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Rossum VS Matplotlib

Compare Rossum VS Matplotlib and see what are their differences

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Rossum logo Rossum

Rossum is AI-powered, cloud-based invoice data capture service that speeds up invoice processing 6x, with up to 98% accuracy. It can be easily customized, integrated and scaled according to your company needs.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Rossum Landing page
    Landing page //
    2023-08-24
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Rossum features and specs

  • High Accuracy
    Rossum's AI engine is known for its high accuracy in extracting data from various types of documents, reducing the need for manual corrections.
  • Scalability
    The platform is highly scalable, making it suitable for businesses of all sizes, from startups to large enterprises.
  • Integrations
    It offers seamless integration with popular ERP, CRM, and other business systems, facilitating smooth workflows.
  • Time Savings
    Automating data extraction processes saves significant time for employees, allowing them to focus on more value-added tasks.
  • User-Friendly Interface
    The platform has a user-friendly interface that makes it easy for employees to manage and validate data.
  • Multi-Language Support
    Rossum supports multiple languages, making it a versatile tool for international businesses.

Possible disadvantages of Rossum

  • Cost
    The pricing can be relatively high for small businesses or startups with limited budgets.
  • Initial Setup
    The initial setup and training period can be time-consuming, requiring significant effort to integrate the system fully.
  • Learning Curve
    Despite the user-friendly interface, there is still a learning curve associated with mastering all features and functionalities.
  • Dependency on Internet
    Being a cloud-based solution, a stable internet connection is essential for uninterrupted service, which could be a limitation in areas with poor connectivity.
  • Customization Limitations
    While it offers many features, there might be specific customization needs that are not easily met by the platform.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of Rossum

Overall verdict

  • Yes, Rossum is generally considered a good solution for businesses looking to streamline their document processing tasks. Its user-friendly interface and robust AI capabilities make it a popular choice among companies aiming to automate their data extraction processes.

Why this product is good

  • Rossum provides an AI-driven platform for automating document processing. It is well-regarded for its ability to efficiently extract information from various document types, reducing the need for manual data entry and improving productivity. The platform leverages machine learning and customizable workflows to adapt to the specific needs of different industries and document formats, enhancing accuracy and speed.

Recommended for

  • Businesses with high volumes of document processing needs
  • Companies seeking to automate their data extraction and reduce manual entry errors
  • Industries such as finance, logistics, healthcare, and insurance that deal with standardized documents
  • Organizations looking to implement AI-driven solutions to improve operational efficiency

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

Rossum videos

Intro & Overview w/ Rossum Electro-Music Assimil8or Eurorack Sampler Module

More videos:

  • Review - Rossum Evolution 1/4: Overview (LMS Eurorack Expansion Project)
  • Review - Rossum Electro-Music Trident // Triple VCO with UNIQUE Analog Tones & Modulation

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Rossum and Matplotlib)
Data Extraction
100 100%
0% 0
Data Science And Machine Learning
OCR
100 100%
0% 0
Technical Computing
0 0%
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 Rossum and Matplotlib

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Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than Rossum. While we know about 114 links to Matplotlib, we've tracked only 4 mentions of Rossum. 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.

Rossum mentions (4)

  • Data management program/software
    Embrace the AI bubble: https://rossum.ai/ (I'm not affiliated). Source: about 3 years ago
  • [HIRING] Python OCR help (freelance help)
    Now my main point (no, not IBM cloud services !) An other way is desktop tool/cloud tool that are OCR dedicated to "formatted documents" like ROSSUM or KLIPPA and... (https://rossum.ai/, https://www.klippa.com/en/ocr/identity-documents/driving-licenses). The idea, if I remember well the business model, is like a lot of small companies need all to make OCR on the same type of documents you can pre-learn an IA then... Source: almost 4 years ago
  • [D] OCR models for invoice reading
    You should check out https://rossum.ai/ I think their product fits your usecase. Source: almost 4 years ago
  • how to create universal regex which can extract lot of data from multiple invoices in python.
    I have seen some site like https://rossum.ai/ and while I think it is very difficult is there a way to improve it like them ? Source: almost 5 years ago

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
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What are some alternatives?

When comparing Rossum and Matplotlib, you can also consider the following products

DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.

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

Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNetsโ€™ platform makes it straightforward and fast to create highly accurate Deep Learning models.

NumPy - NumPy is the fundamental package for scientific computing with Python

Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.