Data-Science-For-Beginners/translations/pcm/INSTALLATION.md

Installation Guide

Dis guide go help you set up your environment to work with di Data Science for Beginners curriculum.

Table of Contents

• Prerequisites
• Quick Start Options
• Local Installation
• Verify Your Installation

Prerequisites

Before you start, you go need:

• Small sabi of command line/terminal
• GitHub account (free)
• Good internet connection for di first setup

Quick Start Options

Option 1: GitHub Codespaces (We recommend am for Beginners)

Di easiest way to start na with GitHub Codespaces, e go give you complete development environment inside your browser.

1. Go di repository
2. Click di Code dropdown menu
3. Select di Codespaces tab
4. Click Create codespace on main
5. Wait make di environment initialize (2-3 minutes)

Your environment don ready with all di dependencies wey dem don pre-install!

Option 2: Local Development

If you wan work for your own computer, follow di detailed instructions wey dey below.

Local Installation

Step 1: Install Git

You go need Git to clone di repository and track your changes.

Windows:

• Download am from git-scm.com
• Run di installer with di default settings

macOS:

• Install am with Homebrew: brew install git
• Or download am from git-scm.com

Linux:

# Debian/Ubuntu
sudo apt-get update
sudo apt-get install git

# Fedora
sudo dnf install git

# Arch
sudo pacman -S git

Step 2: Clone di Repository

# Clone the repository
git clone https://github.com/microsoft/Data-Science-For-Beginners.git

# Navigate to the directory
cd Data-Science-For-Beginners

Step 3: Install Python and Jupyter

You go need Python 3.7 or higher for di data science lessons.

Windows:

1. Download Python from python.org
2. During installation, check "Add Python to PATH"
3. Verify di installation:

python --version

macOS:

# Using Homebrew
brew install python3

# Verify installation
python3 --version

Linux:

# Most Linux distributions come with Python pre-installed
python3 --version

# If not installed:
# Debian/Ubuntu
sudo apt-get install python3 python3-pip

# Fedora
sudo dnf install python3 python3-pip

Step 4: Set Up Python Environment

E good make you use virtual environment to keep di dependencies separate.

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On Windows:
venv\Scripts\activate

# On macOS/Linux:
source venv/bin/activate

Step 5: Install Python Packages

Install di data science libraries wey you need:

pip install jupyter pandas numpy matplotlib seaborn scikit-learn

Step 6: Install Node.js and npm (For Quiz App)

Di quiz app need Node.js and npm.

Windows/macOS:

• Download am from nodejs.org (LTS version we recommend)
• Run di installer

Linux:

# Debian/Ubuntu
# WARNING: Piping scripts from the internet directly into bash can be a security risk.
# It is recommended to review the script before running it:
#   curl -fsSL https://deb.nodesource.com/setup_lts.x -o setup_lts.x
#   less setup_lts.x
# Then run:
#   sudo -E bash setup_lts.x
#
# Alternatively, you can use the one-liner below at your own risk:
curl -fsSL https://deb.nodesource.com/setup_lts.x | sudo -E bash -
sudo apt-get install -y nodejs

# Fedora
sudo dnf install nodejs

# Verify installation
node --version
npm --version

Step 7: Install Quiz App Dependencies

# Navigate to quiz app directory
cd quiz-app

# Install dependencies
npm install

# Return to root directory
cd ..

Step 8: Install Docsify (Optional)

For offline access to di documentation:

npm install -g docsify-cli

Verify Your Installation

Test Python and Jupyter

# Activate your virtual environment if not already activated
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# Start Jupyter Notebook
jupyter notebook

Your browser go open with di Jupyter interface. You fit now navigate go any lesson .ipynb file.

Test Quiz Application

# Navigate to quiz app
cd quiz-app

# Start development server
npm run serve

Di quiz app go dey available for http://localhost:8080 (or another port if 8080 dey busy).

Test Documentation Server

# From the root directory of the repository
docsify serve

Di documentation go dey available for http://localhost:3000.

Using VS Code Dev Containers

If you get Docker installed, you fit use VS Code Dev Containers:

1. Install Docker Desktop
2. Install Visual Studio Code
3. Install di Remote - Containers extension
4. Open di repository for VS Code
5. Press F1 and select "Remote-Containers: Reopen in Container"
6. Wait make di container build (first time only)

Next Steps

• Check di README.md for overview of di curriculum
• Read USAGE.md for common workflows and examples
• Check TROUBLESHOOTING.md if you get issues
• Review CONTRIBUTING.md if you wan contribute

Getting Help

If you get issues:

1. Check di TROUBLESHOOTING.md guide
2. Search di existing GitHub Issues
3. Join our Discord community
4. Create new issue with detailed information about your problem

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Disclaimer:
Dis document don use AI translation service Co-op Translator take translate am. Even though we dey try make e accurate, abeg sabi say automated translations fit get mistake or no correct well. Di original document for di native language na di main correct source. For important information, e good make una use professional human translation. We no go dey responsible for any misunderstanding or wrong interpretation wey fit happen because of dis translation.