How do I reduce "Noise" within a model in python?

I am looking to reduce the volatility of a stock prediction model's plot. The idea is to be able to focus on a trend more than an exact guess.

Example Output Here

from matplotlib import pyplot as plt
plt.figure()
plt.plot(y_pred_org)     # real price over time
plt.plot(y_test_t_org)   # predicted price over time
plt.title('Prediction vs Real Stock Price')
plt.ylabel('Price')
plt.xlabel('Days')
plt.legend(['Prediction', 'Real'], loc='upper left')
plt.show()

You have multiple options:

• As @Juan C stated, you can calculate a moving average.
• Or you could select fewer samples and then use spline interpolation to smooth the curve as explained here: https://www.kite.com/python/answers/how-to-plot-a-smooth-line-with-matplotlib-in-python