Most data scientists and data analysts would agree with the assertion that data scientists and data analysts spend 80% of their time cleaning and transforming data – or simply put, performing data wrangling. Because it’s imperative to transform your data into a tidy form before using it in your data science project.
Our objective is to highlight some of the primary data manipulation techniques within PySpark