Software Alternatives, Accelerators & Startups
Register | Login

Pandas VS Atlassian Design

Compare Pandas VS Atlassian Design and see what are their differences

Kimp
Kimp is an unlimited design company, specializing in graphic design (including print and digital designs, custom illustrations, landing page designs and email designs) and video design. 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. » 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.

Atlassian Design logo Atlassian Design

Design, develop, and deliver
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Atlassian Design Landing page
    Landing page //
    2023-06-22

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.

Atlassian Design features and specs

  • Comprehensive Design System
    Atlassian Design provides a complete and consistent design system for building applications, which helps ensure user interfaces are coherent and professional.
  • Access to Components
    It offers a wide range of pre-built UI components that can be easily integrated into projects, saving time in the development process.
  • Documentation
    Extensive and detailed documentation is available, which helps developers and designers understand how to use the system effectively.
  • Consistency
    Ensures that all components and patterns follow the same design principles, resulting in a more consistent user experience across different products.
  • Community Support
    Being a part of the broader Atlassian community means that there is a wealth of shared knowledge and resources available to help solve common problems.

Possible disadvantages of Atlassian Design

  • Learning Curve
    For new users, especially those not familiar with Atlassian products, the system can have a steep learning curve.
  • Customization Limitations
    While it provides many components, customization options might be limited for more unique or advanced use cases.
  • Dependency
    Relying heavily on Atlassian's design system means that changes or updates from Atlassian can impact your products, necessitating continuous adaptation.
  • Performance
    Using a large number of pre-built components might affect the performance of your application, especially if all components are not optimized for your specific use case.
  • Integration Complexity
    Integrating Atlassian Design with other systems or legacy codebases may require additional effort and potentially complex workarounds.

Analysis of Pandas

Overall verdict

  • Pandas is highly recommended for tasks involving data manipulation and analysis, especially for those working with tabular data. Its efficiency and ease of use make it a staple in the data science toolkit.

Why this product is good

  • Pandas is widely considered a good library for data manipulation and analysis due to its powerful data structures, like DataFrames and Series, which make it easy to work with structured data. It provides a wide array of functions for data cleaning, transformation, and aggregation, which are essential tasks in data analysis. Furthermore, Pandas seamlessly integrates with other libraries in the Python ecosystem, making it a versatile tool for data scientists and analysts. Its extensive documentation and strong community support also contribute to its reputation as a reliable tool for data analysis tasks.

Recommended for

    Pandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.

Analysis of Atlassian Design

Overall verdict

  • Yes, Atlassian Design is generally regarded as a good design system. Its emphasis on clarity, usability, and consistency makes it highly effective for teams looking to create seamless and user-friendly experiences.

Why this product is good

  • Atlassian Design is considered good because it provides a comprehensive and cohesive design system that ensures consistency across Atlassian's products. It is well-documented, user-focused, and continually updated to align with modern design trends and user needs. The platform offers a collection of guidelines, components, and patterns that facilitate the creation of intuitive and accessible user interfaces.

Recommended for

  • UI/UX Designers working on Atlassian products
  • Teams seeking guidance on design consistency
  • Product managers who prioritize a cohesive user experience
  • Developers implementing design systems
  • Design teams looking for a robust design framework

Pandas videos

+ Add

Ozzy Man Reviews: Pandas

More videos:

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

Atlassian Design videos

+ Add

5 things our users want from the Atlassian Design System

More videos:

  • Review - Atlassian Design Week 2017

Category Popularity

0-100% (relative to Pandas and Atlassian Design)

Pandas

Atlassian Design

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Design Tools
0 0%
Design Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Color Palette Generator
0 0%
Color Palette Generator
100% 100

User comments

Share your experience with using Pandas and Atlassian Design. 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 Pandas and Atlassian Design

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

Atlassian Design Reviews

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

Social recommendations and mentions

Based on our record, Pandas seems to be a lot more popular than Atlassian Design. While we know about 219 links to Pandas, we've tracked only 12 mentions of Atlassian Design. 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 / about 1 month 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 2 months 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 2 months 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 / 4 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

Atlassian Design mentions (12)

  • Top 5 Drag-and-Drop Libraries for React
    As the official evolution of react-beautiful-dnd, this library also comes with extensible accessibility features right out of the box. The default assistive controls are based on the Atlassian Design System, so if you’re already using that, integration will be seamless. But if you aren’t, you can easily replace those components with your own, or completely redefine how accessibility is provided and take a more... - Source: dev.to / 4 months ago
  • Getting Started with Color Module for Your Design System
    Atlassian Design System: Atlassian's Design System encompasses a color module encompassing primary, secondary, and functional colors, along with an extended palette for shades and tints. The system provides comprehensive guidelines for effective color usage and emphasizes accessibility. - Source: dev.to / over 1 year ago
  • Making a UI Kit. Is there a good checklist for Must Have elements?
    Atlassian design system: https://atlassian.design/. Source: about 2 years ago
  • What's the best way to encapsulate a feature to make it reusable?
    Regarding discoverability, you could build a directory with documentation. Similarly to how design systems are documented, e.g: https://atlassian.design/ But if you really want to share them you'll probably need to evangelize it somehow. Source: about 2 years ago
  • UI Design Roadmap 2023
    Step 5: Study design system Atlassian design system Primer design system Spectrum, Adobe’s design system Carbon design system. - Source: dev.to / over 2 years ago
View more

What are some alternatives?

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

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

Design Principles - An open source repository of design principles and methods

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

Colorbox.io - Create accessible color systems 🎨

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

Facebook Design - Resources for Designers from the Facebook Design team

Loading...