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我有一个复杂的数据框，一个最小的例子如下：

df <- structure(list(District = c("Adilabad", "Adilabad", "Adilabad", 
                        "Adilabad", "Adilabad", "Adilabad", "Adilabad", "Adilabad", "Adilabad", 
                        "Adilabad"), Subdistt = c("Adilabad", "Adilabad", "Adilabad", 
                        "Tamsi", "Tamsi", "Tamsi", "Tamsi", "Tamsi", "Tamsi", "Tamsi"
                        ), TRU = c("Total", "Rural", "Urban", "Total", "Rural", "Urban", 
                        "Rural", "Rural", "Urban", "Urban"), Level = c("District", "District", 
                        "District", "Sub-District", "Sub-District", "Sub-District", "Village", 
                        "Village", "Town", "Town"), No_HH = c(1277, 364, 913, 
                        1277, 364, 913, 117, 247, 614, 299)), .Names = c("District", 
                        "Subdistt", "TRU", "Level", "No_HH"), row.names = c(NA, 10L), class = "data.frame")

看起来像这样：

   District Subdistt   TRU        Level No_HH
1  Adilabad Adilabad Total     District  1277
2  Adilabad Adilabad Rural     District   364
3  Adilabad Adilabad Urban     District   913
4  Adilabad    Tamsi Total Sub-District  1277
5  Adilabad    Tamsi Rural Sub-District   364
6  Adilabad    Tamsi Urban Sub-District   913
7  Adilabad    Tamsi Rural      Village   117
8  Adilabad    Tamsi Rural      Village   247
9  Adilabad    Tamsi Urban         Town   614
10 Adilabad    Tamsi Urban         Town   299

在某种程度上，每个后续列都是前一列的一种子集。我必须验证农村、城市和总级别的分区和区的总和。

例如：第 7 行和第 8 行之和等于第 5 行中的值。第 5 行是农村分区。随着我们扩展 df，我有许多农村街道。所有农村分区的总和在第 2 行的农村区中给出。

最小预期输出如下：

  District Subdistt   TRU        Level No_HH
1 Adilabad    Tamsi Rural Sub-District   364
2 Adilabad    Tamsi Urban Sub-District   913

364 是上面最小示例中给出的 117 + 247 的总和，而 913 是最小示例中给出的行 614 + 299 的总和。

目前我可以将子集设置为特定值，但不知道如何根据这些复杂的选择求和。有人可以帮忙吗？

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1 回答 1

1

我们能试试

library(dplyr)
df %>%
    filter(Level=='Sub-District' & TRU != 'Total')
#  District Subdistt   TRU        Level No_HH
#1 Adilabad    Tamsi Rural Sub-District   364
#2 Adilabad    Tamsi Urban Sub-District   913

如果我们需要通过summing 得到相同的输出，

df %>%
    filter(!grepl('District', Level)) %>% 
    group_by(District, Subdistt,TRU) %>%
    summarise(No_HH= sum(No_HH)) %>%
    mutate(Level= 'Sub_District')
#  District Subdistt   TRU No_HH        Level
#     (chr)    (chr) (chr) (dbl)        (chr)
# 1 Adilabad    Tamsi Rural   364 Sub_District
# 2 Adilabad    Tamsi Urban   913 Sub_District
于 2015-12-13T08:15:13.307 回答