Variables and data types

Everything in Python is built on a few basic types. You cannot skip this step.

Variables

A variable is a name for a value. Python has no declare step. You assign, and it exists.

city = "Vancouver"
salary = 95000
remote = True

Names are lowercase with underscores: salary_usd, job_title, is_remote. This is the Python style guide (PEP 8). Follow it from day one, so your code looks like everyone else’s.

The five types you need

Type	Example	Used for
int	42, 95000	Counts, whole numbers
float	3.14, 0.1	Decimals, money, ratios
str	"Berlin", 'Berlin'	Text. Single or double quotes, both fine
bool	True, False	Yes/no flags
None	None	”No value yet”. Like NULL in SQL

Check a type with type():

print(type(42))       # <class 'int'>
print(type("42"))     # <class 'str'>

Converting between types

Data arrives as text. From a CSV, from an API, from user input. You convert it before you calculate:

salary_text = "85000"
salary = int(salary_text)        # 85000
ratio = float("0.15")            # 0.15
label = str(2026)                # "2026"

"85000" + 1 is an error. int("85000") + 1 is 85001. Half of beginner bugs are this.

f-strings: how you print

Put an f before the quote, and variables in curly braces:

name = "Anna"
age = 29
print(f"{name} is {age} years old.")     # Anna is 29 years old.
print(f"Salary: {salary:,} USD")         # Salary: 85,000 USD
print(f"Ratio: {ratio:.1%}")             # Ratio: 15.0%

You will use f-strings in every log line and every report. Learn the two formats above: :, for thousands separators, :.1% for percentages.

Arithmetic

10 / 3      # 3.333...  division always gives a float
10 // 3     # 3         integer division
10 % 3      # 1         remainder
2 ** 10     # 1024      power