awesome-datascience
Pandas
awesome-datascience | Pandas | |
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9 | 397 | |
23,777 | 42,039 | |
3.7% | 0.7% | |
6.9 | 10.0 | |
9 days ago | 1 day ago | |
Python | ||
MIT License | BSD 3-clause "New" or "Revised" License |
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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.
awesome-datascience
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About Data analyst, data scientist and data engineer, resources and experiences
Awesome Data Science by Academic
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Good coding groups for black women?
- https://github.com/academic/awesome-datascience
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Mastering Data Science: Top 10 GitHub Repos You Need to Know
9. Awesome Data Science If you’re on the hunt for data science resources, Awesome Data Science is a goldmine. This curated list includes MOOCs, books, courses, blogs, podcasts, software, and more, all related to data science.
- Does anyone know of comprehensive refresher material for a once Senior Data Scientist?
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Beginner Friendly Resources to Master Artificial Intelligence and Machine Learning with Python (2022)
Awesome Data Science – The awesome lists repositories often provides a good collection of resources around a specific topic, and the awesome-datascience repository is no exception. It contains a very comprehensive list of books, moocs, tutorials, and other content for all learnes of all levels of experience.
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High income skills?
There are several on github, such as: https://github.com/academic/awesome-datascience
- ⚙️ Awesome Data Science: An #OpenSource #DataScience repository to learn and apply towards solving real world problems. h/t @Sauain
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Top GitHub repositories to learn Data Science
Awesome Data Science
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[IWantOut] 21f Peru student -> Canada/UK
If you want to expand your skills and knowledge in data science, there's a ton of free online resources out there. For example, this page is a good place to get started. There's lots of communities like /r/learndatascience or similar subs if you get stuck on something.
Pandas
- 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.
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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.
What are some alternatives?
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
gdelt
tensorflow - An Open Source Machine Learning Framework for Everyone
vagas-junior-estagio - Empresas que constantemente oferecem vagas para junior e estagiários sem exigir experiência prévia
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
DataScienceResources - Open Source Data Science Resources.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
data-science-blogs - A curated list of data science blogs
Keras - Deep Learning for humans
ScribeSalad - A collection of YouTube videos transcripts : Podcasts (Joe Rogan Experience, Tim Ferris, Jocko podcast, ..), lectures (YaleCourses, MIT lectures, Jordan B. Peterson talks, ..). A big transcripts salad spanning history, geography, science, politics, film making and more.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration