Clarity and Maintainability: Code that uses inplace=True can be harder to read and maintain, as the changes to the DataFrame or Series are not immediately visible, leading to possible side effects.
Performance: The perceived performance benefits of inplace=True are often misunderstood. In many cases, pandas creates a copy of the data anyway, so the memory and performance advantages may be negligible.
Chained Operations: Using inplace=True in chained operations can lead to errors since the result of an inplace operation is None.
Avoid using pandas inplace=True parameter.
References https://stackoverflow.com/questions/43893457/understanding-inplace-true-in-pandas https://github.com/pandas-dev/pandas/issues/16529