Software Alternatives, Accelerators & Startups

Parseur.com VS Matplotlib

Compare Parseur.com VS Matplotlib and see what are their differences

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Parseur.com logo Parseur.com

Automate text extraction from emails and PDFs by using our powerful email and document parser.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Parseur.com Landing page
    Landing page //
    2021-06-15

Parseur is a leading document processing software ranging from email parsing to PDF extraction. Use Parseur to automate text extraction from emails, PDFs, spreadsheets, attachments and documents and put your business on auto-pilot. Setup is easy as everything is point & click and intuitive. Send parsed data to thousands of applications in real time via our integrations with Google Sheets, Zapier, Microsoft Power Automate and Make or your custom application using webhooks.

Companies in finance, food delivery, real estate, e-commerce, marketing, logistics & delivery, travel, hospitality and more are saving thousands of work hours every month by automating their data entry process with Parseur.

  • Matplotlib Landing page
    Landing page //
    2023-06-14

Parseur.com

$ Details
freemium $39.0 / Monthly (100 pages per month)
Platforms
Browser Web Google Chrome Cross Platform Firefox Safari
Release Date
2016 December

Parseur.com features and specs

  • Ease of Use
    Parseur offers an intuitive drag-and-drop interface, making it easy for users of any technical skill level to set up and customize data extraction templates.
  • Automation Capabilities
    The platform automates the process of extracting data from emails, simplifying workflows and reducing manual effort.
  • Integration Options
    Parseur supports multiple integrations with popular third-party applications like Zapier, Google Sheets, and various CRM systems, enabling seamless data transfer.
  • Support for Multiple File Types
    Parseur can handle various document formats including PDFs, Excel files, and plain text, expanding its usability across different use cases.
  • Accurate Data Extraction
    The platform uses machine learning algorithms to improve the accuracy of data extraction over time, reducing errors and improving data quality.
  • Scalability
    Designed to handle large volumes of data, whether you're processing a dozen emails or thousands, Parseur scales according to your needs.

Possible disadvantages of Parseur.com

  • Pricing
    The service can be expensive for small businesses or startups with limited budgets, especially if higher volumes of emails need to be processed.
  • Learning Curve
    Although the interface is user-friendly, some users may require time to fully understand all features and get the most out of the platform.
  • Limited Offline Capabilities
    Parseur requires an internet connection for most operations, which can be a drawback for users needing offline capabilities.
  • Customer Support
    Some users have reported delays in customer support response times, which can be problematic if immediate help is needed.
  • Template Management
    Managing multiple templates can become cumbersome, especially for businesses with complex and varied data extraction needs.
  • Feature Overload
    For some users, the plethora of features can feel overwhelming, making it easy to overlook or under-utilize certain functionalities.

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 Parseur.com

Overall verdict

  • Parseur.com is generally well-regarded in the industry for its user-friendly approach and robust features, making it a worthwhile tool for businesses in need of parsing solutions.

Why this product is good

  • Parseur.com is considered a good option because it provides a reliable and efficient email parsing solution that automates data extraction from emails, PDFs, spreadsheets, and other documents. It offers an easy-to-use interface, powerful workflows, and integration capabilities with various applications, making it suitable for businesses looking to streamline data processing tasks.

Recommended for

  • Businesses needing to automate data extraction from documents
  • Companies looking to integrate data parsing with other applications
  • Users seeking a no-code or low-code data processing tool
  • Organizations wanting to improve efficiency in data handling and management

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.

Parseur.com videos

Meet Parseur, a powerful tool to extract text from emails and PDFs

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Parseur.com and Matplotlib)
Data Extraction
100 100%
0% 0
Data Science And Machine Learning
AI
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 Parseur.com and Matplotlib

Parseur.com Reviews

  1. Parsing PDF at ease

    When dealing with entities that send lots of data in an unstructured way because they think a PDF is the end of their digitalization process, Parseur is a great tool to automate reading this PDF and converting its data into structured json and then from their you can send it to your endpoint.

  2. Thomas Brunkard
    ยท Head of Marketing at Solution Centre ยท
    Powerful Solution with Excellent Support

    Email may probably never die but that doesn't mean that business processes should be slowed or halted. Parseur enables us to create a lot more efficiencies by handling email data as though it was keyed in by a customer agent.

    There are other services that do this but for the low cost and the ease of use, this service is the best.

    For those of us working in the European Union, Parseur was also easy to assess and approve for GDPR requirements.

    The support for post processing is very powerful and with a extensive export options, it is very easy to get data into the right funnel.

    ๐Ÿ Competitors: Mailparser, Parserr
    ๐Ÿ‘ Pros:    Quickly compliant with gdpr|Microsoft power automate ready|Its flexible and easy to use|Outstanding customer support

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 should be more popular than Parseur.com. It has been mentiond 114 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.

Parseur.com mentions (12)

  • Is it Possible to have info from text messages/emails auto added or removed from an Excel sheet as they come in?
    You can get an account with https://parseur.com/ and then a number with OpenPhone, and Zappier. Those 3 will let you do what you want (easily). Source: over 3 years ago
  • Building an email parser with ChatGPT-4 and Laravel
    Iโ€™m sure this is super cool, but have you considered https://parseur.com itโ€™s built for stuff like this. Source: over 3 years ago
  • Using Power Automate To Parse Email and Extract Information From The Body
    For more complex layouts, or if you have to deal with several layouts, it may be better to use third party document extraction tool that connects to like Parseur. Source: over 3 years ago
  • Email, PDF, to Sales order? Automate Sales Order Entry
    You could use a document parser tool, like Parseur to better automate the process. Source: almost 4 years ago
  • CEO looking for a solution
    And if you ever are in need of an intelligent document processing software, have a look at Parseur.com (of which I'm the co-founder, sorry for the shameless plug ;-)). Source: over 4 years ago
View more

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
View more

What are some alternatives?

When comparing Parseur.com 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

Parsio.io - No-code email & PDF parser

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