Tag: Python

When working with large datasets in PySpark, grouping data and applying aggregations is a common task. In this post, we’ll explore how to group data by a specific column and use aliases for the resulting aggregated columns to improve readability and clarity. Problem Statement Consider the following sample dataset: IdCompra Fecha IdProducto Cantidad Precio IdProveedor

When working with datetime objects in Python, you may encounter the error: This error occurs when comparing two datetime objects where one contains timezone information (offset-aware) and the other does not (offset-naive). To resolve this, you must ensure both datetime objects are either offset-aware or offset-naive before making the comparison. Making a Datetime Offset-Aware in

Accessing content inside an iFrame can be tricky, especially when the content is loaded dynamically. In this blog post, we’ll walk through an example of how to navigate an iFrame, click on an interactive tab, and save the loaded content to a file using Selenium in Python. This example is particularly useful when dealing with

Python’s modular design allows developers to break their code into smaller, reusable components. However, import errors can often disrupt the flow, especially in complex projects. In this post, we’ll discuss a real-world example of resolving an import error while working on a Python project. The Scenario The project’s directory structure is as follows: The file

When working with web scraping, you often encounter scenarios where HTML content is nested or contains encoded data within JavaScript attributes. This post walks through parsing player statistics from a complex HTML table, utilizing Python and the BeautifulSoup library to streamline the extraction of JSON data hidden in JavaScript functions. Project Overview We have an

Investors frequently face the challenge of assessing whether an asset’s return justifies its risk. This is where the Sharpe Ratio becomes invaluable, providing a measure that accounts for both returns and risk in a single metric. In this post, we’ll go over how to calculate and interpret the Sharpe Ratio in Python, using real stock

Introduction In this post, we’ll explore how to use Python programming to compare the performance of two investment firms, Invesco and Blackstone. Invesco is known for its focus on public asset management, while Blackstone specializes in private equity, actively acquiring and managing companies. We’ll examine some key performance and risk metrics to understand how these

Python strives to be simple and clear, so some operations are implemented as built-in functions, while others are object-specific methods. This distinction arises from the way Python handles different types of objects. Built-in Functions len() is a built-in function that works with many different types, including strings, lists, tuples, dictionaries, and more. This allows for

Logging is a vital part of any application, offering insights into the application’s flow, performance, and error handling. In many scenarios, you may want to log messages both to the console and a file, but with different levels of detail. For example, you might display INFO and WARNING messages in the console while logging more

In this blog post, I’ll show you how to download a JSON file from the U.S. Securities and Exchange Commission (SEC) website using Python. The file contains company tickers, which can be useful for various financial analyses and applications. Steps to Download the File Here’s a complete Python script that handles the download: Run the