1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
|
import pandas as pd
import matplotlib.pyplot as plt
import pickle
from decompressor import decompress_arima
decompress_arima()
with open('arima.pkl', 'rb') as pkl:
n_periods = 30
fc, confint = pickle.load(pkl).predict(
n_periods=n_periods, return_conf_int=True)
n_years = ['1960-12-02', '1960-12-03', '1960-12-04', '1960-12-05', '1960-12-06', '1960-12-07', '1960-12-08', '1960-12-09', '1960-12-10', '1960-12-11', '1960-12-12', '1960-12-13', '1960-12-14', '1960-12-15', '1960-12-16',
'1960-12-17', '1960-12-18', '1960-12-19', '1960-12-20', '1960-12-21', '1960-12-22', '1960-12-23', '1960-12-24', '1960-12-25', '1960-12-26', '1960-12-27', '1960-12-28', '1960-12-29', '1960-12-30', '1960-12-31']
city_ids = ["1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031", "1031"]
fc_ind = pd.Series(n_years, city_ids)
fc_series = pd.Series(fc, index=fc_ind)
lower_series = pd.Series(confint[:, 0], index=fc_ind)
upper_series = pd.Series(confint[:, 1], index=fc_ind)
plt.figure(figsize=(12, 5))
plt.plot(fc_series, color="darkred")
plt.fill_between(lower_series.index,
lower_series,
upper_series,
color="k", alpha=.35)
plt.show()
|
