strongbox
Pandas
| strongbox | Pandas | |
|---|---|---|
| 1 | 399 | |
| 495 | 42,159 | |
| - | 1.0% | |
| 0.0 | 10.0 | |
| over 1 year ago | 5 days ago | |
| Java | Python | |
| Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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.
strongbox
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Hacktoberfest: 69 Beginner-Friendly Projects You Can Contribute To
https://github.com/strongbox/strongbox A modern OSS artifact repository manager.
Pandas
- The Birth of Parquet
- PDEP-13: The Pandas Logical Type System
- PHP Doesn't Suck Anymore
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AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
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.
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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.
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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. Instead, we'll focus on what's necessary to make it run serverless.
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Help Us Build Our Roadmap – Pydantic
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
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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.
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Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
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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.
What are some alternatives?
react-native - A framework for building native applications using React
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
Sinatra - Classy web-development dressed in a DSL (official / canonical repo)
tensorflow - An Open Source Machine Learning Framework for Everyone
SaltStack - Software to automate the management and configuration of any infrastructure or application at scale. Get access to the Salt software package repository here:
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Electron - :electron: Build cross-platform desktop apps with JavaScript, HTML, and CSS
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
faker - A library for generating fake data such as names, addresses, and phone numbers.
Keras - Deep Learning for humans
Symfony - The Symfony PHP framework
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration