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17hats VS Matplotlib

Compare 17hats 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

17hats logo 17hats

The all-in-one business system for entrepreneurs.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • 17hats Landing page
    Landing page //
    2023-06-25
  • Matplotlib Landing page
    Landing page //
    2023-06-14

17hats features and specs

  • All-in-One Solution
    17hats combines invoicing, CRM, project management, and scheduling, reducing the need for multiple tools and making it easier to manage business operations in one place.
  • Automation
    The platform offers automation features for workflows, emails, and tasks, saving time and increasing efficiency for small business owners.
  • User-Friendly Interface
    17hats has a user-friendly interface that is easy to navigate, making it accessible for users who may not be technically savvy.
  • Client Portal
    Clients have access to a portal where they can view invoices, sign contracts, and manage appointments, enhancing the professional communication between businesses and their clients.
  • Mobile App
    17hats offers a mobile app, enabling business owners to manage their operations on the go, ensuring flexibility and increased productivity.
  • Customization
    The platform allows for a high level of customization for templates, contracts, and workflows, enabling businesses to tailor the system to better fit their specific needs.

Possible disadvantages of 17hats

  • Learning Curve
    Despite its user-friendly interface, there is still a learning curve due to the wide range of features available, which can be overwhelming for new users.
  • Cost
    17hats can be relatively expensive, especially for very small businesses or startups with limited budgets. The cost might deter some users from fully adopting the platform.
  • Limited Integrations
    While it covers many internal features, 17hats has limited integrations with other popular business tools, which may be a drawback for those who prefer a more interconnected ecosystem.
  • Customer Support
    Some users report that customer support responses can be slow or not as helpful as expected, which can be frustrating when encountering issues that need quick resolution.
  • Template Constraints
    Users have noted that while 17hats offers customization, there are some constraints in the templates provided, which might not cater to all unique business needs.
  • Reporting
    The reporting features in 17hats are not as robust as some other platforms, which can be a limitation for businesses that require detailed analytics and reports.

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 17hats

Overall verdict

  • Overall, 17hats is considered good for entrepreneurs who need an integrated solution for managing their business workflows. It simplifies various aspects of business management and is well-suited for those who wear multiple hats in their business activities.

Why this product is good

  • 17hats is popular because it offers an all-in-one business management platform for freelancers and small business owners. It combines features like project management, billing, client CRM, and scheduling in a single platform, making it convenient for users to handle business operations without needing multiple tools.

Recommended for

    17hats is recommended for freelancers, small business owners, and solo entrepreneurs who are looking for a comprehensive tool to manage projects, clients, finances, and schedules efficiently within a single interface.

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.

17hats videos

+ Add

Reasons to love 17hats

More videos:

  • Review - 17Hats Easy CRM for Creatives
  • Review - HoneyBook Vs Dubsado Vs 17Hats Review

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to 17hats and Matplotlib)

17hats

Matplotlib

CRM
100 100%
CRM
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Sales
100 100%
Sales
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 17hats and Matplotlib

17hats 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 more popular. It has been mentiond 114 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.

17hats mentions (0)

We have not tracked any mentions of 17hats yet. Tracking of 17hats recommendations started around Mar 2021.

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
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What are some alternatives?

When comparing 17hats and Matplotlib, you can also consider the following products

Post Affiliate Pro - Post Affiliate Pro powers 27,000+ businesses. Get advanced tracking, automation, and seamless integrations. Start your 30-day free trial todayโ€”no credit card needed!

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

Contact Apps - With the right app, you can spend less time looking for your contacts and more time actually connecting with them. Here are our top picks.

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

LinkPoint Connect - LinkPoint Connect: Desktop Edition for Salesforce links the work you do in your email to the records you need to update in the CRM.

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

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