R 如何聚合每分钟的推文

我做了一些有趣的推特挖掘。我使用twitters流APi，在足球比赛之前、期间和之后录制了这些推文。现在我想做一个ggplot2图表，显示足球比赛中推特的频率

在原始数据框中，我为每条tweet添加了一行和一个变量“created_at”，其中包含如下日期：

Sat Dec 13:04:34+0000 2014

然后我改变了这样的时间格式

---

tweets$format给定示例数据集：

tweets.df<-as.data.frame(cbind(c("2014-12-13 14:04:34 CET","2014-12-13 14:04:37 CET","2014-12-13 14:04:45 CET","2014-12-13 14:05:23 CET","2014-12-13 14:05:53 CET","2014-12-13 14:05:58 CET","2014-12-13 14:06:33 CET","2014-12-13 14:06:38 CET","2014-12-13 14:06:59 CET","2014-12-13 14:08:16 CET","2014-12-13 14:09:12 CET","2014-12-13 14:09:34 CET","2014-12-13 14:10:05 CET","2014-12-13 14:10:16 CET","2014-12-13 14:10:17 CET","2014-12-13 14:11:13 CET","2014-12-13 14:11:16 CET","2014-12-13 14:12:01 CET","2014-12-13 14:12:30 CET","2014-12-13 14:14:02 CET","2014-12-13 14:14:02 CET","2014-12-13 14:14:02 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:05 CET","2014-12-13 14:14:05 CET","2014-12-13 14:14:07 CET","2014-12-13 14:14:07 CET","2014-12-13 14:14:08 CET","2014-12-13 14:14:08 CET","2014-12-13 14:14:08 CET","2014-12-13 14:14:08 CET","2014-12-13 14:14:11 CET","2014-12-13 14:14:11 CET","2014-12-13 14:14:22 CET","2014-12-13 14:14:48 CET","2014-12-13 14:15:02 CET","2014-12-13 14:15:03 CET","2014-12-13 14:16:20 CET","2014-12-13 14:16:26 CET","2014-12-13 14:17:14 CET","2014-12-13 14:17:24 CET","2014-12-13 14:17:45 CET","2014-12-13 14:17:49 CET","2014-12-13 14:18:05 CET","2014-12-13 14:18:30 CET","2014-12-13 14:19:38 CET"),1), stringsAsFactors=FALSE)
colnames(tweets.df)<-c("time","freq")

然后，您希望使用此方法拆分数据帧，并对子集上的列

freq

求和：

tweets.mins <- split(tweets.df, by.mins)
sapply(tweets.mins,function(x)sum(as.integer(x$freq)))
2014-12-13 14:04:00 2014-12-13 14:05:00 2014-12-13 14:06:00 2014-12-13 14:07:00 2014-12-13 14:08:00 
                  3                   3                   3                   0                   1 
2014-12-13 14:09:00 2014-12-13 14:10:00 2014-12-13 14:11:00 2014-12-13 14:12:00 2014-12-13 14:13:00 
                  2                   3                   2                   2                   0 
2014-12-13 14:14:00 2014-12-13 14:15:00 2014-12-13 14:16:00 2014-12-13 14:17:00 2014-12-13 14:18:00 
                 20                   2                   2                   4                   2 
2014-12-13 14:19:00 
                  1 

---

tweets.mins如果您使用示例输入进行分析，这将更容易回答。我有一个解决方案，但我想要一个数据帧示例，其中包含您希望确保我们在同一轨道上的输出。作为提示，我的想法是使用
dplyr
和
POSIXlt
，这将使您能够访问
$hour
（比只使用gsub它更容易），并使用
dplyr
按
分组，以及
总结
听起来像是
表格的工作，但是如果没有样本数据，很难判断。通常会使用
format.POSIXt
来给出小时：分钟的分类。还有一个
round.POSIXt
，通常很有用。我添加了示例数据。对不起，我在开始时没有包括它。谢谢你帮助我！
tweets.df<-as.data.frame(cbind(c("2014-12-13 14:04:34 CET","2014-12-13 14:04:37 CET","2014-12-13 14:04:45 CET","2014-12-13 14:05:23 CET","2014-12-13 14:05:53 CET","2014-12-13 14:05:58 CET","2014-12-13 14:06:33 CET","2014-12-13 14:06:38 CET","2014-12-13 14:06:59 CET","2014-12-13 14:08:16 CET","2014-12-13 14:09:12 CET","2014-12-13 14:09:34 CET","2014-12-13 14:10:05 CET","2014-12-13 14:10:16 CET","2014-12-13 14:10:17 CET","2014-12-13 14:11:13 CET","2014-12-13 14:11:16 CET","2014-12-13 14:12:01 CET","2014-12-13 14:12:30 CET","2014-12-13 14:14:02 CET","2014-12-13 14:14:02 CET","2014-12-13 14:14:02 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:03 CET","2014-12-13 14:14:05 CET","2014-12-13 14:14:05 CET","2014-12-13 14:14:07 CET","2014-12-13 14:14:07 CET","2014-12-13 14:14:08 CET","2014-12-13 14:14:08 CET","2014-12-13 14:14:08 CET","2014-12-13 14:14:08 CET","2014-12-13 14:14:11 CET","2014-12-13 14:14:11 CET","2014-12-13 14:14:22 CET","2014-12-13 14:14:48 CET","2014-12-13 14:15:02 CET","2014-12-13 14:15:03 CET","2014-12-13 14:16:20 CET","2014-12-13 14:16:26 CET","2014-12-13 14:17:14 CET","2014-12-13 14:17:24 CET","2014-12-13 14:17:45 CET","2014-12-13 14:17:49 CET","2014-12-13 14:18:05 CET","2014-12-13 14:18:30 CET","2014-12-13 14:19:38 CET"),1), stringsAsFactors=FALSE)
colnames(tweets.df)<-c("time","freq")

tweets.df$time <- as.POSIXct(tweets.df$time)

by.mins <- cut.POSIXt(tweets.df$time,"mins")

tweets.mins <- split(tweets.df, by.mins)
sapply(tweets.mins,function(x)sum(as.integer(x$freq)))
2014-12-13 14:04:00 2014-12-13 14:05:00 2014-12-13 14:06:00 2014-12-13 14:07:00 2014-12-13 14:08:00 
                  3                   3                   3                   0                   1 
2014-12-13 14:09:00 2014-12-13 14:10:00 2014-12-13 14:11:00 2014-12-13 14:12:00 2014-12-13 14:13:00 
                  2                   3                   2                   2                   0 
2014-12-13 14:14:00 2014-12-13 14:15:00 2014-12-13 14:16:00 2014-12-13 14:17:00 2014-12-13 14:18:00 
                 20                   2                   2                   4                   2 
2014-12-13 14:19:00 
                  1