python中的季节性分解 [英] seasonal decompose in python

问题描述

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，我得到了以下结果.确实，结果没有显示任何季节性！但是，我在趋势中看到了明显的 sin ！我想知道为什么会这样，我该如何纠正呢?谢谢.

I have a CSV file that contains the average temperature over almost 5 years. After decomposition using seasonal_decompose function from statsmodels.tsa.seasonal, I got the following results. Indeed, the results do not show any seasonal! However, I see a clear sin in the trend! I am wondering why is that and how can I correct it? Thank you.

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

推荐答案

您的 freq 似乎已关闭.

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()

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