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Matplotlib VS Mailjoy

Compare Matplotlib VS Mailjoy 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?
Mailjoy

Delightfully easy direct mail marketing. A DIY direct mail tool created for marketing and growth teams. Design, mail & track personalized direct mail postcards and letters. Digital marketers use Mailjoy to send data-driven mail campaigns.

Rating
0 reviews
Pricing
Freemium
Alternatives Is it good?
Grapple
Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

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 130

Base details

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

Matplotlib
Mailjoy
Website matplotlib.org mailjoy.com
Pricing
Open source
Freemium Official pricing
Platforms —
Web REST API Zapier
Company — 2017
Listed in
Data Science And Machine Learning Development Data Visualization Javascript UI Libraries +1
Web To Print Direct Mail Postcards CMS Tech Direct Mail Marketing Marketing Platform Marketing Automation Direct Mail / Snail Mail Marketing +6

About Matplotlib and Mailjoy

In their own words, as submitted to SaaSHub.

Matplotlib
Mailjoy

No description of Matplotlib yet.

Why Mailjoy? Compared to digital channels, mail is an unsaturated channel that until recently has been generally inaccessible and lacked personalization. Mailjoy is the tool to reach customers or prospects with mail that's relevant and timely to them. Start by customizing any of our free postcard...

Read more about Mailjoy

Features and specs

What each product offers, as listed by its team.

Matplotlib 6 features
Mailjoy 12 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.
  • All in one pricing
    Our simple pricing is fully inclusive of printing, mailing & tracking.
  • Free design templates
    Many design templates, and you can customize any of them to make the design your own.
  • Powerful, easy to use designer
    No need to hire a designer or use expensive software.
  • Delivery tracking
    Mailjoy provides postcard-level delivery tracking. See when each individual mailer is delivered.
  • Personalization
    Incorporate any of your recipients' data to make each postcard unique.
  • Conversion tracking
    See exactly who converted in your campaigns. You can even get notified and automate a followup action when a conversion occurs with our Zapier integration.
  • Integrate with Zapier
    We connect to 5,000+ other apps through our integration with Zapier.
  • API
    We provide a RESTful API to let you integrate with your own workflows.
  • Enterprise pricing
    Ask us - support@mailjoy.com
  • Volume discounts
    Ask us - support@mailjoy.com
  • Agency discounts
    Ask us - support@mailjoy.com
  • Non-profit discounts
    Ask us - support@mailjoy.com

Analysis

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

Matplotlib
Mailjoy

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.

No analysis of Mailjoy yet.

Videos

Walkthroughs and reviews on video.

Matplotlib 1 video + Add
Mailjoy 1 video + Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Your customers' inbox is full. Try mail!

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
Mailjoy
100% 100%
Data Science And Machine Learning
0% 0%
0% 0%
Direct Mail
100% 100%
100% 100%
Technical Computing
0% 0%
0% 0%
Web To Print
100% 100%

Questions & Answers

As answered by people managing Matplotlib and Mailjoy.

What makes your product unique?

Mailjoy's answer:

Compared to digital channels, mail is an unsaturated channel that until recently has been generally inaccessible and lacked personalization. Mailjoy is the tool to reach customers or prospects with mail that’s relevant and timely to them. Start by customizing any of our free postcard and letter templates.

How would you describe the primary audience of your product?

Mailjoy's answer:

We value our small, scrappy customers just as highly as our larger clients, therefore we are on a mission to bring the best tools to the masses, streamlined in a way that allows anyone to dive in and get started in minutes.

What's the story behind your product?

Mailjoy's answer:

When we launched Mailjoy on Product Hunt we received over 700 upvotes and ended up #2 for the day. We were ecstatic, but the real story here is that we actually launched nearly a month earlier without the fanfare of a traditional tech launch.

We had quietly launched Mailjoy a month earlier to a portion of our network through email outreach, Facebook, and Twitter. We had two asks: One was to share with people who might be a good fit for this. The other was to share the website more broadly on social. We ended getting over a dozen shares across different channels which drove 100’s of visitors to the site.

Our first customer came from a share by a friend. By launching early, we found someone who cared enough to take a chance on us right away.

As much as we learned what converted visitors to become customers, we learned what was lacking and caused people not to convert. This helped us reprioritize our roadmap before the Product Hunt launch.

I like to consider a marketing site the showroom that entices people to take a test drive. If the showroom’s offering isn’t appealing, do people really want to go for a test drive? Probably not. We quickly learned what copy we were missing, as well as how potential customers viewed the product based on how we marketed it.

Our code wasn’t perfect and we had bugs. That’s OK. Visitors and users gladly pointed what wasn’t working. P.S — We quickly fixed things.

With a successful launch on Product Hunt behind us, we have more customers, received more feedback, and once again, are reprioritizing our short-term roadmap for things that drive the most growth and solve usability challenges. I fundamentally believe that shipping as soon as possible is the key to maximizing your learnings, and, ultimately, growing faster.

Remember, done is better than perfect.

Why should a person choose your product over its competitors?

Mailjoy's answer:

Mailjoy has a ton of features to help you create mailing lists from your contacts, design beautiful direct mail postcards and letter mailers, track the results, and integrate with other tools you already use. Sending a campaign takes only minutes. Use Mailjoy for a single campaign or make it a part of your marketing toolkit.

Additionally, Mailjoy provides recipient-level delivery tracking, conversion tracking, customer attribution, and the ability to get notified the moment a conversion happens - using unique per-mailer URLs and QR codes.

We've made sending direct mail as trackable and smart as email. Never send another direct mail campaign without the ability to track your return on investment again.

User comments

Share your experience with using Matplotlib and Mailjoy. 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
Mailjoy 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
Mailjoy 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

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Tracking Mailjoy since Mar 2021.

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