Spyder
Pandas
Spyder | Pandas | |
---|---|---|
84 | 397 | |
8,052 | 42,039 | |
0.7% | 0.7% | |
9.9 | 10.0 | |
5 days ago | 1 day ago | |
Python | Python | |
MIT License | 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.
Spyder
- Spyder – The Scientific Python Development Environment
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I've coded in R for years, but I want to learn Python for machine learning/statistical analysis. Where to start, and which IDE?
IDE-wise, I find Spyder to be the most R-like. If you are comfortable with R Studio, maybe check it out.
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Email proves Microsoft's Activision bid is designed to eliminate Playstation
For anyone else who hadn’t heard of Spyder: https://www.spyder-ide.org/
- R user, trying to learn Python... what´s the Rstudio equivalent?
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The Best Python IDE For Mac Users - Part 1
Spyder
- PYTHON vs OCTAVE for Matlab alternative
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Why does Python look one way on my laptop and completely different in this video i wanted to watch?
Spyder - a popular editor for scientific work, the default option if you get the Anaconda implementation of Python which includes many packages used in science and engineering fields
- Too many people go to college for a hobby instead of for a major.
- Which IDE is your favorite? And which IDE would you recommend for trading
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What is your favorite IDE/Text Editor to use for Python?
I also have a fondness for Spyder, which was my first non-IDLE IDE experience. It is heavily geared toward scientific computing.
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?
Visual Studio Code - Visual Studio Code
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
thonny - Python IDE for beginners
tensorflow - An Open Source Machine Learning Framework for Everyone
Atom - :atom: The hackable text editor
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
qtconsole - Jupyter Qt Console
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
jupyter-book - Create beautiful, publication-quality books and documents from computational content.
Keras - Deep Learning for humans
jupyterlab-lsp - Coding assistance for JupyterLab (code navigation + hover suggestions + linters + autocompletion + rename) using Language Server Protocol
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration