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Pandas VS Gitea

Compare Pandas VS Gitea and see what are their differences

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LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Pandas logo Pandas

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

Gitea logo Gitea

A painless self-hosted Git service
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Gitea Landing page
    Landing page //
    2023-07-20

Pandas features and specs

  • Data Wrangling
    Pandas offers robust tools for manipulating, cleaning, and transforming data, making it easier to prepare data for analysis.
  • Flexible Data Structures
    Pandas provides two primary data structures: Series and DataFrame, which are flexible and offer powerful capabilities for handling various types of datasets.
  • Integration with Other Libraries
    Pandas integrates seamlessly with other Python libraries such as NumPy, Matplotlib, and SciPy, facilitating comprehensive data analysis workflows.
  • Performance with Data Size
    For data sizes that fit into memory, Pandas performs excellently with operations and computations being highly optimized.
  • Rich Feature Set
    Pandas provides a wide array of functionalities, including but not limited to group-by operations, merging and joining data sets, time-series functionality, and input/output tools.
  • Community and Documentation
    Pandas has a strong community and extensive documentation, offering a wealth of tutorials, examples, and support for new and experienced users alike.

Possible disadvantages of Pandas

  • Memory Consumption
    Pandas can become memory inefficient with very large datasets because it relies heavily on in-memory operations.
  • Single-threaded
    Many Pandas operations are single-threaded, which can lead to performance bottlenecks when handling very large datasets.
  • Steep Learning Curve
    For users who are new to data analysis or Pandas, there can be a steep learning curve due to its extensive capabilities and complex syntax at times.
  • Less Suitable for Real-time Analytics
    Pandas is not designed for real-time analytics and is better suited for batch processing due to its in-memory operations and single-threaded nature.
  • Error Handling
    Error messages in Pandas can sometimes be cryptic and hard to interpret, making debugging a challenge for users.

Gitea features and specs

  • Open Source
    Gitea is open source, allowing users to freely inspect, modify, and contribute to its codebase. This fosters transparency and community-driven development.
  • Lightweight
    Gitea is designed to be lightweight, making it easy to run even on resource-limited systems. This makes it ideal for self-hosted environments.
  • Easy Installation
    Gitea offers a straightforward installation process, making it simple for users to get up and running quickly without complex setup procedures.
  • Rich Feature Set
    Despite being lightweight, Gitea provides a robust feature set, including issue tracking, pull requests, and continuous integration support, which covers the majority of use cases.
  • Active Community
    Gitea has an active and growing community, which contributes to its development and provides support through forums, documentation, and tutorials.
  • Customizable
    Gitea allows for extensive customization through configuration options and extensions, enabling users to tailor the platform to their specific needs.
  • Self-Hosting
    Users have full control over their repositories and data when self-hosting Gitea, which enhances privacy and security compared to third-party hosting services.

Possible disadvantages of Gitea

  • Limited Enterprise Features
    Gitea may lack some advanced enterprise features found in other platforms like GitHub Enterprise or GitLab, such as advanced permissions management and extensive integrations.
  • Smaller Ecosystem
    Compared to larger platforms like GitHub, Gitea has a smaller ecosystem of plugins and integrations, which may limit certain functionalities.
  • Community Support
    While Gitea has an active community, it lacks the formal, professional support options available from larger commercial services, which might be a drawback for businesses seeking guaranteed support.
  • Learning Curve
    New users may experience a learning curve when transitioning to Gitea, especially if they are accustomed to other platforms with different workflows and interfaces.
  • Scalability Concerns
    For very large projects or organizations, Gitea may face scalability issues, as it is designed to be lightweight and may not handle extremely large loads as well as some competitors.
  • Update Management
    Users are responsible for managing Gitea updates and server maintenance when self-hosting, which requires additional administrative effort compared to cloud-hosted solutions.

Pandas videos

+ Add

Ozzy Man Reviews: Pandas

More videos:

  • Review - Ozzy Man Reviews: PANDAS Part 2
  • Review - Trash Pandas Review with Sam Healey

Gitea videos

+ Add

GITEA REVIEW ⭐ TUTORIAL 👨 RUN YOUR OWN GIT SERVER 💻 $50 FREEBIE 💰

More videos:

  • Review - Migrate to a Microsoft Github Alternative: Gitea
  • Review - Gitea - Git with a cup of tea - Installation and Configuration

Category Popularity

0-100% (relative to Pandas and Gitea)

Pandas

Gitea

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Code Collaboration
0 0%
Code Collaboration
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Git
0 0%
Git
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 Pandas and Gitea

Pandas Reviews

25 Python Frameworks to Master
Pandas is a powerful and flexible open-source library used to perform data analysis in Python. It provides high-performance data structures (i.e., the famous DataFrame) and data analysis tools that make it easy to work with structured data.
Source: kinsta.com
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When it comes to ETL, you can do almost anything with Pandas if you're willing to put in the time. Plus, pandas is extraordinarily easy to run. You can set up a simple script to load data from a Postgre table, transform and clean that data, and then write that data to another Postgre table.
Source: www.xplenty.com

Gitea Reviews

The Top 10 GitHub Alternatives
Gitea is a painless self-hosted all-in-one software development service that includes Git hosting, code review, team collaboration, package registry, and CI/CD. It is similar to GitHub, Bitbucket, and GitLab. Gitea was forked from Gogs originally and almost all the code has been changed.
Source: www.wearedevelopers.com
Top 7 GitHub Alternatives You Should Know (2024)
Gitea is a lightweight, fast, and reliable DevOps platform providing development teams with essential version control and collaboration features. k
Source: snappify.com
Let's Make Sure Github Doesn't Become the only Option
The Pull Request workflow is so dominant now that it’s considered the default path for code to permanently enter into a repository. You can see a similar features in GitHub’s smaller competition Codeberg, GitLab, BitBucket, and Gitea. These competitors don’t offer other, major code collaboration tools, and their Pull Request-like features aren’t just there to help users come...
Source: blog.edwardloveall.com
Gitea - Alternative to GitLab and GitHub
There are still plenty of things you might want centralized on a server somewhere, but it seems like a lot of the value add of GitHub, GitLab, and now Gitea is in making git repos easier to manage and interact with.
Source: news.ycombinator.com

Social recommendations and mentions

Based on our record, Pandas should be more popular than Gitea. It has been mentiond 219 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.

Pandas mentions (219)

  • Top Programming Languages for AI Development in 2025
    Libraries for data science and deep learning that are always changing. - Source: dev.to / 15 days ago
  • How to import sample data into a Python notebook on watsonx.ai and other questions…
    # Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / about 1 month ago
  • How I Hacked Uber’s Hidden API to Download 4379 Rides
    As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / about 1 month ago
  • Must-Know 2025 Developer’s Roadmap and Key Programming Trends
    Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
  • Sample Super Store Analysis Using Python & Pandas
    This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 9 months ago
View more

Gitea mentions (60)

  • Beware Offers of “Help” with Your Projects
    This reminds me of Gogs [0], where the original author refused a lot of good ideas and improvements, eventually leading to a fork [1] that's now a lot more popular and active than the original. [0] https://gogs.io/ [1] https://gitea.io/en-us/. - Source: Hacker News / almost 2 years ago
  • Incident with Issues and Pull Requests
    Yes, we do this using https://gitea.io/en-us/ on a private server. Firewall, backups and a replica running for most projects. Github is only used when it's required by a stakeholder. - Source: Hacker News / about 2 years ago
  • Let's Make Sure GitHub Doesn't Become the Only Option
    There's a number of places out there, some of which also support alternatives to Git itself. By no means a complete list and in no particular order: GitLab - https://about.gitlab.com/ Sourcehut - https://sourcehut.org/ Codeberg - https://codeberg.org/ Launchpad - https://launchpad.net/ Debian Salsa - https://salsa.debian.org/public Pagure - https://pagure.io/pagure For self hsoted options, there's these below... - Source: Hacker News / about 2 years ago
  • If you're on DSM 6 and still waiting for an update on the GitLab package, don't bother
    And if you need GitLab (for runner, etc...) then it's not too bad to run in Docker. But if anyone is looking for a somewhat simpler git solution, gitea is pretty great. Source: about 2 years ago
  • OpenBSD Upgrade 7.2 to 7.3
    Check: Configuration and syntax changes and Special packages. The latter includes changes on PostgreSQL, Python and Gitea. - Source: dev.to / about 2 years ago
View more

What are some alternatives?

When comparing Pandas and Gitea, you can also consider the following products

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

GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.

OpenCV - OpenCV is the world's biggest computer vision library

BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.

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