Data Analytics With Python

Type Hinting in Python Functions Type Hinting in Python Functions As you start to write more complex Python code, you might have come across function definitions that include syntax like : str or -> int . These are examples of type hinting, a feature introduced in Python 3.5 as part of PEP 484. Type hints make your code more explicit and easier to understand. They can also help with debugging and allow some IDEs and tools to provide better autocompletion and linting. 1. Basic Type Hints The most basic type hints are straightforward. Just add a colon and the type after the parameter name in the function definition. You can do the same for the return type by adding -> type before the final colon. Here's an example: def greet(name: str) -> str: return f'Hello, {name}!' In this example, we're saying that the name parameter should be a string, and the function will return a stri...

An Diving Deeper into Function Arguments 5. Diving Deeper into Function Arguments There are several ways to feed arguments into a Python function, allowing for a lot of flexibility. Let's go through some of the most important ones: 5.1 Positional Arguments Positional arguments are the most basic type of argument. They're called "positional" because the order in which you pass them matters. For instance: def greet(name, greeting): print(f'{greeting}, {name}!') greet('Alice', 'Hello') # prints: Hello, Alice! In this example, 'Alice' is the first argument and 'Hello' is the second argument. Their order matches the order of parameters in the function declaration. 5.2 Keyword Arguments Keyword arguments are identified by the keyword used before them when calling the function. You can use keyword arguments to make your code more readable or to specify default values for parameters: def greet...

An Introduction to Python Functions and Data Analysis with Pandas An Introduction to Python Functions An Introduction to Python Functions Functions are one of the most fundamental aspects of programming in Python. A function is a self-contained module of code that accomplishes a specific task. Functions are reusable and can significantly improve the modularity and efficiency of your code. Let's break down the major aspects of function design in Python. 1. Function Declaration The first part of creating a function is the declaration. Here's what a basic function declaration looks like in Python: def function_name(): # code here The keyword def tells Python that you're defining a function. This is followed by the function name and a pair of parentheses. The code for the function goes after the colon, indented under the function name. 2. Parameters and Arguments Functions can...

Comparing Relationships in Dataframes with Python Comparing Relationships in Dataframes with Python If you work with data, chances are you will need to compare different datasets to each other. One specific task could be to compare the relationships between categorical variables in different datasets. In this blog post, we will use Python and its powerful libraries such as Pandas and NumPy to accomplish this task. What are we trying to achieve? Imagine you have two datasets, a 'base' and a 'comparison' dataset. Each dataset has the same categorical variables, for example 'degree_type' and 'acad_degree'. You want to check if the relationship between these variables is the same in both datasets. For instance, if in the base dataset 'AAS' always corresponds to 'Associates', you want to ensure the same applies to the comparison dataset. How do we do it? We start by creating a function, let's cal...