from Markov import Markov
weather_today = Markov()
weather_today.load_data(file_path='./weather.csv')
# Demonstrate that your Markov class works by printing the probability that a windy day follows a cloudy day.
print(weather_today.get_prob('cloudy', 'windy')) # This line should print 0.08
# An example use of the Markov class:
print(weather_today.get_prob('sunny', 'cloudy')) # This line should print 0.3
#!/bin/usr/env python3
from Markov import Markov
weather_today = Markov()
weather_today.load_data()
print(weather_today.get_prob('sunny', 'cloudy'))
from Markov import Markov
import numpy as np
weather_today = Markov()
weather_today.load_data(file_path='./weather.csv')
print(weather_today.get_prob('cloudy', 'windy'))
