[pandas] generate dataframe with nan

import pandas as pd
import numpy as np
from sklearn.datasets import make_classification

perc_nan = 0.3
n_samples = 300000
n_features = 5

df = make_classification(n_samples, n_features)
df = pd.DataFrame(df[0], columns = ['DataPoint_{0}'.format(i) for i in range(n_features)])
c = int(round(df.size * perc_nan))
A = df.to_numpy()
A.ravel()[np.random.choice(A.size, c, replace=False)] = np.nan
colname = df.columns
del df
df = pd.DataFrame(A, columns=colname)
del A