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Given the following text problem statement, write Python code to implement the functionality described below in problem statement
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Problem:
Given the following example:
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Python Code:
import numpy as np
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.decomposition import NMF
from sklearn.pipeline import Pipeline
import pandas as pd
data = load_data()
pipe = Pipeline([
    ("tf_idf", TfidfVectorizer()),
    ("nmf", NMF())
])
pipe.fit_transform(data.test)
tf_idf_out = pipe.named_steps['tf_idf'].transform(data.test)
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