按多个条件对时间序列中的事件类型进行计数

本文介绍了按多个条件对时间序列中的事件类型进行计数的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我希望在一个时间序列中计算组内每个子组的计数/总和。

I'm hoping to calculate count/sum of each subgroup within groups over a time series.

我的问题与这个问题非常相似 随时间序列滚动事件数 。

My question is very similar to this question Rolling Count of Events Over Time Series.

抱歉，我一直在寻找方法来计算时间范围内（第1组的当前日期和前一个N（例如4） ） 天）。我想对组2中的每个子类型重复此过程，即组2是一个较大的组，可能/可能不包含组1中的所有类别。

Apologies for cross-posting, I have been looking for ways to count events for each category in group 1 within a time range (Present date and the previous N (say 4) days). I want to repeat this process for every subtype in group 2, i.e. Group 2 is a larger group that may/may not contains all the categories within Group 1.

，如果我们有一个如下所示的数据框

For example, if we have a data frame that looks like the following

dates = as.Date(c("2011-10-09", "2011-10-15", "2011-10-16", "2011-10-18", "2011-10-21", "2011-10-22", "2011-10-24")) group1=c("A", "A", "A", "A", "L", "L", "A") group2=c("I", "I", "I", "I", "I", "I", "II") df1 <- data.frame(dates, group1, group2)

寻找与此类似的输出。 （编辑）最终，我想散布数据集，以便将组1中的类别放在单独的列中，并根据日期和组2排列行。如何确保组1类别的计数结转到新行（并满足上述时间范围）？

And I'm looking for output similar to this. (Edited) Eventually, I want to spread my dataset so that I will have categories in Group 1 in separate columns, and arrange rows according to dates and Group 2. How can I make sure the count of Group 1 categories is carried forward to the new row (and satisfy the timeframe stated above)?

dates group1 group2 count (A) count (L) 1 2011-10-09 A I 1 0 2 2011-10-15 A I 1 0 3 2011-10-16 A I 2 0 4 2011-10-18 A I 3 0 5 2011-10-21 L I 0 1 6 2011-10-22 L I 0 2 7 2011-10-24 A II 1 0

谢谢！

推荐答案

如果要显示组1和组2中所有事件的发生次数在活动开始前的4天里，您可以只 group_by 两个活动组，然后计数（使用 sapply 分别访问每个日期）。

If you are trying to show the count of all occurrences of events from group1 and group2 in the 4 days leading up to an event, you can just group_by the two event groups and then count (using sapply to access each date separately).

df1 %>% group_by(group1, group2) %>% mutate(count = sapply(dates , function(x){ sum(dates <= x & dates > (x-4)) }))

返回值：

dates group1 group2 count <date> <fctr> <fctr> <int> 1 2011-10-09 A I 1 2 2011-10-15 A I 1 3 2011-10-16 A I 2 4 2011-10-18 A I 3 5 2011-10-21 L I 1 6 2011-10-22 L I 2 7 2011-10-24 A II 1