import sys; print('python', sys.version)
import numpy as np
import pandas as pd
from sklearn.impute import SimpleImputer

si = SimpleImputer(strategy='most_frequent')

n = 1_000_000
df = pd.DataFrame(
    dict(a_string_column = np.random.choice(['a', 'b'], n),
         a_numeric_column = np.random.choice([1, 2], n))
)

print('np.unique:')
%time np.unique(df.a_string_column, return_counts=True)

print('\nsimple imputer numeric:')
%time si.fit(df[['a_numeric_column']])

print('\nsimple imputer string/object:')
%time si.fit(df[['a_string_column']])