How to Clean & Prepare 47,000 Rows of Data Instantly Using Quadratic AI скачать в хорошем качестве

How to Clean & Prepare 47,000 Rows of Data Instantly Using Quadratic AI

In this video, I’ll walk you through a complete, real-world example of cleaning and preparing a messy dataset in Quadratic using AI. We’ll start with NOAA’s raw daily weather observations for Boulder, Colorado — a massive .TXT file with over 47,000 rows — and turn it into a clean, structured table ready for analysis. Along the way, I’ll show you how to: Import and parse raw text data into columns automatically with AI-powered Python Name and organize columns using NOAA’s documentation Identify and remove bad data (like placeholder values of -998°) Drop unnecessary columns to focus on relevant metrics Merge year/month/day into a single date column Visualize results with an AI-generated box plot of monthly temperatures since 1897 Use Quadratic’s AI Research tool to check today’s real temperature and compare it historically By the end, you’ll see how Quadratic can take you from messy, unstructured data to clean visual insights in just a few minutes — no manual Excel wrangling required. 🔗 Try Quadratic for free: https://app.quadratichq.com Chapters 00:00: Intro & Data Source (NOAA Daily Weather Data) 01:24: Importing Raw Text into Quadratic 01:49: Parsing Data with AI-Powered Python 02:36: Naming & Organizing Columns 03:11: Removing Outliers & Cleaning the Table 04:33: Merging Year/Month/Day into a Date Column 05:04: Creating a Monthly Temperature Box Plot 05:26: Comparing Historical & Current Temperatures