Question

说我有以下数据框df

name <- c("Bill", "Rob", "Joe", "Joe")
address <- c("123 Main St", "234 Broad St", NA, "456 North Ave")
favteam <- c("Dodgers", "Mets", "Pirates", NA)

df <- data.frame(name = name, 
                 address = address,
                 favteam = favteam)
df

看起来像：

  name       address favteam
1 Bill   123 Main St Dodgers
2  Rob  234 Broad St    Mets
3  Joe          <NA> Pirates
4  Joe 456 North Ave    <NA>

我想要做的是按名称（或一般来说，任意数量的ID变量）进行折叠，并使用除NA之外的任何其他值替换最终数据中的NA值，像这样：

df_collapse <- foo(df)

  name   address        favteam
1 Bill   123 Main St    Dodgers
2  Rob   234 Broad St      Mets
3  Joe   456 North Ave  Pirates

Answer 1

这是dplyr的选项：

library(dplyr)

df %>%
  group_by(name) %>%
  summarise_each(funs(first(.[!is.na(.)]))) # or summarise_each(funs(first(na.omit(.))))

#Source: local data frame [3 x 3]
#
#  name       address favteam
#1 Bill   123 Main St Dodgers
#2  Joe 456 North Ave Pirates
#3  Rob  234 Broad St    Mets

使用data.table：

library(data.table)
setDT(df)[, lapply(.SD, function(x) x[!is.na(x)][1L]), by = name]
#   name       address favteam
#1: Bill   123 Main St Dodgers
#2:  Rob  234 Broad St    Mets
#3:  Joe 456 North Ave Pirates

或

setDT(df)[, lapply(.SD, function(x) head(na.omit(x), 1L)), by = name]

编辑：

您说在实际数据中，每个名字都有不同数量的非NA回复。在这种情况下，以下方法可能会有所帮助。

考虑这个修改过的样本数据（查看最后一行）：

name <- c("Bill", "Rob", "Joe", "Joe", "Joe")
address <- c("123 Main St", "234 Broad St", NA, "456 North Ave", "123 Boulevard")
favteam <- c("Dodgers", "Mets", "Pirates", NA, NA)

df <- data.frame(name = name, 
                 address = address,
                 favteam = favteam)

df
#  name       address favteam
#1 Bill   123 Main St Dodgers
#2  Rob  234 Broad St    Mets
#3  Joe          <NA> Pirates
#4  Joe 456 North Ave    <NA>
#5  Joe 123 Boulevard    <NA>

然后，您可以使用此data.table方法获取可能因名称而有所不同的非NA响应：

setDT(df)[, lapply(.SD, function(x) unique(na.omit(x))), by = name]
#   name       address favteam
#1: Bill   123 Main St Dodgers
#2:  Rob  234 Broad St    Mets
#3:  Joe 456 North Ave Pirates
#4:  Joe 123 Boulevard Pirates

如何在删除NA值的同时将多个记录合并为一个

1 个答案: