It performs more quickly than other comparable data analysis languages like R and MATLAB. It is able to gracefully handle very high volumes of data transformation, slicing, dicing, and visualisation thanks to its strong memory management capabilities, particularly garbage collection. The most significant feature of Python is its enormous library collection of tools for specialised analysis. For instance, the scientific computing programme NumPy uses an array that consumes substantially less memory than a traditional Python list. And the quantity of these bundles keeps increasing. Python includes packages that allow you to use code written in languages like Java or C directly. When it gives a chance, this aids in improving the code performance by utilising existing code of other languages.