Learn how Python stores and labels data without requiring you to declare a type upfront. This section covers the core data types which are strings, integers, floats, and booleans and how Python infers type automatically at runtime.
Explore how text is handled in Python through string creation, concatenation, formatting with f-strings, and built-in methods like .upper() and slicing while understanding why strings can’t be changed in place.
Explores Python’s core data structures for storing groups of values. Lists are ordered and mutable ideal when data needs to change, allowing items to be added, removed, or updated after creation. Tuples are also ordered but immutable, making them a safer choice for fixed data like coordinates that shouldn’t be modified. Dictionaries store data as key-value pairs rather than by position, enabling fast lookups by key, with the rule that keys must be unique while values can repeat or vary in type. Together, these three structures cover most everyday use cases: use a list when order matters and data changes, a tuple when data should stay fixed, and a dictionary when you need to label and retrieve values by name.
RStudio isn’t just for R it has built-in support for Python through the reticulate package, letting you run Python code, share objects between R and Python, and use Python-based tools (pandas, matplotlib, scikit-learn) without leaving RStudio.