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...

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...

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