Setting Up Your Development Environment

Getting your computer ready for data science does not have to be complicated. This guide walks you through installing the essential tools.

What You Will Install

• Python - The most popular language for data science
• R - Essential for statistical analysis
• VS Code - A powerful, free code editor
• Jupyter Notebooks - Interactive coding environment

Installing Python

Option 1: Anaconda (Recommended for Beginners)

Anaconda bundles Python with common data science libraries.

1. Visit anaconda.com/download
2. Download the installer for your operating system
3. Run the installer with default settings
4. Open Anaconda Navigator from your applications

Anaconda includes: NumPy, Pandas, Matplotlib, Jupyter, and 250+ other packages.

Option 2: Standard Python + pip

For a lighter installation:

1. Visit python.org/downloads
2. Download Python 3.11 or later
3. During installation, check "Add Python to PATH"
4. Open terminal and verify: python --version

Then install common packages:

1pip install numpy pandas matplotlib jupyter scikit-learn
2

Installing R and RStudio

R is essential for statistical analysis and visualization.

1. Install R: Visit r-project.org and download R for your OS
2. Install RStudio: Visit posit.co/download/rstudio-desktop and download the free version
3. Open RStudio - it will automatically find your R installation

Essential R Packages

Open RStudio and run:

1install.packages(c("tidyverse", "ggplot2", "dplyr", "readr"))
2

Installing VS Code

VS Code is a versatile editor that works great for both Python and R.

1. Visit code.visualstudio.com
2. Download and install
3. Install these extensions:
   • Python (by Microsoft)
   • Jupyter (by Microsoft)
   • R (by REditorSupport)

Next Steps

Now that your environment is ready:

• Getting Started with Python - Learn Python basics
• Getting Started with R - Learn R basics