pandas python statsmodels.tsa.seasonal中的值错误
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value error in python statsmodels.tsa.seasonal
提问by reza_v
I have this dataframe with date time indices:
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
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
I have this piece of code for decomposition`
我有这段代码用于decomposition`
from statsmodels.tsa.seasonal import seasonal_decompose
decomposition = seasonal_decompose(ts_log)
trend = decomposition.trend
seasonal = decomposition.seasonal
residual = decomposition.resid
but in the line decomposition = seasonal_decompose(ts_log)i got this error :
但在这一行decomposition = seasonal_decompose(ts_log)我得到了这个错误：
ValueError: You must specify a freq or x must be a pandas object with a timeseries index
Where is the problem?
问题出在哪儿？
采纳答案by reza_v
After some searching i found [here][1] that, i have to add valuesto ts_log.price
经过一番搜索，我发现 [here][1] 那个，我必须添加values到ts_log.price
decomposition = seasonal_decompose(ts_log.price.values, freq=30)
decomposition = seasonal_decompose(ts_log.price.values, freq=30)
Editas to comments. Adding just freq=30is enough!
编辑评论。添加freq=30就够了！
回答by Fares Sayah
You can avoid this error by:
您可以通过以下方式避免此错误：
ts_log = ts_log.asfreq('d')
this may generate some missing values:
这可能会产生一些缺失值：
ts_log = ts_log.fillna(method='bfill').fillna(method='ffill')
