Question

对于示例数据框：

migration <- structure(list(area.old = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 
                                               2L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 1L, 
                                               3L, NA, NA, NA), .Label = c("leeds", "london", "plymouth"), class = "factor"), 
                        area.new = structure(c(7L, 13L, 3L, 2L, 4L, 7L, 6L, 7L, 6L, 
                                               13L, 5L, 8L, 7L, 11L, 12L, 9L, 1L, 10L, 11L, NA, NA, NA, 
                                               NA, 7L, 6L, 6L), .Label = c("bath", "bristol", "cambridge", 
                                                                           "glasgow", "harrogate", "leeds", "london", "manchester", 
                                                                           "newcastle", "oxford", "plymouth", "poole", "york"), class = "factor"), 
                        persons = c(6L, 3L, 2L, 5L, 6L, 7L, 8L, 4L, 5L, 6L, 3L, 4L, 
                                    1L, 1L, 2L, 3L, 4L, 9L, 4L, 5L, 7L, 9L, 10L, 15L, 4L, 7L)), .Names = c("area.old", 
                                                                                                           "area.new", "persons"), class = c("data.table", "data.frame"), row.names = c(NA, 
                                                                                                                                                                                        -26L), .internal.selfref = <pointer: 0x0000000000220788>)

我希望使用以下代码将数据汇总到几个数据框中：

moved.from <- migration[as.character(area.old)!=as.character(area.new), 
                 .(persons = sum(persons)), 
                 by=.(moved.from = area.old)]

moved.to <- migration[as.character(area.old)!=as.character(area.new), 
                 .(persons = sum(persons)), 
                 by=.(moved.to = area.new)]

这会生成两个汇总表，首先详细说明已经从＆area; old.old＆＃39;区域移动的人员总数。第二个表格列出了人们搬到的目的地（在＆＃39; area.new＆＃39;）。这里建议使用此代码（Producing smmary tables for very large datasets）。

当我在我自己的数据上尝试时出现了一个问题，因为我没有告诉R如何处理区域内的NAs。＆＃39;或者＆＃39; area.new＆＃39;列。如何修改此代码以添加所有NA（即将它们包含在moving.from和moving.to数据框底部的行中，添加了NA中的总人数）？

对此的任何帮助都将非常感激。

Answer 1

只需在每个过滤器中添加| is.na作为附加条件

migration[as.character(area.old) != 
            as.character(area.new) | 
            is.na(area.old),
          .(persons = sum(persons)), 
          by = .(moved.from = area.old)]

#    moved.from persons
# 1:     london      24
# 2:      leeds      17
# 3:   plymouth      19
# 4:         NA      26

和

migration[as.character(area.old) !=
            as.character(area.new) |
            is.na(area.new), 
          .(persons = sum(persons)), 
          by = .(moved.to = area.new)]

#       moved.to persons
#  1:       york       9
#  2:  cambridge       2
#  3:    bristol       5
#  4:    glasgow       6
#  5:      leeds       8
#  6:     london       5
#  7:  harrogate       3
#  8: manchester       4
#  9:      poole       2
# 10:  newcastle       3
# 11:       bath       4
# 12:     oxford       9
# 13:         NA      31

作为旁注，我建议将两列转换为字符类，并避免在每个操作中调用as.character。以下应该做

migration[, names(migration)[-3L] := lapply(.SD, as.character), .SDcols = -"persons"]

现在，您可以在不调用area.old的情况下比较area.new和as.character

在摘要表中包含NA

1 个答案: