Pandas DataFrame | pop method
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Pandas DataFrame.pop(~) method removes a single column of a DataFrame. The removal is done in-place, that is, the original DataFrame will be modified and no new DataFrame will be created.
The DataFrame.drop(~) method provides a more flexible API. The drop(~) method can do everything the pop(~) can, but with far more flexibility:
you can remove not only columns, but also rows as well.
drop(~)allows for multiple rows/columns removal, whereaspop(~)only does this one at a time.
Parameters
1. item | string
The name of the column you want removed.
Return Value
A Series that holds the removed column values.
Examples
Consider the following DataFrame:
df = pd.DataFrame({"A":[1,2], "B":[3,4]})df
A B0 1 31 2 4
To remove column A:
df.pop("A")
0 11 2Name: A, dtype: int64
Here, the deleted column is returned as a Series.
The removal is performed in-place, that is, the df will be modified directly without the creation of a new DataFrame. To confirm this, we check the state of the df now that we've called pop(~):
df
B0 31 4
Notice how the column A is now gone.
