pandas-stubs
Pandas
pandas-stubs | Pandas | |
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4 | 399 | |
214 | 42,159 | |
3.7% | 1.0% | |
8.6 | 10.0 | |
9 days ago | 4 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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pandas-stubs
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We are the developers behind pandas, currently preparing for the 2.0 release :) AMA
There is a typing effort that is led by some core members (unfortunately none of them takes part today). You can check the stubs package out at https://github.com/pandas-dev/pandas-stubs. I am not really familiar with the progress there
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Is there a way to have Eglot pickup the virtual env?
I think the issue is that pandas provides its stubs via a separate package namely pandas-stubs. It seems some packages provide their stubs in a separate package i.a.w PEP561. If I install this package I get completions etc. as you might expect.
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TypeScript is terrible for library developers
It gets a lot more complicated than that. One of many, many examples: https://github.com/pandas-dev/pandas-stubs/blob/v1.4.3.22082...
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?
django-stubs - PEP-484 stubs for Django
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
lxml-stubs - Type stubs for the lxml package
tensorflow - An Open Source Machine Learning Framework for Everyone
pfun - Functional, composable, asynchronous, type-safe Python.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
bench-warmers - DigThatData's Public Brainstorming space
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
returns - Make your functions return something meaningful, typed, and safe!
Keras - Deep Learning for humans
bulk-exif-to-excel - Bulk exif data export to excel
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration