Experiments to try: 1  Turn on show energy. 2  Reduce elasticity (bounciness) to less than 1, for example 0.9. 3  Make a small gap between each ball by increasing the offset to above zero, for example 0.1. 4  Try using simultaneous collision handling method. 5  Turn on show forces to see the contact forces and collision impacts.
Data cleaning involves the detection and removal (or correction) of errors and inconsistencies in a data set or database due to the corruption or inaccurate entry of the data. Incomplete, inaccurate or irrelevant data is identified and then either replaced, modified or deleted.
Incorrect or inconsistent data can create a number of problems which lead to the drawing of false conclusions. Therefore data cleaning can be an important element in some data analysis situations. However, data cleaning is not without risks and problems including the loss of important information or valid data. There are a large variety of tools available that can be used to support data cleaning.