Does Pandas `inplace=True` Modify the Original DataFrame or Return a New One?

In-Depth Understanding of inplace=True in Pandas

In the versatile Pandas library, you'll often encounter the option of inplace modification, such as in the following statement:

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

This raises questions about the consequences of using inplace=True. Let's delve into the technicalities:

What is Returned?

When inplace=True, no explicit object is returned. Instead, the original DataFrame df is modified in place.

Object Handling

• inplace=True: The original df object is overwritten and becomes the modified version. No new object is created.
• inplace=False (default): A new DataFrame object is created, containing the modified data. The original df remains unchanged.

Do All Operations Modify Self?

Yes, when inplace=True, all operations modify the caller itself (the original DataFrame df).

Consequences of inplace=False

When inplace=False, a new object is created immediately, and that new object is returned. This is essentially a copy constructor, essentially assigning the new result to a new variable (df = df.an_operation(inplace=False)).

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