dplyr？ - 寻找更有效的方式来汇总数据

Question

再次坚持,希望更多的线索可以提供指针; o)

我有一个数据集; 3,270行datePublished(2013-04-01:2014-03-31)和域名(coindesk,forbes,mashable,nytimes,路透社,techcrunch,thenextweb&theverge).副本在这里)

> df <- read.csv("dplyr_summary_example.csv")
> head(df)
  datePublished  domain
1 2013-04-01     coindesk
2 2013-04-01     coindesk
3 2013-04-13     coindesk
4 2013-04-15     coindesk
5 2013-04-15     coindesk

基本上,df在每次发布故事时都有一行日期/域对.

我想要做的是创建一个看起来有点像的新数据框(例如编号)...

datePublished  coindeskStories  forbesStories... thevergeStories totalStories
2013-04-01     2                1                1               4 
2013-04-13     1                1                0               2
2013-04-15     2                0                1               3

因此,对于df中的每个日期,我希望每个域的总故事列,最后总计列总数(总计的总数很容易).

我一直在看,dplyr它看起来确实可以完成这项工作,但到目前为止,我还没有设法一步到位.

对于每个域,然后加入东西是相当简单的:

daily        <- group_by(df,datePublished) # group stories by date

cnt.nytimes  <- filter(daily, domain=="nytimes")  # filter just the nytimes ones
cnt.nytimes  <- summarise(cnt.nytimes,nytimesStories=n()) # give table of stories by date

cnt.mashable <- filter(daily, domain=="mashable")
cnt.mashable <- summarise(cnt.mashable,mashableStories=n())

df.Stories   <- full_join(cnt.nytimes,cnt.mashable,by="datePublished") # join cnt. dataframes by datePublished
df.Stories   <- arrange(df.Stories,datePublished) #sort by datePublished

df.Stories$totalStories <- apply(df.Stories[c(2:3)],1,sum,na.rm=TRUE) #add a totals column

但是在每个域上执行此操作然后使用连接似乎有点低效.

谁能建议更简单的路线？

Answer 1

关于什么 reshape2::dcast

require(reshape2)
res <- dcast(df, datePublished ~ domain, value.var = "domain", fun.aggregate = length)

结果:

> head(res)
  datePublished coindesk forbes mashable nytimes reuters techcrunch thenextweb theverge
1    2013-04-01        2      2        0       0       0          1          0        2
2    2013-04-02        0      1        1       0       0          0          0        0
3    2013-04-03        0      3        1       0       0          2          0        0
4    2013-04-04        0      0        0       0       0          1          1        1
5    2013-04-05        0      1        0       0       0          1          1        1
6    2013-04-07        0      1        0       1       0          1          0        0

注释:如果您希望datePublished为Date而不是因子使用

df$datePublished <- as.Date(as.character(df$datePublished))

之后 read.csv

Answer 2

要改变宽幅你需要使用tidyr除dplyr.就像是

library(dplyr)
library(tidyr)

df %>% 
    group_by(datePublished, domain) %>%
    summarise(nstories = n()) %>%
    spread(domain, nstories)