时间序列--差分代码

时间序列差分详解

最新推荐文章于 2025-02-15 18:11:08 发布

翻译最新推荐文章于 2025-02-15 18:11:08 发布 · 3.4k 阅读

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本文详细介绍了使用Python进行时间序列数据差分的方法，包括手动差分和自动差分的实现过程，展示了差分前后的数据变化，适用于处理具有趋势或季节性的数据集。

from pandas import read_csv
from pandas import datetime
from pandas import Series
from matplotlib import pyplot

def parser(x):
	return datetime.strptime('190'+x, '%Y-%m')

# create a differenced series
def difference(dataset, interval=1):
	diff = list()
	for i in range(interval, len(dataset)):
		value = dataset[i] - dataset[i - interval]
		diff.append(value)
	return Series(diff)

series = read_csv('shampoo-sales.csv', header=0, parse_dates=[0], index_col=0, squeeze=True, date_parser=parser)
X = series.values
diff = difference(X)
pyplot.plot(diff)
pyplot.show()

手动差分--默认是剪去上一个

Shampoo Sales Dataset Plot 差分之前

Manually Differenced Shampoo Sales Dataset 差分之后

2.自动差分

from pandas import read_csv
from pandas import datetime
from matplotlib import pyplot

def parser(x):
	return datetime.strptime('190'+x, '%Y-%m')

series = read_csv('shampoo-sales.csv', header=0, parse_dates=[0], index_col=0, squeeze=True, date_parser=parser)
diff = series.diff()
pyplot.plot(diff)
pyplot.show()

还是默认1.可以手动设置

https://machinelearningmastery.com/difference-time-series-dataset-python/