Pearson Correlation after Normalization
<p>I want to normalize my data and compute a pearson correlation. If I try this without normalization it works. With normalization I get this error message: AttributeError: 'numpy.ndarray' object has no attribute 'corr'
What can I do to solve this problem?</p>

<pre><code>import numpy as np
import pandas as pd


filename_train = 'C:\Users\xxx.xxx\workspace\Dataset\!train_data.csv'
names = ['a', 'b', 'c', 'd', 'e', ...]
df_train = pd.read_csv(filename_train, names=names)

from sklearn.preprocessing import Normalizer
normalizeddf_train = Normalizer().fit_transform(df_train)

#pearson correlation
pd.set_option('display.width', 100)
pd.set_option('precision', 2)
print(normalizeddf_train.corr(method='pearson'))
</code></pre>