Learn Python from Scratch

Explore Python lists from declaration to access, using square brackets and comma separation. Learn zero-based indexing, slicing, and operations like concatenation and repetition, with multiple data types and nested lists.

Learn to modify lists in Python by replacing elements, appending, inserting, and removing items. Practice indexing from zero and using delete, remove, and insert methods to manage list content.

Learn Python list operations, including sorting in ascending order, reversing, finding minimum and maximum, summing elements, and popping the last item for iteration.

Explore how Python's list sort handles strings with mixed capitalization and numbers, showing uppercase-first and lowercase-first sorting, reverse ordering, and how numbers sort before strings.

Use the extend method to add a second list to your existing list, merging elements and adding multiple items at once.

Explore how zip function pairs elements from two lists into immutable tuples, where first list's order determines content, swapping lists reverses the tuple order, and zip stops at shortest list.

Learn how the Python list index function finds the position of an element in a mixed list of numbers and strings, using zero-based indexing and returning only the first occurrence.

Compute the length of a list in Python with a simple function to determine how many elements it contains, demonstrated by a list of 25 items.

Learn how the list count method works in Python to count occurrences in a mixed list of numbers and strings, like 3 appearing three times and 5 appearing twice.

Learn how to check if a list contains a specific element in Python using the in operator, with examples of true and false results and conditional actions.

Learn how to slice a python list using start, end, and optional step values, using range(50) and zero-based indexing to extract first three, last three, or middle elements.

Explore nested lists in Python to represent matrices for simple linear algebra, using zero-based indexing to access rows and elements.

Use an if statement and truth value testing to check whether a list is empty in Python, then print whether the list is empty or not.

Explore Python dictionaries as key-value mappings within curly braces, learn to create, access, update, and delete items, and convert between keys and values for data science tasks.

Learn how to use the dictionary get method to retrieve values by key and supply a default when keys are missing, preventing errors in automated loops.

Learn how the setdefault method adds missing keys with a default value in a Python dictionary, leaving existing keys unchanged and enabling initialization of entries like adjusted close or high.

Learn how to create and access nested dictionaries in Python, using a stock data example with dates and open, high, low, and close values to build scalable data structures.

explain sets in python as unordered containers of unique, immutable elements, contrasting them with lists, showing creation from various inputs, and using union, intersection, and difference for fast membership checks.

Create and index tuples in Python using parentheses, with slicing. Understand that tuples are immutable, unlike lists, and that sorting returns a list rather than changing the tuple.

Discover how Python lists are homogeneous sequences and tuples are immutable, heterogeneous data structures, using tuples as coordinate sets that stay meaningful while lists change.

Master for loop basics in Python by iterating through lists using range, printing items, building a list of squares with append, and understanding zero indexing and indentation.

Learn how the Python enumerate function adds a counter to an iterable, returning index-value pairs for for loops over lists or dictionaries.

Master list comprehension in Python: build lists from ranges, apply filters, nest loops, unpack results, and transform strings with the title method, including squares and even results.

Use a list comprehension to build a letter list from junk string, then a dictionary comprehension to map each letter to its count.

Learn how to define and use Python functions to reuse code, pass arguments (positional and keyword), provide defaults, handle variadic inputs, and return values like sums, products, and word counts.

Lambdas are anonymous one-expression functions using lambda args: expression. They assign to a variable to compute results like x squared or x*y, useful in data science and the map function.

Learn to sort with Python's sorted and a lambda key to order lists and tuples by last letters or by a specific element, such as the second value in tuples.

Explore how the Python map function applies a function to each list element, using lambda expressions and multiple inputs, and how to capitalize strings with a title function.

Distinguish Python expressions from statements by whether code reduces to a value. See arithmetic and string expressions alongside key statements like def, if, while, and for.