Python Data Types for Data Science
int, float, complex, bool, str — how precision and type choice affect data analysis.
Numbers in Data Science
Python has two core numeric types: int (arbitrary precision whole numbers) and float (64-bit IEEE 754 decimals). Choosing the right one prevents subtle data bugs.
int is Exact and Unbounded
Python integers never overflow. They grow as large as memory allows, which is great for exact counts and large factorials.
big = 2 ** 200
print(big)
print(type(big)) # <class 'int'>All lessons in this course
- Virtual Environments and pip
- Jupyter Notebooks for Data Science
- Python Data Types for Data Science
- Working with the Python REPL and IPython