Pandas
node-express-realworld-example-app | Pandas | |
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7 | 398 | |
3,531 | 42,039 | |
0.3% | 0.7% | |
4.2 | 10.0 | |
7 days ago | 3 days ago | |
TypeScript | Python | |
- | BSD 3-clause "New" or "Revised" License |
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node-express-realworld-example-app
- There is framework for everything.
- some good design pattern for node?
- [AskJS] Open source express app to go through code for learning.
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[AskJS] is there public repo showing production level code of REST APIs using nodejs
Realworld express. Whenever I need an implementation in a new language, I always check to see if there's a realworld repo.
- Well written REST API examples with Express?
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Open source projects to get your hands dirty
check this out https://github.com/gothinkster/node-express-realworld-example-app
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Please send me your open source production Express API code!
I've always thought this was a pretty good place to see how frameworks look in a 'real-world' way. https://github.com/gothinkster/realworld Since each repo is a clone of Medium.com you can see how expressjs compares to NestJS, or Laravel or Spring, etc.
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?
nestjs-realworld-example-app - Exemplary real world backend API built with NestJS + TypeORM / Prisma
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
laravel-realworld-example-app - Exemplary real world backend API built with Laravel
tensorflow - An Open Source Machine Learning Framework for Everyone
spring-boot-realworld-example-app - Example Spring codebase containing real world examples (CRUD, auth, advanced patterns, etc) that adheres to the RealWorld API spec.
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
bulletproof-nodejs - Implementation of a bulletproof node.js API 🛡️
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
realworld - "The mother of all demo apps" — Exemplary fullstack Medium.com clone powered by React, Angular, Node, Django, and many more
Keras - Deep Learning for humans
readable-stream - Node-core streams for userland
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration