VisPy
cheatsheets
| VisPy | cheatsheets | |
|---|---|---|
| 4 | 126 | |
| 3,230 | 7,259 | |
| 0.9% | 0.4% | |
| 8.6 | 7.0 | |
| 4 days ago | 18 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | BSD 2-clause "Simplified" 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.
VisPy
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
VisPy - High-performance scientific visualization based on OpenGL.
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Top 10 growing data visualization libraries in Python in 2023
Github: https://github.com/vispy/vispy
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Seeking library recommendation for 3D visualization of crystal structure
Two similar alternatives you could look at are PyVista which is based on the same framework as Mayavi and VisPy. Mayavi is strongly dependent on the whole Enthought suite which can be a disadvantage if you don’t really use its abilities.
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Show HN: MPL Plotter – Python library to make technical plots more efficiently
2. I recommend Datashader (https://datashader.org/) (HoloViz is super cool) and Vispy (https://vispy.org/). I found Vispy's documentation a bit lacking some time ago, but they probably have improved it since then, and it's very capable. Lastly, check Taichi (https://taichi.graphics/), might not be a conventional data representation library (or rather, not only), but it's amazing and worth a look.
To add some more depth to the Seaborn comparison, and not being an expert Seaborn user, I'd say:
1. MPL Plotter is lighter (but also with less wide-ranging plot options)
cheatsheets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Matplotlib - A Python 2D plotting library.
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How to retrieve and analyze crypto order book data using Python and a cryptocurrency API
Data visualization: utilizing Python's Matplotlib for visualizing order book information.
- Matplotlib
- Ask HN: What plotting tools should I invest in learning?
- Help with an array
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Getting visual studio code to work with imported library
Name: matplotlib Version: 3.7.1 Summary: Python plotting package Home-page: https://matplotlib.org Author: John D. Hunter, Michael Droettboom Author-email: [email protected] License: PSFLocation: /home/huinker/.local/lib/python3.10/site-packages
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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What else should I complete before applying for a data analyst role?
programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not https://cs50.harvard.edu/python/2022/ https://matplotlib.org/
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[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
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[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
What are some alternatives?
PyQtGraph - Fast data visualization and GUI tools for scientific / engineering applications
finplot - Performant and effortless finance plotting for Python
matplotlib - matplotlib: plotting with Python
manim - A community-maintained Python framework for creating mathematical animations.
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
Fast-F1 - FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
pyrender - Easy-to-use glTF 2.0-compliant OpenGL renderer for visualization of 3D scenes.
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
bokeh - Interactive Data Visualization in the browser, from Python
Keras - Deep Learning for humans
Flask JSONDash - :snake: :bar_chart: :chart_with_upwards_trend: Build complex dashboards without any front-end code. Use your own endpoints. JSON config only. Ready to go.
geogebra - GeoGebra apps (mirror)