Data Wrangling in 6 Steps: A Comprehensive Guide

Data wrangling, or data cleaning, is a crucial process in data analysis that involves six key steps. First, data collection gathers raw data from various sources. Second, data exploration identifies data types, structures, and anomalies. Third, data cleaning removes errors, duplicates, and irrelevant information. Fourth, data transformation standardizes and formats the data for consistency. Fifth, data integration combines data from different sources into a unified format.