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DS-1000 / 878 / Given a list of variant length features:

Problem

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Problem:

Given a list of variant length features:

features = [
    ['f1', 'f2', 'f3'],
    ['f2', 'f4', 'f5', 'f6'],
    ['f1', 'f2']
]
where each sample has variant number of features and the feature dtype is str and already one hot.

In order to use feature selection utilities of sklearn, I have to convert the features to a 2D-array which looks like:

    f1  f2  f3  f4  f5  f6
s1   1   1   1   0   0   0
s2   0   1   0   1   1   1
s3   1   1   0   0   0   0
How could I achieve it via sklearn or numpy?

A:

<code>
import pandas as pd
import numpy as np
import sklearn
features = load_data()
def solve(features):
    # return the solution in this function
    # new_features = solve(features)
    ### BEGIN SOLUTION

library

Sklearn

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Source and history

upstream_id / Original problem ID
878
task_id
a5470f70-34d5-5880-b85f-cda67cecabbc
task_key
default--test--878
task_revision_id
1
config / split
default / test

Official source

initial import