the inplace parameter in pandas how it works?
Python’s argument passing model is neither “Pass by Value” nor “Pass by Reference” but it is “Pass by Object Reference”

When you pass a dictionary to a function and modify that dictionary inside the function, the changes will reflect on the dictionary everywhere.
However, here we are dealing with something even less ambiguous. When passing inplace=True to a method call on a pandas object (be it a Series or a DataFrame), we are simply saying: change the current object instead of getting me a new one. Method calls can modify variables of the instances on which they were called - this is independent of whether a language is "call by value" or "call by reference". The only case in which this would get tricky is if a language only had constants (think val) and no variables (think var) - think purely functional languages. Then, it's true - you can only return new objects and can't modify any old ones. In practice, though, even in purest of languages you can find ways to update records in-place.
in pandas the inplace parameter make modification on the reference but I know in python data are sent by value not by reference i want to know how this is implemented or how this work