[Leejohnston]

Beginner’s Guide to Coding for Science

Coding is one of the most valuable skills in modern science. 
Whether you’re studying physics, analysing data, modelling the universe, or doing GCSE maths — learning to program will help you.

This guide gives a clean, friendly introduction to scientific coding using Python.

-----------------------------------------------------------------------

1. Why Python? (The Best Language for Science)

Python is the most popular language for science because:

• It’s easy to read 
• Easy to learn 
• Works on every computer 
• Huge scientific libraries 
• Used by NASA, CERN, Google, and universities 

The main scientific tools in Python include:

• NumPy (numbers & arrays) 
• pandas (data analysis) 
• Matplotlib (graphs) 
• SciPy (maths & physics) 
• SymPy (symbolic maths) 
• TensorFlow / PyTorch (AI & machine learning) 

Python is perfect for beginners *and* advanced researchers.

-----------------------------------------------------------------------

2. Installing Python

The easiest way:

Download Anaconda: 
https://www.anaconda.com/products/distribution

It includes:
• Python 
• Jupyter Notebook 
• Scientific libraries 
• Everything you need to start 

-----------------------------------------------------------------------

3. Your First Scientific Program

Code:

print("Hello Lumin Archive!")

-----------------------------------------------------------------------

4. Example: Simple Physics Simulation (distance = speed × time)

Code:

speed = 20      # in m/s
time = 15      # in seconds

distance = speed * time
print("Distance travelled:", distance, "meters")

-----------------------------------------------------------------------

5. Example: Analysing Data with pandas

Code:

import pandas as pd

data = {
    "Time (s)": [0, 1, 2, 3, 4],
    "Speed (m/s)": [0, 3, 7, 12, 18]
}

df = pd.DataFrame(data)

print(df)

-----------------------------------------------------------------------

6. Example: Plotting a Graph (Speed vs Time)

Code:

import matplotlib.pyplot as plt

time = [0, 1, 2, 3, 4]
speed = [0, 3, 7, 12, 18]

plt.plot(time, speed)
plt.xlabel("Time (s)")
plt.ylabel("Speed (m/s)")
plt.title("Speed-Time Graph")
plt.show()

-----------------------------------------------------------------------

7. Example: Solving an Equation with SymPy

Code:

from sympy import symbols, Eq, solve

x = symbols('x')
equation = Eq(2*x - 7, 15)

solution = solve(equation)
print(solution)

-----------------------------------------------------------------------

8. What Can Coding Do for You?

With coding, you can:
• Simulate planets and orbits 
• Analyse scientific data 
• Draw graphs automatically 
• Build AI models 
• Explore patterns in maths 
• Automate calculations 
• Create your own experiments 
• Solve equations instantly 
• Run physics and chemistry simulations 

Coding = unlimited scientific power.

-----------------------------------------------------------------------

9. Where Beginners Should Start

Recommended learning order:

1. Basic Python (print, variables, lists) 
2. Loops & if statements 
3. Functions 
4. Using NumPy 
5. Plotting with Matplotlib 
6. Data analysis with pandas 
7. Simulations & modelling 
8. AI / machine learning (if you want)

-----------------------------------------------------------------------

Summary

• Python is the best language for science 
• You can analyse data, make graphs, and run simulations with a few lines 
• Coding unlocks deeper understanding of maths, physics, and research 
• Every scientist, student, and curious explorer benefits from learning to program 

This is your starting point — explore, experiment, create.