery applications
• ds-methods — Pipelines architecture for common data science methods and time series analysis
• ds-modules-101 — A small package to help with some routine Data Science activities
• ds-pricing-framework — Read the latest Real Python tutorials
• ds-toolbox — A ToolBox with daily helpers for the analytical part of a Data Scientist.
• dsbundle — Streamline your data science setup with dsbundle in one effortless install.
• dscim — Data-Driven Spatial Climate Impact Model core component code
• dshelper — dshelper: A GUI tool to display pandas dataframe and draw plots in a few clicks
• dslibs-baosws — A unified module of frequently used data-science modules
• dspawpy — Tools for dspaw
• dsplus — Helper functions for data science applications
• dSreg — Joint inference of alternative splicing and regulatory changes
• dstricks — Data science package
• dsu — no summary
• dswe — A python package to supplement the Data Science for Wind Energy (DSWE) book.
• dtaianomaly — A simple-to-use Python package for time series anomaly detection!
• dtg — Heavy-tailed distribution analysis
• dvh-analytics — Create a database of DVHs, views with Bokeh
• dvha — Create a database of DVHs, GUI with wxPython, plots with Bokeh
• dynamask — Dynamask - Explaining Time Series Predictions with Dynamic Masks
• dynamo-release — Mapping Vector Field of Single Cells
• dynapipe — Dynamic Pipeline is a high-level API to help data scientists building models in ensemble way, and automating Machine Learning workflow with simple coding.
• dynetlsm — dynetlsm
• dysregnet — DysRegNet
• e2e-sae — Repo for training sparse autoencoders end-to-end
• eagles — Data science utility package to help practitioners do ML and EDA work.
• eap — This package is designed for empirical asset pricing
• easy-es — Python Event Financial Study
• easy-ht — A Python package for easy Hypothesis Tests
• easycheml — A simple tool for using artificial intelligence in chemistry
• easyclimate — A line of code to analyze climate
• easycreditscoring — Simple library combining efficient credit scoring ML methods
• easyEEG — Concise, agile, and flexible EEG toolbox
• EasyEventStudies — A package to conduct event studies
• easyexplore — Toolbox for easy and effective data exploration
• easypqp — EasyPQP: Simple library generation for OpenSWATH
• ebmdatalab — Package for ebmdatalab jupyter notebook stuff
• eBoruta — Extended Boruta -- a flexible transparent sklearn-compatible python Boruta implementation
• ebosc — extended Better Oscillation Detection, implemented in python3
• Echelon8-test — Backtesting Engine
• EclipsingBinaries — "Binary Star Package for Ball State University's Astronomy Research Group"
• ecoforest — no summary
• ecoform-alvin — Economic models
• econkit — Advanced Econometric Analysis Tools
• econml — This package contains several methods for calculating Conditional Average Treatment Effects
• econmodels — A collection of econometric modelling tools
• econometricMethodsESAN — Economic models
• econuy — Wrangling Uruguayan economic data so you don't have to.
• ecopipeline — Contains functions for use in Ecotope Datapipelines
• EcoStock — A Python package designed for finance professionals and economists
• eda-fe-model — A python package to handle EDA and feature extraction and also return the best hyperparameters for a tabular classification problem.
• EDAeasy — Functions and tools for making Exploratory Data Analysis easy!
• Edatora — A python package that runs exploratory data analysis for users
• edawesome — Quick, easy and customizable data analysis with pandas and seaborn
• edgaro — Explainable imbalanceD learninG compARatOr
• edges-cal — Calibration routines for EDGES data
• edvart — Effective data visualization and reporting tool
• eeg-emotion-recognition — no summary
• eemeter — Open Energy Efficiency Meter
• eensight — A library for measurement and verification of energy efficiency projects.
• eeSDM — Google Earth Engine-based Species Distribution Modeling
• efa-utils — Custom utility functions for exploratory factor analysis with the factor_analyzer package.
• effectsize — Computing effect sizes in Python
• EGCI — Ecoacoustic Global Complexity Index (EGCI)
• eig — Enhanced Integrated Gradients - a method of attributing the prediction of a deep network to its input features
• eir-auto-gp — no summary
• eis_toolkit — EIS Toolkit is a comprehensive collection of tools suitable for mineral prospectivity mapping. This toolkit has been developed as part of the Exploration Information System project which has been funded by European Union.
• elephant — Elephant is a package for analysis of electrophysiology data in Python
• emat — Add a short description here
• emgregs — Python port to Yanxi Li's R emg flare code
• empyricalRMT — Eigenvalue unfolding and spectral observable computation
• emxps — Miscellanous Explanation Methods
• enan — a package for ENrichment ANalyses
• enda — Tools to manipulate energy time-series and contracts, and to perform forecasts.
• endersgame — Online autonomous time series prediction of near martingales
• energy-analysis-toolbox — A set of tools to manipulate and transform power, and energy timeseries data.
• EnergySystemModels — Energy systems models are the mathematical models that are developed in order to represent as reliably as possible various energy-related problems.
• enfobench — Energy forecast benchmarking toolkit.