60 sec project time-series

# сделать проект для time-series за 60 секунд

import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from fbprophet import Prophet

RANDOM_STATE = 12345 # fixed random state for various reasons

df = pd.read_csv('taxi.csv')
df.columns = ['ds', 'y']
df['ds'] = pd.to_datetime(df['ds'])
df = df.set_index('ds').resample('H').sum()
df.reset_index(inplace=True)

X,X_test,y,y_test = train_test_split(df, df.y, test_size=0.1, random_state=RANDOM_STATE, shuffle=False)

m = Prophet()
m.fit(X)

future = m.make_future_dataframe(periods = len(X_test), freq='H')
forecast = m.predict(future)

preds = forecast['yhat'][-len(X_test):]
result = mean_squared_error(y_test, preds) ** 0.5
print(f'RMSE: {result}') # RMSE: 48.28