Learn to code with an Introduction to Python 3

Practice questions solutions for Python basics, including arithmetic with proper parentheses, printing strings and multi-line strings, and using notebooks, variables, concatenation, and user input.

Practice solving Python exercises by collecting user input, using f-strings to format outputs, and mastering string slicing, indexing, and reversing techniques.

Learn the equal equal operator in Python, checking whether two objects are equal and returning true or false for booleans, strings, and numbers.

Practice boolean data type and comparison operators in Python 3: is equal, not equal, greater than, less than, greater than or equal, less than or equal; return true or false.

Learn to use the or operator to combine boolean values, where at least one true yields true, contrasting with and and not operators and common boolean expressions.

Practice using comparison and logical operators in Python 3 to evaluate true or false expressions. Write and test your answers in Python code cells.

Learn to use Python's if and else statements to control code flow, executing alternative blocks when conditions are true or false, with examples using print statements and indentation.

Master multi-branch logic with if, elif, and else in python, printing messages based on final grade thresholds of 90, 80, 70, and 50, ensuring only the first true branch runs.

Learn how if, elif, and else control flow in Python with practical examples, including comparisons, print statements, and f-strings to determine output.

Explore the list data type in Python, create lists with mixed objects, and inspect their types and contents. Practice indexing, slicing, and reversing lists, including empty lists and duplicates.

Change item values in a predefined list by indexing and reassigning at a specific position, demonstrating in‑place modification, appending elements, and handling a nested list.

Explore Python loops, including for loops and while loops, to iterate over iterables such as lists and strings, and understand syntax, indentation, and real-world examples.

Learn to use the range() function to generate number sequences for loops, with default start at zero and end-exclusive behavior, and practice summing 1 to 100 with a running total.

Learn to implement nested for loops in Python to iterate a grid with an outer and inner loop, generating a multiplication table and exploring row and column patterns.

Learn how the break statement in python stops loop execution, with examples using for loops and lists illustrating early termination when a condition is met.

Learn how the while loop works in Python 3 as a condition-driven alternative to the for loop, including true/false evaluation, infinite loop risks, and using break or continue.

Explore Python assignment operators, including plus equals, minus equals, times equals, and divide equals, and learn how these patterns update variables efficiently in loops.

Practice chapter two Python 3 questions, using hints after an initial try, and explore accessing solutions and setting up a Jupiter notebook workflow from GitHub resources.

Learn to determine if a user-entered number is even or odd in Python 3 by using input, convert to int, apply modulo, and print the result.

Print the first and last items of a colors list with list indexing, using zero-based indexing and negative indexing to access the elements.

Explore the fizz buzz problem in Python. Print fizz for multiples of 3, buzz for multiples of 5, and fizz buzz for both, numbers 1 to 100, with proper order.

Learn to compute the intersection of two lists with duplicates removed by building a unique list C, using for each item in A, if in B, and append to C.

Count zeros by iterating through a list of numbers, using a counter initialized to zero, updating it with count = count + 1 or count += 1, then print result.

Generate a random number between one and ten. Use a while loop to keep prompting the user, offering lower or higher hints, until they guess or type stop.

Solve a practice question by asking the user for three integers A, B, C and printing the largest using only comparison and if-else logic, without max.

Learn to generate the Fibonacci sequence in Python by starting with 0 and 1, iterating with a for loop, and appending each new number to build the first thousand terms.

Explore Python built in functions round and sum for rounding numbers and summing lists. Understand how to set decimal places and pass arguments, with guidance to Python documentation.

Learn to define your own functions in Python, follow the dry principle to avoid repetition, and refactor code using function calls, arguments, and simple print examples.

Define local variables inside a function to keep them in a local scope; avoid using the same name for inside and outside variables to prevent confusion.

Learn how the return statement lets a Python function return a value, such as 1+2 equaling 3, and that only one return executes per call, even with multiple options.

Discover how positional arguments pass inputs to Python functions, replacing fixed values with X and Y, and learn how return statements determine the function's output.

Learn how default arguments simplify function calls by providing a default tax rate for the cost before tax, and practice using positional and keyword arguments to compute cost after tax.

Document Python functions with docstrings, using triple-quoted descriptions for parameters and return values. Learn to access this documentation with help and prepare for IDE-based editing.

Learn to write a function that prints a greeting message using two string arguments, name and message, demonstrating positional and keyword arguments, and the role of docstrings.

Define a function that computes the area of a circle by taking the radius as its single argument, returning pi times the radius squared, with pi approximated as 3.14159.

Learn to write a Python function that generates a random list of integers using the random module. Use length, min, and max parameters with for loops, range, and list appends.

Access chapter three practice questions, download the latest Jupiter notebooks, set up your environment, and start solving the minimum of three numbers problem with available hints.

Learn to implement a Python function that sums a list of floats and rounds the result to two decimals using the built-in sum and round.

Practice Chapter 3 questions 5–7, using positional, keyword, and default arguments with the dustoff function, plus understanding local variables and the get_seconds conversion with defaults.

Learn core Python data structures: lists, tuples, dictionaries, and sets, and essential list methods such as sort, count, pop, and remove, plus dictionaries, iterations, and variadic arguments.

Explore common Python list methods beyond sort, including count, pop, and remove, and understand mutability, indexing, and how these methods modify lists in place.

Discover Python list comprehensions by writing compact one-line expressions that build lists from iterables, with examples using range and for loops.

Explore how to build and filter lists with Python list comprehensions, including conditional logic, enumerate for indices, and using zip to combine lists into country stats.

Explore tuples in Python as immutable data structures, defined with parentheses or a trailing comma for single-element tuples, indexed like lists, and support unpacking, including nested forms.

Explore how Python dictionaries map keys to values using curly braces, colons, and key value pairs, then retrieve, store, and list keys and values with practical examples.

Use the in operator to test dictionary keys and fetch ages when present. Loop over names and print ages for existing keys, noting that in checks keys by default.

Explore multiple ways to create dictionaries in Python. Build them from literals, the dict function with tuples, keyword arguments, dict comprehensions, and incremental adding to an empty dict.

Learn how to loop over dictionaries in Python by iterating keys and values with items, and build a growing dictionary from zipped names and ages.

Learn that dictionary keys must be unique, with lookup, adding and updating keys, and looping via items to access keys and values in Python dictionaries.

Learn how the set data type in Python creates an unordered collection of unique items, removing duplicates from lists and supporting add, remove, and membership checks.

Explore variable number of keyword arguments with **kwargs in Python, compare to *args, and learn to access, print, and iterate over kwargs as a dictionary inside a function.

Practice questions for chapter four reinforce Python data structures, including lists, tuples, and dictionaries, with hands-on work in a Jupyter notebook and access to GitHub.

Learn to implement a Python function that removes the first and last items from a list using pop, returning a tuple of the remaining list and the removed numbers.

Learn to work with Python tuples by solving exercises: creating multi-type tuples, applying trailing comma rules for single-element tuples, unpacking into variables, concatenating tuples, and checking membership with a function.

Combine three parallel lists into a list of tuples using zip, producing instrument, color, and price. Compare solutions with and without list comprehensions to reveal practical patterns.

Define a function that takes a list of tuples (name, paid amount) and returns a dictionary totaling each person’s payments across all entries, illustrating tuple handling and dictionary aggregation.

practice 8 guides extracting the unique list of player names and team names, finding the highest and lowest points per game, and computing the mean of those points.

Learn to write a Python function that accepts any number of positional arguments and returns a tuple with the smallest, largest, and average from chapter four practice question nine.

Practice the Python function get car details with required positional arguments year and make, plus keyword arguments, returning a car detail dictionary and signaling type errors when args are missing.

Discover how to use pip to install external Python packages from the Python package index and why you should work inside virtual environments to keep project dependencies isolated.

Create a folder for virtual environments on Mac, set up a Python 3 based environment, install notebook, and run a NumPy example in a notebook.

Set up an interactive development environment with PyCharm community edition, compare it to Jupyter notebooks, and prepare for Python development.

install the PyCharm community edition on mac, download from the official site, and set up the free, open source IDE for Python development.

Set up a PyCharm project on macOS with a dedicated virtual environment to run numpy-based code, organize projects under my notebooks, and import modules into Jupyter notebooks.

Learn to use virtual environments, install packages, and build a small Python project with a pie chart setup to download and open web images on Windows and Mac.

Import the image module and convert image content from a URL into a Pillow image object, using bytes and Pillow to load and work with the image.

Learn to save Pillow images to nested folders using os.path.join, generate unique filenames with enumerate, and collect image info such as width, height, format, and path.

Learn to handle exceptions in Python by using try-except blocks to skip invalid data, convert strings to integers, and distinguish value errors from type errors to keep pipelines running.

Learn to use try and except blocks to handle errors in Python. Raise exceptions with custom messages and explore handling, re-raising, and specific errors like value and key errors.

Explore Python error handling with two examples: validate user input via a while loop and value errors, and handle dictionary operations with multiple exceptions and a finally clause.

Learn to read from and write to files in Python using open, write, append, and context managers, including loops and handling newlines to manage file contents.

Read data from files in Python using with open, f.read, f.readline, and for loops, build line lists, strip newline characters, and briefly explore csv with pandas.

Practice six questions in chapter six to test your understanding of the concepts learned. Solve them independently, review the examples when stuck, and watch for upcoming solution videos.

Explore chapter six practice questions solutions in Python, emphasizing truthy and falsey values, and implement is_empty and add_to_dict with proper mutable-default handling and tests.

Implement read_file to read a local file line by line, strip newlines, and return a list; add error handling for missing files and demonstrate writing data to a file.

Learn how to define Python classes, instantiate objects, and access attributes using the constructor and self. Explore basic object oriented concepts like methods, class methods, class attributes, and simple subclassing.

Add and use methods in a Python class, including an age method using date time to compute birthdate-based age, and a print details method to display information about that person.

Create a bank account class in Python that tracks balance and a transaction history. Learn to implement deposits as instance methods that update state.

Implement a withdrawal method in the bank account class, prevent transactions that would make the balance go negative, and extend the transaction history with time-stamped records for withdrawals.

This lesson demonstrates using a class variable to track all buses in a transit system, updating a shared transit system dictionary whenever buses are added or passengers change.

Explore class inheritance by using a base pet class for cat and dog subclasses in Python, sharing attributes like name, age, color, and owner while customizing behavior.

Discover practical next steps for mastering Python by exploring libraries for your field, from pandas and TensorFlow to Flask; learn tooling like auto-formatting, lint, poetry, and Docker.