每组汇总/汇总多个变量(例如sum、mean)

Question

从数据帧中，有没有一种简单的方法来同时聚合(sum，mean，max等c)多个变量？

以下是一些示例数据：

library(lubridate)
days = 365*2
date = seq(as.Date("2000-01-01"), length = days, by = "day")
year = year(date)
month = month(date)
x1 = cumsum(rnorm(days, 0.05)) 
x2 = cumsum(rnorm(days, 0.05))
df1 = data.frame(date, year, month, x1, x2)

我想按年和月同时聚合来自df2数据框的x1和x2变量。下面的代码聚合了x1变量，但是同时聚合x2变量也是可能的吗？

### aggregate variables by year month
df2=aggregate(x1 ~ year+month, data=df1, sum, na.rm=TRUE)
head(df2)

Answer 1

这个year()函数来自哪里？

您还可以使用reshape2包来执行此任务：

require(reshape2)
df_melt <- melt(df1, id = c("date", "year", "month"))
dcast(df_melt, year + month ~ variable, sum)
#  year month         x1           x2
1  2000     1  -80.83405 -224.9540159
2  2000     2 -223.76331 -288.2418017
3  2000     3 -188.83930 -481.5601913
4  2000     4 -197.47797 -473.7137420
5  2000     5 -259.07928 -372.4563522

Answer 2

可以，在您的formula中，您可以cbind要聚合的数值变量：

aggregate(cbind(x1, x2) ~ year + month, data = df1, sum, na.rm = TRUE)
   year month         x1          x2
1  2000     1   7.862002   -7.469298
2  2001     1 276.758209  474.384252
3  2000     2  13.122369 -128.122613
...
23 2000    12  63.436507  449.794454
24 2001    12 999.472226  922.726589

请参阅?aggregate、formula参数和示例。

Answer 3

使用dplyr包，您可以使用summarise_all、summarise_at或summarise_if函数同时聚合多个变量。对于示例数据集，您可以执行以下操作：

library(dplyr)
# summarising all non-grouping variables
df2 <- df1 %>% group_by(year, month) %>% summarise_all(sum)

# summarising a specific set of non-grouping variables
df2 <- df1 %>% group_by(year, month) %>% summarise_at(vars(x1, x2), sum)
df2 <- df1 %>% group_by(year, month) %>% summarise_at(vars(-date), sum)

# summarising a specific set of non-grouping variables using select_helpers
# see ?select_helpers for more options
df2 <- df1 %>% group_by(year, month) %>% summarise_at(vars(starts_with('x')), sum)
df2 <- df1 %>% group_by(year, month) %>% summarise_at(vars(matches('.*[0-9]')), sum)

# summarising a specific set of non-grouping variables based on condition (class)
df2 <- df1 %>% group_by(year, month) %>% summarise_if(is.numeric, sum)

后两个选项的结果：

    year month        x1         x2
   <dbl> <dbl>     <dbl>      <dbl>
1   2000     1 -73.58134  -92.78595
2   2000     2 -57.81334 -152.36983
3   2000     3 122.68758  153.55243
4   2000     4 450.24980  285.56374
5   2000     5 678.37867  384.42888
6   2000     6 792.68696  530.28694
7   2000     7 908.58795  452.31222
8   2000     8 710.69928  719.35225
9   2000     9 725.06079  914.93687
10  2000    10 770.60304  863.39337
# ... with 14 more rows

注意:为了支持summarise_all、summarise_at和summarise_if，summarise_each被弃用。

正如在my comment above中提到的，您还可以使用reshape2-package中的recast函数：

library(reshape2)
recast(df1, year + month ~ variable, sum, id.var = c("date", "year", "month"))

这将会给你同样的结果。