我有这个带有日期时间索引的数据框:
ts_log:
date price_per_unit
2013-04-04 12.762369
2013-04-05 12.777120
2013-04-06 12.773146
2013-04-07 12.780774
2013-04-08 12.786835
我有这段代码用于分解
from statsmodels.tsa.seasonal import seasonal_decompose
decomposition = seasonal_decompose(ts_log)
trend = decomposition.trend
seasonal = decomposition.seasonal
residual = decomposition.resid
但在行 decomposition = seasonal_decompose(ts_log)
我收到这个错误:
ValueError: You must specify a freq or x must be a pandas object with a timeseries index
问题出在哪里?
最佳答案
经过一番搜索后,我发现 [here][1] 我必须将 values
添加到 ts_log.price
分解 = seasonal_decompose(ts_log.price.values, freq=30)
编辑评论。只需添加 freq=30
就足够了!
关于python - python statsmodels.tsa.seasonal 中的值错误,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/40794282/