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)

Pandas Alternatives

Similar projects and alternatives to Pandas

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better Pandas alternative or higher similarity.

Pandas discussion

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  1. User avatar
    e123459c
    · 3 months ago
    · Reply

    Review ★★★★☆ 8/10

  2. User avatar
    SiavoshZarrasvand
    · 3 months ago
    · Reply

    Review ★★★★☆ 8/10

  3. User avatar
    5d8c8079
    · 3 months ago
    · Reply

    Review ★★★★☆ 8/10

Pandas reviews and mentions

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 2024-09-12.
  • Intro to Ray on GKE
    3 projects | dev.to | 12 Sep 2024
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as we’ve explored here, but Ray Clusters can also be created independent of Kubernetes.
  • Data Visualisation Basics
    3 projects | dev.to | 6 Sep 2024
    pandas: while this library includes some convenient methods for visualizing data that hook into matplotlib, we'll mainly be using it for its main purpose as a general tool for working with data (https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf).
  • Farewell Pandas, and thanks for all the fish
    5 projects | news.ycombinator.com | 29 Aug 2024
  • JIRA Analytics with Pandas
    3 projects | dev.to | 23 Aug 2024
    Many day-to-day tasks may require one-time data analysis, so writing services every time doesn't pay off. You can treat JIRA as a data source and use a typical data analytics tool belt. For example, you may take Jupyter, fetch the list of recent bugs in the project, prepare a list of "features" (attributes valuable for analysis), utilize pandas to calculate the statistics, and try to forecast trends using scikit-learn. In this article, I would like to explain how to do it.
  • Streamlit 101: The fundamentals of a Python data app
    5 projects | dev.to | 20 Aug 2024
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”
  • Useful Python Libraries for AI/ML
    5 projects | dev.to | 10 Aug 2024
    pandas - The standard data analysis and manipulation tool numpy - scientific computing library seaborn - statistical data visualization sklearn - basic machine learning and predictive analysis CausalML - a suite of uplift modeling and causal inference methods PyTorch - professional deep learning framework PivotTablejs - Drag’n’drop Pivot Tables and Charts for Jupyter/IPython Notebook LazyPredict - build and work with and compare multiple models phidata - Build AI Assistants with memory, knowledge and tools. Lux - automates visualization and data analysis pycaret - low-code machine learning library. really nice Cleanlab - for when you are working with messy data drawdata - draw a dataset from inside Jupyter pyforest - lazy import popular data science libs streamlit - simple ui builder, useful for demonstrating ML results
  • 7 Python Excel Libraries: In-Depth Review for Developers
    3 projects | dev.to | 18 Jul 2024
    Pandas is a powerful data manipulation and analysis library that provides easy-to-use data structures and data analysis tools. It includes the read_excel and to_excel functions to read from and write to Excel files. It leverages third-party libraries like OpenPyXL and xlrd to read from and write to Excel files.
  • 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:
  • A note from our sponsor - SaaSHub
    www.saashub.com | 7 Oct 2024
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Stats

Basic Pandas repo stats
408
43,430
9.9
about 10 hours ago

pandas-dev/pandas is an open source project licensed under BSD 3-clause "New" or "Revised" License which is an OSI approved license.

The primary programming language of Pandas is Python.


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