我有一个工作目录,包含37个Locations.csv和37个Behavior.csv
看下面有一些文件与111868-Behavior.csv
和111868-Behavior 2.csv
具有相同的编号,因此也有Locations.csv
#here some of the csv in the work directory
dir()
[1] "111868-Behavior 2.csv" "111868-Behavior.csv"
[3] "111868-Locations 2.csv" "111868-Locations.csv"
[5] "111869-Behavior.csv" "111869-Locations.csv"
[7] "111870-Behavior 2.csv" "111870-Behavior.csv"
[9] "111870-Locations 2.csv" "111870-Locations.csv"
[11] "112696-Behavior 2.csv" "112696-Behavior.csv"
[13] "112696-Locations 2.csv" "112696-Locations.csv"
我无法更改文件名。
我想导入所有36个位置和36个行为,但是当我尝试这个时
#Create list of all behaviors
bhv <- list.files(pattern="*-Behavior.csv")
bhv2 <- list.files(pattern="*-Behavior 2.csv")
#Throw them altogether
bhv_csv = ldply(bhv, read_csv)
bhv_csv2 = ldply(bhv2, read_csv)
#Join bhv_csv and bhv_csv2
b<-rbind(bhv_csv,bhv_csv2)
#Create list of all locations
loc <- list.files(pattern="*-Locations.csv")
loc2 <- list.files(pattern="*-Locations 2.csv")
#Throw them altogether
loc_csv = ldply(loc, read_csv)
loc_csv2 = ldply(loc2, read_csv)
#Join loc_csv and loc_csv2
l<-rbind(loc_csv,loc_csv2)
显示我只有28,而不是像我预期的36
length(unique(b$Ptt))
[1] 28
length(unique(l$Ptt))
[1] 28
这个数字28,大约是没有Behaviors.csv
和Locations.csv
的所有Behaviors 2.csv
和Locations 2.csv
(数字“2”的每一个共8个)
我想以一种显示36个行为和位置的方式导入所有文件行为和所有位置。我怎样才能做到这一点?
您可以使用purrr::map
来简化您的一些代码:
library("tidyverse")
library("readr")
# Create two small csv files
write_lines("a,b\n1,2\n3,4", "file1.csv")
write_lines("a,c\n5,6\n7,8", "file2.csv")
list.files(pattern = "*.csv") %>%
# `map` will cycle through the files and read each one
map(read_csv) %>%
# and then we can bind them all together
bind_rows()
#> Parsed with column specification:
#> cols(
#> a = col_double(),
#> b = col_double()
#> )
#> Parsed with column specification:
#> cols(
#> a = col_double(),
#> c = col_double()
#> )
#> # A tibble: 4 x 3
#> a b c
#> <dbl> <dbl> <dbl>
#> 1 1 2 NA
#> 2 3 4 NA
#> 3 5 NA 6
#> 4 7 NA 8
由reprex package创建于2019-03-28(v0.2.1)