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Matplotlib VS Bar Graph Maker

Compare Matplotlib VS Bar Graph Maker and see what are their differences

Matplotlib

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

Rating
0 reviews
Pricing
Open source
Alternatives Is it good?
Bar Graph Maker

Create a Bar Graph for free with easy to use tools and download the Bar graph as jpg, png or svg file. Customize Bar Chart according to your choice.

Rating
0 reviews
Pricing
Free
Alternatives Is it good?
ScreenSnap Pro
Stop sharing plain, boring screenshots. Add stunning backgrounds, pro annotations, and instant cloud links — all in one click. Pay once, own it forever. sponsored

Which is more popular?

Based on our record, Matplotlib seems to be more popular. It has been mentioned 114 times since March 2021.

social mentions
114 vs 0
Data Science And Machine Learning popularity
100% vs 0%
alternatives listed
240+ vs 32

Base details

Website, pricing, platforms and company facts side by side.

Matplotlib
Bar Graph Maker
Website matplotlib.org bargraphmaker.net
Pricing
Open source
Free
Platforms —
Web Mobile
Listed in
Data Science And Machine Learning Development Data Visualization Javascript UI Libraries +1
Charts Charting Tools And Libraries Design Tools Data Visualization +1

About Matplotlib and Bar Graph Maker

In their own words, as submitted to SaaSHub.

Matplotlib
Bar Graph Maker

No description of Matplotlib yet.

With bar graph maker you can easily make bar charts online without need to install any software. All can be done online. There are various options to customize your bar chart according to your need. You can download the bar graph in various format such as jpg, png or svg format. There are various...

Read more about Bar Graph Maker

Features and specs

What each product offers, as listed by its team.

Matplotlib 6 features
Bar Graph Maker 4 features
  • 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

  • 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.
  • Change the background color
  • Change the position of Legend
  • Change the color of title and legend
  • Download Bar Graph as .jpg, .png or .svg.

Analysis

An editorial look at what each product does well and who it suits.

Matplotlib
Bar Graph Maker

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.

Overall verdict

  • Bar Graph Maker (bargraphmaker.net) is a solid, no-frills online tool for quickly creating simple bar charts without needing to install software or sign up for an account.

Why this product is good

  • Free and accessible directly from your web browser with no downloads or registration required
  • Simple, intuitive interface that lets you input data and generate charts in minutes
  • Offers customization options such as colors, labels, titles, and axis settings
  • Allows you to export or download the finished graph for use in reports, presentations, or documents
  • Lightweight and fast, making it ideal for one-off or quick chart creation tasks

Recommended for

  • Students working on school projects or assignments
  • Teachers preparing visual aids for lessons
  • Small business owners needing quick data visualizations
  • Professionals creating simple charts for presentations or reports
  • Anyone needing a fast, free bar chart without complex spreadsheet software

Videos

Walkthroughs and reviews on video.

Matplotlib 1 video + Add
Bar Graph Maker 0 videos + Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

No Bar Graph Maker videos yet. You could help us improve this page by suggesting one.

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Matplotlib
Bar Graph Maker
100% 100%
Data Science And Machine Learning
0% 0%
0% 0%
Design Tools
100% 100%
100% 100%
Technical Computing
0% 0%
0% 0%
Charts
100% 100%

Questions & Answers

As answered by people managing Matplotlib and Bar Graph Maker.

What makes your product unique?

Bar Graph Maker's answer:

Anyone can make bar graphs with just few clicks

User comments

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

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Matplotlib no reviews yet
Bar Graph Maker no reviews yet

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Matplotlib 114 mentions
Bar Graph Maker 0 mentions
  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib — the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review.... - Source: dev.to / 7 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes it’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... - Source: dev.to / 10 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 / 11 months ago

View more

Tracking Bar Graph Maker since Aug 2023.

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