python 季节性分解

Question

我有一个 CSV 文件，其中包含将近 5 年的平均温度。使用 statsmodels.tsa.seasonal 中的 seasonal_decompose 函数分解后，我得到以下结果。事实上，结果不显示任何季节性！但是，我在趋势中看到了明显的sin！我想知道为什么会这样，我该如何纠正它？谢谢。

nresult = seasonal_decompose(nseries, model='additive', freq=1)
nresult.plot()
plt.show()

Answer 1

您的 freq 好像关闭了。

import numpy as np
import pandas as pd
from statsmodels.tsa.seasonal import seasonal_decompose

# Generate some data
np.random.seed(0)
n = 1500
dates = np.array('2005-01-01', dtype=np.datetime64) + np.arange(n)
data = 12*np.sin(2*np.pi*np.arange(n)/365) + np.random.normal(12, 2, 1500)
df = pd.DataFrame({'data': data}, index=dates)

# Reproduce the example in OP
seasonal_decompose(df, model='additive', freq=1).plot()

# Redo the same thing, but with the known frequency
seasonal_decompose(df, model='additive', freq=365).plot()

python 季节性分解

seasonal decompose in python

python

machine-learning

time-series

matplotlib

statsmodels