matplotlib
Pandas
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matplotlib | Pandas | |
---|---|---|
36 | 393 | |
19,223 | 41,923 | |
1.7% | 1.4% | |
10.0 | 10.0 | |
5 days ago | 2 days ago | |
Python | Python | |
Python License 2.0 | 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.
matplotlib
- How and where is matplotlib package making use of PySide?
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/matplotlib/matplotlib
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Tkinter, PyGame windows too large on Mac
as suggested here.
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[OC] Attempted & Completed Suicide Rate in Canada, 1998/99
Tool: Matplotlib Pyplot
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Help unpickling an old dataset
The issue was described here: https://github.com/matplotlib/matplotlib/issues/8409, but the "solution" was just "this is fixed" which was not helpful to me.
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The Python Packages That Gave Me Nightmares: A Guide to Overcoming Common Challenges
Matplotlib: Matplotlib is a 2D plotting library that allows you to create visualizations of your data. It's a powerful tool for data analysis, but the syntax can be complex and the customization options can be overwhelming. GitHub - https://github.com/matplotlib/matplotlib
- pcolormesh very slow when using "log" axes
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Question: What is matplotlib short for?
A quick google shows: this history.txt:
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Linear Regression
Let's take a small subset i.e 20 data points of our prediction and compare it with actual output using matplotlib library
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Where to find a dynamic charge density animation/simulation?
I will think more about what I want to say next, but for now, I would like to say that I need the super-particles and PIC methods as I think that is the way forward for me. Are there ways to implement these methods in matplotlib, Visit or Paraview? Do I take existing code and import it into those programs to visualize it? Or can I directly program/simulate something in those visualizion tools without needing to import any code?
Pandas
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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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What Would Go in Your Dream Documentation Solution?
So, what I'd like to do is write a documentation package in Python to recreate what I've lost. I plan to build upon the fantastic python-docx and docxtpl packages, and I'll probably rely on pandas from much of the tabular stuff. Here are the features I intend to include:
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How do people know when to use what programming language?
Weirdly most of my time spent with data analysis was in the C layers in pandas.
- Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
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10 Github repositories to achieve Python mastery
Explore here.
What are some alternatives?
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
tensorflow - An Open Source Machine Learning Framework for Everyone
pygal - PYthon svg GrAph plotting Library
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
bqplot - Plotting library for IPython/Jupyter notebooks
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
bokeh - Interactive Data Visualization in the browser, from Python
Keras - Deep Learning for humans
plotnine - A Grammar of Graphics for Python
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration