Pandas VS pyexcel

Compare Pandas vs pyexcel and see what are their differences.

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more (by pandas-dev)

pyexcel

Single API for reading, manipulating and writing data in csv, ods, xls, xlsx and xlsm files (by pyexcel)
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Pandas pyexcel
401 1
42,489 1,181
1.2% 0.7%
10.0 0.0
about 13 hours ago 6 months ago
Python Python
BSD 3-clause "New" or "Revised" License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Pandas

Posts with mentions or reviews of Pandas. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-06-17.
  • Essential Deep Learning Checklist: Best Practices Unveiled
    20 projects | dev.to | 17 Jun 2024
    How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class imbalances, consider techniques like oversampling, undersampling, or synthetic data generation with SMOTE.
  • Awesome List
    25 projects | dev.to | 8 Jun 2024
    Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation.
  • The ultimate guide to creating a secure Python package
    4 projects | dev.to | 8 May 2024
    It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:
  • The Birth of Parquet
    3 projects | news.ycombinator.com | 8 May 2024
  • PDEP-13: The Pandas Logical Type System
    1 project | news.ycombinator.com | 4 May 2024
  • PHP Doesn't Suck Anymore
    5 projects | news.ycombinator.com | 4 May 2024
  • AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
    4 projects | dev.to | 28 Apr 2024
    Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience.
  • Pandas reset_index(): How To Reset Indexes in Pandas
    1 project | dev.to | 27 Apr 2024
    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.
  • Deploying a Serverless Dash App with AWS SAM and Lambda
    3 projects | dev.to | 4 Mar 2024
    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. Instead, we'll focus on what's necessary to make it run serverless.
  • Help Us Build Our Roadmap – Pydantic
    2 projects | news.ycombinator.com | 19 Feb 2024
    there is pull request to integrate in both pydantic extra types and into pandas cose [1]

    [1]: https://github.com/pandas-dev/pandas/issues/53999

pyexcel

Posts with mentions or reviews of pyexcel. We have used some of these posts to build our list of alternatives and similar projects.
  • Advice on ETL and Data Sharing work process
    1 project | /r/ETL | 7 Nov 2023
    You could try and write some simple python using the pyexcel and pandas libraries. I created a tool as a consultant with these packages that parsed spreadsheets with data from factories from all around the world. They did not lock down the Excel files used to submit data and it made it so much harder. If you go this route, I would recommend starting by putting your data into a SQLite database. Once you have your data in a database, you unlock the power of SQL for pulling reports. Also, you can port the data into a proper database if you ever need to. ChatGPT can probably get you a good chunk of the way there.

What are some alternatives?

When comparing Pandas and pyexcel you can also consider the following projects:

Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis

openpyxl

tensorflow - An Open Source Machine Learning Framework for Everyone

XlsxWriter - A Python module for creating Excel XLSX files.

orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis

xlwings - xlwings is a Python library that makes it easy to call Python from Excel and vice versa. It works with Excel on Windows and macOS as well as with Google Sheets and Excel on the web.

Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

xlwt

Keras - Deep Learning for humans

docxtpl - Use a docx as a jinja2 template

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

unoconv - Universal Office Converter - Convert between any document format supported by LibreOffice/OpenOffice.

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