A curated list of Python libraries used for data science.

• Machine Learning Frameworks
• Scientific
• Deep Learning Frameworks
• Deep Learning Tools
• Deep Learning Projects
• Visualization
• AutoML
• Exploration
• Feature Extraction
• Trading
• Misc
• Deployment
• Python Tools
• Data Gathering

• scikit-learn - Machine learning.
• CatBoost - Gradient boosting library with categorical features support.
• LightGBM - Fast, distributed, high performance gradient boosting.
• Xgboost - Scalable, Portable and Distributed Gradient Boosting.
• PyMC - Probabilistic Programming.
• statsmodels - Statistical modeling and econometrics.
• SymPy - A computer algebra system.
• NetworkX - Creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
• dask-ml - Distributed and parallel machine learning.
• imbalanced-learn - Perform under sampling and over sampling.
• lightning - Large-scale linear models.
• sklearn-crfsuite - API for CRFsuite, Conditional Random Fields for labeling sequential data.
• vowpal_porpoise - Wrapper for vowpal_wabbit.
• scikit-optimize - Sequential model-based optimization with a scipy.optimize interface.
• BayesianOptimization - Global optimization with gaussian processes.
• gplearn - Genetic Programming.
• scikit-multilearn - Scikit-learn based module for multi-label.
• mlens - ML-Ensemble high performance ensemble learning.
• speedml - Speed start machine learning projects.
• fastFM - Factorization Machines.
• python-glmnet - glmnet package for fitting generalized linear models.
• hmmlearn - Hidden Markov Models.
• vecstack - stacking (machine learning technique).
• bayespy - Bayesian inference tools.
• modAL - Modular Active Learning framework
• deap - Evolutionary computation framework.
• pyro - Deep universal probabilistic programming with PyTorch.
• civisml-extensions - scikit-learn-compatible estimators from Civis Analytics.
• hyperopt-sklearn - Hyper-parameter optimization for sklearn.
• zhusuan - A Library for Bayesian Deep Learning, Generative Models, Based on Tensorflow.
• Kaggler - Code for Kaggle Data Science Competitions. Includes FTRL.
• modAL - A modular active learning framework.
• scikit-survival - Survival analysis built on top of scikit-learn.
• dstoolbox - Tools that make working with scikit-learn and pandas easier.
• dowhy - A unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
• modin - Unify the way you interact with your data.
• pyomo - Python Optimization MOdels.
• pymc-learn - Practical probabilistic machine learning.
• BAMBI - BAyesian Model-Building Interface.
• pymc4 - A high-level probabilistic programming interface for TensorFlow Probability.
• combo - A Python Toolbox for Machine Learning Model Combination.

• NumPy - A fundamental package for scientific computing with Python.
• SciPy - A Python-based ecosystem of open-source software for mathematics, science, and engineering.
• Pandas - A library providing high-performance, easy-to-use data structures and data analysis tools.
• Numba - NumPy aware dynamic Python compiler using LLVM.
• blaze - NumPy and Pandas for databases.
• astropy - Astronomy and astrophysics.
• Biopython - Astronomy and astrophysics.
• PyDy - Multibody Dynamics.
• DIPY - Diffusion MR Imaging.
• bcolz - Columnar data container that can be compressed.
• nilearn - NeuroImaging.
• patsy - Describing statistical models using symbolic formulas.
• numexpr - Fast numerical array expression evaluator.
• dask - Parallel computing with task scheduling.
• or-tools - Google's Operations Research tools. Classical CS algorithms.
• cvxpy - Python-embedded modeling language for convex optimization problems.

• Tensorflow - DL Framework.
• PyTorch - DL Framework.
• onnx - Open Neutral Network Exchange.
• Keras - High-level neutral networks API.
• tensorlayer - A Deep Learning and Reinforcement Learning Library for Researchers and Engineers.
• chainer - A flexible framework of neural networks for deep learning.
• mxnet - Apache MXNet: A flexible and efficient library for deep learning.

• Edward - Probabilistic programming language in TensorFlow.
• pomegranate - Probabilistic modelling.
• skorch - Scikit-learn PyTorch.
• DLTK - Deep Learning Toolkit for Medical Image Analysis.
• sonnet - TensorFlow-based neural network library.
• rasa_core - Dialogue engine.
• luminoth - Computer Vision.
• allennlp - NLP Research library.
• spotlight - Pytorch Recommender framework.
• tensorforce - TensorFlow library for applied reinforcement learning.
• tensorboard-pytorch - Tensorboard for pytorch.
• keras-vis - Neural network visualization toolkit for keras.
• hyperas - Keras + Hyperopt.
• spaCy - Natural Language processing.
• tensorboard_logger - Log TensorBoard events without touching TensorFlow.
• keras-contrib - Keras community contributions.
• tfdeploy - Deploy tensorflow graphs.
• ktext - Utilities for preprocessing text for deep learning with Keras.
• foolbox - Python toolbox to create adversarial examples that fool neural networks.
• pytorch/vision - Datasets, Transforms and Models specific to Computer Vision.
• gluon-nlp - NLP made easy.
• PyTorch-GAN - PyTorch implementations of Generative Adversarial Networks.
• pytorch/ignite - High-level library to help with training neural networks in PyTorch.
• NMT - Neural machine translation and neural sequence modeling.
• Netron - Visualizer for deep learning and machine learning models.
• gpytorch - A highly efficient and modular implementation of Gaussian Processes in PyTorch.
• tensorly - Tensor Learning in Python.
• einops - Deep learning operations reinvented.
• hiddenlayer - Neural network graphs and training metrics for PyTorch, Tensorflow, and Keras.
• dgl - Python package built to ease deep learning on graph, on top of existing DL frameworks.
• segmentation_models.pytorch - Segmentation models with pretrained backbones.
• pytorch-lightning - The lightweight PyTorch wrapper.

• fairseq - Sequence-to-Sequence Toolkit.
• gradient-checkpointing - Make huge neutral nets fit in memory.
• Detectron - FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
• detectorch - detectron for PyTorch.
• Detectron.pytorch - detectron for PyTorch.
• tensorflow-wavenet - DeepMind's WaveNet.
• wtte-rnn - WTTE-RNN a framework for churn and time to event prediction.
• 3D-convolution-speaker-recognition - Speaker verification.
• DeepRecommender - Recommender systems.
• DrQA - Reading Wikipedia to Answer Open-Domain Questions.
• vqa.pytorch - Visual Question Answering in Pytorch.
• Half-Life Regression - Model for spaced repetition practice.
• learning-to-learn - Learning to Learn in Tensorflow.
• face_recognition - The world's simplest facial recognition api.
• capsule-networks - A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
• Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow.
• tensornets - High level network definitions with pre-trained weights in TensorFlow.
• tensorflow/models - Models and examples built with TensorFlow.
• lightnet - Bringing pjreddie's DarkNet out of the shadows.
• chess-alpha-zero - Chess reinforcement learning by AlphaGo Zero methods.
• TernausNetV2 - Fully Convolutional Network for Instance Segmentation.
• pytorch-openai-transformer-lm - OpenAI's finetuned transformer language model with a script to import the weights pre-trained by OpenAI.
• DensePose - A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body.
• pytorch-yolo-v3 - PyTorch implementation of the YOLO v3 object detection algorithm.
• CoordConv-pytorch - Pytorch implementation of CoordConv.
• PyTorch-NEAT - NeuroEvolution of Augmenting Topologie.
• maskrcnn-benchmark - Fast, modular reference implementation of Semantic Segmentation and Object Detection algorithm in PyTorch.
• Global_Convolutional_Network - GCN architecture for sematic segmentation.
• LovaszSoftmax - Lovász-Softmax loss.
• ludwing - Ludwig is a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code.
• gen-efficientnet-pytorch - Pretrained EfficientNet, MixNet, MobileNetV3, MNASNet A1 and B1, FBNet, Single-Path NAS.

• matplotlib - 2D plotting.
• seaborn - Visualization library.
• bokeh - Interactive web plotting.
• plotly - Collaborative web plotting.
• dash - Interactive Web plotting.
• altair - Declarative statistical visualization.
• folium - Leaflet.js Maps.
• geoplot - High-level geospatial data visualization.
• datashader - Graphics pipeline system.
• mplleaftlet - Matplotlib plots from Python into interactive Leaflet web maps.
• matplotlib-venn - Area-weighted venn-diagrams.
• pyLDAvis - Interactive topic model visualization.
• cufflinks - Productivity Tools for Plotly + Pandas.
• scatterText - Visualizations of how language differs among document types.
• plotnine - ggplot for python.
• ggpy - ggplot for python.
• mizani - scales package.
• bqplot - Plotting library for IPython/Jupyter Notebooks.
• PtitPrince - Raindrop cloud.
• joypy - Ridgeline plots.
• dtreeviz - Decision tree visualization and model interpretation.
• ipyvolume - 3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL.

• Nevergrad - Gradient-free optimization.
• featuretools - Automated feature engineering.
• auto-sklearn - Automated machine learning.
• tpot - Automated machine learning.
• auto_ml - Automated machine learning.
• MLBox - Automated Machine Learning python library.
• devol - Automated deep neural network design via genetic programming.
• skll - SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.
• autokeras - Automated machine learning in Keras.
• SMAC3 - Sequential Model-based Algorithm Configuration.

• mlxtend - A library of extension and helper modules for Python's data analysis and machine learning libraries.
• yellowbrick - Visual analysis and diagnostic tools.
• pandas-profiling - Profiling reports for pandas DataFrame objects.
• Skater - Model Agnostic Interpretation.
• Dora - Exploratory data analysis.
• sklearn-evaluation - scikit-learn model evaluation.
• fitter - simple class to identify the distribution from which a data samples is generated from.
• missingno - Missing data visualization.
• hypertools - Gaining geometric insights into high-dimensional data.
• scikit-plot - Plotting functionality to scikit-learn objects.
• elih - Explain Machine Learning.
• kmeans_smote - Oversampling for imbalanced learning based on k-means and SMOTE.
• pyUpSet - UpSet suite of visualisation methods.
• lime - Explaining the predictions of any machine learning classifier.
• pandas-summary - An extension to pandas dataframes describe function.
• SauceCat/PDPbox - Partial dependence plot toolbox.
• shap - A unified approach to explain the output of any machine learning model.
• eli5 - Debug machine learning classifiers and explain their predictions.
• rfpimp - Permutation and drop-column importance for scikit-learn random forests.
• pypeln - Concurrent data pipelines made easy.
• pycm - Multi-class confusion matrix library in Python.
• great_expectations - Always know what to expect from your data.
• innvestigate - A toolbox to iNNvestigate neural networks' predictions.
• alibi - Algorithms for monitoring and explaining machine learning models.
• InterpretML - Fit interpretable models. Explain blackbox machine learning.
• cleanlab - Finding label errors in datasets and learning with noisy labels.
• dtale - Flask/React client for visualizing pandas data structures
• dabl - Data Analysis Baseline Library

• sklearn-pandas - Pandas integration with sklearn.
• pdpipe - Easy pipelines for pandas DataFrames.
• engarde - Defensive data analysis.
• datacleaner - Tool that automatically cleans data sets and readies them for analysis.
• categorical-encoding - sklearn compatible categorical variable encoders.
• fancyimpute - Multivariate imputation and matrix completion algorithms.
• raccoon - DataFrame with fast insert and appends.
• kmodes - k-modes and k-prototypes clustering algorithm.
• annoy - Approximate Nearest Neighbors.
• datacleaner - Automatically cleans data sets and readies them for analysis.
• scikit-feature - Filter methods for feature selection.
• mifs - Parallelized Mutual Information based Feature Selection module.
• skggm - Scikit-learn compatible estimation of general graphical models.
• dirty_cat - Encoding methods for dirty categorical variables.
• Impyute - Data imputations library to preprocess datasets with missing data.
• eif - Extended Isolation Forest for Anomaly Detection.
• featexp - Feature exploration for supervised learning.
• feature_engine - Feature engineering package with sklearn like functionality.
• stumpy - STUMPY is a powerful and scalable Python library that can be used for a variety of time series data mining tasks.
• n2 - Lightweight approximate Nearest Neighbor library which runs faster even with large datasets.

• Causality - Causal analysis.
• traces - Unevenly-spaced time series analysis.
• PyFlux - Time series library for Python.
• prophet - Tool for producing high quality forecasts.
• tsfresh - Automatic extraction of relevant features from time series.
• tslearn - Machine learning toolkit dedicated to time-series data.
• pyts - A Python package for time series transformation and classification.
• sktime - A scikit-learn compatible Python toolbox for learning with time series data.

• python_speech_features - Speech features.
• speechpy - A Library for Speech Processing and Recognition.
• magenta - Music and Art Generation with Machine Intelligence.
• librosa - Audio and music analysis.
• pydub - Manipulate audio with a simple and easy high level interface.
• pytorch/audio - simple audio I/O for pytorch.

• pillow - PIL fork.
• scikit-image - Image processing.
• hmap - Image histogram remapping.
• pyocr - A wrapper for Tesseract and Cuneiform (Optical Character Recognition).
• scikit-video - Video processing.
• moviepy - Video editing.
• OpenCV - Open Source Computer Vision Library.
• SimpleCV - Wrapper around OpenCV.
• label-maker - Data Preparation for Satellite Machine Learning.
• face_recognition - Facial recognition.
• imgaug - Image augmentation.
• pyvips - Fast image processing.
• aeneas - Set of tools to automagically synchronize audio and text.
• ImageHash - Image hashing.
• Augmentor - Image augmentation library.
• PyAV - Bindings for FFmpeg.
• imutils - Convenience functions to make basic image processing operations.
• albumentations - fast image augmentation library.

• geojson - Python bindings for GeoJSON.
• geopy - Python Geocoding Toolbox.
• OSMnx - Street networks.
• reverse-geocoder - A fast, offline reverse geocoder.
• pysal - Spatial Analysis Library.
• geopandas - Tools for geographic data.

• sum - Automatic summarization of text documents and HTML.
• textract - Extract text from any document.
• newspaper - News extraction, article extraction and content curation.

• BlingFire - A lightning fast Finite State machine and REgular expression manipulation library.
• BERT-pytorch - Google AI 2018 BERT pytorch implementation.
• pytorch-pretrained-BERT - PyTorch version of Google AI's BERT model with script to load Google's pre-trained models.
• gensim - Topic Modeling.
• pattern - Web ining module.
• probablepeople - Parsing unstructured western names into name components.
• Expynent - Regular expression patterns.
• mimesis - Generate synthetic data.
• pyenchant - Spell checking.
• parserator - Domain-specific probabilistic parsers.
• scrubadub - Clean personally identifiable information from dirty dirty text.
• usaddress - Parsing unstructured address strings into address components.
• python-phonenumbers - Python port of Google's libphonenumber.
• jellyfish - Approximate and phonetic matching of strings.
• preprocessing - Simple interface for the CMU Pronouncing Dictionary.
• langid - Stand-alone language identification system.
• fuzzywuzzy - Fuzzy String Matching.
• Fuzzy - Soundex, NYSIIS, Double Metaphone.
• snowball - Snowball compiler and stemming algorithms.
• leven - Levenshtein edit distance.
• flashtext - Extract Keywords from sentence or Replace keywords in sentences.
• polyglot - Multilingual text NLP processing toolkit.
• sentencepiece - Unsupervised text tokenizer for Neural Network-based text generation.
• pyfasttext - Binding for fastText.
• python-wordsegment - English word segmentation.
• pyahocorasick - Exact or approximate multi-pattern string search.
• Wordbatch - Parallel text feature extraction for machine learning.
• langdetect - Port of Google's language-detection library.
• translation - Uses web services for text translation.
• nltk - Natural Language Toolkit.
• unidecode - ASCII transliterations of Unicode text.
• pytorch/text - Data loaders and abstractions for text and NLP.
• textdistance - Compute distance between sequences.
• sent2vec - General purpose unsupervised sentence representations.
• pyhunspell - Python bindings for the Hunspell spellchecker engine.
• facebook/fastText - Library for fast text representation and classification.
• textblob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
• facebook/InferSent - Sentence embeddings (InferSent) and training code for NLI.
• nmslib - Non-Metric Space Library.
• google/sentencepiece - Unsupervised text tokenizer for Neural Network-based text generation.
• ftfy - Fixes mojibake and other glitches in Unicode text, after the fact.
• fletcher - Pandas ExtensionDType/Array backed by Apache Arrow.
• textacy - NLP, before and after spaCy.
• hmtl - Hierarchical Multi-Task Learning - A State-of-the-Art neural network model for several NLP tasks based on PyTorch and AllenNLP.
• pytext - A natural language modeling framework based on PyTorch.
• flair - A very simple framework for state-of-the-art Natural Language Processing.
• LASER - Language-Agnostic SEntence Representations.
• transformer-xl - Attentive Language Models Beyond a Fixed-Length Context.
• textstat - Calculate readability statistics of a text object - paragraphs, sentences, articles.

• louvain - Louvain Community Detection.

• delorean - Time Travel Made Easy.

• Surprise - Analyzing recommender systems.
• trueskill - TrueSkill rating system.
• LightFM - Hybrid recommendation algorithm.
• implicit - Collaborative Filtering for Implicit Datasets.

• Clairvoyant - Identify and monitor social/historical cues.
• zipline - Algorithmic Trading Library.
• qstrader - Advanced Trading Infrastructure.

• sklearn-porter - Transpile trained scikit-learn estimators.
• sklearn-compiledtrees - Compiled Decision Trees for scikit-learn.
• Metrics - Machine learning evaluation metrics.
• bonobo - Extract Transform Load.
• pyemd - Earth Mover's Distance metric.
• fastai - The fast.ai deep learning library, lessons, and tutorials.
• mmh3 - MurmurHash3, a set of fast and robust hash functions.
• fbpca - Fast Randomized PCA/SVD.
• annoy - Approximate Nearest Neighbors.
• mlcrate - Handy tools and functions.
• pipeline - Standard Runtime For Every Real-Time Machine Learning.
• tabulate - Pretty-print tabular data in Python, a library and a command-line utility.
• crayon - A language-agnostic interface to TensorBoard.
• faiss - A library for efficient similarity search and clustering of dense vectors.
• neurtu - A Python package for parametric benchmarks.
• py-spy - Sampling profiler for Python programs.

• palladium - Framework for setting up predictive analytics services.
• lore - Lore makes machine learning approachable for Software Engineers and maintainable for Machine Learning Researchers.
• kubeflow - Machine Learning Toolkit for Kubernetes.
• great_expectations - F framework that helps teams save time and promote analytic integrity with a new twist on automated testing: pipeline tests.
• mara/data-integration - A lightweight opinionated ETL framework, halfway between plain scripts and Apache Airflow.
• airflow - ETL.
• mlflow - Open source platform for the complete machine learning lifecycle.

• pip-tools - Keeps dependencies up to date.
• devpi - PyPI server and packaging/testing/release tool.
• Jupyter Notebook - Notebooks are awseome.
• click - CLI package.
• sacredboard - Dashboard for sacred.
• sacred - Reproduce computational experiments.
• python-flamegraph - Statistical profiler which outputs in format suitable for FlameGraph.
• magic-wormhole - get things from one computer to another, safely.
• memory_profiler - monitoring memory usage of a python program.
• line_profiler - Line-by-line profiling.
• parse - Parse strings using a specification based on the Python format() syntax.
• CleverCSV - CleverCSV is a Python package for handling messy CSV files

• gain - Web crawling framework based on asyncio.
• MechanicalSoup - A Python library for automating interaction with websites.
• camelot - Camelot: PDF Table Extraction for Humans.