当行具有不同的列集时,按行(rbind)组合两个数据帧

Question

是否可以对两个没有相同列的数据帧进行行绑定？我希望保留绑定后不匹配的列.

Answer 1

rbind.fill从包中plyr可能是你正在寻找的.

Answer 2

一个更新的解决方案是使用我认为比它更有效dplyr的bind_rows函数smartbind.

Answer 3

您可以smartbind从gtools包中使用.

例:

library(gtools)
df1 <- data.frame(a = c(1:5), b = c(6:10))
df2 <- data.frame(a = c(11:15), b = c(16:20), c = LETTERS[1:5])
smartbind(df1, df2)
# result
     a  b    c
1.1  1  6 <NA>
1.2  2  7 <NA>
1.3  3  8 <NA>
1.4  4  9 <NA>
1.5  5 10 <NA>
2.1 11 16    A
2.2 12 17    B
2.3 13 18    C
2.4 14 19    D
2.5 15 20    E

Answer 4

如果df1中的列是df2中的列(按列名称):

df3 <- rbind(df1, df2[, names(df1)])

Answer 5

替代方案data.table:

library(data.table)
df1 = data.frame(a = c(1:5), b = c(6:10))
df2 = data.frame(a = c(11:15), b = c(16:20), c = LETTERS[1:5])
rbindlist(list(df1, df2), fill = TRUE)

rbinddata.table只要将对象转换为data.table对象,它也将起作用

rbind(setDT(df1), setDT(df2), fill=TRUE)

也会在这种情况下工作.当你有几个data.tables并且不想构建一个列表时,这可能是更好的选择.

Answer 6

大多数基本R答案解决了只有一个data.frame有附加列或者结果data.frame将具有列的交集的情况.由于OP写道我希望保留绑定后不匹配的列,使用基本R方法解决此问题的答案可能值得发布.

下面,我介绍两种基本R方法:一种改变原始data.frames,另一种不改变原始data.frames.另外,我提供了一种方法,将非破坏性方法推广到两个以上的data.frames.

首先,让我们得到一些样本数据.

# sample data, variable c is in df1, variable d is in df2
df1 = data.frame(a=1:5, b=6:10, d=month.name[1:5])
df2 = data.frame(a=6:10, b=16:20, c = letters[8:12])

两个data.frames,alter originals
为了保留两个data.frames中的所有列rbind(并允许函数工作而不会导致错误),你可以为每个data.frame添加NA列,并填入适当的缺失名称使用setdiff.

# fill in non-overlapping columns with NAs
df1[setdiff(names(df2), names(df1))] <- NA
df2[setdiff(names(df1), names(df2))] <- NA

现在,rbind-em

rbind(df1, df2)
    a  b        d    c
1   1  6  January <NA>
2   2  7 February <NA>
3   3  8    March <NA>
4   4  9    April <NA>
5   5 10      May <NA>
6   6 16     <NA>    h
7   7 17     <NA>    i
8   8 18     <NA>    j
9   9 19     <NA>    k
10 10 20     <NA>    l

请注意,前两行会更改原始data.frames,df1和df2,并为两者添加完整的列集.

两个data.frames,不改变原始文件
要保持原始data.frames不变,首先循环遍历不同的名称,返回一个命名的NA向量,这些NAs与data.frame使用连接成一个列表c.然后,data.frame将结果转换为适当的data.frame rbind.

rbind(
  data.frame(c(df1, sapply(setdiff(names(df2), names(df1)), function(x) NA))),
  data.frame(c(df2, sapply(setdiff(names(df1), names(df2)), function(x) NA)))
)

许多data.frames,不会改变原始文件
在您有两个以上data.frames的实例中,您可以执行以下操作.

# put data.frames into list (dfs named df1, df2, df3, etc)
mydflist <- mget(ls(pattern="df\\d+"))
# get all variable names
allNms <- unique(unlist(lapply(mydflist, names)))

# put em all together
do.call(rbind,
        lapply(mydflist,
               function(x) data.frame(c(x, sapply(setdiff(allNms, names(x)),
                                                  function(y) NA)))))

也许更好看不到原始data.frames的行名？然后这样做.

do.call(rbind,
        c(lapply(mydflist,
                 function(x) data.frame(c(x, sapply(setdiff(allNms, names(x)),
                                                    function(y) NA)))),
          make.row.names=FALSE))

Answer 7

你也可以拔出常用的列名.

> cols <- intersect(colnames(df1), colnames(df2))
> rbind(df1[,cols], df2[,cols])

Answer 8

我写了一个函数来做这个,因为我喜欢我的代码告诉我是否有问题.此函数将明确告诉您哪些列名称不匹配以及您是否存在类型不匹配.然后它会尽力组合data.frames.限制是您一次只能组合两个data.frames.

### combines data frames (like rbind) but by matching column names
# columns without matches in the other data frame are still combined
# but with NA in the rows corresponding to the data frame without
# the variable
# A warning is issued if there is a type mismatch between columns of
# the same name and an attempt is made to combine the columns
combineByName <- function(A,B) {
    a.names <- names(A)
    b.names <- names(B)
    all.names <- union(a.names,b.names)
    print(paste("Number of columns:",length(all.names)))
    a.type <- NULL
    for (i in 1:ncol(A)) {
        a.type[i] <- typeof(A[,i])
    }
    b.type <- NULL
    for (i in 1:ncol(B)) {
        b.type[i] <- typeof(B[,i])
    }
    a_b.names <- names(A)[!names(A)%in%names(B)]
    b_a.names <- names(B)[!names(B)%in%names(A)]
    if (length(a_b.names)>0 | length(b_a.names)>0){
        print("Columns in data frame A but not in data frame B:")
        print(a_b.names)
        print("Columns in data frame B but not in data frame A:")
        print(b_a.names)
    } else if(a.names==b.names & a.type==b.type){
        C <- rbind(A,B)
        return(C)
    }
    C <- list()
    for(i in 1:length(all.names)) {
        l.a <- all.names[i]%in%a.names
        pos.a <- match(all.names[i],a.names)
        typ.a <- a.type[pos.a]
        l.b <- all.names[i]%in%b.names
        pos.b <- match(all.names[i],b.names)
        typ.b <- b.type[pos.b]
        if(l.a & l.b) {
            if(typ.a==typ.b) {
                vec <- c(A[,pos.a],B[,pos.b])
            } else {
                warning(c("Type mismatch in variable named: ",all.names[i],"\n"))
                vec <- try(c(A[,pos.a],B[,pos.b]))
            }
        } else if (l.a) {
            vec <- c(A[,pos.a],rep(NA,nrow(B)))
        } else {
            vec <- c(rep(NA,nrow(A)),B[,pos.b])
        }
        C[[i]] <- vec
    }
    names(C) <- all.names
    C <- as.data.frame(C)
    return(C)
}