Software Alternatives, Accelerators & Startups
Register | Login

Pandas VS Enzyme

Compare Pandas VS Enzyme and see what are their differences

ScreenshotMAX
The all-in-one Screenshot API for developers: capture websites, generate PDFs, record videos, and automate it all with powerful, scalable infrastructure. No browser setup, no hassle. Just clean results, fast. 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.

Enzyme logo Enzyme

Enzyme is a JavaScript testing utility for React.
  • Pandas Landing page
    Landing page //
    2023-05-12
  • Enzyme Landing page
    Landing page //
    2023-10-16

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.

Enzyme features and specs

  • Shallow Rendering
    Allows you to render a component without its children, which speeds up tests and isolates the component being tested.
  • Rich API
    Provides a comprehensive set of APIs that enable deep rendering, traversing, and manipulating of components, making it flexible and powerful for various testing needs.
  • Compatibility with Mocha and Jest
    Easily integrates with popular testing frameworks like Mocha and Jest, ensuring a smooth setup process.
  • Simulate Events
    Supports simulation of user events such as clicks, enabling more realistic interaction testing.
  • Selector Support
    Allows for selecting and finding elements using CSS selectors or component constructors, making it easier to target specific elements in tests.
  • Active Community
    Has a large and active community, which can be a valuable resource for support, plugins, and best practices.

Possible disadvantages of Enzyme

  • Complex Setup
    The initial setup and configuration can be complex, especially for beginners, requiring additional libraries and configurations.
  • Limited Support for New React Features
    Often lags behind in supporting new React features, such as Hooks or the latest Context API, compared to other testing frameworks.
  • Deprecation Warnings
    Issues with deprecation warnings and updates can arise, causing frustrations during maintenance and upgrades.
  • Performance Overhead
    Can be slower compared to other testing libraries, especially when using deep rendering for large components.
  • Inconsistent API
    Some users find the API inconsistent or unintuitive, requiring more effort to learn and use effectively.

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 Enzyme

Overall verdict

  • Enzyme is generally considered a good tool for testing React applications, especially among developers familiar with its API. However, it is worth noting that there has been a shift towards using React Testing Library, which has gained popularity for its focus on testing the application as users would interact with it.

Why this product is good

  • Enzyme is a popular JavaScript testing utility for React that makes it easier to assert, manipulate, and traverse your React Components' output. It provides methods for rendering components, interacting with them, and testing their lifecycle methods, which are essential for writing comprehensive tests for your React applications.

Recommended for

    Enzyme is recommended for developers who are working on React applications and prefer a testing library that provides a more detailed inspection of component internals, or for those maintaining legacy codebases that already rely on Enzyme. If you value testing that emphasizes implementation details, Enzyme can be a good choice.

Pandas videos

+ Add

Ozzy Man Reviews: Pandas

More videos:

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

Enzyme videos

+ Add

Enzymes (Updated)

More videos:

  • Review - Enzymes
  • Review - Over-the-Counter Enzyme Supplements Explained: Mayo Clinic Physician Explains Pros, Cons

Category Popularity

0-100% (relative to Pandas and Enzyme)

Pandas

Enzyme

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Design Tools
0 0%
Design Tools
100% 100

User comments

Share your experience with using Pandas and Enzyme. 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 Enzyme

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

Enzyme Reviews

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

Social recommendations and mentions

Based on our record, Pandas seems to be a lot more popular than Enzyme. While we know about 220 links to Pandas, we've tracked only 3 mentions of Enzyme. 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 (220)

  • 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, A…. - Source: dev.to / 14 days ago
  • Top Programming Languages for AI Development in 2025
    Libraries for data science and deep learning that are always changing. - Source: dev.to / 5 months 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 / 6 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 / 6 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 / 8 months ago
View more

Enzyme mentions (3)

  • Top React Testing Libraries in 2025
    Enzyme is a widely-used testing utility that provides robust tools for interacting with and inspecting React components. Its API supports shallow, full, and static rendering, enabling developers to test components in isolation or with their child components. Enzyme also allows testing lifecycle methods, making it ideal for applications with complex state and props interactions. - Source: dev.to / 6 months ago
  • How we have managed to run Enzyme tests with React 18 app.
    Like many other companies with mature software, we found ourselves at a crossroads with our React application. The app, initially developed in early 2019, was built with React 16 and used Enzyme for unit testing. Over the past five years, the app grew, evolved, gained new features, and went though minor and major refactorings. Obviously, as responsible engineers we always maintained unit test coverage around... - Source: dev.to / 11 months ago
  • What would you consider to be a must for a modern 2022 dev stack?
    React testing library instead of enzyme for testing react UIs. I'll never go back. Source: over 3 years ago

What are some alternatives?

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

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

Jasmine - Behavior-Driven JavaScript

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

Ava - Making conversations accessible for the deaf

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

QUnit - What is QUnit? QUnit is a powerful, easy-to-use JavaScript unit testing framework. It's used by the jQuery, jQuery UI and jQuery Mobile projects and is capable of testing any generic JavaScript code, including itself!

Loading...