import pandas as pd
import numpy as np
from sklearn.preprocessing import Imputer

data = pd.read_csv('/home/josipa/Desktop/coffee_data/coffee_data.csv')
#numerical data imputation
for feature in ['opens', 'closes']:
    print(type(data[[feature]]))
    imputer = Imputer(missing_values=np.nan, strategy='median', axis=0)
    data[[feature]] = data[[feature]].replace('unknown', np.nan)
    print(data[[feature]])
    data[[feature]] = imputer.fit_transform(data[[feature]])
    print(data[[feature]])