Predictions 2

def ratios(x, y, z):

predictions = list(df['Predictions'])[:-1]

price = list(df['Price'])[:-1]

corrects = []

for i in range(len(predictions)-y, len(predictions)-z):

if (predictions[i] * (1.0 + (x/100.0))) > price[i] > (predictions[i] * (1.0 - (x/100.0))):

corrects.append(1.0)

else:

corrects.append(0.0)

return np.average(corrects) * 100

def mape(y_true, y_pred):

y_true, y_pred = np.array(y_true), np.array(y_pred)

return np.mean(np.abs((y_true - y_pred) / y_true)) * 100