NumPy vs. pandas Comparison


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About Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.	About pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format. Intelligent data alignment and integrated handling of missing data: gain automatic label-based alignment in computations and easily manipulate messy data into an orderly form.Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets. Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. Even create domain-specific time offsets and join time series without losing data.
Platforms Supported Windows Supported Mac Supported Linux Supported Cloud Not Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported	Platforms Supported Windows Not Supported Mac Not Supported Linux Not Supported Cloud Supported On-Premises Not Supported iPhone Not Supported iPad Not Supported Android Not Supported Chromebook Not Supported
Audience Component Library solution for DevOps teams	Audience Individuals searching for a data analysis solution
Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported	Support Phone Support Not Supported 24/7 Live Support Not Supported Online Supported
API Offers API Supported	API Offers API Supported
Screenshots and Videos View more images or videos	Screenshots and Videos View more images or videos
Pricing Free Free Version Supported Free Trial Not Supported	Pricing No information available. Free Version Not Supported Free Trial Not Supported
Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software

Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported	Training Documentation Supported Webinars Not Supported Live Online Not Supported In Person Not Supported
Company Information NumPy numpy.org	Company Information pandas Founded: 2008 pandas.pydata.org
Alternatives Polars	Alternatives ML.NET Microsoft
h5py HDF5	OpenRefine
broot	Polars
PyQtGraph	Avanzai
Dask View All	NetworkX View All
Categories Component Libraries Supported	Categories Component Libraries Supported Data Analysis Supported

Integrations 3LC Supported Avanzai Supported Codédex Supported Coiled Supported Dash Supported Flower Supported Spyder Supported Train in Data Supported Yandex Data Proc Supported Cleanlab Not Supported DagsHub Not Supported Dagster Not Supported GLM-5.1 Not Supported GLM-5.2 Not Supported Giskard Not Supported LanceDB Not Supported Unify AI Supported Union Pandera Not Supported h5py Supported scikit-learn Supported Show More Integrations View All 22 Integrations	Integrations 3LC Supported Avanzai Supported Codédex Supported Coiled Supported Dash Supported Flower Supported Spyder Supported Train in Data Supported Yandex Data Proc Supported Cleanlab Supported DagsHub Supported Dagster Supported GLM-5.1 Supported GLM-5.2 Supported Giskard Supported LanceDB Supported Unify AI Not Supported Union Pandera Supported h5py Not Supported scikit-learn Not Supported Show More Integrations View All 33 Integrations
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