Imputation Python Packages

tsdb

a Python toolbox loads 173 public time series datasets for machine/deep learning with a single line of code. Datasets from multiple domains including healthcare, financial, power, traffic, weather, and etc.

pypots

A Python toolkit/library for reality-centric machine/deep learning & data mining on partially-observed time series, with 50+ SOTA neural network models for scientific analysis tasks (imputation, classification, clustering, forecasting, anomaly detection, cleaning) on incomplete industrial irregularly-sampled multivariate TS with NaN missing values

pygrinder

PyGrinder: a Python toolkit for grinding data beans into the incomplete for real-world data simulation by introducing missing values with different missingness patterns, including MCAR (complete at random), MAR (at random), MNAR (not at random), sub sequence missing, and block missing

knnimpute

Python implementations of kNN imputation

handyspark

HandySpark - bringing pandas-like capabilities to Spark dataframes

isotree

(Python, R, C/C++) Isolation Forest and variations such as SCiForest and EIF, with some additions (outlier detection + similarity + NA imputation)

awesomepmc

Copula-based pairwise Markov chains for non-Gaussian time-series classification, estimation, imputation and forecasting.

geoanalytics

This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

univi

UniVI is a scalable multi-modal VAE toolkit for aligning heterogeneous single-cell datasets into a shared latent space—supporting unimodal, dual-modal, and tri-modal (and beyond) integration. It can additionally be used for cross-modal imputation, data generation of biologically-relevant synthetic samples, data denoising, and structured evaluation.

momentfm

MOMENT: A Family of Open Time-series Foundation Models, ICML'24

impyute

Data imputations library to preprocess datasets with missing data

gators

Lightning-fast data preprocessing and feature engineering for Python, built on Polars. 108 sklearn-style transformers for imputation, encoding, scaling, outlier clipping, discretization and feature selection, with Pipeline support and ONNX export for low-latency inference.

pcrsaits

Lightweight post-hoc residual correction for multivariate time-series imputation with SAITS, BRITS, and CSDI. PyPI package, reproducible experiments, and research ablations.

imputegap

ImputeGAP is a comprehensive Python library for imputation of missing values in time series data. It implements user-friendly APIs to easily visualize, analyze, and repair incomplete time series datasets.

tabforge-ml

🔨 [NeurIPS 2026] Official implementation of “TabFORGE: A Tabular Foundation Model for Generative Modelling”

rego

Automatic Time Series Forecasting and Missing Values Imputation

pycorruptor

PyGrinder: a Python toolkit for grinding data beans into the incomplete for real-world data simulation by introducing missing values with different missingness patterns, including MCAR (complete at random), MAR (at random), MNAR (not at random), sub sequence missing, and block missing

datafiller

Data imputation

datawig

Imputation of missing values in tables.

disc

A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.

pi-metaboqc

An object-oriented LC-MS metabolomics quality-control and preprocessing package for filtering, correction, imputation, normalization, assessment, and report generation.

sknnr

scikit-learn compatible estimators for various kNN imputation methods

hesseflux

hesseflux provides functions used in the processing and post-processing of the Eddy covariance flux data of the ICOS ecosystem site FR-Hes.

ae-imputer

A python package used for missing data imputation via autoencoders.