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Matplotlib Alternatives
Similar projects and alternatives to matplotlib
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PyQtGraph
Fast data visualization and GUI tools for scientific / engineering applications
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plotly
The interactive graphing library for Python (includes Plotly Express) :sparkles:
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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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
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Robot Framework
Generic automation framework for acceptance testing and RPA
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
matplotlib reviews and mentions
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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?
Your choices are an n-body simulation (e.g., LAMMPS) with Coulomb interactions or, if your electrons are sufficiently sparse, a particle-in-cell (e.g., Starfish). Your best bets for visualization are going to be matplotlib or something more user-friendly like Visit or Paraview. Without a neutralizing background, however, your electrons are just going to repel each other, hit the walls, and disappear - there's not going to be much interesting to visualize. What are you actually trying to simulate? With more information maybe you could receive some more targeted advice.
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How to model the hanging chain PDE using numerical methods in Python?
There are plenty of data visualization tools in python, but probably the easiest to get started with is Matplotlib
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Best way to learn ML/AI hands-on as a developer?
An example of how I would do this is to just plot your data on a line graph (https://matplotlib.org/) . Are there any repeating trends? Next try splitting your data into day of the week, day of the month, months, etc. Look for any kind of seasonality (we're trying to use the past to predict the future, so if the future is not like the past our models will fail).
- Matplotlib - Visualization with Python
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SerpApi Demo Project: Walmart Coffee Exploratory Data Analysis
Install libraries and tell matplotlib to plot inline (inside notebook) with the help of % magic functions which sets the backend of matplotlib to the inline backend:
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How to make sure a python program runs on a computer that might not have internet connection to download the external libraries used?
The thing is, you will also need to go get the wheels (or *.tar.gz sources) for all of the dependencies of your packages as well! Over in matplotlib's setup.py you can find the following:
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Matplotlib just nuked all of my styles because they now hate abbreviated HTML colors.
GitHub history for rcsetup.py
This commit. You can get that by clicking "View Git Blame" on line 307.
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Reducing the Size of Large PDFs
Oh didn't know about the improved type 42 font support in the new matplotlib! That's good to know and I should check it out.
And good point, the PGF works just as well (results should be identical), but since all the plot information has to be compiled by latex, it ends up ballooning the compilation time of the tex doc and the matplotlib PGF page suggests that you can run into memory issues as well. I was doing this for a thesis with 50+ plots and so still wanted compilation to be fast.
I've suggested this as an improvement to matplotlib, but unlikely to be merged since maybe it's a bit hacky (although it's very similar to what Inkscape's export to LaTeX option does): https://github.com/matplotlib/matplotlib/issues/22297 (the backend file can be found here: https://github.com/matplotlib/matplotlib/files/7921801/backe...)
And the gs script is below:
#!/bin/bash
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matplotlib/matplotlib is an open source project licensed under Python License 2.0 which is an OSI approved license.