facebook prophet.py

m = Prophet()
m.fit(ph_df)
# Create Future dates
future_prices = m.make_future_dataframe(periods=365)

# Predict Prices
forecast = m.predict(future_prices)

import matplotlib.dates as mdates

# Dates
starting_date = dt.datetime(2018, 4, 7)
starting_date1 = mdates.date2num(starting_date)
trend_date = dt.datetime(2018, 6, 7)
trend_date1 = mdates.date2num(trend_date)

pointing_arrow = dt.datetime(2018, 2, 18)
pointing_arrow1 = mdates.date2num(pointing_arrow)

# Learn more Prophet tomorrow and plot the forecast for amazon.
fig = m.plot(forecast)
ax1 = fig.add_subplot(111)
ax1.set_title("Amazon Stock Price Forecast", fontsize=16)
ax1.set_xlabel("Date", fontsize=12)
ax1.set_ylabel("Close Price", fontsize=12)

# Forecast initialization arrow
ax1.annotate('Forecast \n Initialization', xy=(pointing_arrow1, 1350), xytext=(starting_date1,1700),
            arrowprops=dict(facecolor='#ff7f50', shrink=0.1),
            )

# Trend emphasis arrow
ax1.annotate('Upward Trend', xy=(trend_date1, 1225), xytext=(trend_date1,950),
            arrowprops=dict(facecolor='#6cff6c', shrink=0.1),
            )

ax1.axhline(y=1260, color='b', linestyle='-')

plt.show()

Hi Aman,

thank you for sharing your work! I have a question though: I'm trying to replicate your code but when I try to create the forecasts (forecast=m.predict(future_prices)), an error appears saying that the model has not been fit. Do you know how I should resolve it?

Kind regards,
Benedetta Francesconi