When do I use inplace function in pandas?

Data Science, AI and ML
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#1

Inplace Function in Pandas

#2

inplace=True is used depending on if you want to make changes to the original df or not. will drop values and make changes to df. Something similar to python’s build-in sort and sorted

#3

Yes, in Pandas we have many functions has the parameter inplace but by default it is assigned to False.

So, when you do df.dropna(axis='index', how='all', inplace=False) it thinks that you do not want to change the orignial DataFrame, therefore it instead creates a new copy for you with the required changes.

But, when you change the inplace parameter to True

Then it is equivalent to explicitly say that I do not want a new copy of the DataFrame instead do the changes on the given DataFrame

This forces the Python interpreter to not to create a new DataFrame

But you can also avoid using the inplace parameter by reassigning the result to the orignal DataFrame

df = df.dropna(axis='index', how='all')