import datetime
# Plotting data
df.dropna(inplace=True)
df['forecast'] = np.nan
last_date = df.iloc[-1].name
last_unix = last_date.timestamp()
one_day = 86400
next_unix = last_unix + one_day

for i in forecast_prediction:
    next_date = datetime.datetime.fromtimestamp(next_unix)
    next_unix += 86400
    df.loc[next_date] = [np.nan for _ in range(len(df.columns)-1)]+[i]
df['close'].plot(figsize=(15,6), color="green")
df['forecast'].plot(figsize=(15,6), color="orange")
plt.legend(loc=4)
plt.xlabel('Date')
plt.ylabel('Price')
plt.show()