# Python - Data Science

Awesome Python Data Science

Probably the best curated list of data science software in Python

## Contents

- Machine Learning
- Deep Learning
- Web Scraping
- Data Manipulation
- Feature Engineering
- Visualization
- Deployment
- Model Explanation
- Reinforcement Learning
- Probabilistic Methods
- Genetic Programming
- Optimization
- Time Series
- Natural Language Processing
- Computer Audition
- Computer Vision
- Statistics
- Distributed Computing
- Experimentation
- Evaluation
- Computations
- Spatial Analysis
- Quantum Computing
- Conversion

## Machine Learning

### General Purpouse Machine Learning

- scikit-learn - Machine learning in Python.
- Shogun - Machine learning toolbox.
- xLearn - High Performance, Easy-to-use, and Scalable Machine Learning Package.
- cuML - RAPIDS Machine Learning Library.
- modAL - Modular active learning framework for Python3.
- Sparkit-learn - PySpark + scikit-learn = Sparkit-learn.
- mlpack - A scalable C++ machine learning library (Python bindings).
- dlib - Toolkit for making real world machine learning and data analysis applications in C++ (Python bindings).
- MLxtend - Extension and helper modules for Python's data analysis and machine learning libraries.
- hyperlearn - 50%+ Faster, 50%+ less RAM usage, GPU support re-written Sklearn, Statsmodels.
- Reproducible Experiment Platform (REP) - Machine Learning toolbox for Humans.
- scikit-multilearn - Multi-label classification for python.
- seqlearn - Sequence classification toolkit for Python.
- pystruct - Simple structured learning framework for Python.
- sklearn-expertsys - Highly interpretable classifiers for scikit learn.
- RuleFit - Implementation of the rulefit.
- metric-learn - Metric learning algorithms in Python.
- pyGAM - Generalized Additive Models in Python.
- Karate Club - An unsupervised machine learning library for graph structured data.
- Little Ball of Fur - A library for sampling graph structured data.
- causalml - Uplift modeling and causal inference with machine learning algorithms.
- Deepchecks - Validation & testing of ML models and data during model development, deployment, and production.

### Automated Machine Learning

- TPOT - Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
- auto-sklearn - An automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.
- MLBox - A powerful Automated Machine Learning python library.

### Ensemble Methods

- ML-Ensemble - High performance ensemble learning.
- Stacking - Simple and useful stacking library, written in Python.
- stacked_generalization - Library for machine learning stacking generalization.
- vecstack - Python package for stacking (machine learning technique).

### Imbalanced Datasets

- imbalanced-learn - Module to perform under sampling and over sampling with various techniques.
- imbalanced-algorithms - Python-based implementations of algorithms for learning on imbalanced data.

### Random Forests

- rpforest - A forest of random projection trees.
- sklearn-random-bits-forest - Wrapper of the Random Bits Forest program written by (Wang et al., 2016).
- rgf_python - Python Wrapper of Regularized Greedy Forest.

### Extreme Learning Machine

- Python-ELM - Extreme Learning Machine implementation in Python.
- Python Extreme Learning Machine (ELM) - A machine learning technique used for classification/regression tasks.
- hpelm - High performance implementation of Extreme Learning Machines (fast randomized neural networks).

### Kernel Methods

- pyFM - Factorization machines in python.
- fastFM - A library for Factorization Machines.
- tffm - TensorFlow implementation of an arbitrary order Factorization Machine.
- liquidSVM - An implementation of SVMs.
- scikit-rvm - Relevance Vector Machine implementation using the scikit-learn API.
- ThunderSVM - A fast SVM Library on GPUs and CPUs.

### Gradient Boosting

- XGBoost - Scalable, Portable and Distributed Gradient Boosting.
- LightGBM - A fast, distributed, high performance gradient boosting.
- CatBoost - An open-source gradient boosting on decision trees library.
- ThunderGBM - Fast GBDTs and Random Forests on GPUs.

## Deep Learning

### PyTorch

- PyTorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration.
- torchvision - Datasets, Transforms and Models specific to Computer Vision.
- torchtext - Data loaders and abstractions for text and NLP.
- torchaudio - An audio library for PyTorch.
- ignite - High-level library to help with training neural networks in PyTorch.
- PyToune - A Keras-like framework and utilities for PyTorch.
- skorch - A scikit-learn compatible neural network library that wraps pytorch.
- PyTorchNet - An abstraction to train neural networks.
- pytorch_geometric - Geometric Deep Learning Extension Library for PyTorch.
- Catalyst - High-level utils for PyTorch DL & RL research.
- pytorch_geometric_temporal - Temporal Extension Library for PyTorch Geometric.

### TensorFlow

- TensorFlow - Computation using data flow graphs for scalable machine learning by Google.
- TensorLayer - Deep Learning and Reinforcement Learning Library for Researcher and Engineer.
- TFLearn - Deep learning library featuring a higher-level API for TensorFlow.
- Sonnet - TensorFlow-based neural network library.
- tensorpack - A Neural Net Training Interface on TensorFlow.
- Polyaxon - A platform that helps you build, manage and monitor deep learning models.
- NeuPy - NeuPy is a Python library for Artificial Neural Networks and Deep Learning (previously:).
- tfdeploy - Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy.
- tensorflow-upstream - TensorFlow ROCm port.
- TensorFlow Fold - Deep learning with dynamic computation graphs in TensorFlow.
- tensorlm - Wrapper library for text generation / language models at char and word level with RNN.
- TensorLight - A high-level framework for TensorFlow.
- Mesh TensorFlow - Model Parallelism Made Easier.
- Ludwig - A toolbox, that allows to train and test deep learning models without the need to write code.
- Keras - A high-level neural networks API running on top of TensorFlow.
- keras-contrib - Keras community contributions.
- Hyperas - Keras + Hyperopt: A very simple wrapper for convenient hyperparameter.
- Elephas - Distributed Deep learning with Keras & Spark.
- Hera - Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.
- Spektral - Deep learning on graphs.
- qkeras - A quantization deep learning library.

### MXNet

- MXNet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler.
- Gluon - A clear, concise, simple yet powerful and efficient API for deep learning (now included in MXNet).
- MXbox - Simple, efficient and flexible vision toolbox for mxnet framework.
- gluon-cv - Provides implementations of the state-of-the-art deep learning models in computer vision.
- gluon-nlp - NLP made easy.
- Xfer - Transfer Learning library for Deep Neural Networks.
- MXNet - HIP Port of MXNet.

### Others

- Tangent - Source-to-Source Debuggable Derivatives in Pure Python.
- autograd - Efficiently computes derivatives of numpy code.
- Myia - Deep Learning framework (pre-alpha).
- nnabla - Neural Network Libraries by Sony.
- Caffe - A fast open framework for deep learning.
- hipCaffe - The HIP port of Caffe.

## Web Scraping

- BeautifulSoup: The easiest library to scrape static websites for beginners
- Scrapy: Fast and extensible scraping library. Can write rules and create customized scraper without touching the coure
- Selenium: Use Selenium Python API to access all functionalities of Selenium WebDriver in an intuitive way like a real user.
- Pattern: High level scraping for well-establish websites such as Google, Twitter, and Wikipedia. Also has NLP, machine learning algorithms, and visualization
- twitterscraper: Efficient library to scrape twitter

## Data Manipulation

### Data Containers

- pandas - Powerful Python data analysis toolkit.
- pandas_profiling - Create HTML profiling reports from pandas DataFrame objects
- cuDF - GPU DataFrame Library.
- blaze - NumPy and pandas interface to Big Data.
- pandasql - Allows you to query pandas DataFrames using SQL syntax.
- pandas-gbq - pandas Google Big Query.
- xpandas - Universal 1d/2d data containers with Transformers .functionality for data analysis by The Alan Turing Institute.
- pysparkling - A pure Python implementation of Apache Spark's RDD and DStream interfaces.
- Arctic - High performance datastore for time series and tick data.
- datatable - Data.table for Python.
- koalas - pandas API on Apache Spark.
- modin - Speed up your pandas workflows by changing a single line of code.
- swifter - A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner.
- pandas_flavor - A package which allow to write your own flavor of Pandas easily.
- pandas-log - A package which allow to provide feedback about basic pandas operations and find both buisness logic and performance issues.
- vaex - Out-of-Core DataFrames for Python, ML, visualize and explore big tabular data at a billion rows per second.

### Pipelines

- pdpipe - Sasy pipelines for pandas DataFrames.
- SSPipe - Python pipe (|) operator with support for DataFrames and Numpy and Pytorch.
- pandas-ply - Functional data manipulation for pandas.
- Dplython - Dplyr for Python.
- sklearn-pandas - pandas integration with sklearn.
- Dataset - Helps you conveniently work with random or sequential batches of your data and define data processing.
- pyjanitor - Clean APIs for data cleaning.
- meza - A Python toolkit for processing tabular data.
- Prodmodel - Build system for data science pipelines.
- dopanda - Hints and tips for using pandas in an analysis environment.
- CircleCi: Automates your software builds, tests, and deployments.

## Feature Engineering

### General

- Featuretools - Automated feature engineering.
- skl-groups - A scikit-learn addon to operate on set/"group"-based features.
- Feature Forge - A set of tools for creating and testing machine learning feature.
- few - A feature engineering wrapper for sklearn.
- scikit-mdr - A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
- tsfresh - Automatic extraction of relevant features from time series.

### Feature Selection

- scikit-feature - Feature selection repository in python.
- boruta_py - Implementations of the Boruta all-relevant feature selection method.
- BoostARoota - A fast xgboost feature selection algorithm.
- scikit-rebate - A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

## Visualization

### General Purposes

- Matplotlib - Plotting with Python.
- seaborn - Statistical data visualization using matplotlib.
- prettyplotlib - Painlessly create beautiful matplotlib plots.
- python-ternary - Ternary plotting library for python with matplotlib.
- missingno - Missing data visualization module for Python.
- chartify - Python library that makes it easy for data scientists to create charts.
- physt - Improved histograms.

### Interactive plots

- animatplot - A python package for animating plots build on matplotlib.
- plotly - A Python library that makes interactive and publication-quality graphs.
- Bokeh - Interactive Web Plotting for Python.
- Altair - Declarative statistical visualization library for Python. Can easily do many data transformation within the code to create graph
- bqplot - Plotting library for IPython/Jupyter notebooks
- pyecharts - Migrated from Echarts, a charting and visualization library, to Python's interactive visual drawing library.

### Map

- folium - Makes it easy to visualize data on an interactive open street map
- geemap - Python package for interactive mapping with Google Earth Engine (GEE)

### Automatic Plotting

- HoloViews - Stop plotting your data - annotate your data and let it visualize itself.
- AutoViz: Visualize data automatically with 1 line of code (ideal for machine learning)
- SweetViz: Visualize and compare datasets, target values and associations, with one line of code.

### NLP

- pyLDAvis: Visualize interactive topic model

## Deployment

- datapane - A collection of APIs to turn scripts and notebooks into interactive reports.
- binder - Enable sharing and execute Jupyter Notebooks
- fastapi - Modern, fast (high-performance), web framework for building APIs with Python
- streamlit - Make it easy to deploy machine learning model

## Model Explanation

- Shapley - A data-driven framework to quantify the value of classifiers in a machine learning ensemble.
- Alibi - Algorithms for monitoring and explaining machine learning models.
- anchor - Code for "High-Precision Model-Agnostic Explanations" paper.
- aequitas - Bias and Fairness Audit Toolkit.
- Contrastive Explanation - Contrastive Explanation (Foil Trees).
- yellowbrick - Visual analysis and diagnostic tools to facilitate machine learning model selection.
- scikit-plot - An intuitive library to add plotting functionality to scikit-learn objects.
- shap - A unified approach to explain the output of any machine learning model.
- ELI5 - A library for debugging/inspecting machine learning classifiers and explaining their predictions.
- Lime - Explaining the predictions of any machine learning classifier.
- FairML - FairML is a python toolbox auditing the machine learning models for bias.
- L2X - Code for replicating the experiments in the paper
*Learning to Explain: An Information-Theoretic Perspective on Model Interpretation*. - PDPbox - Partial dependence plot toolbox.
- pyBreakDown - Python implementation of R package breakDown.
- PyCEbox - Python Individual Conditional Expectation Plot Toolbox.
- Skater - Python Library for Model Interpretation.
- model-analysis - Model analysis tools for TensorFlow.
- themis-ml - A library that implements fairness-aware machine learning algorithms.
- treeinterpreter - Interpreting scikit-learn's decision tree and random forest predictions.
- AI Explainability 360 - Interpretability and explainability of data and machine learning models.
- Auralisation - Auralisation of learned features in CNN (for audio).
- CapsNet-Visualization - A visualization of the CapsNet layers to better understand how it works.
- lucid - A collection of infrastructure and tools for research in neural network interpretability.
- Netron - Visualizer for deep learning and machine learning models (no Python code, but visualizes models from most Python Deep Learning frameworks).
- FlashLight - Visualization Tool for your NeuralNetwork.
- tensorboard-pytorch - Tensorboard for pytorch (and chainer, mxnet, numpy, ...).
- mxboard - Logging MXNet data for visualization in TensorBoard.

## Reinforcement Learning

- OpenAI Gym - A toolkit for developing and comparing reinforcement learning algorithms.
- Coach - Easy experimentation with state of the art Reinforcement Learning algorithms.
- garage - A toolkit for reproducible reinforcement learning research.
- OpenAI Baselines - High-quality implementations of reinforcement learning algorithms.
- Stable Baselines - A set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines.
- RLlib - Scalable Reinforcement Learning.
- Horizon - A platform for Applied Reinforcement Learning.
- TF-Agents - A library for Reinforcement Learning in TensorFlow.
- TensorForce - A TensorFlow library for applied reinforcement learning.
- TRFL - TensorFlow Reinforcement Learning.
- Dopamine - A research framework for fast prototyping of reinforcement learning algorithms.
- keras-rl - Deep Reinforcement Learning for Keras.
- ChainerRL - A deep reinforcement learning library built on top of Chainer.

## Probabilistic Methods

- pomegranate - Probabilistic and graphical models for Python.
- pyro - A flexible, scalable deep probabilistic programming library built on PyTorch.
- ZhuSuan - Bayesian Deep Learning.
- PyMC - Bayesian Stochastic Modelling in Python.
- PyMC3 - Python package for Bayesian statistical modeling and Probabilistic Machine Learning.
- sampled - Decorator for reusable models in PyMC3.
- Edward - A library for probabilistic modeling, inference, and criticism.
- InferPy - Deep Probabilistic Modelling Made Easy.
- GPflow - Gaussian processes in TensorFlow.
- PyStan - Bayesian inference using the No-U-Turn sampler (Python interface).
- sklearn-bayes - Python package for Bayesian Machine Learning with scikit-learn API.
- skggm - Estimation of general graphical models.
- pgmpy - A python library for working with Probabilistic Graphical Models.
- skpro - Supervised domain-agnostic prediction framework for probabilistic modelling by The Alan Turing Institute.
- Aboleth - A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation.
- PtStat - Probabilistic Programming and Statistical Inference in PyTorch.
- PyVarInf - Bayesian Deep Learning methods with Variational Inference for PyTorch.
- emcee - The Python ensemble sampling toolkit for affine-invariant MCMC.
- hsmmlearn - A library for hidden semi-Markov models with explicit durations.
- pyhsmm - Bayesian inference in HSMMs and HMMs.
- GPyTorch - A highly efficient and modular implementation of Gaussian Processes in PyTorch.
- MXFusion - Modular Probabilistic Programming on MXNet.
- sklearn-crfsuite - A scikit-learn inspired API for CRFsuite.

## Genetic Programming

- gplearn - Genetic Programming in Python.
- DEAP - Distributed Evolutionary Algorithms in Python.
- karoo_gp - A Genetic Programming platform for Python with GPU support.
- monkeys - A strongly-typed genetic programming framework for Python.
- sklearn-genetic - Genetic feature selection module for scikit-learn.

## Optimization

- Spearmint - Bayesian optimization.
- BoTorch - Bayesian optimization in PyTorch.
- scikit-opt - Heuristic Algorithms for optimization.
- SMAC3 - Sequential Model-based Algorithm Configuration.
- Optunity - Is a library containing various optimizers for hyperparameter tuning.
- hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python.
- hyperopt-sklearn - Hyper-parameter optimization for sklearn.
- sklearn-deap - Use evolutionary algorithms instead of gridsearch in scikit-learn.
- sigopt_sklearn - SigOpt wrappers for scikit-learn methods.
- Bayesian Optimization - A Python implementation of global optimization with gaussian processes.
- SafeOpt - Safe Bayesian Optimization.
- scikit-optimize - Sequential model-based optimization with a
`scipy.optimize`

interface. - Solid - A comprehensive gradient-free optimization framework written in Python.
- PySwarms - A research toolkit for particle swarm optimization in Python.
- Platypus - A Free and Open Source Python Library for Multiobjective Optimization.
- GPflowOpt - Bayesian Optimization using GPflow.
- POT - Python Optimal Transport library.
- Talos - Hyperparameter Optimization for Keras Models.
- nlopt - Library for nonlinear optimization (global and local, constrained or unconstrained).

## Time Series

- sktime - A unified framework for machine learning with time series.
- tslearn - Machine learning toolkit dedicated to time-series data.
- tick - Module for statistical learning, with a particular emphasis on time-dependent modelling.
- Prophet - Automatic Forecasting Procedure.
- PyFlux - Open source time series library for Python.
- bayesloop - Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
- luminol - Anomaly Detection and Correlation library.
- dateutil - Powerful extensions to the standard datetime module
- maya - makes it very easy to parse a string and for changing timezones

## Natural Language Processing

- NLTK - Modules, data sets, and tutorials supporting research and development in Natural Language Processing.
- CLTK - The Classical Language Toolkik.
- gensim - Topic Modelling for Humans.
- PSI-Toolkit - A natural language processing toolkit.
- pyMorfologik - Python binding for Morfologik.
- skift - Scikit-learn wrappers for Python fastText.
- Phonemizer - Simple text to phonemes converter for multiple languages.
- flair - Very simple framework for state-of-the-art NLP.
- spaCy - Industrial-Strength Natural Language Processing.

## Computer Audition

- librosa - Python library for audio and music analysis.
- Yaafe - Audio features extraction.
- aubio - A library for audio and music analysis.
- Essentia - Library for audio and music analysis, description and synthesis.
- LibXtract - A simple, portable, lightweight library of audio feature extraction functions.
- Marsyas - Music Analysis, Retrieval and Synthesis for Audio Signals.
- muda - A library for augmenting annotated audio data.
- madmom - Python audio and music signal processing library.

## Computer Vision

- OpenCV - Open Source Computer Vision Library.
- scikit-image - Image Processing SciKit (Toolbox for SciPy).
- imgaug - Image augmentation for machine learning experiments.
- imgaug_extension - Additional augmentations for imgaug.
- Augmentor - Image augmentation library in Python for machine learning.
- albumentations - Fast image augmentation library and easy to use wrapper around other libraries.

## Statistics

- pandas_summary - Extension to pandas dataframes describe function.
- Pandas Profiling - Create HTML profiling reports from pandas DataFrame objects.
- statsmodels - Statistical modeling and econometrics in Python.
- stockstats - Supply a wrapper
`StockDataFrame`

based on the`pandas.DataFrame`

with inline stock statistics/indicators support. - weightedcalcs - A pandas-based utility to calculate weighted means, medians, distributions, standard deviations, and more.
- scikit-posthocs - Pairwise Multiple Comparisons Post-hoc Tests.
- Alphalens - Performance analysis of predictive (alpha) stock factors.

## Distributed Computing

- Horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
- PySpark - Exposes the Spark programming model to Python.
- Veles - Distributed machine learning platform.
- Jubatus - Framework and Library for Distributed Online Machine Learning.
- DMTK - Microsoft Distributed Machine Learning Toolkit.
- PaddlePaddle - PArallel Distributed Deep LEarning.
- dask-ml - Distributed and parallel machine learning.
- Distributed - Distributed computation in Python.

## Experimentation

- Sacred - A tool to help you configure, organize, log and reproduce experiments.
- Xcessiv - A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling.
- Persimmon - A visual dataflow programming language for sklearn.
- Ax - Adaptive Experimentation Platform.
- Neptune - A lightweight ML experiment tracking, results visualization and management tool.

## Evaluation

- recmetrics - Library of useful metrics and plots for evaluating recommender systems.
- Metrics - Machine learning evaluation metric.
- sklearn-evaluation - Model evaluation made easy: plots, tables and markdown reports.
- AI Fairness 360 - Fairness metrics for datasets and ML models, explanations and algorithms to mitigate bias in datasets and models.

## Computations

- numpy - The fundamental package needed for scientific computing with Python.
- Dask - Parallel computing with task scheduling.
- bottleneck - Fast NumPy array functions written in C.
- CuPy - NumPy-like API accelerated with CUDA.
- scikit-tensor - Python library for multilinear algebra and tensor factorizations.
- numdifftools - Solve automatic numerical differentiation problems in one or more variables.
- quaternion - Add built-in support for quaternions to numpy.
- adaptive - Tools for adaptive and parallel samping of mathematical functions.

## Spatial Analysis

## Quantum Computing

- PennyLane - Quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations.
- QML - A Python Toolkit for Quantum Machine Learning.

## Conversion

- sklearn-porter - Transpile trained scikit-learn estimators to C, Java, JavaScript and others.
- ONNX - Open Neural Network Exchange.
- MMdnn - A set of tools to help users inter-operate among different deep learning frameworks.

## Contributing

Contributions are welcome! 😎 Read the contribution guideline.

## License

This work is licensed under the Creative Commons Attribution 4.0 International License - CC BY 4.0

Deprecated Libs Waiting Room

Contribute to this list: https://github.com/krzjoa/awesome-python-data-science