import numpy as np
import pandas as pd
from scipy.spatial import distance

avenues_df = pd.DataFrame([0, 153, 307, 524], index=['Park', 'Lexington', '3rd', '2nd'])
streets_df = pd.DataFrame([0, 81, 159, 240, 324], index=['76', '75', '74', '73', '72'])

address = ['Lexington', '74']
taxies = [
    ['Park', '72'],
    ['2nd', '75'],
    ['3rd', '76'],
]

address_vector = np.array([avenues_df.loc[address[0]], streets_df.loc[address[1]]])
taxi_distances = []
for i in taxies:
    x = np.array([avenues_df.loc[i[0]],streets_df.loc[i[1]]])
    taxi_distances.append(distance.cityblock(x, address_vector))

taxi_distances = np.array(taxi_distances)

index = taxi_distances.argmin()
print(taxies[index])