Software Alternatives, Accelerators & Startups
Register | Login

ShippingEasy VS Matplotlib

Compare ShippingEasy VS Matplotlib and see what are their differences

Agiliron
Omni-Channel SaaS Solution Suite for Retail, Wholesale & eCommerce businesses featured
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.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

ShippingEasy logo ShippingEasy

ShippingEasy is just that: Shipping made easy. Process orders, automate shipping, get discounted rates, and optimize your entire shipping process.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • ShippingEasy Landing page
    Landing page //
    2023-04-16

Simplify and speed up the amount of time it takes to ship out orders by:

โ‹…โ‹…Phone, email and chat support to help you 7am-7pm every business day โ‹…โ‹…Processing orders from Shopify, Amazon, Etsy, eBay, and many other selling channels all from the ShippingEasy app โ‹…โ‹…Eliminating the need for copy/paste of addresses and order information forever โ‹…โ‹…Automatically updating order status back to any of your other selling platforms โ‹…โ‹…Auto-populating customs forms and simplifying international shipments โ‹…โ‹…Printing labels in batches or 1 by 1 - we support your workflow

Manage orders and inventory with Inventory Management

โ‹…โ‹…Two-way syncing for inventory, including FBAโ€”update stock levels in your online store and anywhere else you sell online in real time โ‹…โ‹…Create, send, and update purchase ordersโ€”auto-populate purchase orders, track their status, and more

Robust shipping features give you more options for customers, including:

โ‹…โ‹…Automatically email your customers a tracking # in real time โ‹…โ‹…Automated Emails and pre-built email templates to earn reviews and repeat business โ‹…โ‹…*Beautiful customized packing slips, branded and in color, or print packing slips on 4"x6" shipping labels

  • Matplotlib Landing page
    Landing page //
    2023-06-14

ShippingEasy features and specs

  • User-Friendly Interface
    ShippingEasy is known for its intuitive and easy-to-navigate interface, making it accessible for users with various levels of technical expertise.
  • Integrations
    It offers seamless integrations with major eCommerce platforms such as Amazon, eBay, Shopify, and Magento, facilitating automated workflows.
  • Discounted Shipping Rates
    ShippingEasy provides access to discounted shipping rates from major carriers like USPS, FedEx, and UPS, which can save businesses money on shipping costs.
  • Automation Features
    The platform includes powerful automation tools for routine processes like order processing, batch shipping, and tracking, which help increase efficiency.
  • Customer Support
    ShippingEasy offers robust customer support, including live chat, email support, and extensive online resources like FAQs and tutorials.

Possible disadvantages of ShippingEasy

  • Cost
    While the platform offers a free trial, it can become expensive for small businesses, especially once they scale past the basic plan.
  • Learning Curve
    Despite its user-friendly interface, some users might find the initial setup and learning all the features to be somewhat overwhelming.
  • Limited International Shipping Options
    ShippingEasy has fewer options for international shipping compared to some of its competitors, which might not be ideal for businesses with a global customer base.
  • Occasional Bugs
    Some users report occasional bugs or glitches in the software, which can interrupt workflow and require time to resolve.
  • Update Frequency
    Some users have mentioned that the frequency of updates can be inconvenient, sometimes requiring reconfiguration of settings or processes.

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 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.

ShippingEasy videos

+ Add

ShippingEasy Reviews - Tutorial

More videos:

  • Tutorial - How to Ship Using ShippingEasy

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to ShippingEasy and Matplotlib)

ShippingEasy

Matplotlib

Shipping and Tracking
100 100%
Shipping and Tracking
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Shipping
100 100%
Shipping
0% 0
Technical Computing
0 0%
Technical Computing
100% 100

User comments

Share your experience with using ShippingEasy and Matplotlib. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

ShippingEasy Reviews

We have no reviews of ShippingEasy yet.
Be the first one to post

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 ShippingEasy. While we know about 114 links to Matplotlib, we've tracked only 3 mentions of ShippingEasy. 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.

ShippingEasy mentions (3)

  • Desktop Shipper or Stamps.com?
    However, it turns out that ShippingEasy.Com is actually owned by Stamps.Com. I really can't explain the difference. But in spite of the fact that they are owned by the same company, shippingeasy.com works, and stamp.com does not. Source: almost 5 years ago
  • Cannot purchase next day air label from UPS or FEDEX.COM
    Are both websites down? Is there a third party shipping service than will allow me to purchase next day air shipping label and pick up? I tried shippingeasy.com but it gives me errors when trying to create as UPS account. Source: about 5 years ago
  • Shipping recommendations
    You should look into shippingeasy.com, they were bought by stamps.com! Source: over 5 years ago

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 ShippingEasy and Matplotlib, you can also consider the following products

ShipStation - Seamless eCommerce shipping fulfillment software. Wherever you sell, however you ship, ShipStation can help. Auto order import, batch label print, & more!

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

Stamps.com - Stamps.

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

Shippo - Shipping, easy and affordable for everyone. A set of unified APIs and tools that instantly enables you to ship your goods internationally

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

Loading...