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NumPy VS Jet Admin

Compare NumPy VS Jet Admin and see what are their differences

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A simple way to keep all your data under control. Build your own business applications in just 4 minutes. featured
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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Jet Admin logo Jet Admin

Build business apps really fast
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Jet Admin Landing page
    Landing page //
    2023-05-10

Build custom business apps such as internal tools or client portals incredibly fast and without code. Use drag-and-drop UI components to assemble complex multi-page apps on top of any data source.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Jet Admin features and specs

  • Clean UI
    Can be used for building Customer-Facing Portals
  • Drag & Drop Interface
    Intuitive UI builder with 50+ UI pre-made components
  • Integrations
    30+ Native integrations: DBs, 3rd-party APIs, GraphQL, REST
  • CRUD
    Out-of-the-box for all the DBs, along with Filtering, Searching, Exporting, and Bulk actions

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Analysis of Jet Admin

Overall verdict

  • Jet Admin is generally considered a good choice for businesses looking to efficiently manage their data and operations through custom admin panels. Its ease of use and comprehensive features deliver significant flexibility and support automation, making it a valuable tool for many organizations.

Why this product is good

  • Jet Admin is praised for its ability to help users create powerful admin panels without any coding. It offers a wide range of integrations with popular services, a user-friendly interface, and extensive customization options which make it suitable for companies of different sizes. It also supports complex logic to handle various business workflows, which can streamline and automate many administrative tasks.

Recommended for

    Jet Admin is recommended for startups, SMEs, and large enterprises that need to build customized admin dashboards and internal tools quickly and without extensive coding knowledge. It is particularly beneficial for companies with diverse data sources and workflow automation needs.

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Jet Admin videos

+ Add

No-code Business App Builder

Category Popularity

0-100% (relative to NumPy and Jet Admin)

NumPy

Jet Admin

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
No Code
0 0%
No Code
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Developer Tools
0 0%
Developer Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare NumPy and Jet Admin

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Jet Admin Reviews

We have no reviews of Jet Admin yet.
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Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Jet Admin. While we know about 122 links to NumPy, we've tracked only 3 mentions of Jet Admin. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

NumPy mentions (122)

View more

Jet Admin mentions (3)

  • Internal Tools for Sqlite3
    I don't want to go the expense and setup of a managed database service. I like the concept of using sqlite3, litestream, and AWS S3 for an Internal App. I found an Internal Tools vendor Jetadmin (jetadmin.io) that lists Sqlite as a supported database. It may be that Sqlite is easily integrated with the other tools I looked at, but they don't state it. Source: almost 4 years ago
  • Firefoo - A new Firestore GUI client featuring table view, JS query shell & JSON exporting
    Jetadmin.io - Firestore integration is not working well. Source: about 5 years ago
  • Django admin looks dated and is not mobile friendly, any better options ?
    Had a look at the github and subsequently the demo, I end up at jetadmin.io which by the looks of it is an interesting low-code/no-code environment. However if you use django-jet doesn't that mean you need a jetadmin account? Source: over 5 years ago

What are some alternatives?

When comparing NumPy and Jet Admin, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Retool - Build custom internal tools in minutes.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Appsmith - Appsmith is an open source web framework for building internal tools, admin panels, dashboards, and workflows.

OpenCV - OpenCV is the world's biggest computer vision library

Forest Admin - Execute fast and at scale with no time wasted on internal tools developed in-house.

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