Getting Started with Data Science

Creating a Virtual Environment

Virtual environments keep your projects isolated. Let's create one for data science:

python -m venv ds_env

python3 -m venv ds_env

ds_env\Scripts\activate

source ds_env/bin/activate

pip install numpy pandas matplotlib seaborn
pip install scikit-learn scipy jupyter ipykernel
pip install plotly

python -m ipykernel install --user --name=ds_env --display-name "Python (DS)"

Installation

Test 1: Python & Basic Libraries

Create a new file called test_setup.py and add:

import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

print(f"Python version: {sys.version}")
print(f"NumPy version: {np.__version__}")
print(f"Pandas version: {pd.__version__}")
print(f"Matplotlib version: {plt.matplotlib.__version__}")

# Test NumPy
arr = np.array([1, 2, 3, 4, 5])
print(f"\nNumPy array: {arr}")
print(f"Mean: {arr.mean()}")

# Test Pandas
df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Age': [25, 30, 35]
})
print(f"\nPandas DataFrame:\n{df}")

print("\nAll libraries working correctly!")

Run it from terminal:

python test_setup.py

You should see output with version numbers and test data. If you see errors, revisit the installation steps.

Test 2: Jupyter Notebook

Launch Jupyter Notebook:

jupyter notebook

This should open your browser with the Jupyter interface. Create a new notebook and try:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Create sample data
x = np.linspace(0, 10, 100)
y = np.sin(x)

# Plot
plt.figure(figsize=(10, 6))
plt.plot(x, y)
plt.title('Test Plot: Sine Wave')
plt.xlabel('X')
plt.ylabel('Y')
plt.grid(True)
plt.show()

If you see a sine wave plot, congratulations! Everything is working.

Problem: "python" not recognized

Solution: Python wasn't added to your system PATH during installation.

• Windows: Reinstall Python and check "Add Python to PATH" option, or manually add it:
  1. Search "Environment Variables" in Start Menu
  2. Click "Environment Variables" button
  3. Under "System variables", find "Path" and click "Edit"
  4. Add C:\Users\YourName\AppData\Local\Programs\Python\Python311
• Mac/Linux: Add to your ~/.bashrc or ~/.zshrc:

  export PATH="/usr/local/bin/python3:$PATH"

Problem: Virtual environment won't activate

Solution: Different activation methods depending on your shell:

• Windows Command Prompt: ds_env\Scripts\activate.bat
• Windows PowerShell: ds_env\Scripts\Activate.ps1 (may need to enable scripts first)
• Mac/Linux: source ds_env/bin/activate

If PowerShell gives an error, run: Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

Problem: "ModuleNotFoundError" when importing libraries

Solution: Either the library isn't installed, or you're not in your virtual environment:

# 1. Make sure venv is activated (you should see (ds_env) in prompt)
source ds_env/bin/activate  # or ds_env\Scripts\activate on Windows

# 2. Install the missing library
pip install library-name

# 3. Verify it's installed
pip list | grep library-name

Problem: Jupyter Notebook won't start

Solution: Make sure Jupyter and ipykernel are installed in your virtual environment:

# Activate your virtual environment first
source ds_env/bin/activate

# Reinstall Jupyter
pip install --upgrade jupyter ipykernel

# Register the kernel again
python -m ipykernel install --user --name=ds_env --display-name "Python (DS)"

Problem: VS Code can't find Python interpreter

Solution:

1. Open Command Palette (Ctrl+Shift+P or Cmd+Shift+P)
2. Type "Python: Select Interpreter"
3. Look for your virtual environment path (e.g., ./ds_env/bin/python)
4. If not listed, click "Enter interpreter path" and browse to ds_env/bin/python (or ds_env\Scripts\python.exe on Windows)

Problem: pip install is slow or failing

Solution: Try upgrading pip first:

python -m pip install --upgrade pip

# Then try installing again
pip install package-name

Running Cells