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DS-1000 / 824 / I would like to break down a pandas column, which is the last column, consisting…

Problem

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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
 C      33     [Apple, Orange, Banana]
 A      2.5    [Apple, Grape]
 B      42     [Banana]
I would like to convert this to:

df

Col1   Col2   Apple   Orange   Banana   Grape
 C      33     1        1        1       0
 A      2.5    1        0        0       1
 B      42     0        0        1       0
Similarly, if the original df has four columns, then should do the operation to the 4th one.
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
824
task_id
8f5bab76-5dab-5c94-a167-7875bc69a960
task_key
default--test--824
task_revision_id
1
config / split
default / test

Official source

initial import