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DS-1000 / 823 / I would like to break down a pandas column, which is the last column, consisting…

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Problem:

I would like to break down a pandas column, which is the last column, consisting of a list of elements into as many columns as there are unique elements i.e. one-hot-encode them (with value 1 representing a given element existing in a row and 0 in the case of absence).

For example, taking dataframe df

Col1   Col2    Col3          Col4
 C      33      11       [Apple, Orange, Banana]
 A      2.5     4.5      [Apple, Grape]
 B      42      14       [Banana]
 D      666     1919810  [Suica, Orange]
I would like to convert this to:

df

Col1 Col2     Col3  Apple  Banana  Grape  Orange  Suica
C   33       11      1       1      0       1      0
A  2.5      4.5      1       0      1       0      0
B   42       14      0       1      0       0      0
D  666  1919810      0       0      0       1      1
How can I use pandas/sklearn to achieve this?

A:

<code>
import pandas as pd
import numpy as np
import sklearn
df = load_data()
</code>
df_out = ... # put solution in this variable
BEGIN SOLUTION
<code>

library

Sklearn

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Source and history

upstream_id / Original problem ID
823
task_id
922bdda0-6ea2-5fc3-925b-8e1cfd46dcd5
task_key
default--test--823
task_revision_id
1
config / split
default / test

Official source

initial import