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PubMed.gov VS Matplotlib

Compare PubMed.gov 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

PubMed.gov logo PubMed.gov

PubMed comprises more than 29 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • PubMed.gov Landing page
    Landing page //
    2023-01-25
  • Matplotlib Landing page
    Landing page //
    2023-06-14

PubMed.gov features and specs

  • Comprehensive Database
    PubMed.gov offers access to a vast array of biomedical literature, including millions of citations and summaries from life sciences journals.
  • Free Access
    Users can freely access the database, which can save costs for researchers, students, and the general public.
  • Advanced Search Capabilities
    The platform provides advanced search tools, allowing for detailed queries and filtering options to pinpoint specific studies and articles.
  • Credible Source
    PubMed.gov is maintained by the National Center for Biotechnology Information (NCBI), ensuring that the information is reliable and up-to-date.
  • Linked to Full Texts
    Many citations in PubMed are linked to full-text articles available through journals' websites and other resources such as PubMed Central.

Possible disadvantages of PubMed.gov

  • Full Text Access
    Not all articles are freely available in full text, requiring subscriptions or one-time payments to obtain the complete document.
  • Complex Search Interface
    The advanced search tools can be complex for new users, requiring a learning curve to utilize effectively.
  • Database Overload
    The sheer volume of articles can be overwhelming, making it difficult to find specific information without using precise search terms.
  • Limited Scope of Coverage
    While extensive, PubMed primarily covers biomedical and life sciences literature, potentially excluding relevant information from other scientific disciplines.

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 PubMed.gov

Overall verdict

  • Yes, PubMed.gov is considered an excellent resource for accessing scientific and medical research literature. It is a trusted database widely used across the world by professionals in the medical and research fields.

Why this product is good

  • PubMed.gov, operated by the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine (NLM), is a highly regarded database for accessing a vast array of biomedical literature. It is trusted due to its comprehensive coverage, authoritative content, and peer-reviewed sources. Researchers, healthcare professionals, and students value PubMed for its reliability and the ability to find relevant, up-to-date biomedical information.

Recommended for

  • Healthcare professionals seeking evidence-based medical literature
  • Researchers needing access to scientific studies and articles
  • Students in the medical and biological sciences fields looking for reliable research sources
  • Educators requiring up-to-date references for teaching purposes
  • Policy makers needing scientific data to inform decision-making

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.

PubMed.gov videos

+ Add

PubMed.gov Protandim Peer-Reviewed Research

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to PubMed.gov and Matplotlib)

PubMed.gov

Matplotlib

Research Tools
100 100%
Research Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Mockups
100 100%
Mockups
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 PubMed.gov and Matplotlib

PubMed.gov 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, PubMed.gov should be more popular than Matplotlib. It has been mentiond 592 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.

PubMed.gov mentions (592)

  • UCLA discovers first stroke rehabilitation drug to repair brain damage
    I've read online that "Bacopa Monnieri" is a particularly strong and researched herbal supplement for cognitive maintenance, enhancement and neuroprotection, with the potential of supporting neurogenesis. I've not tried that stuff since money is hard to come by these days. There have been a few human studies. You can find more info here: https://pubmed.ncbi.nlm.nih.gov/?term=bacopa+monnieri+cognition and here:... - Source: Hacker News / 2 months ago
  • Attractive students no longer receive better results as classes moved online
    Https://pubmed.ncbi.nlm.nih.gov/?term=IQ Yes, crickets. - Source: Hacker News / 4 months ago
  • Biohack Your Health: Building a Science-Backed Supplement Advisor with Qdrant & PubMed ๐Ÿงช
    Import requests From bs4 import BeautifulSoup Def fetch_pubmed_abstracts(query, max_results=10): base_url = f"https://pubmed.ncbi.nlm.nih.gov/?term={query}" response = requests.get(base_url) soup = BeautifulSoup(response.text, 'html.parser') links = [f"https://pubmed.ncbi.nlm.nih.gov{a['href']}" for a in soup.select('.docsum-title', limit=max_results)] abstracts = [] for link in links: ... - Source: dev.to / 6 months ago
  • Seven Diabetes Patients Die Due to Undisclosed Bug in Abbott's Glucose Monitors
    I'll respond to the sibling poster with the same contentโ€”yes, DKA won't cause coma as quickly as insulin overdose but it can indeed come on acutely and it absolutely does kill people. I'm a bit frustrated by the number of people on this page who are saying that high BG readings aren't an emergency; the timeline to death isn't weeks or months or 'next time I get to urgent care' but instead 'later today' or 'early... - Source: Hacker News / 7 months ago
  • New gel restores dental enamel and could revolutionise tooth repair
    You could follow the NIH news feed that contains some of what gets funded but its actually quite difficult given the various institutions all over the world that all fund studies including charities and the universities themselves. On an individual topic with time you could learn who most of the major players are and follow their news but its unique to every topic. The potentially easier way at least to get a lay... - Source: Hacker News / 8 months 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 PubMed.gov and Matplotlib, you can also consider the following products

Google Scholar - Google Scholar is a freely accessible web search engine that indexes the full text of scholarly...

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

SCI-HUB - It provides mass and public access to tens of millions of research papers

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

arXiv - arXiv is a free distribution service and an open-access archive for scholarly articles.

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

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