pandas python中的聚合时间序列
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Aggregate time series in python
提问by PK10
How do we aggregate the time series by hour or minutely granularity? If I have a time series like the following then I want the values to be aggregated by hour. Does pandas support it or is there a nifty way to do it in python?
我们如何按小时或分钟的粒度聚合时间序列？如果我有一个如下所示的时间序列，那么我希望按小时聚合这些值。pandas 是否支持它，或者在 python 中是否有一种很好的方法来做到这一点？
timestamp, value
2012-04-30T22:25:31+00:00, 1
2012-04-30T22:25:43+00:00, 1
2012-04-30T22:29:04+00:00, 2
2012-04-30T22:35:09+00:00, 4
2012-04-30T22:39:28+00:00, 1
2012-04-30T22:47:54+00:00, 8
2012-04-30T22:50:49+00:00, 9
2012-04-30T22:51:57+00:00, 1
2012-04-30T22:54:50+00:00, 1
2012-04-30T22:57:22+00:00, 0
2012-04-30T22:58:38+00:00, 7
2012-04-30T23:05:21+00:00, 1
2012-04-30T23:08:56+00:00, 1
I also tried to make sure I have the correct data types in my data frame by calling:
我还尝试通过调用来确保我的数据框中有正确的数据类型：
print data_frame.dtypes
and I get the following as out put
我得到以下内容
ts datetime64[ns]
val int64
When I call group by on the data frame
当我在数据框上调用 group by 时
grouped = data_frame.groupby(lambda x: x.minute)
I get the following error:
我收到以下错误：
grouped = data_frame.groupby(lambda x: x.minute)
AttributeError: 'int' object has no attribute 'minute'
回答by grechut
http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.resample.htmlDataFrame.resample method. You can specify here way of aggregation, in your case sum.
http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.resample.htmlDataFrame.resample 方法。您可以在此处指定聚合方式，在您的情况下sum。
data_frame.resample("1Min", how="sum")
http://pandas.pydata.org/pandas-docs/dev/timeseries.html#up-and-downsampling
http://pandas.pydata.org/pandas-docs/dev/timeseries.html#up-and-downsampling
