pandas :按时间间隔滚动平均值 [英] Pandas: rolling mean by time interval

问题描述

我是Pandas的新手....我有一堆民意测验数据.我想计算一个滚动平均值，以基于三天的窗口来获取每一天的估算值.据我从此问题中了解到，rolling_ *函数会计算基于指定数量的值而不是特定日期时间范围的窗口.

I'm new to Pandas.... I've got a bunch of polling data; I want to compute a rolling mean to get an estimate for each day based on a three-day window. As I understand from this question, the rolling_* functions compute the window based on a specified number of values, and not a specific datetime range.

是否存在实现此功能的其他功能?还是我坚持写自己的书?

Is there a different function that implements this functionality? Or am I stuck writing my own?

样本输入数据:

polls_subset.tail(20)
Out[185]: 
            favorable  unfavorable  other

enddate                                  
2012-10-25       0.48         0.49   0.03
2012-10-25       0.51         0.48   0.02
2012-10-27       0.51         0.47   0.02
2012-10-26       0.56         0.40   0.04
2012-10-28       0.48         0.49   0.04
2012-10-28       0.46         0.46   0.09
2012-10-28       0.48         0.49   0.03
2012-10-28       0.49         0.48   0.03
2012-10-30       0.53         0.45   0.02
2012-11-01       0.49         0.49   0.03
2012-11-01       0.47         0.47   0.05
2012-11-01       0.51         0.45   0.04
2012-11-03       0.49         0.45   0.06
2012-11-04       0.53         0.39   0.00
2012-11-04       0.47         0.44   0.08
2012-11-04       0.49         0.48   0.03
2012-11-04       0.52         0.46   0.01
2012-11-04       0.50         0.47   0.03
2012-11-05       0.51         0.46   0.02
2012-11-07       0.51         0.41   0.00

每个日期的输出将只有一行.

Output would have only one row for each date.

修改x2:固定错字

推荐答案

同时，添加了时间窗口功能.请参阅下面的链接:

In the meantime, a time-window capability was added. See the link below:

https://github.com/pydata/pandas/pull/13513

In [1]: df = DataFrame({'B': range(5)})

In [2]: df.index = [Timestamp('20130101 09:00:00'),
   ...:             Timestamp('20130101 09:00:02'),
   ...:             Timestamp('20130101 09:00:03'),
   ...:             Timestamp('20130101 09:00:05'),
   ...:             Timestamp('20130101 09:00:06')]

In [3]: df
Out[3]: 
                     B
2013-01-01 09:00:00  0
2013-01-01 09:00:02  1
2013-01-01 09:00:03  2
2013-01-01 09:00:05  3
2013-01-01 09:00:06  4

In [4]: df.rolling(2, min_periods=1).sum()
Out[4]: 
                       B
2013-01-01 09:00:00  0.0
2013-01-01 09:00:02  1.0
2013-01-01 09:00:03  3.0
2013-01-01 09:00:05  5.0
2013-01-01 09:00:06  7.0

In [5]: df.rolling('2s', min_periods=1).sum()
Out[5]: 
                       B
2013-01-01 09:00:00  0.0
2013-01-01 09:00:02  1.0
2013-01-01 09:00:03  3.0
2013-01-01 09:00:05  3.0
2013-01-01 09:00:06  7.0

这篇关于 pandas :按时间间隔滚动平均值的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！