10 min read

Environment Setup

Working in notebooks (Jupyter/Colab) and VS Code; managing environments and packages

What You'll Learn

Setting up Python development environments
Working with Jupyter Notebooks and Google Colab
Using VS Code for Python development
Managing virtual environments
Installing and managing packages

Development Environments

Jupyter Notebooks:

Interactive computing environment
Combines code, visualizations, and text
Perfect for data analysis and exploration
Runs in your browser

Google Colab:

Free cloud-based Jupyter notebooks
No setup required
Free GPU access
Easy sharing and collaboration

VS Code:

Full-featured code editor
Excellent Python support
Integrated terminal and debugger
Extensions for data science

Virtual Environments

Why use virtual environments?

Isolate project dependencies
Avoid package conflicts
Reproducible environments
Clean project structure

Creating virtual environment:

terminal

# Using venv
python -m venv myenv

# Activate on Windows
myenv\Scripts\activate

# Activate on Mac/Linux
source myenv/bin/activate

Package Management

pip - Python package installer:

terminal

# Install package
pip install pandas

# Install specific version
pip install pandas==1.5.0

# Install from requirements.txt
pip install -r requirements.txt

# List installed packages
pip list

# Create requirements.txt
pip freeze > requirements.txt

Essential packages for data analysis:

pandas - Data manipulation
numpy - Numerical computing
matplotlib - Visualization
seaborn - Statistical visualization
jupyter - Interactive notebooks

Jupyter Notebooks

Starting Jupyter:

terminal

# Install Jupyter
pip install jupyter

# Start Jupyter Notebook
jupyter notebook

# Start JupyterLab
jupyter lab

Notebook shortcuts:

Shift + Enter - Run cell
Ctrl + Enter - Run cell (stay)
A - Insert cell above
B - Insert cell below
DD - Delete cell
M - Convert to Markdown
Y - Convert to Code

Google Colab

Getting started:

Go to colab.research.google.com
Sign in with Google account
Create new notebook
Start coding!

Colab advantages:

No setup required
Free GPU/TPU access
Google Drive integration
Easy sharing

VS Code Setup

Installing Python extension:

Open VS Code
Go to Extensions (Ctrl+Shift+X)
Search "Python"
Install Microsoft Python extension

Key features:

IntelliSense (auto-completion)
Debugging
Linting
Jupyter support
Git integration

Best Practices

Project structure:

project/
├── data/
│   ├── raw/
│   └── processed/
├── notebooks/
├── src/
├── requirements.txt
└── README.md

Environment management:

One virtual environment per project
Keep requirements.txt updated
Document dependencies
Use .gitignore for venv/

Practice Questions

Test your understanding with these practice questions. Click "Show Answer" to see the solution and "Try Code Editor" to experiment with code.

Practice Exercise

What command would you use to create a virtual environment named "data_project"?

starter_code.py

# Type the command to create a virtual environment
# (This is a bash command, not Python code)

Practice Exercise

Write Python code to check which packages are installed in your environment

starter_code.py

import pkg_resources

# Get list of installed packages
# Your code here

Practice Exercise

How would you install pandas version 2.0.0 specifically?

starter_code.py

# Write the pip command to install pandas 2.0.0
# (This is a bash command)

Practice & Experiment

Test your understanding by running Python code directly in your browser. Try the examples from the article above!

Python Crash Course I