NumPy Alternatives & Competitors
The best NumPy alternatives based on verified products, community votes, reviews and other factors.
Some of the top features or benefits of NumPy are: Performance, Versatility, Ease of Use, Community Support, and Integrations. You can visit the info page to learn more.
We have listed more than 10 alternatives to NumPy. You can find them below. The top competitors are: Pandas, Scikit-learn, and OpenCV. Apart from the top ones, people also compare NumPy with htm.java, Banana.dev, and Dlib. The latest product that identified NumPy as a competitor is Equana.dev. "25 Python Frameworks to Master" is the last article that we know that reviews or compares NumPy to other products.
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/pandas-alternatives
Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Key Pandas features:
Data Wrangling Flexible Data Structures Integration with Other Libraries Performance with Data Size
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/scikit-learn-alternatives
scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Key Scikit-learn features:
Ease of Use Extensive Documentation and Community Support Integration with Other Libraries Variety of Algorithms
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Visit website
Calculate in a notebook and share — from everyday math to engineering.
Key Calcumber features:
🌿 Naturally type expressions 🔗 Copy and share 🧩 Variables and constants 🧪 Scientific functions
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/opencv-alternatives
OpenCV is the world's biggest computer vision library.
Key OpenCV features:
Comprehensive Library Cross-Platform Compatibility Open Source Large Community Support
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/dataiku-alternatives
Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.
Key Dataiku features:
User-Friendly Interface Collaborative Environment End-to-End Workflow Integrations and Extensibility
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/exploratory-alternatives
Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.
Key Exploratory features:
User-friendly Interface Integration with R Rich Visualization Options Collaborative Features
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/htm-java-alternatives
htm.java is a Hierarchical Temporal Memory implementation in Java, it provide a Java version of NuPIC that has a 1-to-1 correspondence to all systems, functionality and tests provided by Numenta's open source implementation.
Key htm.java features:
Biologically Inspired Algorithms Time Series Prediction Open Source Java Ecosystem Integration
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/figure-eight-alternatives
Figure Eight is the essential Human-in-the-Loop Machine Learning platform.
Key Figure Eight features:
Scalability Diverse Workforce Workflow Customization Integration Capabilities
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/weka-alternatives
WEKA is a set of powerful data mining tools that run on Java.
Key WEKA features:
User-Friendly Interface Wide Range of Algorithms Open Source Extensive Documentation
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/turi-graphlab-create-alternatives
GraphLab Create is an extensible machine learning framework that enables developers and data scientists to easily build and deploy apps.
Key Turi GraphLab Create features:
Ease of Use Scalability Integrated Toolset Graph Processing Capabilities
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/dimml-alternatives
The DimML programming language enables users to run any data solution on any website with only a single line of code.
Key DimML features:
Ease of Use Scalability Integration Customization
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/logical-glue-alternatives
Logical Glue helps Lenders and Insurance organisations make better decisions with a highly intuitive and user-friendly Machine Learning Platform.
Key Logical Glue features:
Interpretability User-Friendly Interface Automated Machine Learning Regulatory Compliance
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/rapidminer-alternatives
RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.
Key RapidMiner features:
Ease of Use Integration Capabilities Comprehensive Feature Set Community and Support
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/oracle-data-science-platform-alternatives
DataScience combines human intellect with machine-powered analysis to create actionable insights from complex data.
Key Oracle Data Science Platform features:
Integrated Ecosystem Scalability Security Automated Machine Learning














Isn't it obvious?
The most useful number crunching library for Python.