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Mattscreative edited this page Nov 20, 2025 · 2 revisions

🔬 Linux Scientific Computing Guide

Complete beginner-friendly guide to scientific computing on Linux, covering Arch Linux, CachyOS, and other distributions including Python scientific libraries, R, MATLAB alternatives, and data analysis tools.

📋 Table of Contents

  1. Python Scientific Libraries
  2. R Statistical Computing
  3. MATLAB Alternatives
  4. Data Analysis Tools
  5. Troubleshooting

🐍 Python Scientific Libraries

NumPy

Install NumPy:

# Install NumPy
pip install numpy

# Or system package
sudo pacman -S python-numpy

SciPy

Install SciPy:

# Install SciPy
pip install scipy

# Or system package
sudo pacman -S python-scipy

Matplotlib

Install Matplotlib:

# Install Matplotlib
pip install matplotlib

# Or system package
sudo pacman -S python-matplotlib

Pandas

Install Pandas:

# Install Pandas
pip install pandas

# Or system package
sudo pacman -S python-pandas

📊 R Statistical Computing

Install R

Arch/CachyOS:

# Install R
sudo pacman -S r

# Install RStudio (optional)
yay -S rstudio-desktop-bin

Debian/Ubuntu:

sudo apt install r-base

Fedora:

sudo dnf install R

Use R

Launch R:

# Launch R
R

# Or RStudio
rstudio

🧮 MATLAB Alternatives

Octave

Install Octave:

# Install Octave
sudo pacman -S octave

# Launch
octave

Scilab

Install Scilab:

# Install Scilab
yay -S scilab-bin

📈 Data Analysis Tools

Jupyter

Install Jupyter:

# Install Jupyter
pip install jupyter

# Launch
jupyter notebook

Spyder

Install Spyder:

# Install Spyder
sudo pacman -S spyder

# Launch
spyder

🔧 Troubleshooting

Library Import Errors

Check installation:

# Check Python
python -c "import numpy; print(numpy.__version__)"

# Reinstall if needed
pip install --upgrade numpy

📝 Summary

This guide covered scientific computing tools for Arch Linux, CachyOS, and other distributions.

🔗 Next Steps

This guide covers Arch Linux, CachyOS, and other Linux distributions. For distribution-specific details, refer to your distribution's documentation.

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