回答问题

我有一个 CSV 文件,其中包含近 5 年的平均温度。使用statsmodels.tsa.seasonal中的seasonal_decompose函数分解后,得到以下结果。确实,结果没有显示任何季节性!但是,我在趋势中看到了清晰的sin!我想知道为什么会这样,我该如何纠正?谢谢你。

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

Answers

看起来您的freq已关闭。

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()