As a Data Engineer, I collect, extract and transform raw data in order to provide clean, reliable and usable data.
📘 Introduction Working with structured data is a core part of any data engineering or analytics workflow. DuckDB, often called the SQLite for analytics, makes it incredibly easy to query local data files—including JSON—without requiring a complex setup. In this tutorial, you’ll learn how to load JSON data...
📘 Introduction In this tutorial, you’ll learn how to load data from a Parquet file into a DuckDB database using Python. DuckDB’s native Parquet support makes it fast and efficient to work with columnar data, making it ideal for analytics, ETL pipelines, and Python data projects. You’ll see...
📘 Introduction In this tutorial, you will learn how to insert data from a CSV file into a DuckDB database using Python. DuckDB is a powerful in-process analytical database that makes working with structured data fast, simple, and efficient—perfect for data projects, notebooks, and local analytics. ✅ Prerequisites Before you begin,...
📘 Introduction DuckDB has quickly become a favorite tool among data engineers and analysts because of its speed, simplicity, and ability to run analytical SQL queries directly within Python. Whether you’re prototyping data pipelines, running local analytics, or managing lightweight data storage, knowing how to insert data into DuckDB is...
📘 Introduction Renaming columns is one of the most common transformations you’ll perform when cleaning or standardizing data in PySpark. Whether you’re aligning tables from different systems, preparing data for machine learning, or simply making column names more readable, updating many column names at once can quickly become tedious...
📘 Introduction One of DuckDB’s most useful features is the ability to query CSV files directly—no need to load them into a database first. This tutorial will guide you through running SQL queries on a CSV file using Python. ✅ Prerequisites Before you begin, make sure you have: 🐍☑️ Installed Python...
📘 Introduction If you enjoy working with pandas but wish you could use clean, powerful SQL at any time, then DuckDB is the right tool for you. With DuckDB, you can query your DataFrames instantly without having to set up a database, run a server, or change your workflow. ✅ Prerequisites Before...
📘Introduction In this blog post, we’ll walk through how to install DuckDB, a fast and lightweight analytical database engine designed for modern data workflows. Whether you're working on data analysis, ETL pipelines, or experimenting with in-process SQL queries, DuckDB is incredibly easy to set up and use....
📘 Introduction In many real-world datasets, the same type of information can appear in more than one column. A customer may provide an email address, a phone number, or a backup contact, and different systems may populate different fields. When you want to select the first available non-null value from several...