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Matplotlib VS HasData

Compare Matplotlib VS HasData and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

HasData logo HasData

HasData is a top web scraping platform for developers and enterprises. It delivers structured, real-time data from the web using scalable APIs and no-code tools, removing the need to manage proxies, browsers, or anti-bot systems.
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  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • HasData Landing page
    Landing page //
    2025-10-09
  • HasData HasData API's Playground
    HasData API's Playground //
    2025-10-09
  • HasData HasData No-Code Scrapers
    HasData No-Code Scrapers //
    2025-10-09

HasData is one of the best web scraping API platforms built for performance, stability, and scale. It delivers enterprise-grade APIs built for speed, reliability, and accuracy. Businesses that depend on live search data, competitive intelligence, and public web data trust HasData for its consistent performance and transparent infrastructure.

The HasData SERP API is one of the fastest and most reliable on the market. It processes millions of requests per hour with a median latency around 1.75 seconds, providing clean and complete Google Search results without dealing with captchas, proxy management, or rotating browser setups. HasDataโ€™s infrastructure scales horizontally across self-managed Kubernetes clusters to ensure zero downtime during heavy traffic bursts or sustained data-collection workloads.

The HasData Web Scraping API goes beyond search. It provides a unified, resilient system that handles complex scraping tasks automatically โ€” covering dynamic pages, anti-bot protection, and JavaScript rendering. Developers get structured JSON results instantly, with no need to handle HTML parsing, headless browsers, or maintenance overhead.

HasData offers a broad range of specialized APIs, covering key platforms including Google Maps, Zillow, Amazon, Indeed, and many more. Each API is designed for production-level use cases where uptime, precision, and response speed matter more than anything else. Whether for SEO monitoring, price intelligence, lead generation, or market analytics, HasData removes the technical pain points so teams can focus on data, not scraping infrastructure.

For companies that require the best scraping performance without operational risk, HasData is a proven choice. It combines real-time data extraction power, consistent reliability, and developer-friendly APIs to support everything from startups to large enterprises running millions of daily requests.

Matplotlib

Website
matplotlib.org
Pricing URL
-
$ Details
Platforms
-
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HasData

Website
hasdata.com
Pricing URL
Official HasData Pricing
$ Details
Free Trial $49 / Monthly (Up to 200,000 Requests | 15 concurrent requests)
Platforms
Cloud Web Python Node JS PHP Go Zapier Browser
Startup details
Country
United States
State
TX
City
HOUSTON
Founder(s)
Roman Miliushkevich, Sergey Ermakovich
Employees
10 - 19
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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.

HasData features and specs

  • Sub-2s Median Latency
    Every API request completes in about 2.1 seconds on average, even under high load.
  • 99.9% uptime SLA
    Stay online with highly reliable servers, automated failover, and 24/7 infrastructure monitoring.
  • Up to 10M Requests/Hour
    Handle massive scraping operations with infrastructure built to support 10 million hourly API calls.
  • 100M+ Proxies
    Access hundreds of millions rotating IPs for global coverage and unblockable data collection.
  • JavaScript Rendering
    Extract content from dynamic, JavaScript-heavy websites without manual browser emulation.
  • Auto-Retry & Failover
    Built-in error handling and retries ensure high success rates even under volatile network conditions.
  • Clean Structured Output
    Deliver consistent, parsed JSON with metadata, images, text, listings, and links.
  • Full Anti-Bot Protection
    Bypasses Cloudflare, Datadome, and Akamai automatically โ€” no proxy rotation or browser setup required.
  • Easy Integration
    Connect in minutes using clear API documentation, SDKs, and straightforward REST architecture.

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.

Analysis of HasData

Overall verdict

  • HasData is a solid web scraping and data extraction platform that offers reliable APIs and tools for collecting structured data from websites, making it a good choice for businesses and developers needing scalable data solutions.

Why this product is good

  • Provides ready-to-use scraping APIs that handle proxies, CAPTCHAs, and JavaScript rendering automatically
  • Offers scalable infrastructure suitable for both small projects and large-scale data extraction needs
  • Supports structured data output formats like JSON and HTML for easy integration
  • Includes documentation and developer-friendly tools to speed up implementation
  • Handles anti-bot measures so users can focus on data rather than infrastructure

Recommended for

  • Developers building applications that require automated web data collection
  • Businesses conducting market research and competitor price monitoring
  • E-commerce companies tracking product data and reviews
  • Data analysts and researchers gathering large datasets from the web
  • SEO professionals monitoring search engine results and rankings

Matplotlib videos

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Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

HasData videos

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Category Popularity

0-100% (relative to Matplotlib and HasData)

Matplotlib

HasData

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Extraction
0 0%
Data Extraction
100% 100
Technical Computing
100 100%
Technical Computing
0% 0
Web Scraping
0 0%
Web Scraping
100% 100

Questions & Answers

As answered by people managing Matplotlib and HasData.

What makes your product unique?

HasData's answer:

HasData combines high-speed infrastructure with intelligent web data extraction. Its APIs handle JavaScript rendering, IP rotation, and anti-bot bypassing at scaleโ€”without requiring additional tooling. Developers can integrate once and retrieve clean, reliable data instantly.

Why should a person choose your product over its competitors?

HasData's answer:

Choose HasData for performance, reliability, and simplicity. Its APIs deliver fast response times, high accuracy, and zero hidden limits. The platform is built for real-world scrapingโ€”resilient under load, stable in production, and trusted by high-volume users.

How would you describe the primary audience of your product?

HasData's answer:

HasData serves developers, data engineers, and businesses that need scalable, automated access to public web data. These users build tools, analytics platforms, and competitive intelligence systems powered by structured, real-time information.

What's the story behind your product?

HasData's answer:

HasData was created to eliminate the complexity of large-scale web scraping. Frustrated by fragile scripts, unreliable proxies, and blocked requests, the founders built a unified platform that turns scraping into a dependable API service.

Which are the primary technologies used for building your product?

HasData's answer:

HasData runs on a distributed infrastructure using Golang, Python, and Node.js. It leverages headless Chromium for rendering, Kubernetes for scaling, and global IP rotation systems for reliable data extraction across regions.

Who are some of the biggest customers of your product?

HasData's answer:

HasData serves leading companies in SEO, digital marketing, cybersecurity, and content intelligence. These clients rely on HasData to power large-scale data collection, competitive analysis, plagiarism detection, and local search insightsโ€”handling millions of requests per day without service disruption.

User comments

Share your experience with using Matplotlib and HasData. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Matplotlib and HasData

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.
Source: www.technotification.com
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.
Source: searchbusinessanalytics.techtarget.com
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.
Source: www.analyticsvidhya.com
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...
Source: www.geeksforgeeks.org

HasData Reviews

We have no reviews of HasData yet.
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Social recommendations and mentions

Based on our record, Matplotlib seems to be more popular. 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.

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 / 5 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 / 8 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 / 9 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 / 10 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 / 11 months ago
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HasData mentions (0)

We have not tracked any mentions of HasData yet. Tracking of HasData recommendations started around Oct 2025.

What are some alternatives?

When comparing Matplotlib and HasData, 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.

Apify - Apify is a web scraping and automation platform that can turn any website into an API.

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

ScrapingBee - ScrapingBee is a Web Scraping API that handles proxies and Headless browser for you, so you can focus on extracting the data you want, and nothing else.

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

Zyte - We're Zyte (formerly Scrapinghub), the central point of entry for all your web data needs.

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