Software Alternatives, Accelerators & Startups

Splid VS Matplotlib

Compare Splid VS Matplotlib and see what are their differences

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.

Splid logo Splid

Splid helps friends manage their money.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Splid Landing page
    Landing page //
    2018-09-30
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Splid features and specs

  • User-Friendly Interface
    Splid offers an intuitive and easy-to-use interface that makes it simple for users to split expenses without any confusion.
  • Offline Functionality
    Users can log expenses and use the app even without an internet connection, which is useful in remote areas.
  • Multiple Currency Support
    Splid allows users to add expenses in different currencies, making it convenient for international travel and expenses.
  • No Sign-Up Required
    The app does not require users to create an account, simplifying access and reducing privacy concerns.
  • Easy Sharing
    Users can easily share expense reports with group members via a link, simplifying communication and transparency.

Possible disadvantages of Splid

  • Limited Integration
    Splid lacks integration with other financial apps or services, which can limit its functionality for some users.
  • Manual Expense Entry
    All expenses must be entered manually, which can be time-consuming compared to apps that offer receipt scanning.
  • No Real-Time Sync
    Changes are not updated in real-time across devices, potentially leading to discrepancies if multiple users are managing a list.
  • Basic Features Free
    While the basic app is free, advanced features require a paid upgrade, which might not be ideal for all users.
  • Limited to Group Expense
    Splid is focused on group expense sharing, lacking features for individual finance management or budgeting.

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.

Splid videos

"Splid" by Kvelertak (ALBUM OF THE YEAR CONTENDER?) | ALBUM REVIEW

More videos:

  • Review - Album Review/Reaction: Kvelertak - Splid
  • Review - Kvelertak: Splid -- ๐Ÿ’ฟ album review ๐Ÿ’ฟ

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Splid and Matplotlib)
Personal Finance
100 100%
0% 0
Data Science And Machine Learning
Bill-Splitting Apps
100 100%
0% 0
Technical Computing
0 0%
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 Splid and Matplotlib

Splid Reviews

  1. dee parkes
    ยท retired at retired ยท
    great! easy to use, versatile, flexible. Recommended.

    I prefer this app to similar ones I've tried. It seems clearer, more straightforward and simpler to use for normal holidays etc. But if you need more complex arrangements it's versatile too: in that you can have multiple currencies; and groups containing different people.


12 Best Bill Splitting Apps in 2023
Splid is an excellent app for those who want to take their bill splitting to the next level. It is among the popular bill splitting apps that supports advanced features like location-based payment suggestions, detailed accounts of shared expenses, and a user-friendly interface, Splid app makes splitting bills easier than ever before.
Best Bill-Splitting Apps
Splitting up the cost of group trips can be tough. Splid allows you to add in all the expenses of a trip and then split it up among each person on the trip. The app is useful for splitting up non-trip expenses as well. Multiple payees can be added to each expense, for example, if two people covered the cost of groceries upfront, but five people need to chip in on the bill....

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.
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.
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.
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...

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than Splid. While we know about 114 links to Matplotlib, we've tracked only 2 mentions of Splid. 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.

Splid mentions (2)

  • Running an Open Source App: Usage, Costs and Community Donations
    Would be interesting to see how this compares to https://splid.app/. - Source: Hacker News / almost 2 years ago
  • Show HN: An alternative to Splitwise, more minimalist, no ads, no account
    Https://splid.app/ is a great no-account alternative. - Source: Hacker News / about 4 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
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What are some alternatives?

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

Splitwise - Splitwise is a free tool for friends and roommates to track bills and other shared expenses, so that everyone gets paid back. On the web, iPhone, and Android!

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

Tricount - Manage and share expenses with friends

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

Settle Up - SETTLE UP is an indispensable app for friends and flatmates who need to keep track of shared bills...

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