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DS-1000 / 926 / Here is my code:

Problem

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Problem:

Here is my code:

count = CountVectorizer(lowercase = False)

vocabulary = count.fit_transform([words])
print(count.get_feature_names())
For example if:

 words = "Hello @friend, this is a good day. #good."
I want it to be separated into this:

['Hello', '@friend', 'this', 'is', 'a', 'good', 'day', '#good']
Currently, this is what it is separated into:

['Hello', 'friend', 'this', 'is', 'a', 'good', 'day']

A:

runnable code
<code>
import numpy as np
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer
words = load_data()
</code>
feature_names = ... # put solution in this variable
BEGIN SOLUTION
<code>

library

Sklearn

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Source and history

upstream_id / Original problem ID
926
task_id
a312465b-a617-5a82-a193-68de0ede7262
task_key
default--test--926
task_revision_id
1
config / split
default / test

Official source

initial import