Understanding inplace=True

Question

In the pandas library many times there is an option to change the object inplace such as with the following statement...

df.dropna(axis=\'index\         


        

Answer 1

inplace=True makes the function impure. It changes the original dataframe and returns None. In that case, You breaks the DSL chain. Because most of dataframe functions return a new dataframe, you can use the DSL conveniently. Like

df.sort_values().rename().to_csv()

Function call with inplace=True returns None and DSL chain is broken. For example

df.sort_values(inplace=True).rename().to_csv()

will throw NoneType object has no attribute 'rename'

Something similar with python’s build-in sort and sorted. lst.sort() returns None and sorted(lst) returns a new list.

Generally, do not use inplace=True unless you have specific reason of doing so. When you have to write reassignment code like df = df.sort_values(), try attaching the function call in the DSL chain, e.g.

df = pd.read_csv().sort_values()...