list 将 Data.frames 列表重组为单个数据框
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Recombining a list of Data.frames into a single data frame
提问by CGN
I am sorry if this question has been answered already. Also, this is my first time on stackoverflow.
如果已经回答了这个问题，我很抱歉。此外，这是我第一次使用 stackoverflow。
I have a beginner R question concerning lists , data frames and merge()and/or rbind().
我有一个关于列表、数据框merge()和/或rbind().
I started with a Panel that looks like this
我从一个看起来像这样的面板开始
COUNTRY YEAR VAR
A 1
A 2
B 1
B 2
For efficiency purposes, I created a list that consists of one data frame for each country and performed a variety of calculations on each individual data.frame. However, I cannot seem to combine the individual data frames into one large frame again.
为了提高效率，我创建了一个列表，其中包含每个国家/地区的一个数据框，并对每个人进行了各种计算data.frame。但是，我似乎无法再次将单个数据帧合并为一个大帧。
rbind()and merge()both tell me that only replacement of elements is allowed.
rbind()并且merge()都告诉我只允许替换元素。
Could someone tell me what I am doing wrong/ and how to actually recombine the data frames?
有人能告诉我我做错了什么/以及如何实际重新组合数据帧吗？
Thank you
谢谢
回答by datanalytics.com
Maybe you want to do something like:
也许你想做这样的事情：
do.call("rbind", my.df.list)
do.call("rbind", my.df.list)
回答by lbcommer
dplyr lets you use bind_rows function for that:
dplyr 允许您使用 bind_rows 函数：
library(dplyr)
foo <- list(df1 = data.frame(x=c('a', 'b', 'c'),y = c(1,2,3)),
df2 = data.frame(x=c('d', 'e', 'f'),y = c(4,5,6)))
bind_rows(foo)
回答by alberto
Note that the basic solution
注意基本解决方案
do.call("rbind", my.df.list)
will be slow if we have many dataframes. A scalable solution is:
如果我们有很多数据帧，速度会很慢。一个可扩展的解决方案是：
library(data.table)
rbindlist(my.df.list)
which, from the docs, is the same as do.call("rbind", l) on data.frames, but much faster.
其中，从文档中，是same as do.call("rbind", l) on data.frames, but much faster.
回答by doug
There might be a better way to do this, but this seems to work and it's straightforward. (My code has four lines so that it's easier to see the steps; these four could easily be combined.)
可能有更好的方法来做到这一点，但这似乎有效而且很简单。（我的代码有四行，所以更容易看到步骤；这四行很容易组合。）
# first re-create your data frame:
A = matrix( ceiling(10*runif(8)), nrow=4)
colnames(A) = c("country", "year_var")
dfa = data.frame(A)
# now re-create the list you made from the individual rows of the data frame:
df1 = dfa[1,]
df2 = dfa[2,]
df3 = dfa[3,]
df4 = dfa[4,]
df_all = list(df1, df2, df3, df4)
# to recreate your original data frame:
x = unlist(df_all) # from your list create a single 1D array
A = matrix(x, nrow=4) # dimension that array in accord w/ your original data frame
colnames(A) = c("country", "year_var") # put the column names back on
dfa = data.frame(A) # from the matrix, create your original data frame
回答by Shane
plyr is probably best. Another useful approach if the data frames can be different is to use reshape:
plyr 可能是最好的。如果数据框可以不同，另一种有用的方法是使用 reshape：
library(reshape)
data <- merge_recurse(listofdataframes)
Look at my answer to this related question on merging data frames.
看看我对这个有关合并数据框的相关问题的回答。
