Basics of Python Programming for Beginners (with Jupyter)

Variables are containers that store values in Python, such as a = 5, can be printed and reassigned. Python uses dynamic typing, and names must avoid spaces; underscores are allowed.

Explore Python data types such as strings, integers, floats, complex numbers, and booleans, and learn how to use tuples, ranges, dictionaries, sets, and frozen sets.

Explore the numbers type in Python, including integers and floats, with hands-on examples. Learn to round values and cast between int, float, and string, and print the results.

Explore Python strings and string functions in a Jupyter notebook, using index, count, and split to manipulate text for automation and file handling.

Learn boolean logic in Python by evaluating true and false, using comparisons like greater than and equals, applying not, and building if conditions in Jupyter.

Explore Python operators, including addition, subtraction, multiplication, division, modulus, and exponent, and learn to combine them with variables and parentheses to perform arithmetic and print results.

Explore how Python lists store mixed data types, index and slice items, modify values, loop through elements, search with if statements, and extend lists with append, remove, and concatenation.

Compare Python tuples to lists by highlighting immutability, using parentheses instead of square brackets, and demonstrating indexing to access items.

Create sets with curly brackets, note they are unordered and unindexed so you cannot reference a middle value, loop with for x in set one, and add items with set.add('bread').

Explore dictionaries in Python, an ordered data collection that stores different data types and is indexed by keys. Learn to create, update, and check keys, and add entries like color.

Explore Python conditional logic with if, else, and elif, including nested conditions, boolean checks, and string comparisons, then see how default else handles unmatched cases.

Explore how while and for loops control Python code, using conditions, indentation, and break to exit loops; see examples that print and iterate over a list.

Define and call functions in Python to encapsulate reusable logic, pass parameters, and produce dynamic outputs, reducing clutter and enabling repeated execution with simple calls.

Learn how to work with JSON in Python using the json module, including loading, accessing fields, and writing dictionaries to json strings or files.

Explore how try and except blocks in Python let you run code safely, catch errors to prevent crashes, and continue execution, including handling timeouts.

Learn how to collect user data in Python with the input function, using prompts that pause execution, and run these scripts in Jupyter notebooks or from the command prompt.

Learn to use data frames with pandas in a jupyter notebook, installing pandas with pip, and creating and printing seeded data frames. Expand to add rows and columns for manipulation.