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environment-setup

Installs Miniconda and configures a Python research environment for data visualization.

Updated Jul 5, 2026
Search Tags:#research#data visualization#python#environment setup#matplotlib#conda#miniconda
One-click install
npx skills add https://github.com/huaibovip/research-marketplace --skill environment-setup-huaibovip
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: environment-setup
Source: https://github.com/huaibovip/research-marketplace/tree/main/plugins/research-writing-assistant/skills/environment-setup
Command: npx skills add https://github.com/huaibovip/research-marketplace --skill environment-setup-huaibovip

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, pandas, scipy, matplotlib, seaborn, scikit-learn, statsmodels, jupyter, ipykernel, openpyxl.

What problem does it solve? Setting up a working Python environment for scientific plotting often fails due to missing conda installations, shell misconfiguration, or dependency conflicts. This Skill automates the full setup so plotting scripts run without environment errors. ## Core Features & Use Cases - Cross-platform Miniconda installation: Automated silent install flows for macOS (arm64/x86_64), Linux, and Windows PowerShell, including shell initialization. - Research environment creation: Creates a research conda environment with Python 3.11 and installs numpy, pandas, scipy, matplotlib, seaborn, scikit-learn, statsmodels, and Jupyter kernel registration. - Self-check and troubleshooting: Runs an import verification script and provides fixes for common issues like conda: command not found, slow downloads (Tsinghua mirror), and package conflicts. - Use Case: A user asks to plot experimental data with Python but has no environment ready; the Skill detects the OS, installs Miniconda, creates the environment, installs plotting libraries, and verifies everything works. ## Quick Start Set up a Python environment with matplotlib and pandas so I can create data visualizations for my research paper.

Frequently Asked Questions about environment-setup

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I install Miniconda on macOS from the command line?▼

Download the Miniconda installer script matching your architecture (arm64 or x86_64) with curl, run it silently with bash using the -b flag targeting $HOME/miniconda3, then run conda init for your shell and verify with conda --version.

How to create a conda environment for Python data visualization?▼

Run conda create -n research python=3.11 -y, activate it with conda activate research, then pip install numpy, pandas, matplotlib, seaborn, scikit-learn, and statsmodels. Register a Jupyter kernel with python -m ipykernel install if needed.

Why does 'conda: command not found' happen after installation?▼

This happens when the conda binary directory is not on your PATH or the shell was not initialized. Export $HOME/miniconda3/bin to PATH and run conda init for your shell, then restart the terminal session.

Can I install Miniconda silently on Windows with PowerShell?▼

Yes. Download the Windows x86_64 installer with Invoke-WebRequest, then run it with Start-Process using the /S silent flag and /D target path. Afterwards run conda init powershell and refresh the PATH in the current session.

How do I fix slow pip downloads or package conflicts in conda?▼

For slow downloads, set a mirror such as the Tsinghua PyPI index with pip config set global.index-url. For package conflicts, create a fresh environment with conda create -n research_clean python=3.11 and reinstall from requirements.txt.

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