季节差分python代码

以下是一个使用Python进行季节差分的示例代码：

from numpy import sin, radians
import matplotlib.pyplot as plt

def difference(dataset, interval=1):
    diff = list()
    for i in range(interval, len(dataset)):
        value = dataset\[i\] - dataset\[i - interval\]
        diff.append(value)
    return diff

def inverse_difference(last_ob, value):
    return value + last_ob

data = \[sin(radians(i)) for i in range(360)\] + \[sin(radians(i)) for i in range(360)\]
diff = difference(data, 360)
inverted = \[inverse_difference(data\[i\], diff\[i\]) for i in range(len(diff))\]

fig, axes = plt.subplots(3, 1)
axes\[0\].plot(data)
axes\[0\].title.set_text('data')
axes\[1\].plot(diff)
axes\[1\].title.set_text('diff')
axes\[2\].plot(inverted)
axes\[2\].title.set_text('inverted')

plt.tight_layout()
plt.show()

这段代码首先定义了一个数据集`data`，其中包含了一个周期为360的正弦波。然后使用`difference`函数对数据进行季节差分，将差分后的结果存储在`diff`中。接着使用`inverse_difference`函数将差分后的数据复原，得到`inverted`。最后，使用Matplotlib库将原始数据、差分数据和复原数据绘制在三个子图中展示出来。

希望这个代码能够帮助到你！
#### 引用[.reference_title]
- *1* *3* [时间序列笔记：python中如何用差分消趋势和季节性因素](https://blog.csdn.net/htuhxf/article/details/105354693)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control_2,239^v3^insert_chatgpt"}} ] [.reference_item]
- *2* [SARIMA季节项时间序列分析流程+python代码](https://blog.csdn.net/qq_35167821/article/details/111958925)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control_2,239^v3^insert_chatgpt"}} ] [.reference_item]
[ .reference_list ]