Software Alternatives, Accelerators & Startups
Register | Login

Adobe Acrobat DC VS NumPy

Compare Adobe Acrobat DC VS NumPy and see what are their differences

DocRaptor
As the only API powered by the Prince HTML-to-PDF engine, DocRaptor provides the best support for complex PDFs with powerful support for headers, page breaks, page numbers, flexbox, watermarks, accessible PDFs, and much more featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Adobe Acrobat DC logo Adobe Acrobat DC

Make your job easier with Adobe Acrobat DC, the trusted PDF creator. Use Acrobat to convert, edit and sign PDF files at your desk or on the go.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Adobe Acrobat DC Landing page
    Landing page //
    2022-01-18
  • NumPy Landing page
    Landing page //
    2023-05-13

Adobe Acrobat DC features and specs

  • Comprehensive Features
    Adobe Acrobat DC offers a wide range of features such as PDF editing, conversion, merging, digital signatures, and OCR (Optical Character Recognition). This makes it a highly versatile tool for working with PDF documents.
  • Cross-Platform Compatibility
    It is available on Windows, macOS, and mobile platforms, allowing users to work on their PDF documents across different devices.
  • Cloud Integration
    Adobe Acrobat DC integrates with Adobe Document Cloud, enabling users to access their documents from anywhere, share files, and collaborate with others in real-time.
  • Security Features
    The software offers robust security features, including password protection, encryption, and redaction, which help in protecting sensitive information.
  • User-Friendly Interface
    The program has an intuitive and user-friendly interface, making it relatively easy for both novice and advanced users to navigate and use its wide array of tools.

Possible disadvantages of Adobe Acrobat DC

  • Cost
    Adobe Acrobat DC is subscription-based and can be expensive compared to some other PDF solutions. The cost might be prohibitive for individual users or small businesses with a limited budget.
  • Resource-Intensive
    The software can be resource-intensive, requiring a significant amount of system memory and processing power, which may affect the performance of older computers.
  • Complexity
    Due to its extensive features, there can be a learning curve for new users to fully understand and utilize all available tools and functions.
  • Login Requirements
    Users are required to create and log in to an Adobe account to access all features, which can be an inconvenience for those preferring software that can be used offline without any account registration.
  • Frequent Updates
    While updates can bring new features and security patches, frequent updates can also be disruptive and may require restarting the application, which can be inconvenient during critical work.

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.

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.

Adobe Acrobat DC videos

+ Add

Adobe Acrobat DC Essentials: 01 - Introduction to Acrobat

More videos:

  • Review - Adobe Acrobat DC Send For Review feature overview

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

Category Popularity

0-100% (relative to Adobe Acrobat DC and NumPy)

Adobe Acrobat DC

NumPy

PDF Tools
100 100%
PDF Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
PDF Editor
100 100%
PDF Editor
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Adobe Acrobat DC and NumPy. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Adobe Acrobat DC Reviews

Systweak PDF Editor Review: Is It the Best Full-featured Alternative of Acrobat
Compared to PDF editors like PDF Element, Adobe Acrobat, and others, you need to pay less for Systweak PDF Editor. This means paying a decent amount of money. You can access a slew of features that allow modifying PDFs without any restrictions. Those who are looking for pocket-friendly PDF editing software should give Systweak PDF Editor a try. Since its release, the tool...
Source: www.systweak.com
The Most Recommended 9 Free PDF Readers in 2023
Repeated trial and comprehensive comparison can help you choose the most suitable PDF reader. If you are looking for the best PDF viewer on Windows 10, GeekerPDF is the perfect choice as it can help you read, create annotations, and edit PDFs on Windows. It supports all file formats, and PDF files are loaded, converted, and moved quickly, which can improve your work...
Source: www.geekersoft.com
3 Ways to compress PDF for free
Adobe Acrobat DC is Adobe's newest product. Adobe is a PDF format creator whose products have PDF compression capabilities. But the Adobe tools can be overwhelming because of the number of features.
Source: www.geekersoft.com
8 Best Adobe Acrobat Alternatives In 2022 [Updated List]
Pro Tip: When selecting the alternative for Adobe Acrobat, don’t just consider its cost, but also consider the features it offers. Invest in it only if it fulfills all that you need from a PDF editor. Why Look for Adobe Acrobat Alternatives
Source: www.softwaretestinghelp.com
10 Best PDF Expert Alternatives for Various Tasks in 2022
Adobe Acrobat DC comes with wide-ranged functions and is aimed at creating PDF documents by using editing, operative conditions for separate treating of text and images, signing, annotating docs, splitting & merging file pages, and more.
Source: fixthephoto.com

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

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 119 times since March 2021. 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.

Adobe Acrobat DC mentions (0)

We have not tracked any mentions of Adobe Acrobat DC yet. Tracking of Adobe Acrobat DC recommendations started around Mar 2021.

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 4 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

What are some alternatives?

When comparing Adobe Acrobat DC and NumPy, you can also consider the following products

Wondershare PDFelement - All-in-one PDF editor

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

Google Docs - Create a new document and edit with others at the same time -- from your computer, phone or tablet. Get stuff done with or without an internet connection. Use Docs to edit Word files. Free from Google.

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

Foxit PhantomPDF - Edit PDF files with our feature-rich PDF Editor. Download Foxit PDF Editor to convert, sign, scan / OCR & more. A speedy PDF Editor alternative to Adobe Acrobat.

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

Loading...