Data analysis and visualization libraries
202 libraries, 95 updated this year
The tools around the model: loading and cleaning data, computing statistics and drawing charts. In Python that means NumPy, pandas and SciPy for computation, statsmodels for statistical models, and matplotlib, seaborn, plotly, bokeh and altair for plots. Streamlit, Gradio and Dash turn analysis scripts into small web apps, and Apache Superset builds dashboards on top of SQL databases.
202 libraries
Supersetapache/incubator-superset
A data exploration platform designed to be visual, intuitive, and interactive.
scikit-learnscikit-learn/scikit-learn
A Python module for machine learning built on top of SciPy.
Pandaspandas-dev/pandas
A library providing high-performance, easy-to-use data structures and data analysis tools.
Streamlitstreamlit/streamlit
Streamlit is an framework to create beautiful data apps in hours, not weeks.
Gradiogradio-app/gradio
A Python library for quickly creating and sharing demos of models. Debug models interactively in your browser, get feedback from collaborators, and generate public links without deploying anything.
Dashplotly/dash
A framework for creating analytical web applications built on top of Plotly.js, React, and Flask
SciPyscipy/scipy
A Python-based ecosystem of open-source software for mathematics, science, and engineering.
DLibdavisking/dlib
DLib has C++ and Python interfaces for face detection and training general object detectors.
PredictionIOapache/predictionio Archived
PredictionIO, a machine learning server for software developers and data engineers.
limemarcotcr/lime
Lime is about explaining what machine learning classifiers (or models) are doing. It is able to explain any black box classifier, with two or more classes.
Weights & Biaseswandb/wandb
Machine learning experiment tracking, dataset versioning, hyperparameter search, visualization, and collaboration
Numbanumba/numba
Python JIT (just in time) compiler to LLVM aimed at scientific Python by the developers of Cython and NumPy.
Patternclips/pattern
A web mining module for the Python programming language. It has tools for natural language processing, machine learning, among others.
Vaexvaexio/vaex
A high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular datasets. Documentation can be found here.
dc.jsdc-js/dc.js
Multi-Dimensional charting built to work natively with crossfilter rendered with d3.js
imbalanced-learnscikit-learn-contrib/imbalanced-learn
Python module to perform under sampling and oversampling with various techniques.
InterpretMLinterpretml/interpret
InterpretML implements the Explainable Boosting Machine (EBM), a modern, fully interpretable machine learning model based on Generalized Additive Models (GAMs). This open-source package also provides visualization tools for EBMs, other glass-box models, and black-box explanations.
Orangebiolab/orange3
Open source data visualization and data analysis for novices and experts.
shinyrstudio/shiny
Is the basis for truly interactive displays and dashboards in R. However, some measure of interactivity can be achieved with htmlwidgets bringing javascript libraries to R. These include, plotly, dygraphs, highcharter, and several others.
mlxtendrasbt/mlxtend
A library consisting of useful tools for data science and machine learning tasks.
dplyrtidyverse/dplyr
A data manipulation package that helps to solve the most common data manipulation problems.
PyQtGraphpyqtgraph/pyqtgraph
A pure-python graphics and GUI library built on PyQt4 / PySide and NumPy.
data.tableRdatatable/data.table
Data.table provides a high-performance version of base R’s data.frame with syntax and feature enhancements for ease of use, convenience and programming speed.