I’ve spent years wrangling data in Python, and one of the most common things I do is check the size of my dataset. Whether I am loading a CSV of US Census data or analyzing California housing prices, I always need to know how many records I am dealing with. Knowing the number of rows … Read more >>
During my years working with large datasets in Python, I’ve found that selecting specific rows is one of the most frequent tasks you’ll perform. Whether you are cleaning financial records or analyzing census data, knowing how to grab a row by its index is a fundamental skill. In this tutorial, I will show you exactly … Read more >>
As a seasoned Python developer, I have spent countless hours wrangling data for various US-based fintech and retail firms. One of the most frequent tasks I encounter is the need to pull a specific column out of a Pandas DataFrame and turn it into a standard Python list. Whether I am preparing data for a … Read more >>
Dealing with date information in Python can be a bit like navigating traffic in New York City—it’s hectic until you know the right lanes to be in. In my years of developing data pipelines, I’ve found that dates rarely arrive in the format you actually need for analysis. Usually, they show up as simple strings, … Read more >>
Recently, during a TypeScript webinar, someone asked if TypeScript is a frontend or backend tool. In fact, this is a common question asked by many developers: Is TypeScript better suited for frontend or backend development? The answer is both! In this tutorial, I will explain the capabilities of TypeScript for both frontend and backend development. … Read more >>
Working with Python for over years, I often find myself needing to transform data structures for reports or UI displays. One task that comes up frequently is converting a tuple, that immutable sequence we all love, into a single, readable string. In this guide, I will show you exactly how to handle this conversion using … Read more >>
In my Python development journey, I’ve often encountered situations where data arrives in a format that isn’t quite ready for calculations. One common scenario is receiving a single-element tuple from a database or an API when you actually need an integer to perform math. It can be a bit frustrating when your code throws a … Read more >>
Python backends, I’ve often had to ship data from a script to a web front-end or a REST API. Usually, this means taking a Python tuple, perhaps something you fetched from a SQL database, and turning it into a JSON string. While it seems like a simple task, there are a few nuances regarding data … Read more >>
When I first started building data pipelines for financial firms in New York, I realized how often “numbers” aren’t what they seem. One minute, you are processing a stock price, and the next, a floating-point error turns a clean 100 into 100.00000004. In Python, distinguishing between a float and a true integer is a task … Read more >>
I’ve often found myself handling data in tuples, especially when fetching records from a database or reading static configuration files. While tuples are great for integrity because they are immutable, there comes a point where you need the key-value lookup speed of a dictionary to make your code efficient. In this tutorial, I will show … Read more >>
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