Data para pruebas de SES

Data4SeS.py

data = [
    446.6565,
    454.4733,
    455.663,
    423.6322,
    456.2713,
    440.5881,
    425.3325,
    485.1494,
    506.0482,
    526.792,
    514.2689,
    494.211,
]
index = pd.date_range(start="1996", end="2008", freq="A")
oildata = pd.Series(data, index)

data = [
    17.5534,
    21.86,
    23.8866,
    26.9293,
    26.8885,
    28.8314,
    30.0751,
    30.9535,
    30.1857,
    31.5797,
    32.5776,
    33.4774,
    39.0216,
    41.3864,
    41.5966,
]
index = pd.date_range(start="1990", end="2005", freq="A")
air = pd.Series(data, index)

data = [
    263.9177,
    268.3072,
    260.6626,
    266.6394,
    277.5158,
    283.834,
    290.309,
    292.4742,
    300.8307,
    309.2867,
    318.3311,
    329.3724,
    338.884,
    339.2441,
    328.6006,
    314.2554,
    314.4597,
    321.4138,
    329.7893,
    346.3852,
    352.2979,
    348.3705,
    417.5629,
    417.1236,
    417.7495,
    412.2339,
    411.9468,
    394.6971,
    401.4993,
    408.2705,
    414.2428,
]
index = pd.date_range(start="1970", end="2001", freq="A")
livestock2 = pd.Series(data, index)

data = [407.9979, 403.4608, 413.8249, 428.105, 445.3387, 452.9942, 455.7402]
index = pd.date_range(start="2001", end="2008", freq="A")
livestock3 = pd.Series(data, index)

data = [
    41.7275,
    24.0418,
    32.3281,
    37.3287,
    46.2132,
    29.3463,
    36.4829,
    42.9777,
    48.9015,
    31.1802,
    37.7179,
    40.4202,
    51.2069,
    31.8872,
    40.9783,
    43.7725,
    55.5586,
    33.8509,
    42.0764,
    45.6423,
    59.7668,
    35.1919,
    44.3197,
    47.9137,
]
index = pd.date_range(start="2005", end="2010-Q4", freq="QS-OCT")
aust = pd.Series(data, index)