Introduction to Python: Why, Install & Jupyter Notebooks

What is programming?

A program is a set of precise instructions a computer follows. Computers only understand machine code (0s and 1s), so we write instructions in a programming language that humans can read, and a translator turns them into something the machine can run.

Compiled vs interpreted

Python is usually called interpreted. In reality CPython (the standard version) first compiles your code to bytecode (.pyc files) and then a virtual machine executes it. Python code that needs speed calls libraries written in C (NumPy, pandas), so data work is fast anyway.

Why Python for data?

Getting set up: three options

Jupyter notebooks

A Jupyter notebook (.ipynb) mixes code cells, Markdown cells (text, headings, images) and outputs (tables, charts) in one document. It is the standard tool for exploring data and sharing analysis. The name comes from Julia, Python and R.

The kernel

The kernel is the Python process behind the notebook. Variables you create stay in its memory until you restart it. Cells can be run in any order, which is flexible but dangerous: a notebook can look right while depending on a cell you deleted. Before sharing, always Restart Kernel and Run All to prove the notebook works top to bottom.

Essential shortcuts (Jupyter / Colab)

Your first code

print("Hello, data world!")

Hello, data world!

Python is also a calculator:

2 + 3 * 4

14

(2 + 3) * 4, 10 / 4, 10 // 4, 10 % 4, 2 ** 10

(20, 2.5, 2, 2, 1024)

The last expression in a notebook cell is displayed automatically; to show several things use print().

name = "Varun"
learners = 25
print("Welcome to the course,", name)
print(f"This batch has {learners} learners")

Welcome to the course, Varun
This batch has 25 learners

Comments

# This is a comment: Python ignores everything after the hash
price = 120          # you can also put a comment at the end of a line
"""A triple-quoted string on its own line is often used
as a multi-line comment or docstring"""

Write comments to explain why, not what. x = x + 1 # add one is noise; # compensate for the header row is useful.

Errors are normal

Every programmer sees errors daily. Learn to read them from the bottom line up:

print("Total:", total_amount)

NameError: name 'total_amount' is not defined

NameError: name 'total_amount' is not defined says exactly what happened: we used a name we never created. Common beginner errors:

Markdown cells

Change a cell to Markdown to write notes next to your code:

# Title
## Section
Some **bold** and *italic* text, a [link](https://example.com), and a list:
- item one
- item two

| Column | Value |
|---|---|
| A | 1 |

Good notebooks tell a story: a title, the question, the data, the steps with short explanations, and a conclusion.

Magic commands and useful tools

Jupyter adds special commands beginning with %:

Reproducibility habits

1. Folder per project: data/, notebooks/, src/, README.md.
2. Virtual environment per project and a requirements.txt (pip freeze > requirements.txt).
3. Use relative paths (data/sales.csv), not C:\Users\you\Desktop\….
4. Set random seeds (np.random.seed(42)) so results repeat.
5. Restart and Run All before sharing; keep notebooks short and focused.
6. Version control: commit to Git; clear outputs of big notebooks.
7. Do not commit data with personal information or secrets (API keys); use environment variables.

Summary

print("Asha Rao")
length, width = 12, 7.5
print("Area:", length * width)          # 90.0
import sys; print(sys.version)
print(undefined_name)                    # NameError: name 'undefined_name' is not defined
undefined_name = 5; print(undefined_name)