我认为没有 REFUND 行,至少有read_excel
函数可以直接读取数据。但是我在 R 中很新,我可能是错的。
也就是说,我首先想到的是构建自己的功能。下面的一个似乎工作。
library(readxl)
library(data.table)
file.list <- dir(path = ".", pattern='\\.xlsx', full.names = T)
my_read_data<-function(x){ #x list of files
df.list<- lapply(x, function(x){read_excel(path=x,skip=1,col_names = TRUE,
col_types=c("text","numeric","text"))})
#skip -> skip the line with the title
#col_names -> use the first row as column names, i.e., col1, col2 and col3
#col_types-> vector containing one entry per column indicating the type of data
my.data <- rbindlist(df.list)
my.data.clean<-my.data[my.data$col1!="REFUND",] #select only rows without "REFUND"
return(my.data.clean)
}
为了运行该功能,我将您的 Excel 示例复制了四次,更改了 REFUND 行的位置。我得到的结果如下。
the.data<-my_read_data(file.list)
>the.data
col1 col2 col3
1: A 1 359283060959987
2: B 2 359258069826064
3: C 3 359286062903911
4: A -1 359283060959987
5: A 1 359283060959987
6: B 2 359258069826064
7: C 3 359286062903911
8: A -1 359283060959987
9: A 1 359283060959987
10: B 2 359258069826064
11: C 3 359286062903911
12: A -1 359283060959987
13: A 1 359283060959987
14: B 2 359258069826064
15: C 3 359286062903911
16: A -1 359283060959987
EDIT - 传递要更改为字符类型的列的函数
关于您的评论,也许您可以考虑使用此功能:
my_read_data2<-function(x,character_col=NULL){ #x->list of files
# character_col->column to be change to character
# can be more than one
df.list<- lapply(x, function(x){read_excel(path=x,skip=1,col_names = TRUE)})
my.data <- rbindlist(df.list)
my.data.clean<-my.data[my.data$col1!="REFUND",] #select only rows without "REFUND"
# changing column selected by character_col to character
# since the result from step above is a data table,
# access to elements is different from data frame
if(!is.null(character_col)){ #this allow you to use the function using only
# default results from read_excel
my.data.clean[, eval(character_col):= lapply(.SD, as.character),
.SDcols= character_col]
}
# eval -> you need to evaluate the argument you pass to the function,
# otherwise you'll end up with an additional character_col column
# that will be a list of all the columns you include in .SDcols
#.SD -> is the subset of the data table, in this case
# .SDcols specifies the columns that are included in .SD.
return(my.data.clean[]) # in that case, don't forget the [] to avoid
#the odd behaviour when calling your resulting data table
#(see link at the end)
}
例子:
the.data<-my_read_data2(file.list)
str(the.data)
>str(the.data)
Classes ‘data.table’ and 'data.frame': 16 obs. of 3 variables:
$ col1: chr "A" "B" "C" "A" ...
$ col2: num 1 2 3 -1 1 2 3 -1 1 2 ...
$ col3: num 3.59e+14 3.59e+14 3.59e+14 3.59e+14 3.59e+14 ...
- attr(*, ".internal.selfref")=<externalptr>
the.data1<-my_read_data2(file.list,"col3")
str(the.data1)
> str(the.data1)
Classes ‘data.table’ and 'data.frame': 16 obs. of 3 variables:
$ col1: chr "A" "B" "C" "A" ...
$ col2: num 1 2 3 -1 1 2 3 -1 1 2 ...
$ col3: chr "359283060959987" "359258069826064" "359286062903911" "359283060959987" ...
- attr(*, ".internal.selfref")=<externalptr>
您还可以使用多个列:
the.data2<-my_read_data2(file.list,c("col2","col3"))
the.data3<-my_read_data2(file.list,c(2,3))
从函数返回后未打印 data.table 对象
希望对你有帮助