I Cleaned a Messy CSV File Using Pandas .  Here’s the Exact Process I Follow Every Time.

A repeatable five-step workflow using Python's Pandas library can systematically diagnose and fix common flaws in messy datasets. The process begins with careful data loading and moves into a critical inspection phase to understand the data's health. Key functions like `df.info()` and `df.describe()` are used to diagnose problems by revealing missing values, incorrect data types, and impossible statistical entries. This structured approach also uncovers issues such as inconsistent categorical data, transforming data cleaning from guesswork into a reliable procedure.