python-guide
Pandas
python-guide | Pandas | |
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5 | 397 | |
27,716 | 42,039 | |
1.0% | 0.7% | |
0.0 | 10.0 | |
19 days ago | 1 day ago | |
Batchfile | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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python-guide
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Top 10 GitHub Repositories for Python and Java Developers
1. RealPython/Python-guide - This repository offers a comprehensive guide to Python, covering a variety of topics such as installation, setup, and more advanced concepts like machine learning and web development. https://github.com/realpython/python-guide
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10 Github repositories to achieve Python mastery
Explore here.
- How can I obtain Hitchhikers Guide to Python as an ebook?
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Want to Stand Out From Other Job Applicants? Try Contributing to Open Source.
I'm not saying run off and merge a major update into React; You can start much smaller than that. I started by writing small documentation fixes (1, 2, 3), and eventually added new functionality to libraries that I've used in some side projects (1).
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IT HAPPENED. I got hired!
Congratulations!! Along with another comment made here, I have this starred on my GitHub for when I do get around learning Python: https://github.com/realpython/python-guide
Pandas
- PDEP-13: The Pandas Logical Type System
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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.
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Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential.
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