如果您将 data.frames 从列表复制到新环境,则可以使用envir
参数sqldf
或通过命名列表的元素,并使用with
.
注意几件事:
注意区别
str(c(df1,df2))
##List of 4
## $ CustomerId: int [1:6] 1 2 3 4 5 6
## $ Product : Factor w/ 2 levels "Radio","Toaster": 2 2 2 1 1 1
## $ CustomerId: num [1:3] 2 4 6
## $ State : Factor w/ 2 levels "Alabama","Ohio": 1 1 2
str(list(df1,df2))
##List of 2
## $ :'data.frame': 6 obs. of 2 variables:
## ..$ CustomerId: int [1:6] 1 2 3 4 5 6
## ..$ Product : Factor w/ 2 levels "Radio","Toaster": 2 2 2 1 1 1
## $ :'data.frame': 3 obs. of 2 variables:
## ..$ CustomerId: num [1:3] 2 4 6
## ..$ State : Factor w/ 2 levels "Alabama","Ohio": 1 1 2
- 我已经调整了 sql 查询以反映 data.frames 中的名称(根据您的第二种方法)
命名数据
dflist <- list(df1,df2)
names(dflist) <- c('df1','df2')
创造一个新的工作环境
# create a new environment
e <- new.env()
# assign the elements of dflist to this new environment
for(.x in names(dflist)){
assign(value = dflist[[.x]], x=.x, envir = e)
}
# this could also be done using mapply / lapply
# eg
# invisible(mapply(assign, value = dflist, x = names(dflist), MoreArgs =list(envir = e)))
# run the sql query
sqldf("select a.CustomerId, a.Product, b.State from df1 a
inner join df2 b on b.CustomerId = a.CustomerId", envir = e)
## CustomerId Product State
## 1 2 Toaster Alabama
## 2 4 Radio Alabama
## 3 6 Radio Ohio
使用更简单的方法with
您可以简单地使用with
which 在本地进行评估(重要的是 dflist 是此处的命名列表)
# this is far simpler!!
with(dflist,sqldf("select a.CustomerId, a.Product, b.State from df1 a
inner join df2 b on b.CustomerId = a.CustomerId"))
另一种简单的方法使用proto
这使用proto
加载的包sqldf
dflist <- list(a = df1, b = df2)
sqldf( "select a.CustomerId, a.Product, b.State from df1 a
inner join df2 b on b.CustomerId = a.CustomerId",
envir = as.proto(dflist))
使用数据表
或者您可以使用data.table
which givesql-like
方法(参见FAQ 2.16)
library(data.table)
dflist <- list(data.table(df1),data.table(df2))
names(dflist) <- c('df1','df2')
invisible(lapply(dflist, setkeyv, 'CustomerId'))
with(dflist, df1[df2])
## CustomerId Product State
## 1: 2 Toaster Alabama
## 2: 4 Radio Alabama
## 3: 6 Radio Ohio