Data cleaning, also known as data cleansing or data wrangling, involves the process of detecting and correcting (or removing) corrupt or inaccurate records from a dataset. In the context of Nanotechnology, data cleaning is crucial due to the highly precise and intricate nature of the data involved. This ensures the reliability and accuracy of the data used for research and development, simulations, and material characterization.
