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Pandas VS KEEL

Compare Pandas VS KEEL and see what are their differences

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Powerful SaaS integration toolkit for SaaS developers - create, amplify, manage and publish native integrations from within your app. featured
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.

KEEL logo KEEL

KEEL contains classical knowledge extraction algorithms, preprocessing techniques, Computational Intelligence based learning algorithms, evolutionary rule learning algorithms, genetic fuzzy systems, evolutionary neural networks, etc.
  • Pandas Landing page
    Landing page //
    2023-05-12
  • KEEL Landing page
    Landing page //
    2021-09-20

Pandas videos

+ Add

Ozzy Man Reviews: Pandas

More videos:

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

KEEL videos

+ Add

Creating a "High Performance Twin Fin Keel" Design Vlog by Noel Salas

More videos:

  • Review - 2019 Twin and keel fin guide / Rob Machado Seaside Quad fins
  • Review - FCS II Rob Machado "FW Glazer" Tri-Keel

Category Popularity

0-100% (relative to Pandas and KEEL)

Pandas

KEEL

Data Science And Machine Learning
97 97%
Data Science And Machine Learning
3% 3
Data Science Tools
97 97%
Data Science Tools
3% 3
Python Tools
100 100%
Python Tools
0% 0
Development
0 0%
Development
100% 100

User comments

Share your experience with using Pandas and KEEL. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Pandas and KEEL

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

KEEL Reviews

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

Social recommendations and mentions

Based on our record, Pandas seems to be more popular. It has been mentiond 197 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 (197)

  • Pandas reset_index(): How To Reset Indexes in Pandas
    In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / about 9 hours ago
  • Deploying a Serverless Dash App with AWS SAM and Lambda
    Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / about 2 months ago
  • Stuff I Learned during Hanukkah of Data 2023
    Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 4 months ago
  • Exploring Open-Source Alternatives to Landing AI for Robust MLOps
    Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
  • Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
    Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential. - Source: dev.to / 5 months ago
View more

KEEL mentions (0)

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

What are some alternatives?

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

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

Apache Mahout - Distributed Linear Algebra

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

KNIME - KNIME, the open platform for your data.

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

WEKA - WEKA is a set of powerful data mining tools that run on Java.

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