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Data Miner VS Matplotlib

Compare Data Miner VS Matplotlib and see what are their differences

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

Data Miner logo Data Miner

Data Miner is a Google Chrome extension that helps you scrape data from web pages and into a CSV file or Excel spreadsheet.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Data Miner Landing page
    Landing page //
    2021-10-14
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Data Miner features and specs

  • User-Friendly Interface
    Data Miner offers a clean and intuitive user interface that allows users to easily navigate and set up web scraping tasks without requiring extensive technical knowledge.
  • Browser Extension
    Being available as a browser extension for both Chrome and Edge makes it easy to install and use directly within the browser, without needing separate software installations.
  • Pre-built Recipes
    Data Miner provides a library of pre-built recipes for common web scraping tasks, enabling users to quickly deploy scrapers without starting from scratch.
  • Custom Recipes
    Users have the option to create custom recipes, offering flexibility and the ability to tailor scraping tasks to specific needs.
  • Cloud Storage
    Offers cloud storage options that allow users to save and manage their scraped data directly on the platform for easy access and organization.
  • Export Options
    Supports multiple export formats like CSV, XLS, and Google Sheets, making it easy for users to integrate scraped data with other tools and workflows.
  • Scheduling
    Allows users to schedule scraping tasks, automating the data collection process at specified intervals.

Possible disadvantages of Data Miner

  • Limited Free Tier
    The free version of Data Miner is limited in terms of the number of rows and pages that can be scraped, which may not be sufficient for more extensive data collection needs.
  • Learning Curve
    While the interface is user-friendly, there can still be a learning curve for users unfamiliar with web scraping concepts and the tool itself.
  • Browser Dependence
    As Data Miner is a browser extension, its functionality is limited to the browser environment, which might not be ideal for more complex or large-scale web scraping tasks.
  • Potential Website Restrictions
    Some websites actively prevent scraping activities, which could limit the effectiveness of Data Miner on certain web pages.
  • Subscription Cost
    Advanced features and higher usage requirements necessitate a subscription plan, which may be costly for individual users or small businesses.
  • Reliance on Internet Stability
    As an online tool, its performance can be hindered by poor internet connectivity, potentially disrupting the scraping process.

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 Data Miner

Overall verdict

  • Data Miner is generally considered a good tool for individuals and businesses that need to quickly and easily extract large amounts of data from websites without the need for advanced technical skills. It is appreciated for its ease of use and effectiveness in various scenarios.

Why this product is good

  • Data Miner (dataminer.io) is a web scraping tool that allows users to extract data from websites into various formats such as CSV or Excel. It is known for its user-friendly interface and does not require any programming skills, making it accessible to many users. Additionally, it offers a number of ready-made scraping recipes and the ability to create custom ones, adding flexibility to its use.

Recommended for

  • Researchers
  • Marketers
  • Data Analysts
  • Business Professionals
  • Anyone needing to automate data extraction from websites

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.

Data Miner videos

+ Add

Data Miner 4.0

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Data Miner and Matplotlib)

Data Miner

Matplotlib

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

Data Miner Reviews

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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.
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

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than Data Miner. While we know about 114 links to Matplotlib, we've tracked only 7 mentions of Data Miner. 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.

Data Miner mentions (7)

  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Data Miner - A browser extension (Google Chrome, MS Edge) for data extraction from web pages CSV or Excel. The free plan gives you 500 pages/month. - Source: dev.to / over 2 years ago
  • What's something you'd like to see implemented on AO3?
    The web app at https://dataminer.io/. If you open it on your Saved for Later page, it should show you a public "recipe" that I made to scrape the data. Possibly others as well. Source: over 3 years ago
  • free-for.dev
    Data Miner - A browser extension (Google Chrome, MS Edge) for data extraction from web pages CSV or Excel. The free plan gives you 500 pages/month. - Source: dev.to / over 3 years ago
  • Need help exporting references from CENTRAL
    Ungh, annoying. There are lots of free scraping tools you could play with like https://dataminer.io but I have no idea how practical that approach will be for you. Source: over 3 years ago
  • Are cover letters super important in getting internships and jobs?
    Go on your states licensure website, look up the directory of licensed professionals and use a data mining tool (https://dataminer.io/) to scrape the website of all the emails or everyone who's licensed. Source: about 4 years ago
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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 Data Miner and Matplotlib, you can also consider the following products

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

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

import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.

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

Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.

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

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