Recursion and While Loops in Python

Recursion in Python

• Recursion is when a function calls itself to solve a problem.
• Useful for problems that can be divided into smaller subproblems like factorial computation, Fibonacci sequences, and tree traversals.
• Recursive functions are a construct where a function can call itself.

Factorial Calculation

• Base case: if n == 0 or n == 1, return 1
• Recursive case: return n * factorial(n - 1)

Stack Diagrams for Recursive Functions

• A stack diagram visualizes how function calls are stored in memory.
• Call stack follows the Last In, First Out (LIFO) principle.
• The last function call must finish before the previous one can continue.
• After factorial(4) completes, the call stack is emptied.

The while Statement in Python

• A while loop executes a block of code repeatedly as long as a condition is true.
• It is used when the number of iterations is unknown in advance.
• The loop runs while the condition is True, or stops if False.

Using break to Exit Early

• The break statement stops the loop immediately.

Using continue to Skip an Iteration

• The continue statement skips the rest of the loop's body for that iteration.

Infinite while Loop

• An infinite loop runs forever until a break statement is executed.
• The loop runs forever until the user types "exit".

while with else

• The else block runs only if the loop is not exited using break.

Two-Dimensional Tables in Python

• A 2D table is a data structure with rows and columns, similar to a spreadsheet or database table.
• You can create and manipulate 2D tables using lists of lists, dictionaries, NumPy arrays, or pandas DataFrames.

Using Lists of Lists (Basic Approach)

• A list of lists is the simplest way to store a table in Python.

Accessing Specific Elements

• Elements can be accessed using their row and column indices.

Using Tabulate for Pretty Tables

• The tabulate library helps format tables in a readable way.
• pip install tabulate

Using Dictionaries (Access by Column Name)

• Dictionaries allow more structured data representation.

Using Pandas for Powerful Table Operations

• Pandas is useful for filtering, sorting, and analyzing table data.
• pip install pandas

Advantages of Pandas

• Pandas is useful for filtering, sorting, and analyzing table data.

Using NumPy for Numerical 2D Tables

• NumPy is ideal for numerical data and matrix operations.
• pip install numpy

Strings

• A Python string is a collection of characters surrounded by single, double, or triple quotes.
• The computer stores strings as a combination of 0s and 1s internally.
• Each character is encoded in ASCII or Unicode.
• Strings can be created using single, double, or triple quotes.
• Strings are immutable, meaning their contents cannot be changed after creation.
• Type of a string variable can be checked using type(str)

Strings Indexing and Splitting

• Indexing of Python strings starts from 0.
• An IndexError occurs when trying to access an index that doesn't exist.

Reassigning Strings

• String objects do not support item assignment.
• Strings are immutable in Python.
• Can be reassigned completely to a new content.

Deleting the String

• Strings are immutable, so characters cannot be deleted or removed from string.
• An entire string can be deleted using the del keyword.

Length of a String

• Use the len() function to find the number of characters in a string.

Traversing a String with a for Loop

• Iterate through each character in a string using a for loop.

String Slices

• Slicing extracts parts of a string using the syntax string[start:end:step].
• Default start is 0, default end is length of string.
• A reversed string can be obtained using a step of -1.

String Comparison

• Strings are compared using relational operators (==, !=, <, >, <=, >=).
• Comparison is based on lexicographical order (dictionary order).

Finding a Substring (find Function)

• find(substring) returns the first index where the substring is found, otherwise -1.