DATA WRANGLING: PREPARING DATA FOR ANALYSIS Data wrangling makes sure that the data is accurate, consistent, and ready for analysis. Without proper data wrangling, data analysis can be unreliable and misleading, leading to incorrect conclusions and decisions. In this article, we will look at the most common data handling methods used in various stages of data wrangling. Data wrangling is an essential step in the data science pipeline. Raw data can be messy, incomplete, or inconsistent, making it difficult to analyze and derive insights from. In addition, data may come from multiple sources, such as different databases or file formats, each with its own structure and syntax…